Increase of Gas-Turbine Plant Efficiency by Optimizing Operation of Compressors

NASA Astrophysics Data System (ADS)

Matveev, V.; Goriachkin, E.; Volkov, A.

2018-01-01

The article presents optimization method for improving of the working process of axial compressors of gas turbine engines. Developed method allows to perform search for the best geometry of compressor blades automatically by using optimization software IOSO and CFD software NUMECA Fine/Turbo. The calculation of the compressor parameters was performed for work and stall point of its performance map on each optimization step. Study was carried out for seven-stage high-pressure compressor and three-stage low-pressure compressors. As a result of optimization, improvement of efficiency was achieved for all investigated compressors.

Optimized survey design for electrical resistivity tomography: combined optimization of measurement configuration and electrode placement

NASA Astrophysics Data System (ADS)

Uhlemann, Sebastian; Wilkinson, Paul B.; Maurer, Hansruedi; Wagner, Florian M.; Johnson, Timothy C.; Chambers, Jonathan E.

2018-07-01

Within geoelectrical imaging, the choice of measurement configurations and electrode locations is known to control the image resolution. Previous work has shown that optimized survey designs can provide a model resolution that is superior to standard survey designs. This paper demonstrates a methodology to optimize resolution within a target area, while limiting the number of required electrodes, thereby selecting optimal electrode locations. This is achieved by extending previous work on the `Compare-R' algorithm, which by calculating updates to the resolution matrix optimizes the model resolution in a target area. Here, an additional weighting factor is introduced that allows to preferentially adding measurement configurations that can be acquired on a given set of electrodes. The performance of the optimization is tested on two synthetic examples and verified with a laboratory study. The effect of the weighting factor is investigated using an acquisition layout comprising a single line of electrodes. The results show that an increasing weight decreases the area of improved resolution, but leads to a smaller number of electrode positions. Imaging results superior to a standard survey design were achieved using 56 per cent fewer electrodes. The performance was also tested on a 3-D acquisition grid, where superior resolution within a target at the base of an embankment was achieved using 22 per cent fewer electrodes than a comparable standard survey. The effect of the underlying resistivity distribution on the performance of the optimization was investigated and it was shown that even strong resistivity contrasts only have minor impact. The synthetic results were verified in a laboratory tank experiment, where notable image improvements were achieved. This work shows that optimized surveys can be designed that have a resolution superior to standard survey designs, while requiring significantly fewer electrodes. This methodology thereby provides a means for improving the efficiency of geoelectrical imaging.

Optimized survey design for Electrical Resistivity Tomography: combined optimization of measurement configuration and electrode placement

NASA Astrophysics Data System (ADS)

Uhlemann, Sebastian; Wilkinson, Paul B.; Maurer, Hansruedi; Wagner, Florian M.; Johnson, Timothy C.; Chambers, Jonathan E.

2018-03-01

Within geoelectrical imaging, the choice of measurement configurations and electrode locations is known to control the image resolution. Previous work has shown that optimized survey designs can provide a model resolution that is superior to standard survey designs. This paper demonstrates a methodology to optimize resolution within a target area, while limiting the number of required electrodes, thereby selecting optimal electrode locations. This is achieved by extending previous work on the `Compare-R' algorithm, which by calculating updates to the resolution matrix optimizes the model resolution in a target area. Here, an additional weighting factor is introduced that allows to preferentially adding measurement configurations that can be acquired on a given set of electrodes. The performance of the optimization is tested on two synthetic examples and verified with a laboratory study. The effect of the weighting factor is investigated using an acquisition layout comprising a single line of electrodes. The results show that an increasing weight decreases the area of improved resolution, but leads to a smaller number of electrode positions. Imaging results superior to a standard survey design were achieved using 56 per cent fewer electrodes. The performance was also tested on a 3D acquisition grid, where superior resolution within a target at the base of an embankment was achieved using 22 per cent fewer electrodes than a comparable standard survey. The effect of the underlying resistivity distribution on the performance of the optimization was investigated and it was shown that even strong resistivity contrasts only have minor impact. The synthetic results were verified in a laboratory tank experiment, where notable image improvements were achieved. This work shows that optimized surveys can be designed that have a resolution superior to standard survey designs, while requiring significantly fewer electrodes. This methodology thereby provides a means for improving the efficiency of geoelectrical imaging.

Topologically Optimized Nano-Positioning Stage Integrating with a Capacitive Comb Sensor.

PubMed

Chen, Tao; Wang, Yaqiong; Liu, Huicong; Yang, Zhan; Wang, Pengbo; Sun, Lining

2017-01-28

Nano-positioning technology has been widely used in many fields, such as microelectronics, optical engineering, and micro manufacturing. This paper presents a one-dimensional (1D) nano-positioning system, adopting a piezoelectric ceramic (PZT) actuator and a multi-objective topological optimal structure. The combination of a nano-positioning stage and a feedback capacitive comb sensor has been achieved. In order to obtain better performance, a wedge-shaped structure is used to apply the precise pre-tension for the piezoelectric ceramics. Through finite element analysis and experimental verification, better static performance and smaller kinetic coupling are achieved. The output displacement of the system achieves a long-stroke of up to 14.7 μm and high-resolution of less than 3 nm. It provides a flexible and efficient way in the design and optimization of the nano-positioning system.

Topologically Optimized Nano-Positioning Stage Integrating with a Capacitive Comb Sensor

PubMed Central

Chen, Tao; Wang, Yaqiong; Liu, Huicong; Yang, Zhan; Wang, Pengbo; Sun, Lining

2017-01-01

Nano-positioning technology has been widely used in many fields, such as microelectronics, optical engineering, and micro manufacturing. This paper presents a one-dimensional (1D) nano-positioning system, adopting a piezoelectric ceramic (PZT) actuator and a multi-objective topological optimal structure. The combination of a nano-positioning stage and a feedback capacitive comb sensor has been achieved. In order to obtain better performance, a wedge-shaped structure is used to apply the precise pre-tension for the piezoelectric ceramics. Through finite element analysis and experimental verification, better static performance and smaller kinetic coupling are achieved. The output displacement of the system achieves a long-stroke of up to 14.7 μm and high-resolution of less than 3 nm. It provides a flexible and efficient way in the design and optimization of the nano-positioning system. PMID:28134854

Thermal optimality of net ecosystem exchange of carbon dioxide and underlying mechanisms

USDA-ARS?s Scientific Manuscript database

It has been well established that individual organisms can acclimate and adapt to temperature change to optimize their performance (i.e., achieve thermal optimality). However, whether ecosystems with an assembly of organisms would also undergo thermal optimization has not been examined on a broader ...

A Technical Survey on Optimization of Processing Geo Distributed Data

NASA Astrophysics Data System (ADS)

Naga Malleswari, T. Y. J.; Ushasukhanya, S.; Nithyakalyani, A.; Girija, S.

2018-04-01

With growing cloud services and technology, there is growth in some geographically distributed data centers to store large amounts of data. Analysis of geo-distributed data is required in various services for data processing, storage of essential information, etc., processing this geo-distributed data and performing analytics on this data is a challenging task. The distributed data processing is accompanied by issues in storage, computation and communication. The key issues to be dealt with are time efficiency, cost minimization, utility maximization. This paper describes various optimization methods like end-to-end multiphase, G-MR, etc., using the techniques like Map-Reduce, CDS (Community Detection based Scheduling), ROUT, Workload-Aware Scheduling, SAGE, AMP (Ant Colony Optimization) to handle these issues. In this paper various optimization methods and techniques used are analyzed. It has been observed that end-to end multiphase achieves time efficiency; Cost minimization concentrates to achieve Quality of Service, Computation and reduction of Communication cost. SAGE achieves performance improvisation in processing geo-distributed data sets.

CUDA Optimization Strategies for Compute- and Memory-Bound Neuroimaging Algorithms

PubMed Central

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W.

2011-01-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. PMID:21159404

CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.

PubMed

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W

2012-06-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

On the balancing of structural and acoustic performance of a sandwich panel based on topology, property, and size optimization

NASA Astrophysics Data System (ADS)

Cameron, Christopher J.; Lind Nordgren, Eleonora; Wennhage, Per; Göransson, Peter

2014-06-01

Balancing structural and acoustic performance of a multi-layered sandwich panel is a formidable undertaking. Frequently the gains achieved in terms of reduced weight, still meeting the structural design requirements, are lost by the changes necessary to regain acceptable acoustic performance. To alleviate this, a design method for a multifunctional load bearing vehicle body panel is proposed which attempts to achieve a balance between structural and acoustic performance. The approach is based on numerical modelling of the structural and acoustic behaviour in a combined topology, size, and property optimization in order to achieve a three dimensional optimal distribution of structural and acoustic foam materials within the bounding surfaces of a sandwich panel. In particular the effects of the coupling between one of the bounding surface face sheets and acoustic foam are examined for its impact on both the structural and acoustic overall performance of the panel. The results suggest a potential in introducing an air gap between the acoustic foam parts and one of the face sheets, provided that the structural design constraints are met without prejudicing the layout of the different foam types.

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

Wind Turbine Optimization with WISDEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dykes, Katherine L; Damiani, Rick R; Graf, Peter A

This presentation for the Fourth Wind Energy Systems Engineering Workshop explains the NREL wind energy systems engineering initiative-developed analysis platform and research capability to capture important system interactions to achieve a better understanding of how to improve system-level performance and achieve system-level cost reductions. Topics include Wind-Plant Integrated System Design and Engineering Model (WISDEM) and multidisciplinary design analysis and optimization.

Parameter Optimization and Electrode Improvement of Rotary Stepper Micromotor

NASA Astrophysics Data System (ADS)

Sone, Junji; Mizuma, Toshinari; Mochizuki, Shunsuke; Sarajlic, Edin; Yamahata, Christophe; Fujita, Hiroyuki

We developed a three-phase electrostatic stepper micromotor and performed a numerical simulation to improve its performance for practical use and to optimize its design. We conducted its circuit simulation by simplifying its structure, and the effect of springback force generated by supported mechanism using flexures was considered. And we considered new improvement method for electrodes. This improvement and other parameter optimizations achieved the low voltage drive of micromotor.

Measuring the performance of telephone-based disease surveillance systems in local health departments.

PubMed

Dausey, David J; Chandra, Anita; Schaefer, Agnes G; Bahney, Ben; Haviland, Amelia; Zakowski, Sarah; Lurie, Nicole

2008-09-01

We tested telephone-based disease surveillance systems in local health departments to identify system characteristics associated with consistent and timely responses to urgent case reports. We identified a stratified random sample of 74 health departments and conducted a series of unannounced tests of their telephone-based surveillance systems. We used regression analyses to identify system characteristics that predicted fast connection with an action officer (an appropriate public health professional). Optimal performance in consistently connecting callers with an action officer in 30 minutes or less was achieved by 31% of participating health departments. Reaching a live person upon dialing, regardless of who that person was, was the strongest predictor of optimal performance both in being connected with an action officer and in consistency of connection times. Health departments can achieve optimal performance in consistently connecting a caller with an action officer in 30 minutes or less and may improve performance by using a telephone-based disease surveillance system in which the phone is answered by a live person at all times.

Application of controller partitioning optimization procedure to integrated flight/propulsion control design for a STOVL aircraft

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Schmidt, Phillip H.

1993-01-01

A parameter optimization framework has earlier been developed to solve the problem of partitioning a centralized controller into a decentralized, hierarchical structure suitable for integrated flight/propulsion control implementation. This paper presents results from the application of the controller partitioning optimization procedure to IFPC design for a Short Take-Off and Vertical Landing (STOVL) aircraft in transition flight. The controller partitioning problem and the parameter optimization algorithm are briefly described. Insight is provided into choosing various 'user' selected parameters in the optimization cost function such that the resulting optimized subcontrollers will meet the characteristics of the centralized controller that are crucial to achieving the desired closed-loop performance and robustness, while maintaining the desired subcontroller structure constraints that are crucial for IFPC implementation. The optimization procedure is shown to improve upon the initial partitioned subcontrollers and lead to performance comparable to that achieved with the centralized controller. This application also provides insight into the issues that should be addressed at the centralized control design level in order to obtain implementable partitioned subcontrollers.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Improving of the working process of axial compressors of gas turbine engines by using an optimization method

NASA Astrophysics Data System (ADS)

Marchukov, E.; Egorov, I.; Popov, G.; Baturin, O.; Goriachkin, E.; Novikova, Y.; Kolmakova, D.

2017-08-01

The article presents one optimization method for improving of the working process of an axial compressor of gas turbine engine. Developed method allows to perform search for the best geometry of compressor blades automatically by using optimization software IOSO and CFD software NUMECA Fine/Turbo. Optimization was performed by changing the form of the middle line in the three sections of each blade and shifts of three sections of the guide vanes in the circumferential and axial directions. The calculation of the compressor parameters was performed for work and stall point of its performance map on each optimization step. Study was carried out for seven-stage high-pressure compressor and three-stage low-pressure compressors. As a result of optimization, improvement of efficiency was achieved for all investigated compressors.

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

PubMed Central

Lancaster, Jenessa; Lorenz, Romy; Leech, Rob; Cole, James H.

2018-01-01

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm). For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm). This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian optimization framework to the new dataset, out-performing the parameters optimized for the initial training dataset. Our study outlines the proof-of-principle that neuroimaging models for brain-age prediction can use Bayesian optimization to derive case-specific pre-processing parameters. Our results suggest that different pre-processing parameters are selected when optimization is conducted in specific contexts. This potentially motivates use of optimization techniques at many different points during the experimental process, which may improve statistical sensitivity and reduce opportunities for experimenter-led bias. PMID:29483870

Risk modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

2013-09-01

Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

Comparison of evolutionary algorithms for LPDA antenna optimization

NASA Astrophysics Data System (ADS)

Lazaridis, Pavlos I.; Tziris, Emmanouil N.; Zaharis, Zaharias D.; Xenos, Thomas D.; Cosmas, John P.; Gallion, Philippe B.; Holmes, Violeta; Glover, Ian A.

2016-08-01

A novel approach to broadband log-periodic antenna design is presented, where some of the most powerful evolutionary algorithms are applied and compared for the optimal design of wire log-periodic dipole arrays (LPDA) using Numerical Electromagnetics Code. The target is to achieve an optimal antenna design with respect to maximum gain, gain flatness, front-to-rear ratio (F/R) and standing wave ratio. The parameters of the LPDA optimized are the dipole lengths, the spacing between the dipoles, and the dipole wire diameters. The evolutionary algorithms compared are the Differential Evolution (DE), Particle Swarm (PSO), Taguchi, Invasive Weed (IWO), and Adaptive Invasive Weed Optimization (ADIWO). Superior performance is achieved by the IWO (best results) and PSO (fast convergence) algorithms.

Routing performance analysis and optimization within a massively parallel computer

DOEpatents

Archer, Charles Jens; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen

2013-04-16

An apparatus, program product and method optimize the operation of a massively parallel computer system by, in part, receiving actual performance data concerning an application executed by the plurality of interconnected nodes, and analyzing the actual performance data to identify an actual performance pattern. A desired performance pattern may be determined for the application, and an algorithm may be selected from among a plurality of algorithms stored within a memory, the algorithm being configured to achieve the desired performance pattern based on the actual performance data.

Optimal Control-Based Adaptive NN Design for a Class of Nonlinear Discrete-Time Block-Triangular Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2016-11-01

In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.

Data Transfer Advisor with Transport Profiling Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S.; Liu, Qiang; Yun, Daqing

The network infrastructures have been rapidly upgraded in many high-performance networks (HPNs). However, such infrastructure investment has not led to corresponding performance improvement in big data transfer, especially at the application layer, largely due to the complexity of optimizing transport control on end hosts. We design and implement ProbData, a PRofiling Optimization Based DAta Transfer Advisor, to help users determine the most effective data transfer method with the most appropriate control parameter values to achieve the best data transfer performance. ProbData employs a profiling optimization based approach to exploit the optimal operational zone of various data transfer methods in supportmore » of big data transfer in extreme scale scientific applications. We present a theoretical framework of the optimized profiling approach employed in ProbData as wellas its detailed design and implementation. The advising procedure and performance benefits of ProbData are illustrated and evaluated by proof-of-concept experiments in real-life networks.« less

Exquisite Moments: Achieving Optimal Flow in Three Activity-Based Groups Regardless of Early-Childhood Adversity

ERIC Educational Resources Information Center

Thomson, Paula; Jaque, S. Victoria

2016-01-01

Flow experiences (also known as optimal performance) occur when people engage in activities they enjoy. The authors discuss such events in their study that examined a number of healthy, active individuals (performing artists, athletes, and others engaged in a range of recreational activities) and divided these into three groups based on adverse…

Measurement of damping and temperature: Precision bounds in Gaussian dissipative channels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Monras, Alex; Illuminati, Fabrizio

2011-01-15

We present a comprehensive analysis of the performance of different classes of Gaussian states in the estimation of Gaussian phase-insensitive dissipative channels. In particular, we investigate the optimal estimation of the damping constant and reservoir temperature. We show that, for two-mode squeezed vacuum probe states, the quantum-limited accuracy of both parameters can be achieved simultaneously. Moreover, we show that for both parameters two-mode squeezed vacuum states are more efficient than coherent, thermal, or single-mode squeezed states. This suggests that at high-energy regimes, two-mode squeezed vacuum states are optimal within the Gaussian setup. This optimality result indicates a stronger form ofmore » compatibility for the estimation of the two parameters. Indeed, not only the minimum variance can be achieved at fixed probe states, but also the optimal state is common to both parameters. Additionally, we explore numerically the performance of non-Gaussian states for particular parameter values to find that maximally entangled states within d-dimensional cutoff subspaces (d{<=}6) perform better than any randomly sampled states with similar energy. However, we also find that states with very similar performance and energy exist with much less entanglement than the maximally entangled ones.« less

Nozzle design study for a quasi-axisymmetric scramjet-powered vehicle at Mach 7.9 flight conditions

NASA Astrophysics Data System (ADS)

Tanimizu, Katsuyoshi; Mee, David J.; Stalker, Raymond J.; Jacobs, Peter A.

2013-09-01

A nozzle shape optimization study for a quasi-axisymmetric scramjet has been performed for a Mach 7.9 operating condition with hydrogen fuel, aiming at the application of a hypersonic airbreathing vehicle. In this study, the nozzle geometry which is parameterized by a set of design variables, is optimized for the single objective of maximum net thrust using an in-house CFD solver for inviscid flowfields with a simple force prediction methodology. The combustion is modelled using a simple chemical reaction code. The effects of the nozzle design on the overall vehicle performance are discussed. For the present geometry, net thrust is achieved for the optimized vehicle design. The results of the nozzle-optimization study show that performance is limited by the nozzle area ratio that can be incorporated into the vehicle without leading to too large a base diameter of the vehicle and increasing the external drag of the vehicle. This study indicates that it is very difficult to achieve positive thrust at Mach 7.9 using the basic geometry investigated.

Modeling of organic solar cell using response surface methodology

NASA Astrophysics Data System (ADS)

Suliman, Rajab; Mitul, Abu Farzan; Mohammad, Lal; Djira, Gemechis; Pan, Yunpeng; Qiao, Qiquan

Polymer solar cells have drawn much attention during the past few decades due to their low manufacturing cost and incompatibility for flexible substrates. In solution-processed organic solar cells, the optimal thickness, annealing temperature, and morphology are key components to achieving high efficiency. In this work, response surface methodology (RSM) is used to find optimal fabrication conditions for polymer solar cells. In order to optimize cell efficiency, the central composite design (CCD) with three independent variables polymer concentration, polymer-fullerene ratio, and active layer spinning speed was used. Optimal device performance was achieved using 10.25 mg/ml polymer concentration, 0.42 polymer-fullerene ratio, and 1624 rpm of active layer spinning speed. The predicted response (the efficiency) at the optimum stationary point was found to be 5.23% for the Poly(diketopyrrolopyrrole-terthiophene) (PDPP3T)/PC60BM solar cells. Moreover, 97% of the variation in the device performance was explained by the best model. Finally, the experimental results are consistent with the CCD prediction, which proves that this is a promising and appropriate model for optimum device performance and fabrication conditions.

Performance Optimization of Marine Science and Numerical Modeling on HPC Cluster

PubMed Central

Yang, Dongdong; Yang, Hailong; Wang, Luming; Zhou, Yucong; Zhang, Zhiyuan; Wang, Rui; Liu, Yi

2017-01-01

Marine science and numerical modeling (MASNUM) is widely used in forecasting ocean wave movement, through simulating the variation tendency of the ocean wave. Although efforts have been devoted to improve the performance of MASNUM from various aspects by existing work, there is still large space unexplored for further performance improvement. In this paper, we aim at improving the performance of propagation solver and data access during the simulation, in addition to the efficiency of output I/O and load balance. Our optimizations include several effective techniques such as the algorithm redesign, load distribution optimization, parallel I/O and data access optimization. The experimental results demonstrate that our approach achieves higher performance compared to the state-of-the-art work, about 3.5x speedup without degrading the prediction accuracy. In addition, the parameter sensitivity analysis shows our optimizations are effective under various topography resolutions and output frequencies. PMID:28045972

Fast approximation for joint optimization of segmentation, shape, and location priors, and its application in gallbladder segmentation.

PubMed

Saito, Atsushi; Nawano, Shigeru; Shimizu, Akinobu

2017-05-01

This paper addresses joint optimization for segmentation and shape priors, including translation, to overcome inter-subject variability in the location of an organ. Because a simple extension of the previous exact optimization method is too computationally complex, we propose a fast approximation for optimization. The effectiveness of the proposed approximation is validated in the context of gallbladder segmentation from a non-contrast computed tomography (CT) volume. After spatial standardization and estimation of the posterior probability of the target organ, simultaneous optimization of the segmentation, shape, and location priors is performed using a branch-and-bound method. Fast approximation is achieved by combining sampling in the eigenshape space to reduce the number of shape priors and an efficient computational technique for evaluating the lower bound. Performance was evaluated using threefold cross-validation of 27 CT volumes. Optimization in terms of translation of the shape prior significantly improved segmentation performance. The proposed method achieved a result of 0.623 on the Jaccard index in gallbladder segmentation, which is comparable to that of state-of-the-art methods. The computational efficiency of the algorithm is confirmed to be good enough to allow execution on a personal computer. Joint optimization of the segmentation, shape, and location priors was proposed, and it proved to be effective in gallbladder segmentation with high computational efficiency.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

NASA Astrophysics Data System (ADS)

Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai

2014-05-01

We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

Bonato, C; Blok, M S; Dinani, H T; Berry, D W; Markham, M L; Twitchen, D J; Hanson, R

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Optimized quantum sensing with a single electron spin using real-time adaptive measurements

NASA Astrophysics Data System (ADS)

Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

2016-03-01

Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

Using string invariants for prediction searching for optimal parameters

NASA Astrophysics Data System (ADS)

Bundzel, Marek; Kasanický, Tomáš; Pinčák, Richard

2016-02-01

We have developed a novel prediction method based on string invariants. The method does not require learning but a small set of parameters must be set to achieve optimal performance. We have implemented an evolutionary algorithm for the parametric optimization. We have tested the performance of the method on artificial and real world data and compared the performance to statistical methods and to a number of artificial intelligence methods. We have used data and the results of a prediction competition as a benchmark. The results show that the method performs well in single step prediction but the method's performance for multiple step prediction needs to be improved. The method works well for a wide range of parameters.

Robust optimization of front members in a full frontal car impact

NASA Astrophysics Data System (ADS)

Aspenberg (né Lönn), David; Jergeus, Johan; Nilsson, Larsgunnar

2013-03-01

In the search for lightweight automobile designs, it is necessary to assure that robust crashworthiness performance is achieved. Structures that are optimized to handle a finite number of load cases may perform poorly when subjected to various dispersions. Thus, uncertainties must be accounted for in the optimization process. This article presents an approach to optimization where all design evaluations include an evaluation of the robustness. Metamodel approximations are applied both to the design space and the robustness evaluations, using artifical neural networks and polynomials, respectively. The features of the robust optimization approach are displayed in an analytical example, and further demonstrated in a large-scale design example of front side members of a car. Different optimization formulations are applied and it is shown that the proposed approach works well. It is also concluded that a robust optimization puts higher demands on the finite element model performance than normally.

Electrochemical model based charge optimization for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Pramanik, Sourav; Anwar, Sohel

2016-05-01

In this paper, we propose the design of a novel optimal strategy for charging the lithium-ion battery based on electrochemical battery model that is aimed at improved performance. A performance index that aims at minimizing the charging effort along with a minimum deviation from the rated maximum thresholds for cell temperature and charging current has been defined. The method proposed in this paper aims at achieving a faster charging rate while maintaining safe limits for various battery parameters. Safe operation of the battery is achieved by including the battery bulk temperature as a control component in the performance index which is of critical importance for electric vehicles. Another important aspect of the performance objective proposed here is the efficiency of the algorithm that would allow higher charging rates without compromising the internal electrochemical kinetics of the battery which would prevent abusive conditions, thereby improving the long term durability. A more realistic model, based on battery electro-chemistry has been used for the design of the optimal algorithm as opposed to the conventional equivalent circuit models. To solve the optimization problem, Pontryagins principle has been used which is very effective for constrained optimization problems with both state and input constraints. Simulation results show that the proposed optimal charging algorithm is capable of shortening the charging time of a lithium ion cell while maintaining the temperature constraint when compared with the standard constant current charging. The designed method also maintains the internal states within limits that can avoid abusive operating conditions.

GPU accelerated particle visualization with Splotch

NASA Astrophysics Data System (ADS)

Rivi, M.; Gheller, C.; Dykes, T.; Krokos, M.; Dolag, K.

2014-07-01

Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organization and classification of particles. We deploy a reference cosmological simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimizations and exploitation of hybrid systems and emerging accelerators.

An optimized and low-cost FPGA-based DNA sequence alignment--a step towards personal genomics.

PubMed

Shah, Hurmat Ali; Hasan, Laiq; Ahmad, Nasir

2013-01-01

DNA sequence alignment is a cardinal process in computational biology but also is much expensive computationally when performing through traditional computational platforms like CPU. Of many off the shelf platforms explored for speeding up the computation process, FPGA stands as the best candidate due to its performance per dollar spent and performance per watt. These two advantages make FPGA as the most appropriate choice for realizing the aim of personal genomics. The previous implementation of DNA sequence alignment did not take into consideration the price of the device on which optimization was performed. This paper presents optimization over previous FPGA implementation that increases the overall speed-up achieved as well as the price incurred by the platform that was optimized. The optimizations are (1) The array of processing elements is made to run on change in input value and not on clock, so eliminating the need for tight clock synchronization, (2) the implementation is unrestrained by the size of the sequences to be aligned, (3) the waiting time required for the sequences to load to FPGA is reduced to the minimum possible and (4) an efficient method is devised to store the output matrix that make possible to save the diagonal elements to be used in next pass, in parallel with the computation of output matrix. Implemented on Spartan3 FPGA, this implementation achieved 20 times performance improvement in terms of CUPS over GPP implementation.

Physics issues in diffraction limited storage ring design

NASA Astrophysics Data System (ADS)

Fan, Wei; Bai, ZhengHe; Gao, WeiWei; Feng, GuangYao; Li, WeiMin; Wang, Lin; He, DuoHui

2012-05-01

Diffraction limited electron storage ring is considered a promising candidate for future light sources, whose main characteristics are higher brilliance, better transverse coherence and better stability. The challenge of diffraction limited storage ring design is how to achieve the ultra low beam emittance with acceptable nonlinear performance. Effective linear and nonlinear parameter optimization methods based on Artificial Intelligence were developed for the storage ring physical design. As an example of application, partial physical design of HALS (Hefei Advanced Light Source), which is a diffraction limited VUV and soft X-ray light source, was introduced. Severe emittance growth due to the Intra Beam Scattering effect, which is the main obstacle to achieve ultra low emittance, was estimated quantitatively and possible cures were discussed. It is inspiring that better performance of diffraction limited storage ring can be achieved in principle with careful parameter optimization.

Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

DOE PAGES

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok; ...

2016-01-01

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok

Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

Joint optimization of source, mask, and pupil in optical lithography

NASA Astrophysics Data System (ADS)

Li, Jia; Lam, Edmund Y.

2014-03-01

Mask topography effects need to be taken into consideration for more advanced resolution enhancement techniques in optical lithography. However, rigorous 3D mask model achieves high accuracy at a large computational cost. This work develops a combined source, mask and pupil optimization (SMPO) approach by taking advantage of the fact that pupil phase manipulation is capable of partially compensating for mask topography effects. We first design the pupil wavefront function by incorporating primary and secondary spherical aberration through the coefficients of the Zernike polynomials, and achieve optimal source-mask pair under the condition of aberrated pupil. Evaluations against conventional source mask optimization (SMO) without incorporating pupil aberrations show that SMPO provides improved performance in terms of pattern fidelity and process window sizes.

Analysis of the Characteristics of a Rotary Stepper Micromotor

NASA Astrophysics Data System (ADS)

Sone, Junji; Mizuma, Toshinari; Masunaga, Masakazu; Mochizuki, Shunsuke; Sarajic, Edin; Yamahata, Christophe; Fujita, Hiroyuki

A 3-phase electrostatic stepper micromotor was developed. To improve its performance for actual use, we have conducted numerical simulation to optimize the design. An improved simulation method is needed for calculation of various cases. To conduct circuit simulation of this micromotor, its structure is simplified, and a function for computing the force excited by the electrostatic field is added to the circuit simulator. We achieved a reasonably accurate simulation. We also considered an optimal drive waveform to achieve low-voltage operation.

A hybrid multi-objective evolutionary algorithm for wind-turbine blade optimization

NASA Astrophysics Data System (ADS)

Sessarego, M.; Dixon, K. R.; Rival, D. E.; Wood, D. H.

2015-08-01

A concurrent-hybrid non-dominated sorting genetic algorithm (hybrid NSGA-II) has been developed and applied to the simultaneous optimization of the annual energy production, flapwise root-bending moment and mass of the NREL 5 MW wind-turbine blade. By hybridizing a multi-objective evolutionary algorithm (MOEA) with gradient-based local search, it is believed that the optimal set of blade designs could be achieved in lower computational cost than for a conventional MOEA. To measure the convergence between the hybrid and non-hybrid NSGA-II on a wind-turbine blade optimization problem, a computationally intensive case was performed using the non-hybrid NSGA-II. From this particular case, a three-dimensional surface representing the optimal trade-off between the annual energy production, flapwise root-bending moment and blade mass was achieved. The inclusion of local gradients in the blade optimization, however, shows no improvement in the convergence for this three-objective problem.

Design of materials with prescribed nonlinear properties

NASA Astrophysics Data System (ADS)

Wang, F.; Sigmund, O.; Jensen, J. S.

2014-09-01

We systematically design materials using topology optimization to achieve prescribed nonlinear properties under finite deformation. Instead of a formal homogenization procedure, a numerical experiment is proposed to evaluate the material performance in longitudinal and transverse tensile tests under finite deformation, i.e. stress-strain relations and Poissons ratio. By minimizing errors between actual and prescribed properties, materials are tailored to achieve the target. Both two dimensional (2D) truss-based and continuum materials are designed with various prescribed nonlinear properties. The numerical examples illustrate optimized materials with rubber-like behavior and also optimized materials with extreme strain-independent Poissons ratio for axial strain intervals of εi∈[0.00, 0.30].

Delta-doping optimization for high quality p-type GaN

NASA Astrophysics Data System (ADS)

Bayram, C.; Pau, J. L.; McClintock, R.; Razeghi, M.

2008-10-01

Delta (δ -) doping is studied in order to achieve high quality p-type GaN. Atomic force microscopy, x-ray diffraction, photoluminescence, and Hall measurements are performed on the samples to optimize the δ-doping characteristics. The effect of annealing on the electrical, optical, and structural quality is also investigated for different δ-doping parameters. Optimized pulsing conditions result in layers with hole concentrations near 1018 cm-3 and superior crystal quality compared to conventional p-GaN. This material improvement is achieved thanks to the reduction in the Mg activation energy and self-compensation effects in δ-doped p-GaN.

Achievable rate maximization for decode-and-forward MIMO-OFDM networks with an energy harvesting relay.

PubMed

Du, Guanyao; Yu, Jianjun

2016-01-01

This paper investigates the system achievable rate for the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system with an energy harvesting (EH) relay. Firstly we propose two protocols, time switching-based decode-and-forward relaying (TSDFR) and a flexible power splitting-based DF relaying (PSDFR) protocol by considering two practical receiver architectures, to enable the simultaneous information processing and energy harvesting at the relay. In PSDFR protocol, we introduce a temporal parameter to describe the time division pattern between the two phases which makes the protocol more flexible and general. In order to explore the system performance limit, we discuss the system achievable rate theoretically and formulate two optimization problems for the proposed protocols to maximize the system achievable rate. Since the problems are non-convex and difficult to solve, we first analyze them theoretically and get some explicit results, then design an augmented Lagrangian penalty function (ALPF) based algorithm for them. Numerical results are provided to validate the accuracy of our analytical results and the effectiveness of the proposed ALPF algorithm. It is shown that, PSDFR outperforms TSDFR to achieve higher achievable rate in such a MIMO-OFDM relaying system. Besides, we also investigate the impacts of the relay location, the number of antennas and the number of subcarriers on the system performance. Specifically, it is shown that, the relay position greatly affects the system performance of both protocols, and relatively worse achievable rate is achieved when the relay is placed in the middle of the source and the destination. This is different from the MIMO-OFDM DF relaying system without EH. Moreover, the optimal factor which indicates the time division pattern between the two phases in the PSDFR protocol is always above 0.8, which means that, the common division of the total transmission time into two equal phases in previous work applying PS-based receiver is not optimal.

NASA Human Health and Performance Information Architecture Panel

NASA Technical Reports Server (NTRS)

Johnson-Throop, Kathy; Kadwa, Binafer; VanBaalen, Mary

2014-01-01

The Human Health and Performance (HH&P) Directorate at NASA's Johnson Space Center has a mission to enable optimization of human health and performance throughout all phases of spaceflight. All HH&P functions are ultimately aimed at achieving this mission. Our activities enable mission success, optimizing human health and productivity in space before, during, and after the actual spaceflight experience of our crews, and include support for ground-based functions. Many of our spaceflight innovations also provide solutions for terrestrial challenges, thereby enhancing life on Earth.

Performance optimization of dense-array concentrator photovoltaic system considering effects of circumsolar radiation and slope error.

PubMed

Wong, Chee-Woon; Chong, Kok-Keong; Tan, Ming-Hui

2015-07-27

This paper presents an approach to optimize the electrical performance of dense-array concentrator photovoltaic system comprised of non-imaging dish concentrator by considering the circumsolar radiation and slope error effects. Based on the simulated flux distribution, a systematic methodology to optimize the layout configuration of solar cells interconnection circuit in dense array concentrator photovoltaic module has been proposed by minimizing the current mismatch caused by non-uniformity of concentrated sunlight. An optimized layout of interconnection solar cells circuit with minimum electrical power loss of 6.5% can be achieved by minimizing the effects of both circumsolar radiation and slope error.

Optimizing piezoelectric receivers for acoustic power transfer applications

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2018-07-01

In this paper, we aim to optimize piezoelectric plate receivers for acoustic power transfer applications by analyzing the influence of the losses and of the acoustic boundary conditions. We derive the analytic expressions of the efficiency of the receiver with the optimal electric loads attached, and analyze the maximum efficiency value and its frequency with different loss and acoustic boundary conditions. To validate the analytical expressions that we have derived, we perform experiments in water with composite transducers of different filling fractions, and see that a lower acoustic impedance mismatch can compensate the influence of large dielectric and acoustic losses to achieve a good performance. Finally, we briefly compare the advantages and drawbacks of composite transducers and pure PZT (lead zirconate titanate) plates as acoustic power receivers, and conclude that 1–3 composites can achieve similar efficiency values in low power applications due to their adjustable acoustic impedance.

Aerodynamic optimization of supersonic compressor cascade using differential evolution on GPU

NASA Astrophysics Data System (ADS)

Aissa, Mohamed Hasanine; Verstraete, Tom; Vuik, Cornelis

2016-06-01

Differential Evolution (DE) is a powerful stochastic optimization method. Compared to gradient-based algorithms, DE is able to avoid local minima but requires at the same time more function evaluations. In turbomachinery applications, function evaluations are performed with time-consuming CFD simulation, which results in a long, non affordable, design cycle. Modern High Performance Computing systems, especially Graphic Processing Units (GPUs), are able to alleviate this inconvenience by accelerating the design evaluation itself. In this work we present a validated CFD Solver running on GPUs, able to accelerate the design evaluation and thus the entire design process. An achieved speedup of 20x to 30x enabled the DE algorithm to run on a high-end computer instead of a costly large cluster. The GPU-enhanced DE was used to optimize the aerodynamics of a supersonic compressor cascade, achieving an aerodynamic loss minimization of 20%.

Optimized Two-Party Video Chat with Restored Eye Contact Using Graphics Hardware

NASA Astrophysics Data System (ADS)

Dumont, Maarten; Rogmans, Sammy; Maesen, Steven; Bekaert, Philippe

We present a practical system prototype to convincingly restore eye contact between two video chat participants, with a minimal amount of constraints. The proposed six-fold camera setup is easily integrated into the monitor frame, and is used to interpolate an image as if its virtual camera captured the image through a transparent screen. The peer user has a large freedom of movement, resulting in system specifications that enable genuine practical usage. Our software framework thereby harnesses the powerful computational resources inside graphics hardware, and maximizes arithmetic intensity to achieve over real-time performance up to 42 frames per second for 800 ×600 resolution images. Furthermore, an optimal set of fine tuned parameters are presented, that optimizes the end-to-end performance of the application to achieve high subjective visual quality, and still allows for further algorithmic advancement without loosing its real-time capabilities.

Aerodynamic optimization of supersonic compressor cascade using differential evolution on GPU

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aissa, Mohamed Hasanine; Verstraete, Tom; Vuik, Cornelis

Differential Evolution (DE) is a powerful stochastic optimization method. Compared to gradient-based algorithms, DE is able to avoid local minima but requires at the same time more function evaluations. In turbomachinery applications, function evaluations are performed with time-consuming CFD simulation, which results in a long, non affordable, design cycle. Modern High Performance Computing systems, especially Graphic Processing Units (GPUs), are able to alleviate this inconvenience by accelerating the design evaluation itself. In this work we present a validated CFD Solver running on GPUs, able to accelerate the design evaluation and thus the entire design process. An achieved speedup of 20xmore » to 30x enabled the DE algorithm to run on a high-end computer instead of a costly large cluster. The GPU-enhanced DE was used to optimize the aerodynamics of a supersonic compressor cascade, achieving an aerodynamic loss minimization of 20%.« less

Robust optimization of a tandem grating solar thermal absorber

NASA Astrophysics Data System (ADS)

Choi, Jongin; Kim, Mingeon; Kang, Kyeonghwan; Lee, Ikjin; Lee, Bong Jae

2018-04-01

Ideal solar thermal absorbers need to have a high value of the spectral absorptance in the broad solar spectrum to utilize the solar radiation effectively. Majority of recent studies about solar thermal absorbers focus on achieving nearly perfect absorption using nanostructures, whose characteristic dimension is smaller than the wavelength of sunlight. However, precise fabrication of such nanostructures is not easy in reality; that is, unavoidable errors always occur to some extent in the dimension of fabricated nanostructures, causing an undesirable deviation of the absorption performance between the designed structure and the actually fabricated one. In order to minimize the variation in the solar absorptance due to the fabrication error, the robust optimization can be performed during the design process. However, the optimization of solar thermal absorber considering all design variables often requires tremendous computational costs to find an optimum combination of design variables with the robustness as well as the high performance. To achieve this goal, we apply the robust optimization using the Kriging method and the genetic algorithm for designing a tandem grating solar absorber. By constructing a surrogate model through the Kriging method, computational cost can be substantially reduced because exact calculation of the performance for every combination of variables is not necessary. Using the surrogate model and the genetic algorithm, we successfully design an effective solar thermal absorber exhibiting a low-level of performance degradation due to the fabrication uncertainty of design variables.

Tuning HDF5 for Lustre File Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howison, Mark; Koziol, Quincey; Knaak, David

2010-09-24

HDF5 is a cross-platform parallel I/O library that is used by a wide variety of HPC applications for the flexibility of its hierarchical object-database representation of scientific data. We describe our recent work to optimize the performance of the HDF5 and MPI-IO libraries for the Lustre parallel file system. We selected three different HPC applications to represent the diverse range of I/O requirements, and measured their performance on three different systems to demonstrate the robustness of our optimizations across different file system configurations and to validate our optimization strategy. We demonstrate that the combined optimizations improve HDF5 parallel I/O performancemore » by up to 33 times in some cases running close to the achievable peak performance of the underlying file system and demonstrate scalable performance up to 40,960-way concurrency.« less

A novel high-performance self-powered ultraviolet photodetector: Concept, analytical modeling and analysis

NASA Astrophysics Data System (ADS)

Ferhati, H.; Djeffal, F.

2017-12-01

In this paper, a new MSM-UV-photodetector (PD) based on dual wide band-gap material (DM) engineering aspect is proposed to achieve high-performance self-powered device. Comprehensive analytical models for the proposed sensor photocurrent and the device properties are developed incorporating the impact of DM aspect on the device photoelectrical behavior. The obtained results are validated with the numerical data using commercial TCAD software. Our investigation demonstrates that the adopted design amendment modulates the electric field in the device, which provides the possibility to drive appropriate photo-generated carriers without an external applied voltage. This phenomenon suggests achieving the dual role of effective carriers' separation and an efficient reduce of the dark current. Moreover, a new hybrid approach based on analytical modeling and Particle Swarm Optimization (PSO) is proposed to achieve improved photoelectric behavior at zero bias that can ensure favorable self-powered MSM-based UV-PD. It is found that the proposed design methodology has succeeded in identifying the optimized design that offers a self-powered device with high-responsivity (98 mA/W) and superior ION/IOFF ratio (480 dB). These results make the optimized MSM-UV-DM-PD suitable for providing low cost self-powered devices for high-performance optical communication and monitoring applications.

Integrated multidisciplinary design optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Mantay, Wayne R.

1989-01-01

The NASA/Army research plan for developing the logic elements for helicopter rotor design optimization by integrating appropriate disciplines and accounting for important interactions among the disciplines is discussed. The paper describes the optimization formulation in terms of the objective function, design variables, and constraints. The analysis aspects are discussed, and an initial effort at defining the interdisciplinary coupling is summarized. Results are presented on the achievements made in the rotor aerodynamic performance optimization for minimum hover horsepower, rotor dynamic optimization for vibration reduction, rotor structural optimization for minimum weight, and integrated aerodynamic load/dynamics optimization for minimum vibration and weight.

Optimal Design of Calibration Signals in Space-Borne Gravitational Wave Detectors

NASA Technical Reports Server (NTRS)

Nofrarias, Miquel; Karnesis, Nikolaos; Gibert, Ferran; Armano, Michele; Audley, Heather; Danzmann, Karsten; Diepholz, Ingo; Dolesi, Rita; Ferraioli, Luigi; Ferroni, Valerio;

Optimal Design of Calibration Signals in Space Borne Gravitational Wave Detectors

NASA Technical Reports Server (NTRS)

Nofrarias, Miquel; Karnesis, Nikolaos; Gibert, Ferran; Armano, Michele; Audley, Heather; Danzmann, Karsten; Diepholz, Ingo; Dolesi, Rita; Ferraioli, Luigi; Thorpe, James I.

2014-01-01

Future space borne gravitational wave detectors will require a precise definition of calibration signals to ensure the achievement of their design sensitivity. The careful design of the test signals plays a key role in the correct understanding and characterization of these instruments. In that sense, methods achieving optimal experiment designs must be considered as complementary to the parameter estimation methods being used to determine the parameters describing the system. The relevance of experiment design is particularly significant for the LISA Pathfinder mission, which will spend most of its operation time performing experiments to characterize key technologies for future space borne gravitational wave observatories. Here we propose a framework to derive the optimal signals in terms of minimum parameter uncertainty to be injected to these instruments during its calibration phase. We compare our results with an alternative numerical algorithm which achieves an optimal input signal by iteratively improving an initial guess. We show agreement of both approaches when applied to the LISA Pathfinder case.

Aerodynamic design optimization of a fuel efficient high-performance, single-engine, business airplane

NASA Technical Reports Server (NTRS)

Holmes, B. J.

1980-01-01

A design study has been conducted to optimize a single-engine airplane for a high-performance cruise mission. The mission analyzed included a cruise speed of about 300 knots, a cruise range of about 1300 nautical miles, and a six-passenger payload (5340 N (1200 lb)). The purpose of the study is to investigate the combinations of wing design, engine, and operating altitude required for the mission. The results show that these mission performance characteristics can be achieved with fuel efficiencies competitive with present-day high-performance, single- and twin-engine, business airplanes. It is noted that relaxation of the present Federal Aviation Regulation, Part 23, stall-speed requirement for single-engine airplanes facilitates the optimization of the airplane for fuel efficiency.

Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design.

PubMed

Bertocci, Francesco; Fort, Ada; Vignoli, Valerio; Mugnaini, Marco; Berni, Rossella

2017-06-10

Eight different types of nanostructured perovskites based on YCoO 3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO 2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo 0 . 9 Pd 0 . 1 O 3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312 ∘ C for CO (284 ppm, from design) and response equal to -14.17% at 185 ∘ C for NO 2 (16 ppm, from design). Analogously, for NO 2 (16 ppm, from design), the material type YCo 0 . 9 O 2 . 85 + 1 % Pd (Mt8) allows for optimizing the response value at - 15 . 39 % with a working temperature at 181 . 0 ∘ C, whereas for YCo 0 . 95 Pd 0 . 05 O 3 (Mt3), the best response value is achieved at - 15 . 40 % with the temperature equal to 204 ∘ C.

Optimization of Perovskite Gas Sensor Performance: Characterization, Measurement and Experimental Design

PubMed Central

Bertocci, Francesco; Fort, Ada; Vignoli, Valerio; Mugnaini, Marco; Berni, Rossella

2017-01-01

Eight different types of nanostructured perovskites based on YCoO3 with different chemical compositions are prepared as gas sensor materials, and they are studied with two target gases NO2 and CO. Moreover, a statistical approach is adopted to optimize their performance. The innovative contribution is carried out through a split-plot design planning and modeling, also involving random effects, for studying Metal Oxide Semiconductors (MOX) sensors in a robust design context. The statistical results prove the validity of the proposed approach; in fact, for each material type, the variation of the electrical resistance achieves a satisfactory optimized value conditional to the working temperature and by controlling for the gas concentration variability. Just to mention some results, the sensing material YCo0.9Pd0.1O3 (Mt1) achieved excellent solutions during the optimization procedure. In particular, Mt1 resulted in being useful and feasible for the detection of both gases, with optimal response equal to +10.23% and working temperature at 312∘C for CO (284 ppm, from design) and response equal to −14.17% at 185∘C for NO2 (16 ppm, from design). Analogously, for NO2 (16 ppm, from design), the material type YCo0.9O2.85+1%Pd (Mt8) allows for optimizing the response value at −15.39% with a working temperature at 181.0∘C, whereas for YCo0.95Pd0.05O3 (Mt3), the best response value is achieved at −15.40% with the temperature equal to 204∘C. PMID:28604587

Comparison of different treatment planning optimization methods for vaginal HDR brachytherapy with multichannel applicators: A reduction of the high doses to the vaginal mucosa is possible.

PubMed

Carrara, Mauro; Cusumano, Davide; Giandini, Tommaso; Tenconi, Chiara; Mazzarella, Ester; Grisotto, Simone; Massari, Eleonora; Mazzeo, Davide; Cerrotta, Annamaria; Pappalardi, Brigida; Fallai, Carlo; Pignoli, Emanuele

2017-12-01

A direct planning approach with multi-channel vaginal cylinders (MVCs) used for HDR brachytherapy of vaginal cancers is particularly challenging. Purpose of this study was to compare the dosimetric performances of different forward and inverse methods used for the optimization of MVC-based vaginal treatments for endometrial cancer, with a particular attention to the definition of strategies useful to limit the high doses to the vaginal mucosa. Twelve postoperative vaginal HDR brachytherapy treatments performed with MVCs were considered. Plans were retrospectively optimized with three different methods: Dose Point Optimization followed by Graphical Optimization (DPO + GrO), Inverse Planning Simulated Annealing with two different class solutions as starting conditions (surflPSA and homogIPSA) and Hybrid Inverse Planning Optimization (HIPO). Several dosimetric parameters related to target coverage, hot spot extensions and sparing of organs at risk were analyzed to evaluate the quality of the achieved treatment plans. Dose homogeneity index (DHI), conformal index (COIN) and a further parameter quantifying the proportion of the central catheter loading with respect to the overall loading (i.e., the central catheter loading index: CCLI) were also quantified. The achieved PTV coverage parameters were highly correlated with each other but uncorrelated with the hot spot quantifiers. HomogIPSA and HIPO achieved higher DHIs and CCLIs and lower volumes of high doses than DPO + GrO and surflPSA. Within the investigated optimization methods, HIPO and homoglPSA showed the highest dose homogeneity to the target. In particular, homogIPSA resulted also the most effective in reducing hot spots to the vaginal mucosa. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Heifer body weight gain and reproductive achievement in response to protein and energy supplementation while grazing dormant range forage

USDA-ARS?s Scientific Manuscript database

Heifers grazing winter range require supplemental nutrients to compliment dormant forage to achieve optimal growth and performance. A study was conducted to evaluate nutritional environment and effect of different supplementation strategies for developing heifers grazing dormant winter range. Eigh...

Optimization of an electrokinetic mixer for microfluidic applications.

PubMed

Bockelmann, Hendryk; Heuveline, Vincent; Barz, Dominik P J

2012-06-01

This work is concerned with the investigation of the concentration fields in an electrokinetic micromixer and its optimization in order to achieve high mixing rates. The mixing concept is based on the combination of an alternating electrical excitation applied to a pressure-driven base flow in a meandering microchannel geometry. The electrical excitation induces a secondary electrokinetic velocity component, which results in a complex flow field within the meander bends. A mathematical model describing the physicochemical phenomena present within the micromixer is implemented in an in-house finite-element-method code. We first perform simulations comparable to experiments concerned with the investigation of the flow field in the bends. The comparison of the complex flow topology found in simulation and experiment reveals excellent agreement. Hence, the validated model and numerical schemes are employed for a numerical optimization of the micromixer performance. In detail, we optimize the secondary electrokinetic flow by finding the best electrical excitation parameters, i.e., frequency and amplitude, for a given waveform. Two optimized electrical excitations featuring a discrete and a continuous waveform are discussed with respect to characteristic time scales of our mixing problem. The results demonstrate that the micromixer is able to achieve high mixing degrees very rapidly.

Optimization of an electrokinetic mixer for microfluidic applications

PubMed Central

Bockelmann, Hendryk; Heuveline, Vincent; Barz, Dominik P. J.

2012-01-01

This work is concerned with the investigation of the concentration fields in an electrokinetic micromixer and its optimization in order to achieve high mixing rates. The mixing concept is based on the combination of an alternating electrical excitation applied to a pressure-driven base flow in a meandering microchannel geometry. The electrical excitation induces a secondary electrokinetic velocity component, which results in a complex flow field within the meander bends. A mathematical model describing the physicochemical phenomena present within the micromixer is implemented in an in-house finite-element-method code. We first perform simulations comparable to experiments concerned with the investigation of the flow field in the bends. The comparison of the complex flow topology found in simulation and experiment reveals excellent agreement. Hence, the validated model and numerical schemes are employed for a numerical optimization of the micromixer performance. In detail, we optimize the secondary electrokinetic flow by finding the best electrical excitation parameters, i.e., frequency and amplitude, for a given waveform. Two optimized electrical excitations featuring a discrete and a continuous waveform are discussed with respect to characteristic time scales of our mixing problem. The results demonstrate that the micromixer is able to achieve high mixing degrees very rapidly. PMID:22712034

A systematic optimization for graphene-based supercapacitors

NASA Astrophysics Data System (ADS)

Deuk Lee, Sung; Lee, Han Sung; Kim, Jin Young; Jeong, Jaesik; Kahng, Yung Ho

2017-08-01

Increasing the energy-storage density for supercapacitors is critical for their applications. Many researchers have attempted to identify optimal candidate component materials to achieve this goal, but investigations into systematically optimizing their mixing rate for maximizing the performance of each candidate material have been insufficient, which hinders the progress in their technology. In this study, we employ a statistically systematic method to determine the optimum mixing ratio of three components that constitute graphene-based supercapacitor electrodes: reduced graphene oxide (rGO), acetylene black (AB), and polyvinylidene fluoride (PVDF). By using the extreme-vertices design, the optimized proportion is determined to be (rGO: AB: PVDF  =  0.95: 0.00: 0.05). The corresponding energy-storage density increases by a factor of 2 compared with that of non-optimized electrodes. Electrochemical and microscopic analyses are performed to determine the reason for the performance improvements.

Extended Information Ratio for Portfolio Optimization Using Simulated Annealing with Constrained Neighborhood

NASA Astrophysics Data System (ADS)

Orito, Yukiko; Yamamoto, Hisashi; Tsujimura, Yasuhiro; Kambayashi, Yasushi

The portfolio optimizations are to determine the proportion-weighted combination in the portfolio in order to achieve investment targets. This optimization is one of the multi-dimensional combinatorial optimizations and it is difficult for the portfolio constructed in the past period to keep its performance in the future period. In order to keep the good performances of portfolios, we propose the extended information ratio as an objective function, using the information ratio, beta, prime beta, or correlation coefficient in this paper. We apply the simulated annealing (SA) to optimize the portfolio employing the proposed ratio. For the SA, we make the neighbor by the operation that changes the structure of the weights in the portfolio. In the numerical experiments, we show that our portfolios keep the good performances when the market trend of the future period becomes different from that of the past period.

A Simple Analytic Model for Estimating Mars Ascent Vehicle Mass and Performance

NASA Technical Reports Server (NTRS)

Woolley, Ryan C.

2014-01-01

The Mars Ascent Vehicle (MAV) is a crucial component in any sample return campaign. In this paper we present a universal model for a two-stage MAV along with the analytic equations and simple parametric relationships necessary to quickly estimate MAV mass and performance. Ascent trajectories can be modeled as two-burn transfers from the surface with appropriate loss estimations for finite burns, steering, and drag. Minimizing lift-off mass is achieved by balancing optimized staging and an optimized path-to-orbit. This model allows designers to quickly find optimized solutions and to see the effects of design choices.

Parallel Aircraft Trajectory Optimization with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Falck, Robert D.; Gray, Justin S.; Naylor, Bret

2016-01-01

Trajectory optimization is an integral component for the design of aerospace vehicles, but emerging aircraft technologies have introduced new demands on trajectory analysis that current tools are not well suited to address. Designing aircraft with technologies such as hybrid electric propulsion and morphing wings requires consideration of the operational behavior as well as the physical design characteristics of the aircraft. The addition of operational variables can dramatically increase the number of design variables which motivates the use of gradient based optimization with analytic derivatives to solve the larger optimization problems. In this work we develop an aircraft trajectory analysis tool using a Legendre-Gauss-Lobatto based collocation scheme, providing analytic derivatives via the OpenMDAO multidisciplinary optimization framework. This collocation method uses an implicit time integration scheme that provides a high degree of sparsity and thus several potential options for parallelization. The performance of the new implementation was investigated via a series of single and multi-trajectory optimizations using a combination of parallel computing and constraint aggregation. The computational performance results show that in order to take full advantage of the sparsity in the problem it is vital to parallelize both the non-linear analysis evaluations and the derivative computations themselves. The constraint aggregation results showed a significant numerical challenge due to difficulty in achieving tight convergence tolerances. Overall, the results demonstrate the value of applying analytic derivatives to trajectory optimization problems and lay the foundation for future application of this collocation based method to the design of aircraft with where operational scheduling of technologies is key to achieving good performance.

An inverse dynamics approach to trajectory optimization for an aerospace plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1992-01-01

An inverse dynamics approach for trajectory optimization is proposed. This technique can be useful in many difficult trajectory optimization and control problems. The application of the approach is exemplified by ascent trajectory optimization for an aerospace plane. Both minimum-fuel and minimax types of performance indices are considered. When rocket augmentation is available for ascent, it is shown that accurate orbital insertion can be achieved through the inverse control of the rocket in the presence of disturbances.

Optimizing spacecraft design - optimization engine development : progress and plans

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Feather, Martin S.; Dunphy, Julia R; Salcedo, Jose; Menzies, Tim

2003-01-01

At JPL and NASA, a process has been developed to perform life cycle risk management. This process requires users to identify: goals and objectives to be achieved (and their relative priorities), the various risks to achieving those goals and objectives, and options for risk mitigation (prevention, detection ahead of time, and alleviation). Risks are broadly defined to include the risk of failing to design a system with adequate performance, compatibility and robustness in addition to more traditional implementation and operational risks. The options for mitigating these different kinds of risks can include architectural and design choices, technology plans and technology back-up options, test-bed and simulation options, engineering models and hardware/software development techniques and other more traditional risk reduction techniques.

An optimized implementation of a fault-tolerant clock synchronization circuit

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

1995-01-01

A fault-tolerant clock synchronization circuit was designed and tested. A comparison to a previous design and the procedure followed to achieve the current optimization are included. The report also includes a description of the system and the results of tests performed to study the synchronization and fault-tolerant characteristics of the implementation.

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Southern Medical University, Guangzhou, Guangdong; Tian, Z

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subjectmore » to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.« less

Optimization and performance improvement of an electromagnetic-type energy harvester with consideration of human walking vibration

NASA Astrophysics Data System (ADS)

Seo, Jongho; Kim, Jin-Su; Jeong, Un-Chang; Kim, Yong-Dae; Kim, Young-Cheol; Lee, Hanmin; Oh, Jae-Eung

2016-02-01

In this study, we derived an equation of motion for an electromechanical system in view of the components and working mechanism of an electromagnetic-type energy harvester (ETEH). An electromechanical transduction factor (ETF) was calculated using a finite-element analysis (FEA) based on Maxwell's theory. The experimental ETF of the ETEH measured by means of sine wave excitation was compared with and FEA data. Design parameters for the stationary part of the energy harvester were optimized in terms of the power performance by using a response surface method (RSM). With optimized design parameters, the ETEH showed an improvement in performance. We experimented with the optimized ETEH (OETEH) with respect to changes in the external excitation frequency and the load resistance by taking human body vibration in to account. The OETEH achieved a performance improvement of about 30% compared to the initial model.

Experiences in autotuning matrix multiplication for energy minimization on GPUs

DOE PAGES

Anzt, Hartwig; Haugen, Blake; Kurzak, Jakub; ...

2015-05-20

In this study, we report extensive results and analysis of autotuning the computationally intensive graphics processing units kernel for dense matrix–matrix multiplication in double precision. In contrast to traditional autotuning and/or optimization for runtime performance only, we also take the energy efficiency into account. For kernels achieving equal performance, we show significant differences in their energy balance. We also identify the memory throughput as the most influential metric that trades off performance and energy efficiency. Finally, as a result, the performance optimal case ends up not being the most efficient kernel in overall resource use.

EmptyHeaded: A Relational Engine for Graph Processing

PubMed Central

Aberger, Christopher R.; Tu, Susan; Olukotun, Kunle; Ré, Christopher

2016-01-01

There are two types of high-performance graph processing engines: low- and high-level engines. Low-level engines (Galois, PowerGraph, Snap) provide optimized data structures and computation models but require users to write low-level imperative code, hence ensuring that efficiency is the burden of the user. In high-level engines, users write in query languages like datalog (SociaLite) or SQL (Grail). High-level engines are easier to use but are orders of magnitude slower than the low-level graph engines. We present EmptyHeaded, a high-level engine that supports a rich datalog-like query language and achieves performance comparable to that of low-level engines. At the core of EmptyHeaded’s design is a new class of join algorithms that satisfy strong theoretical guarantees but have thus far not achieved performance comparable to that of specialized graph processing engines. To achieve high performance, EmptyHeaded introduces a new join engine architecture, including a novel query optimizer and data layouts that leverage single-instruction multiple data (SIMD) parallelism. With this architecture, EmptyHeaded outperforms high-level approaches by up to three orders of magnitude on graph pattern queries, PageRank, and Single-Source Shortest Paths (SSSP) and is an order of magnitude faster than many low-level baselines. We validate that EmptyHeaded competes with the best-of-breed low-level engine (Galois), achieving comparable performance on PageRank and at most 3× worse performance on SSSP. PMID:28077912

Analytical optimal pulse shapes obtained with the aid of genetic algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guerrero, Rubén D., E-mail: rdguerrerom@unal.edu.co; Arango, Carlos A.; Reyes, Andrés

2015-09-28

We propose a methodology to design optimal pulses for achieving quantum optimal control on molecular systems. Our approach constrains pulse shapes to linear combinations of a fixed number of experimentally relevant pulse functions. Quantum optimal control is obtained by maximizing a multi-target fitness function using genetic algorithms. As a first application of the methodology, we generated an optimal pulse that successfully maximized the yield on a selected dissociation channel of a diatomic molecule. Our pulse is obtained as a linear combination of linearly chirped pulse functions. Data recorded along the evolution of the genetic algorithm contained important information regarding themore » interplay between radiative and diabatic processes. We performed a principal component analysis on these data to retrieve the most relevant processes along the optimal path. Our proposed methodology could be useful for performing quantum optimal control on more complex systems by employing a wider variety of pulse shape functions.« less

Global optimization method based on ray tracing to achieve optimum figure error compensation

NASA Astrophysics Data System (ADS)

Liu, Xiaolin; Guo, Xuejia; Tang, Tianjin

2017-02-01

Figure error would degrade the performance of optical system. When predicting the performance and performing system assembly, compensation by clocking of optical components around the optical axis is a conventional but user-dependent method. Commercial optical software cannot optimize this clocking. Meanwhile existing automatic figure-error balancing methods can introduce approximate calculation error and the build process of optimization model is complex and time-consuming. To overcome these limitations, an accurate and automatic global optimization method of figure error balancing is proposed. This method is based on precise ray tracing to calculate the wavefront error, not approximate calculation, under a given elements' rotation angles combination. The composite wavefront error root-mean-square (RMS) acts as the cost function. Simulated annealing algorithm is used to seek the optimal combination of rotation angles of each optical element. This method can be applied to all rotational symmetric optics. Optimization results show that this method is 49% better than previous approximate analytical method.

Effect of experimental design on the prediction performance of calibration models based on near-infrared spectroscopy for pharmaceutical applications.

PubMed

Bondi, Robert W; Igne, Benoît; Drennen, James K; Anderson, Carl A

2012-12-01

Near-infrared spectroscopy (NIRS) is a valuable tool in the pharmaceutical industry, presenting opportunities for online analyses to achieve real-time assessment of intermediates and finished dosage forms. The purpose of this work was to investigate the effect of experimental designs on prediction performance of quantitative models based on NIRS using a five-component formulation as a model system. The following experimental designs were evaluated: five-level, full factorial (5-L FF); three-level, full factorial (3-L FF); central composite; I-optimal; and D-optimal. The factors for all designs were acetaminophen content and the ratio of microcrystalline cellulose to lactose monohydrate. Other constituents included croscarmellose sodium and magnesium stearate (content remained constant). Partial least squares-based models were generated using data from individual experimental designs that related acetaminophen content to spectral data. The effect of each experimental design was evaluated by determining the statistical significance of the difference in bias and standard error of the prediction for that model's prediction performance. The calibration model derived from the I-optimal design had similar prediction performance as did the model derived from the 5-L FF design, despite containing 16 fewer design points. It also outperformed all other models estimated from designs with similar or fewer numbers of samples. This suggested that experimental-design selection for calibration-model development is critical, and optimum performance can be achieved with efficient experimental designs (i.e., optimal designs).

Population pharmacokinetics of phenytoin after intravenous administration of fosphenytoin sodium in pediatric patients, adult patients, and healthy volunteers.

PubMed

Tanaka, Jun; Kasai, Hidefumi; Shimizu, Kenji; Shimasaki, Shigeki; Kumagai, Yuji

2013-03-01

We performed a population pharmacokinetic analysis of phenytoin after intravenous administration of fosphenytoin sodium in healthy, neurosurgical, and epileptic subjects, including pediatric patients, and determined the optimal dose and infusion rate for achieving the therapeutic range. We used pooled data obtained from two phase I studies and one phase III study performed in Japan. The population pharmacokinetic analysis was performed using NONMEM software. The optimal dose and infusion rate were determined using simulation results obtained using the final model. The therapeutic range for total plasma phenytoin concentration is 10-20 μg/mL. We used a linear two-compartment model with conversion of fosphenytoin to phenytoin. Pharmacokinetic parameters of phenytoin, such as total clearance and central and peripheral volume of distribution were influenced by body weight. The dose simulations are as follows. In adult patients, the optimal dose and infusion rate of phenytoin for achieving the therapeutic range was 22.5 mg/kg and 3 mg/kg/min respectively. In pediatric patients, the total plasma concentration of phenytoin was within the therapeutic range for a shorter duration than that in adult patients at 22.5 mg/kg (3 mg/kg/min). However, many pediatric patients showed phenytoin concentration within the toxic range after administration of a dose of 30 mg/kg. The pharmacokinetics of phenytoin after intravenous administration of fosphenytoin sodium could be described using a linear two-compartment model. The administration of fosphenytoin sodium 22.5 mg/kg at an infusion rate of 3 mg/kg/min was optimal for achieving the desired plasma phenytoin concentration.

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Flight-Test Performance

NASA Technical Reports Server (NTRS)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads to specified values. This technique has been implemented and flown on the National Aeronautics and Space Administration Full-scale Advanced Systems Testbed aircraft. The flight tests illustrate that the approach achieves the desired performance and show promising potential benefits. The flights also uncovered some important issues that will need to be addressed for production application.

Computed a multiple band metamaterial absorber and its application based on the figure of merit value

NASA Astrophysics Data System (ADS)

Chen, Chao; Sheng, Yuping; Jun, Wang

2018-01-01

A high performed multiple band metamaterial absorber is designed and computed through the software Ansofts HFSS 10.0, which is constituted with two kinds of separated metal particles sub-structures. The multiple band absorption property of the metamaterial absorber is based on the resonance of localized surface plasmon (LSP) modes excited near edges of metal particles. The damping constant of gold layer is optimized to obtain a near-perfect absorption rate. Four kinds of dielectric layers is computed to achieve the perfect absorption perform. The perfect absorption perform of the metamaterial absorber is enhanced through optimizing the structural parameters (R = 75 nm, w = 80 nm). Moreover, a perfect absorption band is achieved because of the plasmonic hybridization phenomenon between LSP modes. The designed metamaterial absorber shows high sensitive in the changed of the refractive index of the liquid. A liquid refractive index sensor strategy is proposed based on the computed figure of merit (FOM) value of the metamaterial absorber. High FOM values (116, 111, and 108) are achieved with three liquid (Methanol, Carbon tetrachloride, and Carbon disulfide).

Blast optimization for improved dragline productivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Humphreys, M.; Baldwin, G.

1994-12-31

A project aimed at blast optimization for large open pit coal mines is utilizing blast monitoring and analysis techniques, advanced dragline monitoring equipment, and blast simulation software, to assess the major controlling factors affecting both blast performance and subsequent dragline productivity. This has involved collaborative work between the explosives supplier, mine operator, monitoring equipment manufacturer, and a mining research organization. The results from trial blasts and subsequently monitored dragline production have yielded promising results and continuing studies are being conducted as part of a blast optimization program. It should be stressed that the optimization of blasting practices for improved draglinemore » productivity is a site specific task, achieved through controlled and closely monitored procedures. The benefits achieved at one location can not be simply transferred to another minesite unless similar improvement strategies are first implemented.« less

High Temperature Steam Electrolysis: Demonstration of Improved Long-Term Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

J. E. O'Brien; X. Zhang; R. C. O'Brien

2011-11-01

Long-term performance is an ongoing issue for hydrogen production based on high-temperature steam electrolysis (HTSE). For commercial deployment, solid-oxide electrolysis stacks must achieve high performance with long-term degradation rates of {approx}0.5%/1000 hours or lower. Significant progress has been achieved toward this goal over the past few years. This paper will provide details of progress achieved under the Idaho National Laboratory high temperature electrolysis research program. Recent long-term stack tests have achieved high initial performance with degradation rates less than 5%/khr. These tests utilize internally manifolded stacks with electrode-supported cells. The cell material sets are optimized for the electrolysis mode ofmore » operation. Details of the cells and stacks will be provided along with details of the test apparatus, procedures, and results.« less

Analysis and optimization of solid oxide fuel cell-based auxiliary power units using a generic zero-dimensional fuel cell model

NASA Astrophysics Data System (ADS)

Göll, S.; Samsun, R. C.; Peters, R.

Fuel-cell-based auxiliary power units can help to reduce fuel consumption and emissions in transportation. For this application, the combination of solid oxide fuel cells (SOFCs) with upstream fuel processing by autothermal reforming (ATR) is seen as a highly favorable configuration. Notwithstanding the necessity to improve each single component, an optimized architecture of the fuel cell system as a whole must be achieved. To enable model-based analyses, a system-level approach is proposed in which the fuel cell system is modeled as a multi-stage thermo-chemical process using the "flowsheeting" environment PRO/II™. Therein, the SOFC stack and the ATR are characterized entirely by corresponding thermodynamic processes together with global performance parameters. The developed model is then used to achieve an optimal system layout by comparing different system architectures. A system with anode and cathode off-gas recycling was identified to have the highest electric system efficiency. Taking this system as a basis, the potential for further performance enhancement was evaluated by varying four parameters characterizing different system components. Using methods from the design and analysis of experiments, the effects of these parameters and of their interactions were quantified, leading to an overall optimized system with encouraging performance data.

Modeling and optimization of a hybrid solar combined cycle (HYCS)

NASA Astrophysics Data System (ADS)

Eter, Ahmad Adel

2011-12-01

The main objective of this thesis is to investigate the feasibility of integrating concentrated solar power (CSP) technology with the conventional combined cycle technology for electric generation in Saudi Arabia. The generated electricity can be used locally to meet the annual increasing demand. Specifically, it can be utilized to meet the demand during the hours 10 am-3 pm and prevent blackout hours, of some industrial sectors. The proposed CSP design gives flexibility in the operation system. Since, it works as a conventional combined cycle during night time and it switches to work as a hybrid solar combined cycle during day time. The first objective of the thesis is to develop a thermo-economical mathematical model that can simulate the performance of a hybrid solar-fossil fuel combined cycle. The second objective is to develop a computer simulation code that can solve the thermo-economical mathematical model using available software such as E.E.S. The developed simulation code is used to analyze the thermo-economic performance of different configurations of integrating the CSP with the conventional fossil fuel combined cycle to achieve the optimal integration configuration. This optimal integration configuration has been investigated further to achieve the optimal design of the solar field that gives the optimal solar share. Thermo-economical performance metrics which are available in the literature have been used in the present work to assess the thermo-economic performance of the investigated configurations. The economical and environmental impact of integration CSP with the conventional fossil fuel combined cycle are estimated and discussed. Finally, the optimal integration configuration is found to be solarization steam side in conventional combined cycle with solar multiple 0.38 which needs 29 hectare and LEC of HYCS is 63.17 $/MWh under Dhahran weather conditions.

Optimizing the Usability of Brain-Computer Interfaces.

PubMed

Zhang, Yin; Chase, Steve M

2018-05-01

Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. An open question in the field is how to map neural activity to device movement in order to achieve the most proficient control. This question is complicated by the fact that learning, especially the long-term skill learning that accompanies weeks of practice, can allow subjects to improve performance over time. Typical approaches to this problem attempt to maximize the biomimetic properties of the device in order to limit the need for extensive training. However, it is unclear if this approach would ultimately be superior to performance that might be achieved with a nonbiomimetic device once the subject has engaged in extended practice and learned how to use it. Here we approach this problem using ideas from optimal control theory. Under the assumption that the brain acts as an optimal controller, we present a formal definition of the usability of a device and show that the optimal postlearning mapping can be written as the solution of a constrained optimization problem. We then derive the optimal mappings for particular cases common to most brain-computer interfaces. Our results suggest that the common approach of creating biomimetic interfaces may not be optimal when learning is taken into account. More broadly, our method provides a blueprint for optimal device design in general control-theoretic contexts.

Robust Constrained Optimization Approach to Control Design for International Space Station Centrifuge Rotor Auto Balancing Control System

NASA Technical Reports Server (NTRS)

Postma, Barry Dirk

2005-01-01

This thesis discusses application of a robust constrained optimization approach to control design to develop an Auto Balancing Controller (ABC) for a centrifuge rotor to be implemented on the International Space Station. The design goal is to minimize a performance objective of the system, while guaranteeing stability and proper performance for a range of uncertain plants. The Performance objective is to minimize the translational response of the centrifuge rotor due to a fixed worst-case rotor imbalance. The robustness constraints are posed with respect to parametric uncertainty in the plant. The proposed approach to control design allows for both of these objectives to be handled within the framework of constrained optimization. The resulting controller achieves acceptable performance and robustness characteristics.

How do employees and managers perceive depression: a worksite case study.

PubMed

Hauck, Katelyn; Chard, Gill

2009-01-01

The impact of depression in the workplace is significant. If managers and employees understood depression better they could assist those with depression to achieve optimal work performance. The case study was a medium-sized, privately owned forest products company located in western Canada. Individual interviews were used to explore the views of employees and managers about depression and its impact on work performance. Suggest that how one perceives workplace support for depression is influenced by the interaction of the following factors: a) knowledge and understanding of depression, b) roles and responsibilities within the work environment, and c) perceptions of work role boundaries. Better links are needed between employees and managers to enhance workplace collaborations and achieve optimal work performance. The implementation of mental health support programs and the vocational role of occupational therapy in addressing the impact of depression in the workplace are discussed.

Hybrid digital-analog coding with bandwidth expansion for correlated Gaussian sources under Rayleigh fading

NASA Astrophysics Data System (ADS)

Yahampath, Pradeepa

2017-12-01

Consider communicating a correlated Gaussian source over a Rayleigh fading channel with no knowledge of the channel signal-to-noise ratio (CSNR) at the transmitter. In this case, a digital system cannot be optimal for a range of CSNRs. Analog transmission however is optimal at all CSNRs, if the source and channel are memoryless and bandwidth matched. This paper presents new hybrid digital-analog (HDA) systems for sources with memory and channels with bandwidth expansion, which outperform both digital-only and analog-only systems over a wide range of CSNRs. The digital part is either a predictive quantizer or a transform code, used to achieve a coding gain. Analog part uses linear encoding to transmit the quantization error which improves the performance under CSNR variations. The hybrid encoder is optimized to achieve the minimum AMMSE (average minimum mean square error) over the CSNR distribution. To this end, analytical expressions are derived for the AMMSE of asymptotically optimal systems. It is shown that the outage CSNR of the channel code and the analog-digital power allocation must be jointly optimized to achieve the minimum AMMSE. In the case of HDA predictive quantization, a simple algorithm is presented to solve the optimization problem. Experimental results are presented for both Gauss-Markov sources and speech signals.

150-nm DR contact holes die-to-database inspection

NASA Astrophysics Data System (ADS)

Kuo, Shen C.; Wu, Clare; Eran, Yair; Staud, Wolfgang; Hemar, Shirley; Lindman, Ofer

2000-07-01

Using a failure analysis-driven yield enhancements concept, based on an optimization of the mask manufacturing process and UV reticle inspection is studied and shown to improve the contact layer quality. This is achieved by relating various manufacturing processes to very fine tuned contact defect detection. In this way, selecting an optimized manufacturing process with fine-tuned inspection setup is achieved in a controlled manner. This paper presents a study, performed on a specially designed test reticle, which simulates production contact layers of design rule 250nm, 180nm and 150nm. This paper focuses on the use of advanced UV reticle inspection techniques as part of the process optimization cycle. Current inspection equipment uses traditional and insufficient methods of small contact-hole inspection and review.

Transonic airfoil analysis and design in nonuniform flow

NASA Technical Reports Server (NTRS)

Chang, J. F.; Lan, C. E.

1986-01-01

A nonuniform transonic airfoil code is developed for applications in analysis, inverse design and direct optimization involving an airfoil immersed in propfan slipstream. Problems concerning the numerical stability, convergence, divergence and solution oscillations are discussed. The code is validated by comparing with some known results in incompressible flow. A parametric investigation indicates that the airfoil lift-drag ratio can be increased by decreasing the thickness ratio. A better performance can be achieved if the airfoil is located below the slipstream center. Airfoil characteristics designed by the inverse method and a direct optimization are compared. The airfoil designed with the method of direct optimization exhibits better characteristics and achieves a gain of 22 percent in lift-drag ratio with a reduction of 4 percent in thickness.

A Neuroscience Approach to Optimizing Brain Resources for Human Performance in Extreme Environments

PubMed Central

Paulus, Martin P.; Potterat, Eric G.; Taylor, Marcus K.; Van Orden, Karl F.; Bauman, James; Momen, Nausheen; Padilla, Genieleah A.; Swain, Judith L.

2009-01-01

Extreme environments requiring optimal cognitive and behavioral performance occur in a wide variety of situations ranging from complex combat operations to elite athletic competitions. Although a large literature characterizes psychological and other aspects of individual differences in performances in extreme environments, virtually nothing is known about the underlying neural basis for these differences. This review summarizes the cognitive, emotional, and behavioral consequences of exposure to extreme environments, discusses predictors of performance, and builds a case for the use of neuroscience approaches to quantify and understand optimal cognitive and behavioral performance. Extreme environments are defined as an external context that exposes individuals to demanding psychological and/or physical conditions, and which may have profound effects on cognitive and behavioral performance. Examples of these types of environments include combat situations, Olympic-level competition, and expeditions in extreme cold, at high altitudes, or in space. Optimal performance is defined as the degree to which individuals achieve a desired outcome when completing goal-oriented tasks. It is hypothesized that individual variability with respect to optimal performance in extreme environments depends on a well “contextualized” internal body state that is associated with an appropriate potential to act. This hypothesis can be translated into an experimental approach that may be useful for quantifying the degree to which individuals are particularly suited to performing optimally in demanding environments. PMID:19447132

Performance Enhancement of Radial Distributed System with Distributed Generators by Reconfiguration Using Binary Firefly Algorithm

NASA Astrophysics Data System (ADS)

Rajalakshmi, N.; Padma Subramanian, D.; Thamizhavel, K.

2015-03-01

The extent of real power loss and voltage deviation associated with overloaded feeders in radial distribution system can be reduced by reconfiguration. Reconfiguration is normally achieved by changing the open/closed state of tie/sectionalizing switches. Finding optimal switch combination is a complicated problem as there are many switching combinations possible in a distribution system. Hence optimization techniques are finding greater importance in reducing the complexity of reconfiguration problem. This paper presents the application of firefly algorithm (FA) for optimal reconfiguration of radial distribution system with distributed generators (DG). The algorithm is tested on IEEE 33 bus system installed with DGs and the results are compared with binary genetic algorithm. It is found that binary FA is more effective than binary genetic algorithm in achieving real power loss reduction and improving voltage profile and hence enhancing the performance of radial distribution system. Results are found to be optimum when DGs are added to the test system, which proved the impact of DGs on distribution system.

Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell-Boltzmann gases

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Amin Nabakhteh, Mohammad; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah; Bidi, Mokhtar

2017-10-01

The motivation behind this work is to explore a nanoscale irreversible Stirling refrigerator with respect to size impacts and shows two novel thermo-ecological criteria. Two distinct strategies were suggested in the optimization process and the consequences of every strategy were examined independently. In the primary strategy, with the purpose of maximizing the energetic sustainability index and modified the ecological coefficient of performance (MECOP) and minimizing the dimensionless Ecological function, a multi-objective optimization algorithm (MOEA) was used. In the second strategy, with the purpose of maximizing the ECOP and MECOP and minimizing the dimensionless Ecological function, a MOEA was used. To conclude the final solution from each strategy, three proficient decision makers were utilized. Additionally, to quantify the deviation of the results gained from each decision makers, two different statistical error indexes were employed. Finally, based on the comparison between the results achieved from proposed scenarios reveals that by maximizing the MECOP the maximum values of ESI, ECOP, and a minimum of ecfare achieved.

Evolutionary Bi-objective Optimization for Bulldozer and Its Blade in Soil Cutting

NASA Astrophysics Data System (ADS)

Sharma, Deepak; Barakat, Nada

2018-02-01

An evolutionary optimization approach is adopted in this paper for simultaneously achieving the economic and productive soil cutting. The economic aspect is defined by minimizing the power requirement from the bulldozer, and the soil cutting is made productive by minimizing the time of soil cutting. For determining the power requirement, two force models are adopted from the literature to quantify the cutting force on the blade. Three domain-specific constraints are also proposed, which are limiting the power from the bulldozer, limiting the maximum force on the bulldozer blade and achieving the desired production rate. The bi-objective optimization problem is solved using five benchmark multi-objective evolutionary algorithms and one classical optimization technique using the ɛ-constraint method. The Pareto-optimal solutions are obtained with the knee-region. Further, the post-optimal analysis is performed on the obtained solutions to decipher relationships among the objectives and decision variables. Such relationships are later used for making guidelines for selecting the optimal set of input parameters. The obtained results are then compared with the experiment results from the literature that show a close agreement among them.

Branch target buffer design and optimization

NASA Technical Reports Server (NTRS)

Perleberg, Chris H.; Smith, Alan J.

1993-01-01

Consideration is given to two major issues in the design of branch target buffers (BTBs), with the goal of achieving maximum performance for a given number of bits allocated to the BTB design. The first issue is BTB management; the second is what information to keep in the BTB. A number of solutions to these problems are reviewed, and various optimizations in the design of BTBs are discussed. Design target miss ratios for BTBs are developed, making it possible to estimate the performance of BTBs for real workloads.

Potential of extended airbreathing operation of a two-stage launch vehicle by scramjet propulsion

NASA Astrophysics Data System (ADS)

Schoettle, U. M.; Hillesheimer, M.; Rahn, M.

This paper examines the application of scramjet propulsion to extend the ramjet operation of an airbreathing two-stage launch designed for horizontal takeoff and landing. Performance comparisons are made for two alternative propulsion concepts. The mission performance predictions presented are obtained from a multistep optimization procedure employing both trajectory optimization and vehicle design steps to achieve maximum payload capabilities. The simulation results are shown to offer an attractive payload advantage of the scramjet variant over the ramjet powered vehicle.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jorgensen, S.

Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].

Sensitivity of Space Station alpha joint robust controller to structural modal parameter variations

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Cooper, Paul A.; Lim, Tae W.

1991-01-01

The photovoltaic array sun tracking control system of Space Station Freedom is described. A synthesis procedure for determining optimized values of the design variables of the control system is developed using a constrained optimization technique. The synthesis is performed to provide a given level of stability margin, to achieve the most responsive tracking performance, and to meet other design requirements. Performance of the baseline design, which is synthesized using predicted structural characteristics, is discussed and the sensitivity of the stability margin is examined for variations of the frequencies, mode shapes and damping ratios of dominant structural modes. The design provides enough robustness to tolerate a sizeable error in the predicted modal parameters. A study was made of the sensitivity of performance indicators as the modal parameters of the dominant modes vary. The design variables are resynthesized for varying modal parameters in order to achieve the most responsive tracking performance while satisfying the design requirements. This procedure of reoptimization design parameters would be useful in improving the control system performance if accurate model data are provided.

Testing the Limits of Optimizing Dual-Task Performance in Younger and Older Adults

PubMed Central

Strobach, Tilo; Frensch, Peter; Müller, Herrmann Josef; Schubert, Torsten

2012-01-01

Impaired dual-task performance in younger and older adults can be improved with practice. Optimal conditions even allow for a (near) elimination of this impairment in younger adults. However, it is unknown whether such (near) elimination is the limit of performance improvements in older adults. The present study tests this limit in older adults under conditions of (a) a high amount of dual-task training and (b) training with simplified component tasks in dual-task situations. The data showed that a high amount of dual-task training in older adults provided no evidence for an improvement of dual-task performance to the optimal dual-task performance level achieved by younger adults. However, training with simplified component tasks in dual-task situations exclusively in older adults provided a similar level of optimal dual-task performance in both age groups. Therefore through applying a testing the limits approach, we demonstrated that older adults improved dual-task performance to the same level as younger adults at the end of training under very specific conditions. PMID:22408613

Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zuo, Liudong; Zhu, Michelle M.; Wu, Chase Q.

2016-11-22

Many next-generation e-science applications need fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliabilitymore » requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.« less

A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.; Garg, Devendra P.

1998-01-01

This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.

Evolutionary Design of Controlled Structures

NASA Technical Reports Server (NTRS)

Masters, Brett P.; Crawley, Edward F.

1997-01-01

Basic physical concepts of structural delay and transmissibility are provided for simple rod and beam structures. Investigations show the sensitivity of these concepts to differing controlled-structures variables, and to rational system modeling effects. An evolutionary controls/structures design method is developed. The basis of the method is an accurate model formulation for dynamic compensator optimization and Genetic Algorithm based updating of sensor/actuator placement and structural attributes. One and three dimensional examples from the literature are used to validate the method. Frequency domain interpretation of these controlled structure systems provide physical insight as to how the objective is optimized and consequently what is important in the objective. Several disturbance rejection type controls-structures systems are optimized for a stellar interferometer spacecraft application. The interferometric designs include closed loop tracking optics. Designs are generated for differing structural aspect ratios, differing disturbance attributes, and differing sensor selections. Physical limitations in achieving performance are given in terms of average system transfer function gains and system phase loss. A spacecraft-like optical interferometry system is investigated experimentally over several different optimized controlled structures configurations. Configurations represent common and not-so-common approaches to mitigating pathlength errors induced by disturbances of two different spectra. Results show that an optimized controlled structure for low frequency broadband disturbances achieves modest performance gains over a mass equivalent regular structure, while an optimized structure for high frequency narrow band disturbances is four times better in terms of root-mean-square pathlength. These results are predictable given the nature of the physical system and the optimization design variables. Fundamental limits on controlled performance are discussed based on the measured and fit average system transfer function gains and system phase loss.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bales, Benjamin B; Barrett, Richard F

In almost all modern scientific applications, developers achieve the greatest performance gains by tuning algorithms, communication systems, and memory access patterns, while leaving low level instruction optimizations to the compiler. Given the increasingly varied and complicated x86 architectures, the value of these optimizations is unclear, and, due to time and complexity constraints, it is difficult for many programmers to experiment with them. In this report we explore the potential gains of these 'last mile' optimization efforts on an AMD Barcelona processor, providing readers with relevant information so that they can decide whether investment in the presented optimizations is worthwhile.

Additive manufacturing: Toward holistic design

DOE PAGES

Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L.; ...

2017-03-18

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jared, Bradley H.; Aguilo, Miguel A.; Beghini, Lauren L.

Here, additive manufacturing offers unprecedented opportunities to design complex structures optimized for performance envelopes inaccessible under conventional manufacturing constraints. Additive processes also promote realization of engineered materials with microstructures and properties that are impossible via traditional synthesis techniques. Enthused by these capabilities, optimization design tools have experienced a recent revival. The current capabilities of additive processes and optimization tools are summarized briefly, while an emerging opportunity is discussed to achieve a holistic design paradigm whereby computational tools are integrated with stochastic process and material awareness to enable the concurrent optimization of design topologies, material constructs and fabrication processes.

DSP code optimization based on cache

NASA Astrophysics Data System (ADS)

Xu, Chengfa; Li, Chengcheng; Tang, Bin

2013-03-01

DSP program's running efficiency on board is often lower than which via the software simulation during the program development, which is mainly resulted from the user's improper use and incomplete understanding of the cache-based memory. This paper took the TI TMS320C6455 DSP as an example, analyzed its two-level internal cache, and summarized the methods of code optimization. Processor can achieve its best performance when using these code optimization methods. At last, a specific algorithm application in radar signal processing is proposed. Experiment result shows that these optimization are efficient.

Effect of operational cycle time length on nitrogen removal in an alternating oxidation ditch system.

PubMed

Mantziaras, I D; Stamou, A; Katsiri, A

2011-06-01

This paper refers to nitrogen removal optimization of an alternating oxidation ditch system through the use of a mathematical model and pilot testing. The pilot system where measurements have been made has a total volume of 120 m(3) and consists of two ditches operating in four phases during one cycle and performs carbon oxidation, nitrification, denitrification and settling. The mathematical model consists of one-dimensional mass balance (convection-dispersion) equations based on the IAWPRC ASM 1 model. After the calibration and verification of the model, simulation system performance was made. Optimization is achieved by testing operational cycles and phases with different time lengths. The limits of EU directive 91/271 for nitrogen removal have been used for comparison. The findings show that operational cycles with smaller time lengths can achieve higher nitrogen removals and that an "equilibrium" between phase time percentages in the whole cycle, for a given inflow, must be achieved.

Design Optimization Tool for Synthetic Jet Actuators Using Lumped Element Modeling

NASA Technical Reports Server (NTRS)

Gallas, Quentin; Sheplak, Mark; Cattafesta, Louis N., III; Gorton, Susan A. (Technical Monitor)

2005-01-01

The performance specifications of any actuator are quantified in terms of an exhaustive list of parameters such as bandwidth, output control authority, etc. Flow-control applications benefit from a known actuator frequency response function that relates the input voltage to the output property of interest (e.g., maximum velocity, volumetric flow rate, momentum flux, etc.). Clearly, the required performance metrics are application specific, and methods are needed to achieve the optimal design of these devices. Design and optimization studies have been conducted for piezoelectric cantilever-type flow control actuators, but the modeling issues are simpler compared to synthetic jets. Here, lumped element modeling (LEM) is combined with equivalent circuit representations to estimate the nonlinear dynamic response of a synthetic jet as a function of device dimensions, material properties, and external flow conditions. These models provide reasonable agreement between predicted and measured frequency response functions and thus are suitable for use as design tools. In this work, we have developed a Matlab-based design optimization tool for piezoelectric synthetic jet actuators based on the lumped element models mentioned above. Significant improvements were achieved by optimizing the piezoceramic diaphragm dimensions. Synthetic-jet actuators were fabricated and benchtop tested to fully document their behavior and validate a companion optimization effort. It is hoped that the tool developed from this investigation will assist in the design and deployment of these actuators.

Propulsion system-flight control integration and optimization: Flight evaluation and technology transition

NASA Technical Reports Server (NTRS)

Burcham, Frank W., Jr.; Gilyard, Glenn B.; Myers, Lawrence P.

1990-01-01

Integration of propulsion and flight control systems and their optimization offers significant performance improvements. Research programs were conducted which have developed new propulsion and flight control integration concepts, implemented designs on high-performance airplanes, demonstrated these designs in flight, and measured the performance improvements. These programs, first on the YF-12 airplane, and later on the F-15, demonstrated increased thrust, reduced fuel consumption, increased engine life, and improved airplane performance; with improvements in the 5 to 10 percent range achieved with integration and with no changes to hardware. The design, software and hardware developments, and testing requirements were shown to be practical.

Assessment and Verification of SLS Block 1-B Exploration Upper Stage State and Stage Disposal Performance

NASA Technical Reports Server (NTRS)

Patrick, Sean; Oliver, Emerson

2018-01-01

One of the SLS Navigation System's key performance requirements is a constraint on the payload system's delta-v allocation to correct for insertion errors due to vehicle state uncertainty at payload separation. The SLS navigation team has developed a Delta-Delta-V analysis approach to assess the effect on trajectory correction maneuver (TCM) design needed to correct for navigation errors. This approach differs from traditional covariance analysis based methods and makes no assumptions with regard to the propagation of the state dynamics. This allows for consideration of non-linearity in the propagation of state uncertainties. The Delta-Delta-V analysis approach re-optimizes perturbed SLS mission trajectories by varying key mission states in accordance with an assumed state error. The state error is developed from detailed vehicle 6-DOF Monte Carlo analysis or generated using covariance analysis. These perturbed trajectories are compared to a nominal trajectory to determine necessary TCM design. To implement this analysis approach, a tool set was developed which combines the functionality of a 3-DOF trajectory optimization tool, Copernicus, and a detailed 6-DOF vehicle simulation tool, Marshall Aerospace Vehicle Representation in C (MAVERIC). In addition to delta-v allocation constraints on SLS navigation performance, SLS mission requirement dictate successful upper stage disposal. Due to engine and propellant constraints, the SLS Exploration Upper Stage (EUS) must dispose into heliocentric space by means of a lunar fly-by maneuver. As with payload delta-v allocation, upper stage disposal maneuvers must place the EUS on a trajectory that maximizes the probability of achieving a heliocentric orbit post Lunar fly-by considering all sources of vehicle state uncertainty prior to the maneuver. To ensure disposal, the SLS navigation team has developed an analysis approach to derive optimal disposal guidance targets. This approach maximizes the state error covariance prior to the maneuver to develop and re-optimize a nominal disposal maneuver (DM) target that, if achieved, would maximize the potential for successful upper stage disposal. For EUS disposal analysis, a set of two tools was developed. The first considers only the nominal pre-disposal maneuver state, vehicle constraints, and an a priori estimate of the state error covariance. In the analysis, the optimal nominal disposal target is determined. This is performed by re-formulating the trajectory optimization to consider constraints on the eigenvectors of the error ellipse applied to the nominal trajectory. A bisection search methodology is implemented in the tool to refine these dispersions resulting in the maximum dispersion feasible for successful disposal via lunar fly-by. Success is defined based on the probability that the vehicle will not impact the lunar surface and will achieve a characteristic energy (C3) relative to the Earth such that it is no longer in the Earth-Moon system. The second tool propagates post-disposal maneuver states to determine the success of disposal for provided trajectory achieved states. This is performed using the optimized nominal target within the 6-DOF vehicle simulation. This paper will discuss the application of the Delta-Delta-V analysis approach for performance evaluation as well as trajectory re-optimization so as to demonstrate the system's capability in meeting performance constraints. Additionally, further discussion of the implementation of assessing disposal analysis will be provided.

Design of wide-angle solar-selective absorbers using aperiodic metal-dielectric stacks.

PubMed

Sergeant, Nicholas P; Pincon, Olivier; Agrawal, Mukul; Peumans, Peter

2009-12-07

Spectral control of the emissivity of surfaces is essential in applications such as solar thermal and thermophotovoltaic energy conversion in order to achieve the highest conversion efficiencies possible. We investigated the spectral performance of planar aperiodic metal-dielectric multilayer coatings for these applications. The response of the coatings was optimized for a target operational temperature using needle-optimization based on a transfer matrix approach. Excellent spectral selectivity was achieved over a wide angular range. These aperiodic metal-dielectric stacks have the potential to significantly increase the efficiency of thermophotovoltaic and solar thermal conversion systems. Optimal coatings for concentrated solar thermal conversion were modeled to have a thermal emissivity <7% at 720K while absorbing >94% of the incident light. In addition, optimized coatings for solar thermophotovoltaic applications were modeled to have thermal emissivity <16% at 1750K while absorbing >85% of the concentrated solar radiation.

Probing optimal measurement configuration for optical scatterometry by the multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Chen, Xiuguo; Gu, Honggang; Jiang, Hao; Zhang, Chuanwei; Liu, Shiyuan

2018-04-01

Measurement configuration optimization (MCO) is a ubiquitous and important issue in optical scatterometry, whose aim is to probe the optimal combination of measurement conditions, such as wavelength, incidence angle, azimuthal angle, and/or polarization directions, to achieve a higher measurement precision for a given measuring instrument. In this paper, the MCO problem is investigated and formulated as a multi-objective optimization problem, which is then solved by the multi-objective genetic algorithm (MOGA). The case study on the Mueller matrix scatterometry for the measurement of a Si grating verifies the feasibility of the MOGA in handling the MCO problem in optical scatterometry by making a comparison with the Monte Carlo simulations. Experiments performed at the achieved optimal measurement configuration also show good agreement between the measured and calculated best-fit Mueller matrix spectra. The proposed MCO method based on MOGA is expected to provide a more general and practical means to solve the MCO problem in the state-of-the-art optical scatterometry.

Optimizing Excited-State Electronic-Structure Codes for Intel Knights Landing: A Case Study on the BerkeleyGW Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deslippe, Jack; da Jornada, Felipe H.; Vigil-Fowler, Derek

2016-10-06

We profile and optimize calculations performed with the BerkeleyGW code on the Xeon-Phi architecture. BerkeleyGW depends both on hand-tuned critical kernels as well as on BLAS and FFT libraries. We describe the optimization process and performance improvements achieved. We discuss a layered parallelization strategy to take advantage of vector, thread and node-level parallelism. We discuss locality changes (including the consequence of the lack of L3 cache) and effective use of the on-package high-bandwidth memory. We show preliminary results on Knights-Landing including a roofline study of code performance before and after a number of optimizations. We find that the GW methodmore » is particularly well-suited for many-core architectures due to the ability to exploit a large amount of parallelism over plane-wave components, band-pairs, and frequencies.« less

Performance seeking control (PSC) for the F-15 highly integrated digital electronic control (HIDEC) aircraft

NASA Technical Reports Server (NTRS)

Orme, John S.

1995-01-01

The performance seeking control algorithm optimizes total propulsion system performance. This adaptive, model-based optimization algorithm has been successfully flight demonstrated on two engines with differing levels of degradation. Models of the engine, nozzle, and inlet produce reliable, accurate estimates of engine performance. But, because of an observability problem, component levels of degradation cannot be accurately determined. Depending on engine-specific operating characteristics PSC achieves various levels performance improvement. For example, engines with more deterioration typically operate at higher turbine temperatures than less deteriorated engines. Thus when the PSC maximum thrust mode is applied, for example, there will be less temperature margin available to be traded for increasing thrust.

Carbon Nanotubes as FET Channel: Analog Design Optimization considering CNT Parameter Variability

NASA Astrophysics Data System (ADS)

Samar Ansari, Mohd.; Tripathi, S. K.

2017-08-01

Carbon nanotubes (CNTs), both single-walled as well as multi-walled, have been employed in a plethora of applications pertinent to semiconductor materials and devices including, but not limited to, biotechnology, material science, nanoelectronics and nano-electro mechanical systems (NEMS). The Carbon Nanotube Field Effect Transistor (CNFET) is one such electronic device which effectively utilizes CNTs to achieve a boost in the channel conduction thereby yielding superior performance over standard MOSFETs. This paper explores the effects of variability in CNT physical parameters viz. nanotube diameter, pitch, and number of CNT in the transistor channel, on the performance of a chosen analog circuit. It is further shown that from the analyses performed, an optimal design of the CNFETs can be derived for optimizing the performance of the analog circuit as per a given specification set.

High-Performance Fully Printable Perovskite Solar Cells via Blade-Coating Technique under the Ambient Condition

DOE PAGES

Yang, Zhibin; Chueh, Chu-Chen; Zuo, Fan; ...

2015-04-30

A fully printable perovskite solar cell (PVSC) is demonstrated using a blade-coating technique under ambient conditions with controlled humidity. The influence of humidity on perovskite's crystallization is systematically investigated to realize the ambient processing condition. A high power conversion efficiency of 10.44% is achieved after optimizing the blade-coating process and, more importantly, a high-performance flexible PVSC is demonstrated for the first time. A high efficiency of 7.14% is achieved.

Design-of-experiments to Reduce Life-cycle Costs in Combat Aircraft Inlets

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.; Baust, Henry D.; Agrell, Johan

2003-01-01

It is the purpose of this study to demonstrate the viability and economy of Design- of-Experiments (DOE), to arrive at micro-secondary flow control installation designs that achieve optimal inlet performance for different mission strategies. These statistical design concepts were used to investigate the properties of "low unit strength" micro-effector installation. "Low unit strength" micro-effectors are micro-vanes, set a very low angle-of incidence, with very long chord lengths. They are designed to influence the neat wall inlet flow over an extended streamwise distance. In this study, however, the long chord lengths were replicated by a series of short chord length effectors arranged in series over multiple bands of effectors. In order to properly evaluate the performance differences between the single band extended chord length installation designs and the segmented multiband short chord length designs, both sets of installations must be optimal. Critical to achieving optimal micro-secondary flow control installation designs is the understanding of the factor interactions that occur between the multiple bands of micro-scale vane effectors. These factor interactions are best understood and brought together in an optimal manner through a structured DOE process, or more specifically Response Surface Methods (RSM).

High Performance Graphene Nano-ribbon Thermoelectric Devices by Incorporation and Dimensional Tuning of Nanopores

PubMed Central

Sharafat Hossain, Md; Al-Dirini, Feras; Hossain, Faruque M.; Skafidas, Efstratios

2015-01-01

Thermoelectric properties of Graphene nano-ribbons (GNRs) with nanopores (NPs) are explored for a range of pore dimensions in order to achieve a high performance two-dimensional nano-scale thermoelectric device. We reduce thermal conductivity of GNRs by introducing pores in them in order to enhance their thermoelectric performance. The electrical properties (Seebeck coefficient and conductivity) of the device usually degrade with pore inclusion; however, we tune the pore to its optimal dimension in order to minimize this degradation, enhancing the overall thermoelectric performance (high ZT value) of our device. We observe that the side channel width plays an important role to achieve optimal performance while the effect of pore length is less pronounced. This result is consistent with the fact that electronic conduction in GNRs is dominated along its edges. Ballistic transport regime is assumed and a semi-empirical method using Huckel basis set is used to obtain the electrical properties, while the phononic system is characterized by Tersoff empirical potential model. The proposed device structure has potential applications as a nanoscale local cooler and as a thermoelectric power generator. PMID:26083450

High Performance Graphene Nano-ribbon Thermoelectric Devices by Incorporation and Dimensional Tuning of Nanopores.

PubMed

Hossain, Md Sharafat; Al-Dirini, Feras; Hossain, Faruque M; Skafidas, Efstratios

2015-06-17

Thermoelectric properties of Graphene nano-ribbons (GNRs) with nanopores (NPs) are explored for a range of pore dimensions in order to achieve a high performance two-dimensional nano-scale thermoelectric device. We reduce thermal conductivity of GNRs by introducing pores in them in order to enhance their thermoelectric performance. The electrical properties (Seebeck coefficient and conductivity) of the device usually degrade with pore inclusion; however, we tune the pore to its optimal dimension in order to minimize this degradation, enhancing the overall thermoelectric performance (high ZT value) of our device. We observe that the side channel width plays an important role to achieve optimal performance while the effect of pore length is less pronounced. This result is consistent with the fact that electronic conduction in GNRs is dominated along its edges. Ballistic transport regime is assumed and a semi-empirical method using Huckel basis set is used to obtain the electrical properties, while the phononic system is characterized by Tersoff empirical potential model. The proposed device structure has potential applications as a nanoscale local cooler and as a thermoelectric power generator.

Comparison study of thickness swell performance of commercial oriented strandboard flooring products

Treesearch

Hongmei Gu; Siqun Wang; Trairat Neimsuwan; Sunguo Wang

2005-01-01

The multiple layer structure of oriented strandboard (OSB) has a significant influence on its performance, including thickness swell (TS). TS is recognized as an important performance property for OSB products. Optimization of TS through layer property ma- nipulation to achieve the lowest total TS while maintaining acceptable mechanical properties is attainable if the...

Transitioning to Performance-Based State Funding: Concerns, Commitment, and Cautious Optimism

ERIC Educational Resources Information Center

Wayt, Lindsay K.; LaCost, Barbara Y.

2016-01-01

The introduction of performance-based state funding of higher education can be traced to the late 1970s which eliminated bonuses, and replaced regular state funding in part or completely, with funding tied to achievement of state-defined performance goals, which often include student outcomes, like graduation and retention rates. In this article,…

Quantitative analysis of the anti-noise performance of an m-sequence in an electromagnetic method

NASA Astrophysics Data System (ADS)

Yuan, Zhe; Zhang, Yiming; Zheng, Qijia

2018-02-01

An electromagnetic method with a transmitted waveform coded by an m-sequence achieved better anti-noise performance compared to the conventional manner with a square-wave. The anti-noise performance of the m-sequence varied with multiple coding parameters; hence, a quantitative analysis of the anti-noise performance for m-sequences with different coding parameters was required to optimize them. This paper proposes the concept of an identification system, with the identified Earth impulse response obtained by measuring the system output with the input of the voltage response. A quantitative analysis of the anti-noise performance of the m-sequence was achieved by analyzing the amplitude-frequency response of the corresponding identification system. The effects of the coding parameters on the anti-noise performance are summarized by numerical simulation, and their optimization is further discussed in our conclusions; the validity of the conclusions is further verified by field experiment. The quantitative analysis method proposed in this paper provides a new insight into the anti-noise mechanism of the m-sequence, and could be used to evaluate the anti-noise performance of artificial sources in other time-domain exploration methods, such as the seismic method.

Optimal design of leak-proof SRAM cell using MCDM method

NASA Astrophysics Data System (ADS)

Wang, Qi; Kang, Sung-Mo

2003-04-01

As deep-submicron CMOS technology advances, on-chip cache has become a bottleneck on microprocessor's performance. Meanwhile, it also occupies a big percentage of processor area and consumes large power. Speed, power and area of SRAM are mutually contradicting, and not easy to be met simultaneously. Many existent leakage suppression techniques have been proposed, but they limit the circuit's performance. We apply a Multi-Criteria Decision Making strategy to perform a minimum delay-power-area optimization on SRAM circuit under some certain constraints. Based on an integrated device and circuit-level approach, we search for a process that yields a targeted composite performance. In consideration of the huge amount of simulation workload involved in the optimal design-seeking process, most of this process is automated to facilitate our goal-pursuant. With varying emphasis put on delay, power or area, different optimal SRAM designs are derived and a gate-oxide thickness scaling limit is projected. The result seems to indicate that a better composite performance could be achieved under a thinner oxide thickness. Under the derived optimal oxide thickness, the static leakage power consumption contributes less than 1% in the total power dissipation.

Mass-based design and optimization of wave rotors for gas turbine engine enhancement

NASA Astrophysics Data System (ADS)

Chan, S.; Liu, H.

2017-03-01

An analytic method aiming at mass properties was developed for the preliminary design and optimization of wave rotors. In the present method, we introduce the mass balance principle into the design and thus can predict and optimize the mass qualities as well as the performance of wave rotors. A dedicated least-square method with artificial weighting coefficients was developed to solve the over-constrained system in the mass-based design. This method and the adoption of the coefficients were validated by numerical simulation. Moreover, the problem of fresh air exhaustion (FAE) was put forward and analyzed, and exhaust gas recirculation (EGR) was investigated. Parameter analyses and optimization elucidated which designs would not only achieve the best performance, but also operate with minimum EGR and no FAE.

Study of the fractional order proportional integral controller for the permanent magnet synchronous motor based on the differential evolution algorithm.

PubMed

Zheng, Weijia; Pi, Youguo

2016-07-01

A tuning method of the fractional order proportional integral speed controller for a permanent magnet synchronous motor is proposed in this paper. Taking the combination of the integral of time and absolute error and the phase margin as the optimization index, the robustness specification as the constraint condition, the differential evolution algorithm is applied to search the optimal controller parameters. The dynamic response performance and robustness of the obtained optimal controller are verified by motor speed-tracking experiments on the motor speed control platform. Experimental results show that the proposed tuning method can enable the obtained control system to achieve both the optimal dynamic response performance and the robustness to gain variations. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Robust and fast nonlinear optimization of diffusion MRI microstructure models.

PubMed

Harms, R L; Fritz, F J; Tobisch, A; Goebel, R; Roebroeck, A

2017-07-15

Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models. In addition, non-linear optimization is computationally expensive leading to very long run times, which can be prohibitive in large group or population studies. In this technical note we investigate the performance of several optimization algorithms and initialization strategies over a few of the most popular diffusion microstructure models, including NODDI and CHARMED. We evaluate whether a single well performing optimization approach exists that could be applied to many models and would equate both run time and fit aspects. All models, algorithms and strategies were implemented on the Graphics Processing Unit (GPU) to remove run time constraints, with which we achieve whole brain dataset fits in seconds to minutes. We then evaluated fit, accuracy, precision and run time for different models of differing complexity against three common optimization algorithms and three parameter initialization strategies. Variability of the achieved quality of fit in actual data was evaluated on ten subjects of each of two population studies with a different acquisition protocol. We find that optimization algorithms and multi-step optimization approaches have a considerable influence on performance and stability over subjects and over acquisition protocols. The gradient-free Powell conjugate-direction algorithm was found to outperform other common algorithms in terms of run time, fit, accuracy and precision. Parameter initialization approaches were found to be relevant especially for more complex models, such as those involving several fiber orientations per voxel. For these, a fitting cascade initializing or fixing parameter values in a later optimization step from simpler models in an earlier optimization step further improved run time, fit, accuracy and precision compared to a single step fit. This establishes and makes available standards by which robust fit and accuracy can be achieved in shorter run times. This is especially relevant for the use of diffusion microstructure modeling in large group or population studies and in combining microstructure parameter maps with tractography results. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Hydropower Generation Performance Testing at Plants in Thailand and Laos

DOE PAGES

Kern, Jamie; Hadjerioua, Boualem; Christian, Mark H.; ...

2017-04-01

An operational assessment of four hydropower plants in Southeast Asia revealed that gains in both energy production and water conservation could be achieved with little monetary investment through operational optimization efforts.

Hydropower Generation Performance Testing at Plants in Thailand and Laos

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kern, Jamie; Hadjerioua, Boualem; Christian, Mark H.

An operational assessment of four hydropower plants in Southeast Asia revealed that gains in both energy production and water conservation could be achieved with little monetary investment through operational optimization efforts.

Graphene Modified TiO2 Composite Photocatalysts: Mechanism, Progress and Perspective

PubMed Central

Tang, Bo; Chen, Haiqun; Peng, Haoping; Wang, Zhengwei; Huang, Weiqiu

2018-01-01

Graphene modified TiO2 composite photocatalysts have drawn increasing attention because of their high performance. Some significant advancements have been achieved with the continuous research, such as the corresponding photocatalytic mechanism that has been revealed. Specific influencing factors have been discovered and potential optimizing methods are proposed. The latest developments in graphene assisted TiO2 composite photocatalysts are abstracted and discussed. Based on the primary reasons behind the observed phenomena of these composite photocatalysts, probable development directions and further optimizing strategies are presented. Moreover, several novel detective technologies—beyond the decomposition test—which can be used to judge the photocatalytic performances of the resulting photocatalysts are listed and analyzed. Although some objectives have been achieved, new challenges still exist and hinder the widespread application of graphene-TiO2 composite photocatalysts, which deserves further study. PMID:29439545

Joint Machine Learning and Game Theory for Rate Control in High Efficiency Video Coding.

PubMed

Gao, Wei; Kwong, Sam; Jia, Yuheng

2017-08-25

In this paper, a joint machine learning and game theory modeling (MLGT) framework is proposed for inter frame coding tree unit (CTU) level bit allocation and rate control (RC) optimization in High Efficiency Video Coding (HEVC). First, a support vector machine (SVM) based multi-classification scheme is proposed to improve the prediction accuracy of CTU-level Rate-Distortion (R-D) model. The legacy "chicken-and-egg" dilemma in video coding is proposed to be overcome by the learning-based R-D model. Second, a mixed R-D model based cooperative bargaining game theory is proposed for bit allocation optimization, where the convexity of the mixed R-D model based utility function is proved, and Nash bargaining solution (NBS) is achieved by the proposed iterative solution search method. The minimum utility is adjusted by the reference coding distortion and frame-level Quantization parameter (QP) change. Lastly, intra frame QP and inter frame adaptive bit ratios are adjusted to make inter frames have more bit resources to maintain smooth quality and bit consumption in the bargaining game optimization. Experimental results demonstrate that the proposed MLGT based RC method can achieve much better R-D performances, quality smoothness, bit rate accuracy, buffer control results and subjective visual quality than the other state-of-the-art one-pass RC methods, and the achieved R-D performances are very close to the performance limits from the FixedQP method.

Advanced and innovative wind energy concept development: Dynamic inducer system

NASA Astrophysics Data System (ADS)

Lissaman, P. B. S.; Zalay, A. D.; Hibbs, B. H.

1981-05-01

The performance benefits of the dynamic inducer tip vane system was demonstrated Tow-tests conducted on a three-bladed, 3.6-meter diameter rotor show that a dynamic inducer can achieve a power coefficient (based pon power blade swept area) of 0.5, which exceeds that of a plain rotor by about 35%. Wind tunnel tests conducted on a one-third scale model of the dynamic inducer achieved a power coefficient of 0.62 which exceeded that of a plain rotor by about 70%. The dynamic inducer substantially improves the performance of conventional rotors and indications are that higher power coefficients can be achieved through additional aerodynamic optimization.

Traffic Games: Modeling Freeway Traffic with Game Theory

PubMed Central

Cortés-Berrueco, Luis E.; Gershenson, Carlos; Stephens, Christopher R.

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers’ interactions. PMID:27855176

Traffic Games: Modeling Freeway Traffic with Game Theory.

PubMed

Cortés-Berrueco, Luis E; Gershenson, Carlos; Stephens, Christopher R

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers' interactions.

An inverse dynamics approach to trajectory optimization and guidance for an aerospace plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1992-01-01

The optimal ascent problem for an aerospace planes is formulated as an optimal inverse dynamic problem. Both minimum-fuel and minimax type of performance indices are considered. Some important features of the optimal trajectory and controls are used to construct a nonlinear feedback midcourse controller, which not only greatly simplifies the difficult constrained optimization problem and yields improved solutions, but is also suited for onboard implementation. Robust ascent guidance is obtained by using combination of feedback compensation and onboard generation of control through the inverse dynamics approach. Accurate orbital insertion can be achieved with near-optimal control of the rocket through inverse dynamics even in the presence of disturbances.

A terahertz performance of hybrid single walled CNT based amplifier with analytical approach

NASA Astrophysics Data System (ADS)

Kumar, Sandeep; Song, Hanjung

2018-01-01

This work is focuses on terahertz performance of hybrid single walled carbon nanotube (CNT) based amplifier and proposed for measurement of soil parameters application. The proposed circuit topology provides hybrid structure which achieves wide impedance bandwidth of 0.33 THz within range of 1.07-THz to 1.42-THz with fractional amount of 28%. The single walled RF CNT network executes proposed ambition and proves its ability to resonant at 1.25-THz with analytical approach. Moreover, a RF based microstrip transmission line radiator used as compensator in the circuit topology which achieves more than 30 dB of gain. A proper methodology is chosen for achieves stability at circuit level in order to obtain desired optimal conditions. The fundamental approach optimizes matched impedance condition at (50+j0) Ω and noise variation with impact of series resistances for the proposed hybrid circuit topology and demonstrates the accuracy of performance parameters at the circuit level. The chip fabrication of the proposed circuit by using RF based commercial CMOS process of 45 nm which reveals promising results with simulation one. Additionally, power measurement analysis achieves highest output power of 26 dBm with power added efficiency of 78%. The succeed minimum noise figure from 0.6 dB to 0.4 dB is outstanding achievement for circuit topology at terahertz range. The chip area of hybrid circuit is 0.65 mm2 and power consumption of 9.6 mW.

Choosing Sensor Configuration for a Flexible Structure Using Full Control Synthesis

NASA Technical Reports Server (NTRS)

Lind, Rick; Nalbantoglu, Volkan; Balas, Gary

1997-01-01

Optimal locations and types for feedback sensors which meet design constraints and control requirements are difficult to determine. This paper introduces an approach to choosing a sensor configuration based on Full Control synthesis. A globally optimal Full Control compensator is computed for each member of a set of sensor configurations which are feasible for the plant. The sensor configuration associated with the Full Control system achieving the best closed-loop performance is chosen for feedback measurements to an output feedback controller. A flexible structure is used as an example to demonstrate this procedure. Experimental results show sensor configurations chosen to optimize the Full Control performance are effective for output feedback controllers.

Optimization of chiral lattice based metastructures for broadband vibration suppression using genetic algorithms

NASA Astrophysics Data System (ADS)

Abdeljaber, Osama; Avci, Onur; Inman, Daniel J.

2016-05-01

One of the major challenges in civil, mechanical, and aerospace engineering is to develop vibration suppression systems with high efficiency and low cost. Recent studies have shown that high damping performance at broadband frequencies can be achieved by incorporating periodic inserts with tunable dynamic properties as internal resonators in structural systems. Structures featuring these kinds of inserts are referred to as metamaterials inspired structures or metastructures. Chiral lattice inserts exhibit unique characteristics such as frequency bandgaps which can be tuned by varying the parameters that define the lattice topology. Recent analytical and experimental investigations have shown that broadband vibration attenuation can be achieved by including chiral lattices as internal resonators in beam-like structures. However, these studies have suggested that the performance of chiral lattice inserts can be maximized by utilizing an efficient optimization technique to obtain the optimal topology of the inserted lattice. In this study, an automated optimization procedure based on a genetic algorithm is applied to obtain the optimal set of parameters that will result in chiral lattice inserts tuned properly to reduce the global vibration levels of a finite-sized beam. Genetic algorithms are considered in this study due to their capability of dealing with complex and insufficiently understood optimization problems. In the optimization process, the basic parameters that govern the geometry of periodic chiral lattices including the number of circular nodes, the thickness of the ligaments, and the characteristic angle are considered. Additionally, a new set of parameters is introduced to enable the optimization process to explore non-periodic chiral designs. Numerical simulations are carried out to demonstrate the efficiency of the optimization process.

Setup optimization toward accurate ageing studies of gas filled detectors

NASA Astrophysics Data System (ADS)

Abuhoza, A.; Schmidt, H. R.; Biswas, S.; Frankenfeld, U.; Hehner, J.; Schmidt, C. J.

2013-08-01

An infrastructure has been set up at the GSI detector laboratory to study the influence of construction materials on the ageing properties of gas filled detectors, such as multi-wire proportional chamber (MWPC), gas electron multiplier (GEM). Optimization of an ageing setup was performed by observing the variation of the normalized gain obtained using two identical MWPCs. An accuracy in the relative gain measurement below 1% has been achieved by monitoring environmental conditions and by systematic improvements of the measuring equipment. Ageing test of fiberglass G11 has been performed.

Multidisciplinary Aerospace Systems Optimization: Computational AeroSciences (CAS) Project

NASA Technical Reports Server (NTRS)

Kodiyalam, S.; Sobieski, Jaroslaw S. (Technical Monitor)

2001-01-01

The report describes a method for performing optimization of a system whose analysis is so expensive that it is impractical to let the optimization code invoke it directly because excessive computational cost and elapsed time might result. In such situation it is imperative to have user control the number of times the analysis is invoked. The reported method achieves that by two techniques in the Design of Experiment category: a uniform dispersal of the trial design points over a n-dimensional hypersphere and a response surface fitting, and the technique of krigging. Analyses of all the trial designs whose number may be set by the user are performed before activation of the optimization code and the results are stored as a data base. That code is then executed and referred to the above data base. Two applications, one of the airborne laser system, and one of an aircraft optimization illustrate the method application.

Gigaflop performance on a CRAY-2: Multitasking a computational fluid dynamics application

NASA Technical Reports Server (NTRS)

Tennille, Geoffrey M.; Overman, Andrea L.; Lambiotte, Jules J.; Streett, Craig L.

1991-01-01

The methodology is described for converting a large, long-running applications code that executed on a single processor of a CRAY-2 supercomputer to a version that executed efficiently on multiple processors. Although the conversion of every application is different, a discussion of the types of modification used to achieve gigaflop performance is included to assist others in the parallelization of applications for CRAY computers, especially those that were developed for other computers. An existing application, from the discipline of computational fluid dynamics, that had utilized over 2000 hrs of CPU time on CRAY-2 during the previous year was chosen as a test case to study the effectiveness of multitasking on a CRAY-2. The nature of dominant calculations within the application indicated that a sustained computational rate of 1 billion floating-point operations per second, or 1 gigaflop, might be achieved. The code was first analyzed and modified for optimal performance on a single processor in a batch environment. After optimal performance on a single CPU was achieved, the code was modified to use multiple processors in a dedicated environment. The results of these two efforts were merged into a single code that had a sustained computational rate of over 1 gigaflop on a CRAY-2. Timings and analysis of performance are given for both single- and multiple-processor runs.

Realizing Rec. 2020 color gamut with quantum dot displays.

PubMed

Zhu, Ruidong; Luo, Zhenyue; Chen, Haiwei; Dong, Yajie; Wu, Shin-Tson

2015-09-07

We analyze how to realize Rec. 2020 wide color gamut with quantum dots. For photoluminescence, our simulation indicates that we are able to achieve over 97% of the Rec. 2020 standard with quantum dots by optimizing the emission spectra and redesigning the color filters. For electroluminescence, by optimizing the emission spectra of quantum dots is adequate to render over 97% of the Rec. 2020 standard. We also analyze the efficiency and angular performance of these devices, and then compare results with LCDs using green and red phosphors-based LED backlight. Our results indicate that quantum dot display is an outstanding candidate for achieving wide color gamut and high optical efficiency.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Arno, Michele; ICFO-Institut de Ciencies Fotoniques, E-08860 Castelldefels; Quit Group, Dipartimento di Fisica, via Bassi 6, I-27100 Pavia

We address the problem of quantum reading of optical memories, namely the retrieving of classical information stored in the optical properties of a media with minimum energy. We present optimal strategies for ambiguous and unambiguous quantum reading of unitary optical memories, namely when one's task is to minimize the probability of errors in the retrieved information and when perfect retrieving of information is achieved probabilistically, respectively. A comparison of the optimal strategy with coherent probes and homodyne detection shows that the former saves orders of magnitude of energy when achieving the same performances. Experimental proposals for quantum reading which aremore » feasible with present quantum optical technology are reported.« less

Overtaking method based on sand-sifter mechanism: Why do optimistic value functions find optimal solutions in multi-armed bandit problems?

PubMed

Ochi, Kento; Kamiura, Moto

2015-09-01

A multi-armed bandit problem is a search problem on which a learning agent must select the optimal arm among multiple slot machines generating random rewards. UCB algorithm is one of the most popular methods to solve multi-armed bandit problems. It achieves logarithmic regret performance by coordinating balance between exploration and exploitation. Since UCB algorithms, researchers have empirically known that optimistic value functions exhibit good performance in multi-armed bandit problems. The terms optimistic or optimism might suggest that the value function is sufficiently larger than the sample mean of rewards. The first definition of UCB algorithm is focused on the optimization of regret, and it is not directly based on the optimism of a value function. We need to think the reason why the optimism derives good performance in multi-armed bandit problems. In the present article, we propose a new method, which is called Overtaking method, to solve multi-armed bandit problems. The value function of the proposed method is defined as an upper bound of a confidence interval with respect to an estimator of expected value of reward: the value function asymptotically approaches to the expected value of reward from the upper bound. If the value function is larger than the expected value under the asymptote, then the learning agent is almost sure to be able to obtain the optimal arm. This structure is called sand-sifter mechanism, which has no regrowth of value function of suboptimal arms. It means that the learning agent can play only the current best arm in each time step. Consequently the proposed method achieves high accuracy rate and low regret and some value functions of it can outperform UCB algorithms. This study suggests the advantage of optimism of agents in uncertain environment by one of the simplest frameworks. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

PubMed

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-06-12

Particle swarm optimization (PSO) is a powerful metaheuristic population-based global optimization algorithm. However, when it is applied to nonseparable objective functions, its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates superior performance across several nonlinear, multimodal benchmark functions compared with the rotation-invariant PSO algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in the ReaxFF- lg reactive force field was carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents better performance compared to a genetic algorithm optimization method in the optimization of the parameters of a ReaxFF- lg correction model. The computational framework is implemented in a stand-alone C++ code that allows the straightforward development of ReaxFF reactive force fields.

Relating quantum privacy and quantum coherence: an operational approach.

PubMed

Devetak, I; Winter, A

2004-08-20

Given many realizations of a state or a channel as a resource, two parties can generate a secret key as well as entanglement. We describe protocols to perform the secret key distillation (as it turns out, with optimal rate). Then we show how to achieve optimal entanglement generation rates by "coherent" implementation of a class of secret key agreement protocols, proving the long-conjectured "hashing inequality."

Inert gas ion source program

NASA Technical Reports Server (NTRS)

Ramsey, W. D.

1978-01-01

THe original 12 cm hexagonal magneto-electrostatic containment discharge chamber has been optimized for argon and xenon operation. Argon mass utilization efficiencies of 65 to 77 percent were achieved at keeper-plus-main discharge energy consumptions of 200 to 458 eV/ion, respectively. Xenon performance of 84 to 96 percent mass utilization was realized at 203 to 350 eV/ion. The optimization process and test results are discussed.

Elite-adapted wheelchair sports performance: a systematic review.

PubMed

Perret, Claudio

2017-01-01

Elite-adapted sports performance has considerably improved over the last decades and winning or losing races at Paralympic Games is often a matter of a split second. In other words, every single detail counts, which underlines the necessity of optimizing training interventions and equipment for athletes in order to achieve top-class performance. However, to date, studies which include Paralympic elite athletes are scarce. A comprehensive literature search was performed to identify potential strategies and interventions in order to optimize elite-adapted wheelchair sports performance, whereas the focus lay on respiratory muscle training (RMT), cooling (CI) and nutritional interventions (NI) as well as on individual equipment adaptations (IEA). The total number of studies identified for the final analysis was six for RMT, two for CI, three for NI and seven for IEA, respectively. Results point predominantly towards performance enhancing benefits for CI and IEA, whereas NI and RMT provided inhomogenous findings. In comparison to the able-bodied population, research in the field of Paralympic elite sport is scarce. CI and IEA seem to have significant performance enhancing benefits, whereas NI and RMT revealed controversial findings. However, due to the limited number of elite athletes with a spinal cord injury available to participate in scientific studies, general conclusions are difficult to make at this stage and in daily practice recommendations are still given mainly on an individual basis or based on personal experiences of coaches, athletes and scientists. Implications for Rehabilitaton Based on the knowledge gained in elite sports, wheelchair equipment could be optimized also for daily use. Elite sports performance could inspire wheelchair users to achieve their personal fitness goals.

High-performance organic light-emitting diodes comprising ultrastable glass layers

PubMed Central

Rodríguez-Viejo, Javier

2018-01-01

Organic light-emitting diodes (OLEDs) are one of the key solid-state light sources for various applications including small and large displays, automotive lighting, solid-state lighting, and signage. For any given commercial application, OLEDs need to perform at their best, which is judged by their device efficiency and operational stability. We present OLEDs that comprise functional layers fabricated as ultrastable glasses, which represent the thermodynamically most favorable and, thus, stable molecular conformation achievable nowadays in disordered solids. For both external quantum efficiencies and LT70 lifetimes, OLEDs with four different phosphorescent emitters show >15% enhancements over their respective reference devices. The only difference to the latter is the growth condition used for ultrastable glass layers that is optimal at about 85% of the materials’ glass transition temperature. These improvements are achieved through neither material refinements nor device architecture optimization, suggesting a general applicability of this concept to maximize the OLED performance, no matter which specific materials are used. PMID:29806029

The role of principal in optimizing school climate in primary schools

NASA Astrophysics Data System (ADS)

Murtedjo; Suharningsih

2018-01-01

This article was written based on the occurrence of elementary school changes that never counted because of the low quality, became the school of choice of the surrounding community with the many national achievements ever achieved. This article is based on research data conducted in primary schools. In this paper focused on the role of school principals in an effort to optimize school climate. To describe the principal’s role in optimizing school climate using a qualitative approach to the design of Multi-Site Study. The appointment of the informant was done by snowball technique. Data collection through in-depth interviews, participant observation, and documentation. Data credibility checking uses triangulation techniques, member checks, and peer discussions. Auditability is performed by the auditor. The collected data is analyzed by site analysis and cross-site analysis. The result of the research shows that the principal in optimizing the conducive school climate by creating the physical condition of the school and the socio-emotional condition is pleasant, so that the teachers in implementing the learning process become passionate, happy learners which ultimately improve their learning achievement and can improve the school quality.

Improving the efficiency of single and multiple teleportation protocols based on the direct use of partially entangled states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fortes, Raphael; Rigolin, Gustavo, E-mail: rigolin@ifi.unicamp.br

We push the limits of the direct use of partially pure entangled states to perform quantum teleportation by presenting several protocols in many different scenarios that achieve the optimal efficiency possible. We review and put in a single formalism the three major strategies known to date that allow one to use partially entangled states for direct quantum teleportation (no distillation strategies permitted) and compare their efficiencies in real world implementations. We show how one can improve the efficiency of many direct teleportation protocols by combining these techniques. We then develop new teleportation protocols employing multipartite partially entangled states. The threemore » techniques are also used here in order to achieve the highest efficiency possible. Finally, we prove the upper bound for the optimal success rate for protocols based on partially entangled Bell states and show that some of the protocols here developed achieve such a bound. -- Highlights: •Optimal direct teleportation protocols using directly partially entangled states. •We put in a single formalism all strategies of direct teleportation. •We extend these techniques for multipartite partially entangle states. •We give upper bounds for the optimal efficiency of these protocols.« less

SU-E-I-43: Pediatric CT Dose and Image Quality Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, G; Singh, R

2014-06-01

Purpose: To design an approach to optimize radiation dose and image quality for pediatric CT imaging, and to evaluate expected performance. Methods: A methodology was designed to quantify relative image quality as a function of CT image acquisition parameters. Image contrast and image noise were used to indicate expected conspicuity of objects, and a wide-cone system was used to minimize scan time for motion avoidance. A decision framework was designed to select acquisition parameters as a weighted combination of image quality and dose. Phantom tests were used to acquire images at multiple techniques to demonstrate expected contrast, noise and dose.more » Anthropomorphic phantoms with contrast inserts were imaged on a 160mm CT system with tube voltage capabilities as low as 70kVp. Previously acquired clinical images were used in conjunction with simulation tools to emulate images at different tube voltages and currents to assess human observer preferences. Results: Examination of image contrast, noise, dose and tube/generator capabilities indicates a clinical task and object-size dependent optimization. Phantom experiments confirm that system modeling can be used to achieve the desired image quality and noise performance. Observer studies indicate that clinical utilization of this optimization requires a modified approach to achieve the desired performance. Conclusion: This work indicates the potential to optimize radiation dose and image quality for pediatric CT imaging. In addition, the methodology can be used in an automated parameter selection feature that can suggest techniques given a limited number of user inputs. G Stevens and R Singh are employees of GE Healthcare.« less

Development and design of experiments optimization of a high temperature proton exchange membrane fuel cell auxiliary power unit with onboard fuel processor

NASA Astrophysics Data System (ADS)

Karstedt, Jörg; Ogrzewalla, Jürgen; Severin, Christopher; Pischinger, Stefan

In this work, the concept development, system layout, component simulation and the overall DOE system optimization of a HT-PEM fuel cell APU with a net electric power output of 4.5 kW and an onboard methane fuel processor are presented. A highly integrated system layout has been developed that enables fast startup within 7.5 min, a closed system water balance and high fuel processor efficiencies of up to 85% due to the recuperation of the anode offgas burner heat. The integration of the system battery into the load management enhances the transient electric performance and the maximum electric power output of the APU system. Simulation models of the carbon monoxide influence on HT-PEM cell voltage, the concentration and temperature profiles within the autothermal reformer (ATR) and the CO conversion rates within the watergas shift stages (WGSs) have been developed. They enable the optimization of the CO concentration in the anode gas of the fuel cell in order to achieve maximum system efficiencies and an optimized dimensioning of the ATR and WGS reactors. Furthermore a DOE optimization of the global system parameters cathode stoichiometry, anode stoichiometry, air/fuel ratio and steam/carbon ratio of the fuel processing system has been performed in order to achieve maximum system efficiencies for all system operating points under given boundary conditions.

Periodic Application of Stochastic Cost Optimization Methodology to Achieve Remediation Objectives with Minimized Life Cycle Cost

NASA Astrophysics Data System (ADS)

Kim, U.; Parker, J.

2016-12-01

Many dense non-aqueous phase liquid (DNAPL) contaminated sites in the U.S. are reported as "remediation in progress" (RIP). However, the cost to complete (CTC) remediation at these sites is highly uncertain and in many cases, the current remediation plan may need to be modified or replaced to achieve remediation objectives. This study evaluates the effectiveness of iterative stochastic cost optimization that incorporates new field data for periodic parameter recalibration to incrementally reduce prediction uncertainty and implement remediation design modifications as needed to minimize the life cycle cost (i.e., CTC). This systematic approach, using the Stochastic Cost Optimization Toolkit (SCOToolkit), enables early identification and correction of problems to stay on track for completion while minimizing the expected (i.e., probability-weighted average) CTC. This study considers a hypothetical site involving multiple DNAPL sources in an unconfined aquifer using thermal treatment for source reduction and electron donor injection for dissolved plume control. The initial design is based on stochastic optimization using model parameters and their joint uncertainty based on calibration to site characterization data. The model is periodically recalibrated using new monitoring data and performance data for the operating remediation systems. Projected future performance using the current remediation plan is assessed and reoptimization of operational variables for the current system or consideration of alternative designs are considered depending on the assessment results. We compare remediation duration and cost for the stepwise re-optimization approach with single stage optimization as well as with a non-optimized design based on typical engineering practice.

DESIGN AND PERFORMANCE CHARACTERISTICS OF A TURBULENT MIXING CONDENSATION NUCLEI COUNTER. (R826654)

EPA Science Inventory

The design and optimization of operation parameters of a Turbulent Mixing Condensation Nuclei Counter (TMCNC) are discussed as well as its performance using dibutylphthalate (DBP) as the working fluid. A detection limit of 3 nm has been achieved at a flow rate of 2.8 lmin^-1<...

Optimal Designs for Performance Assessments: The Subject Factor.

ERIC Educational Resources Information Center

Parkes, Jay

Much speculation abounds concerning how expensive performance assessments are or are going to be. Recent projections indicate that, in order to achieve an acceptably high generalizability coefficient, many additional tasks may need to be added, which will enlarge costs. Such projections are, to some degree, correct, and to some degree simplistic.…

Matching achievement contexts with implicit theories to maximize motivation after failure: a congruence model.

PubMed

El-Alayli, Amani

2006-12-01

Previous research has shown that matching person variables with achievement contexts can produce the best motivational outcomes. The current study examines whether this is also true when matching entity and incremental beliefs with the appropriate motivational climate. Participants were led to believe that a personal attribute was fixed (entity belief) or malleable (incremental belief). After thinking that they failed a test that assessed the attribute, participants performed a second (related) task in a context that facilitated the pursuit of either performance or learning goals. Participants were expected to exhibit greater effort on the second task in the congruent conditions (entity belief plus performance goal climate and incremental belief plus learning goal climate) than in the incongruent conditions. These results were obtained, but only for participants who either valued competence on the attribute or had high achievement motivation. Results are discussed in terms of developing strategies for optimizing motivation in achievement settings.

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1990-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Multidisciplinary optimization of aeroservoelastic systems using reduced-size models

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1992-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

A Robust Adaptive Autonomous Approach to Optimal Experimental Design

NASA Astrophysics Data System (ADS)

Gu, Hairong

Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy

PubMed Central

Zhang, Lina; Zhang, Chengjin; Gao, Rui; Yang, Runtao; Song, Qing

2016-01-01

Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information), PSSM (Position Specific Scoring Matrix), RSA (Relative Solvent Accessibility), and CTD (Composition, Transition, Distribution). The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest), SMO (Sequential Minimal Optimization), NNA (Nearest Neighbor Algorithm), and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection) method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew’s Correlation Coefficient) of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc. PMID:27662651

The Nike-Black Brant V development program

NASA Technical Reports Server (NTRS)

Sevier, H.; Payne, B.; Ott, R.; Montag, W.

1976-01-01

The Nike-Black Brant V represents a combined U.S.-Canadian program to achieve a 40 percent increase in apogee performance over that of the unboosted BBV, with minimum component modification and no meaningful increase in flight environment levels. The process of achieving these objectives is described, in particular optimization of sustainer coast period and roll history, and the techniques used to ensure good stage separation. Details of the structural test program and subsequent successful vehicle proving flight are provided. Basic performance data are preented, with an indication of the further potential offered by Terrier boost.

High Energy, Long Cycle Life Lithium-ion Batteries for PHEV Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Donghai; Manthiram, Arumugam; Wang, Chao-Yang

High-loading and high quality PSU Si anode has been optimized and fabricated. The electrochemical performance has been utilized. The PSU Si-graphite anode exhibits the mass loading of 5.8 mg/cm2, charge capacity of 850 mAh/ g and good cycling performance. This optimized electrode has been used for full-cell fabrication. The performance enhancement of Ni-rich materials can be achieved by a diversity of strategies. Higher Mn content and a small amount of Al doping can improve the electrochemical performance by suppressing interfacial side reactions with electrolytes, thus greatly benefiting the cyclability of the samples. Also, surface coatings of Li-rich materials and AlFmore » 3 are able to improve the performance stability of Ni-rich cathodes. One kilogram of optimized concentration-gradient LiNi 0.76Co 0.10Mn 0.14O 2 (CG) with careful control of composition, morphology and electrochemical performance was delivered to our collaborators. The sample achieved an initial specific capacity close to 190 mA h g -1 at C/10 rate and 180 mA h g -1 at C/3 rate as well as good cyclability in pouch full cells with a 4.4 V upper cut-off voltage at room temperature. Electrolyte additive with Si-N skeleton forms a less resistant SEI on the surface of silicon anode (from PSU) as evidenced by the evolution of the impedance at various lithiation/de-lithiation stages and the cycling data The prelithiation result demonstrates a solution processing method to achieve large area, uniform SLMP coating on well-made anode surface for the prelithiation of lithium-ion batteries. The prelithiation effect with this method is applied both in graphite half cells, graphite/NMC full cells, SiO half cells, SiO/NMC full cells, Si-Graphite half cells and Si-Graphite/NMC full cells with improvements in cycle performance and higher first cycle coulombic efficiency than their corresponding cells without SLMP prelithiation. As to the full cell fabrication and test, full pouch cells with high capacity of 2.2 Ah and 1.2 Ah have been fabricated and delivered. The cells show great uniformity and good cycling performance. The prelithiation method effectively compensate the loss in the first cycle. The cell with high energy density and long-cycle life has been achieved.« less

Network anomaly detection system with optimized DS evidence theory.

PubMed

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

Network Anomaly Detection System with Optimized DS Evidence Theory

PubMed Central

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

Optimal Design of a Thermoelectric Cooling/Heating System for Car Seat Climate Control (CSCC)

NASA Astrophysics Data System (ADS)

Elarusi, Abdulmunaem; Attar, Alaa; Lee, Hosung

2017-04-01

In the present work, the optimum design of thermoelectric car seat climate control (CSCC) is studied analytically in an attempt to achieve high system efficiency. Optimal design of a thermoelectric device (element length, cross-section area and number of thermocouples) is carried out using our newly developed optimization method based on the ideal thermoelectric equations and dimensional analysis to improve the performance of the thermoelectric device in terms of the heating/cooling power and the coefficient of performance (COP). Then, a new innovative system design is introduced which also includes the optimum input current for the initial (transient) startup warming and cooling before the car heating ventilation and air conditioner (HVAC) is active in the cabin. The air-to-air heat exchanger's configuration was taken into account to investigate the optimal design of the CSCC.

Improving the mixing performance of side channel type micromixers using an optimal voltage control model.

PubMed

Wu, Chien-Hsien; Yang, Ruey-Jen

2006-06-01

Electroosmotic flow in microchannels is restricted to low Reynolds number regimes. Since the inertia forces are extremely weak in such regimes, turbulent conditions do not readily develop, and hence species mixing occurs primarily as a result of diffusion. Consequently, achieving a thorough species mixing generally relies upon the use of extended mixing channels. This paper aims to improve the mixing performance of conventional side channel type micromixers by specifying the optimal driving voltages to be applied to each channel. In the proposed approach, the driving voltages are identified by constructing a simple theoretical scheme based on a 'flow-rate-ratio' model and Kirchhoff's law. The numerical and experimental results confirm that the optimal voltage control approach provides a better mixing performance than the use of a single driving voltage gradient.

The optimal dissolved oxygen profile in a nitrifying activated sludge process - comparisons with ammonium feedback control.

PubMed

Amand, L; Carlsson, B

2013-01-01

Ammonium feedback control is increasingly used to determine the dissolved oxygen (DO) set-point in aerated activated sludge processes for nitrogen removal. This study compares proportional-integral (PI) ammonium feedback control with a DO profile created from a mathematical minimisation of the daily air flow rate. All simulated scenarios are set to reach the same treatment level of ammonium, based on a daily average concentration. The influent includes daily variations only and the model has three aerated zones. Comparisons are made at different plant loads and DO concentrations, and the placement of the ammonium sensor is investigated. The results show that ammonium PI control can achieve the best performance if the DO set-point is limited at a maximum value and with little integral action in the controller. Compared with constant DO control the best-performing ammonium controller can achieve 1-3.5% savings in the air flow rate, while the optimal solution can achieve a 3-7% saving. Energy savings are larger when operating at higher DO concentrations.

Superlattice photonic crystal as broadband solar absorber for high temperature operation.

PubMed

Rinnerbauer, Veronika; Shen, Yichen; Joannopoulos, John D; Soljačić, Marin; Schäffler, Friedrich; Celanovic, Ivan

2014-12-15

A high performance solar absorber using a 2D tantalum superlattice photonic crystal (PhC) is proposed and its design is optimized for high-temperature energy conversion. In contrast to the simple lattice PhC, which is limited by diffraction in the short wavelength range, the superlattice PhC achieves solar absorption over broadband spectral range due to the contribution from two superposed lattices with different cavity radii. The superlattice PhC geometry is tailored to achieve maximum thermal transfer efficiency for a low concentration system of 250 suns at 1500 K reaching 85.0% solar absorptivity. In the high concentration case of 1000 suns, the superlattice PhC absorber achieves a solar absorptivity of 96.2% and a thermal transfer efficiency of 82.9% at 1500 K, amounting to an improvement of 10% and 5%, respectively, versus the simple square lattice PhC absorber. In addition, the performance of the superlattice PhC absorber is studied in a solar thermophotovoltaic system which is optimized to minimize absorber re-emission by reducing the absorber-to-emitter area ratio and using a highly reflective silver aperture.

Predictive genomics DNA profiling for athletic performance.

PubMed

Kambouris, Marios; Ntalouka, Foteini; Ziogas, Georgios; Maffulli, Nicola

2012-12-01

Genes control biological processes such as muscle, cartilage and bone formation, muscle energy production and metabolism (mitochondriogenesis, lactic acid removal), blood and tissue oxygenation (erythropoiesis, angiogenesis, vasodilatation), all essential in sport and athletic performance. DNA sequence variations in such genes confer genetic advantages that can be exploited, or genetic 'barriers' that could be overcome to achieve optimal athletic performance. Predictive Genomic DNA Profiling for athletic performance reveals genetic variations that may be associated with better suitability for endurance, strength and speed sports, vulnerability to sports-related injuries and individualized nutritional requirements. Knowledge of genetic 'suitability' in respect to endurance capacity or strength and speed would lead to appropriate sport and athletic activity selection. Knowledge of genetic advantages and barriers would 'direct' an individualized training program, nutritional plan and nutritional supplementation to achieving optimal performance, overcoming 'barriers' that results from intense exercise and pressure under competition with minimum waste of time and energy and avoidance of health risks (hypertension, cardiovascular disease, inflammation, and musculoskeletal injuries) related to exercise, training and competition. Predictive Genomics DNA profiling for Athletics and Sports performance is developing into a tool for athletic activity and sport selection and for the formulation of individualized and personalized training and nutritional programs to optimize health and performance for the athlete. Human DNA sequences are patentable in some countries, while in others DNA testing methodologies [unless proprietary], are non patentable. On the other hand, gene and variant selection, genotype interpretation and the risk and suitability assigning algorithms based on the specific Genomic variants used are amenable to patent protection.

Improving the magnetoelectric performance of Metglas/PZT laminates by annealing in a magnetic field.

PubMed

Freeman, E; Harper, J; Goel, N; Gilbert, I; Unguris, J; Schiff, S J; Tadigadapa, S

2017-01-01

A comprehensive investigation of magnetostriction optimization in Metglas 2605SA1 ribbons is performed to enhance magnetoelectric performance. We explore a range of annealing conditions to relieve remnant stress and align the magnetic domains in the Metglas, while minimizing unwanted crystallization. The magnetostriction coefficient, magnetoelectric coefficient, and magnetic domain alignment are correlated to optimize magnetoelectric performance. We report on direct magnetostriction observed by in-plane Doppler vibrometer and domain imagining using scanning electron microscopy with polarization analysis for a range of annealing conditions. We find that annealing in an oxygen-free environment at 400 °C for 30 min yields an optimal magnetoelectric coefficient, magnetostriction and magnetostriction coefficient. The optimized ribbons had a magnetostriction of 50.6 ± 0.2 μ m m -1 and magnetoelectric coefficient of 79.3 ± 1.5 μ m m -1 mT -1 . The optimized Metglas 2605SA1 ribbons and PZT-5A (d 31 mode) sensor achieves a magnetic noise floor of approximately 600 pT Hz -1/2 at 100 Hz and a magnetoelectric coefficient of 6.1 ± 0.03 MV m -1 T -1 .

Improving the magnetoelectric performance of Metglas/PZT laminates by annealing in a magnetic field

NASA Astrophysics Data System (ADS)

Freeman, E.; Harper, J.; Goel, N.; Gilbert, I.; Unguris, J.; Schiff, S. J.; Tadigadapa, S.

2017-08-01

A comprehensive investigation of magnetostriction optimization in Metglas 2605SA1 ribbons is performed to enhance magnetoelectric performance. We explore a range of annealing conditions to relieve remnant stress and align the magnetic domains in the Metglas, while minimizing unwanted crystallization. The magnetostriction coefficient, magnetoelectric coefficient, and magnetic domain alignment are correlated to optimize magnetoelectric performance. We report on direct magnetostriction observed by in-plane Doppler vibrometer and domain imagining using scanning electron microscopy with polarization analysis for a range of annealing conditions. We find that annealing in an oxygen-free environment at 400 {}\\circ {{C}} for 30 min yields an optimal magnetoelectric coefficient, magnetostriction and magnetostriction coefficient. The optimized ribbons had a magnetostriction of 50.6 ± 0.2 μ {{m}} {{{m}}}-1 and magnetoelectric coefficient of 79.3 ± 1.5 µm m-1 mT-1. The optimized Metglas 2605SA1 ribbons and PZT-5A (d31 mode) sensor achieves a magnetic noise floor of approximately 600 pT {{{H}}{{z}}}-1/2 at 100 Hz and a magnetoelectric coefficient of 6.1 ± 0.03 MV m-1 T-1.

A novel non-uniform control vector parameterization approach with time grid refinement for flight level tracking optimal control problems.

PubMed

Liu, Ping; Li, Guodong; Liu, Xinggao; Xiao, Long; Wang, Yalin; Yang, Chunhua; Gui, Weihua

2018-02-01

High quality control method is essential for the implementation of aircraft autopilot system. An optimal control problem model considering the safe aerodynamic envelop is therefore established to improve the control quality of aircraft flight level tracking. A novel non-uniform control vector parameterization (CVP) method with time grid refinement is then proposed for solving the optimal control problem. By introducing the Hilbert-Huang transform (HHT) analysis, an efficient time grid refinement approach is presented and an adaptive time grid is automatically obtained. With this refinement, the proposed method needs fewer optimization parameters to achieve better control quality when compared with uniform refinement CVP method, whereas the computational cost is lower. Two well-known flight level altitude tracking problems and one minimum time cost problem are tested as illustrations and the uniform refinement control vector parameterization method is adopted as the comparative base. Numerical results show that the proposed method achieves better performances in terms of optimization accuracy and computation cost; meanwhile, the control quality is efficiently improved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Mechanism of bandwidth improvement in passively cooled SMA position actuators

NASA Astrophysics Data System (ADS)

Gorbet, R. B.; Morris, K. A.; Chau, R. C. C.

2009-09-01

The heating of shape memory alloy (SMA) materials leads to a thermally driven phase change which can be used to do work. An SMA wire can be thermally cycled by controlling electric current through the wire, creating an electro-mechanical actuator. Such actuators are typically heated electrically and cooled through convection. The thermal time constants and lack of active cooling limit the operating frequencies. In this work, the bandwidth of a still-air-cooled SMA wire controlled with a PID controller is improved through optimization of the controller gains. Results confirm that optimization can improve the ability of the actuator to operate at a given frequency. Overshoot is observed in the optimal controllers at low frequencies. This is a result of hysteresis in the wire's contraction-temperature characteristic, since different input temperatures can achieve the same output value. The optimal controllers generate overshoot during heating, in order to cause the system to operate at a point on the hysteresis curve where faster cooling can be achieved. The optimization results in a controller which effectively takes advantage of the multi-valued nature of the hysteresis to improve performance.

Successful Optimization of Adalimumab Therapy in Refractory Uveitis Due to Behçet's Disease.

PubMed

Martín-Varillas, José Luis; Calvo-Río, Vanesa; Beltrán, Emma; Sánchez-Bursón, Juan; Mesquida, Marina; Adán, Alfredo; Hernandez, María Victoria; Garfella, Marisa Hernández; Pascual, Elia Valls; Martínez-Costa, Lucía; Sellas-Fernández, Agustí; Cordero-Coma, Miguel; Díaz-Llopis, Manuel; Gallego, Roberto; Salom, David; Ortego, Norberto; García-Serrano, José L; Callejas-Rubio, José-Luis; Herreras, José M; García-Aparicio, Ángel; Maíz, Olga; Blanco, Ana; Torre, Ignacio; Díaz-Valle, David; Pato, Esperanza; Aurrecoechea, Elena; Caracuel, Miguel A; Gamero, Fernando; Minguez, Enrique; Carrasco-Cubero, Carmen; Olive, Alejandro; Vázquez, Julio; Ruiz-Moreno, Oscar; Manero, Javier; Muñoz-Fernández, Santiago; Martinez, Myriam Gandía; Rubio-Romero, Esteban; Toyos-Sáenz de Miera, F Javier; López Longo, Francisco Javier; Nolla, Joan M; Revenga, Marcelino; González-Vela, Carmen; Loricera, Javier; Atienza-Mateo, Belén; Demetrio-Pablo, Rosalía; Hernández, José Luis; González-Gay, Miguel A; Blanco, Ricardo

2018-03-27

To assess efficacy, safety, and cost-effectiveness of adalimumab (ADA) therapy optimization in a large series of patients with uveitis due to Behçet disease (BD) who achieved remission after the use of this biologic agent. Open-label multicenter study of ADA-treated patients with BD uveitis refractory to conventional immunosuppressants. Sixty-five of 74 patients with uveitis due to BD, who achieved remission after a median ADA duration of 6 (range, 3-12) months. ADA was optimized in 23 (35.4%) of them. This biologic agent was maintained at a dose of 40 mg/subcutaneously/2 weeks in the remaining 42 patients. After remission, based on a shared decision between the patient and the treating physician, ADA was optimized. When agreement between patient and physician was reached, optimization was performed by prolonging the ADA dosing interval progressively. Comparison between optimized and nonoptimized patients was performed. Efficacy, safety, and cost-effectiveness in optimized and nonoptimized groups. To determine efficacy, intraocular inflammation (anterior chamber cells, vitritis, and retinal vasculitis), macular thickness, visual acuity, and the sparing effect of glucocorticoids were assessed. No demographic or ocular differences were found at the time of ADA onset between the optimized and the nonoptimized groups. Most ocular outcomes were similar after a mean ± standard deviation follow-up of 34.7±13.3 and 26±21.3 months in the optimized and nonoptimized groups, respectively. However, relevant adverse effects were only seen in the nonoptimized group (lymphoma, pneumonia, severe local reaction at the injection site, and bacteremia by Escherichia coli, 1 each). Moreover, the mean ADA treatment costs were lower in the optimized group than in the nonoptimized group (6101.25 euros/patient/year vs. 12 339.48; P < 0.01). ADA optimization in BD uveitis refractory to conventional therapy is effective, safe, and cost-effective. Copyright © 2018 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Practical synchronization on complex dynamical networks via optimal pinning control

NASA Astrophysics Data System (ADS)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Comparison between goal programming and cointegration approaches in enhanced index tracking

NASA Astrophysics Data System (ADS)

Lam, Weng Siew; Jamaan, Saiful Hafizah Hj.

2013-04-01

Index tracking is a popular form of passive fund management in stock market. Passive management is a buy-and-hold strategy that aims to achieve rate of return similar to the market return. Index tracking problem is a problem of reproducing the performance of a stock market index, without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio that minimizes risk or tracking error. An improved index tracking (enhanced index tracking) is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the tracking error. Enhanced index tracking aims to generate excess return over the return achieved by the index. The objective of this study is to compare the portfolio compositions and performances by using two different approaches in enhanced index tracking problem, which are goal programming and cointegration. The result of this study shows that the optimal portfolios for both approaches are able to outperform the Malaysia market index which is Kuala Lumpur Composite Index. Both approaches give different optimal portfolio compositions. Besides, the cointegration approach outperforms the goal programming approach because the cointegration approach gives higher mean return and lower risk or tracking error. Therefore, the cointegration approach is more appropriate for the investors in Malaysia.

Optimization and evaluation of a proportional derivative controller for planar arm movement.

PubMed

Jagodnik, Kathleen M; van den Bogert, Antonie J

2010-04-19

In most clinical applications of functional electrical stimulation (FES), the timing and amplitude of electrical stimuli have been controlled by open-loop pattern generators. The control of upper extremity reaching movements, however, will require feedback control to achieve the required precision. Here we present three controllers using proportional derivative (PD) feedback to stimulate six arm muscles, using two joint angle sensors. Controllers were first optimized and then evaluated on a computational arm model that includes musculoskeletal dynamics. Feedback gains were optimized by minimizing a weighted sum of position errors and muscle forces. Generalizability of the controllers was evaluated by performing movements for which the controller was not optimized, and robustness was tested via model simulations with randomly weakened muscles. Robustness was further evaluated by adding joint friction and doubling the arm mass. After optimization with a properly weighted cost function, all PD controllers performed fast, accurate, and robust reaching movements in simulation. Oscillatory behavior was seen after improper tuning. Performance improved slightly as the complexity of the feedback gain matrix increased. Copyright 2009 Elsevier Ltd. All rights reserved.

Optimization and evaluation of a proportional derivative controller for planar arm movement

PubMed Central

Jagodnik, Kathleen M.; van den Bogert, Antonie J.

2013-01-01

In most clinical applications of functional electrical stimulation (FES), the timing and amplitude of electrical stimuli have been controlled by open-loop pattern generators. The control of upper extremity reaching movements, however, will require feedback control to achieve the required precision. Here we present three controllers using proportional derivative (PD) feedback to stimulate six arm muscles, using two joint angle sensors. Controllers were first optimized and then evaluated on a computational arm model that includes musculoskeletal dynamics. Feedback gains were optimized by minimizing a weighted sum of position errors and muscle forces. Generalizability of the controllers was evaluated by performing movements for which the controller was not optimized, and robustness was tested via model simulations with randomly weakened muscles. Robustness was further evaluated by adding joint friction and doubling the arm mass. After optimization with a properly weighted cost function, all PD controllers performed fast, accurate, and robust reaching movements in simulation. Oscillatory behavior was seen after improper tuning. Performance improved slightly as the complexity of the feedback gain matrix increased. PMID:20097345

Optimal estimation of entanglement in optical qubit systems

NASA Astrophysics Data System (ADS)

Brida, Giorgio; Degiovanni, Ivo P.; Florio, Angela; Genovese, Marco; Giorda, Paolo; Meda, Alice; Paris, Matteo G. A.; Shurupov, Alexander P.

2011-05-01

We address the experimental determination of entanglement for systems made of a pair of polarization qubits. We exploit quantum estimation theory to derive optimal estimators, which are then implemented to achieve ultimate bound to precision. In particular, we present a set of experiments aimed at measuring the amount of entanglement for states belonging to different families of pure and mixed two-qubit two-photon states. Our scheme is based on visibility measurements of quantum correlations and achieves the ultimate precision allowed by quantum mechanics in the limit of Poissonian distribution of coincidence counts. Although optimal estimation of entanglement does not require the full tomography of the states we have also performed state reconstruction using two different sets of tomographic projectors and explicitly shown that they provide a less precise determination of entanglement. The use of optimal estimators also allows us to compare and statistically assess the different noise models used to describe decoherence effects occurring in the generation of entanglement.

Using optimal control methods with constraints to generate singlet states in NMR

NASA Astrophysics Data System (ADS)

Rodin, Bogdan A.; Kiryutin, Alexey S.; Yurkovskaya, Alexandra V.; Ivanov, Konstantin L.; Yamamoto, Satoru; Sato, Kazunobu; Takui, Takeji

2018-06-01

A method is proposed for optimizing the performance of the APSOC (Adiabatic-Passage Spin Order Conversion) technique, which can be exploited in NMR experiments with singlet spin states. In this technique magnetization-to-singlet conversion (and singlet-to-magnetization conversion) is performed by using adiabatically ramped RF-fields. Optimization utilizes the GRAPE (Gradient Ascent Pulse Engineering) approach, in which for a fixed search area we assume monotonicity to the envelope of the RF-field. Such an approach allows one to achieve much better performance for APSOC; consequently, the efficiency of magnetization-to-singlet conversion is greatly improved as compared to simple model RF-ramps, e.g., linear ramps. We also demonstrate that the optimization method is reasonably robust to possible inaccuracies in determining NMR parameters of the spin system under study and also in setting the RF-field parameters. The present approach can be exploited in other NMR and EPR applications using adiabatic switching of spin Hamiltonians.

Enhancing sound absorption and transmission through flexible multi-layer micro-perforated structures.

PubMed

Bravo, Teresa; Maury, Cédric; Pinhède, Cédric

2013-11-01

Theoretical and experimental results are presented into the sound absorption and transmission properties of multi-layer structures made up of thin micro-perforated panels (ML-MPPs). The objective is to improve both the absorption and insulation performances of ML-MPPs through impedance boundary optimization. A fully coupled modal formulation is introduced that predicts the effect of the structural resonances onto the normal incidence absorption coefficient and transmission loss of ML-MPPs. This model is assessed against standing wave tube measurements and simulations based on impedance translation method for two double-layer MPP configurations of relevance in building acoustics and aeronautics. Optimal impedance relationships are proposed that ensure simultaneous maximization of both the absorption and the transmission loss under normal incidence. Exhaustive optimization of the double-layer MPPs is performed to assess the absorption and/or transmission performances with respect to the impedance criterion. It is investigated how the panel volumetric resonances modify the excess dissipation that can be achieved from non-modal optimization of ML-MPPs.

Parameterized LMI Based Diagonal Dominance Compensator Study for Polynomial Linear Parameter Varying System

NASA Astrophysics Data System (ADS)

Han, Xiaobao; Li, Huacong; Jia, Qiusheng

2017-12-01

For dynamic decoupling of polynomial linear parameter varying(PLPV) system, a robust dominance pre-compensator design method is given. The parameterized precompensator design problem is converted into an optimal problem constrained with parameterized linear matrix inequalities(PLMI) by using the conception of parameterized Lyapunov function(PLF). To solve the PLMI constrained optimal problem, the precompensator design problem is reduced into a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a new constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator is achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation on a turbofan engine PLPV model.

Computer-Simulation Surrogates for Optimization: Application to Trapezoidal Ducts and Axisymmetric Bodies

NASA Technical Reports Server (NTRS)

Otto, John C.; Paraschivoiu, Marius; Yesilyurt, Serhat; Patera, Anthony T.

1995-01-01

Engineering design and optimization efforts using computational systems rapidly become resource intensive. The goal of the surrogate-based approach is to perform a complete optimization with limited resources. In this paper we present a Bayesian-validated approach that informs the designer as to how well the surrogate performs; in particular, our surrogate framework provides precise (albeit probabilistic) bounds on the errors incurred in the surrogate-for-simulation substitution. The theory and algorithms of our computer{simulation surrogate framework are first described. The utility of the framework is then demonstrated through two illustrative examples: maximization of the flowrate of fully developed ow in trapezoidal ducts; and design of an axisymmetric body that achieves a target Stokes drag.

The extension of the thermal-vacuum test optimization program to multiple flights

NASA Technical Reports Server (NTRS)

Williams, R. E.; Byrd, J.

1981-01-01

The thermal vacuum test optimization model developed to provide an approach to the optimization of a test program based on prediction of flight performance with a single flight option in mind is extended to consider reflight as in space shuttle missions. The concept of 'utility', developed under the name of 'availability', is used to follow performance through the various options encountered when the capabilities of reflight and retrievability of space shuttle are available. Also, a 'lost value' model is modified to produce a measure of the probability of a mission's success, achieving a desired utility using a minimal cost test strategy. The resulting matrix of probabilities and their associated costs provides a means for project management to evaluate various test and reflight strategies.

Control strategy optimization of HVAC plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Facci, Andrea Luigi; Zanfardino, Antonella; Martini, Fabrizio

In this paper we present a methodology to optimize the operating conditions of heating, ventilation and air conditioning (HVAC) plants to achieve a higher energy efficiency in use. Semi-empiric numerical models of the plant components are used to predict their performances as a function of their set-point and the environmental and occupied space conditions. The optimization is performed through a graph-based algorithm that finds the set-points of the system components that minimize energy consumption and/or energy costs, while matching the user energy demands. The resulting model can be used with systems of almost any complexity, featuring both HVAC components andmore » energy systems, and is sufficiently fast to make it applicable to real-time setting.« less

Difficulty of distinguishing product states locally

NASA Astrophysics Data System (ADS)

Croke, Sarah; Barnett, Stephen M.

2017-01-01

Nonlocality without entanglement is a rather counterintuitive phenomenon in which information may be encoded entirely in product (unentangled) states of composite quantum systems in such a way that local measurement of the subsystems is not enough for optimal decoding. For simple examples of pure product states, the gap in performance is known to be rather small when arbitrary local strategies are allowed. Here we restrict to local strategies readily achievable with current technology: those requiring neither a quantum memory nor joint operations. We show that even for measurements on pure product states, there can be a large gap between such strategies and theoretically optimal performance. Thus, even in the absence of entanglement, physically realizable local strategies can be far from optimal for extracting quantum information.

Optimum color filters for CCD digital cameras

NASA Astrophysics Data System (ADS)

Engelhardt, Kai; Kunz, Rino E.; Seitz, Peter; Brunner, Harald; Knop, Karl

1993-12-01

As part of the ESPRIT II project No. 2103 (MASCOT) a high performance prototype color CCD still video camera was developed. Intended for professional usage such as in the graphic arts, the camera provides a maximum resolution of 3k X 3k full color pixels. A high colorimetric performance was achieved through specially designed dielectric filters and optimized matrixing. The color transformation was obtained by computer simulation of the camera system and non-linear optimization which minimized the perceivable color errors as measured in the 1976 CIELUV uniform color space for a set of about 200 carefully selected test colors. The color filters were designed to allow perfect colorimetric reproduction in principle and at the same time with imperceptible color noise and with special attention to fabrication tolerances. The camera system includes a special real-time digital color processor which carries out the color transformation. The transformation can be selected from a set of sixteen matrices optimized for different illuminants and output devices. Because the actual filter design was based on slightly incorrect data the prototype camera showed a mean colorimetric error of 2.7 j.n.d. (CIELUV) in experiments. Using correct input data in the redesign of the filters, a mean colorimetric error of only 1 j.n.d. (CIELUV) seems to be feasible, implying that it is possible with such an optimized color camera to achieve such a high colorimetric performance that the reproduced colors in an image cannot be distinguished from the original colors in a scene, even in direct comparison.

The Inverse Optimal Control Problem for a Three-Loop Missile Autopilot

NASA Astrophysics Data System (ADS)

Hwang, Donghyeok; Tahk, Min-Jea

2018-04-01

The performance characteristics of the autopilot must have a fast response to intercept a maneuvering target and reasonable robustness for system stability under the effect of un-modeled dynamics and noise. By the conventional approach, the three-loop autopilot design is handled by time constant, damping factor and open-loop crossover frequency to achieve the desired performance requirements. Note that the general optimal theory can be also used to obtain the same gain as obtained from the conventional approach. The key idea of using optimal control technique for feedback gain design revolves around appropriate selection and interpretation of the performance index for which the control is optimal. This paper derives an explicit expression, which relates the weight parameters appearing in the quadratic performance index to the design parameters such as open-loop crossover frequency, phase margin, damping factor, or time constant, etc. Since all set of selection of design parameters do not guarantee existence of optimal control law, explicit inequalities, which are named the optimality criteria for the three-loop autopilot (OC3L), are derived to find out all set of design parameters for which the control law is optimal. Finally, based on OC3L, an efficient gain selection procedure is developed, where time constant is set to design objective and open-loop crossover frequency and phase margin as design constraints. The effectiveness of the proposed technique is illustrated through numerical simulations.

Optimization of a miniature Maglev ventricular assist device for pediatric circulatory support.

PubMed

Zhang, Juntao; Koert, Andrew; Gellman, Barry; Gempp, Thomas M; Dasse, Kurt A; Gilbert, Richard J; Griffith, Bartley P; Wu, Zhongjun J

2007-01-01

A miniature Maglev blood pump based on magnetically levitated bearingless technology is being developed and optimized for pediatric patients. We performed impeller optimization by characterizing the hemodynamic and hemocompatibility performances using a combined computational and experimental approach. Both three-dimensional flow features and hemolytic characteristics were analyzed using computational fluid dynamics (CFD) modeling. Hydraulic pump performances and hemolysis levels of three different impeller designs were quantified and compared numerically. Two pump prototypes were constructed from the two impeller designs and experimentally tested. Comparison of CFD predictions with experimental results showed good agreement. The optimized impeller remarkably increased overall pump hydraulic output by more than 50% over the initial design. The CFD simulation demonstrated a clean and streamlined flow field in the main flow path. The numerical results by hemolysis model indicated no significant high shear stress regions. Through the use of CFD analysis and bench-top testing, the small pediatric pump was optimized to achieve a low level of blood damage and improved hydraulic performance and efficiency. The Maglev pediatric blood pump is innovative due to its small size, very low priming volume, excellent hemodynamic and hematologic performance, and elimination of seal-related and bearing-related failures due to adoption of magnetically levitated bearingless motor technology, making it ideal for pediatric applications.

Towards Implementation of a Generalized Architecture for High-Level Quantum Programming Language

NASA Astrophysics Data System (ADS)

Ameen, El-Mahdy M.; Ali, Hesham A.; Salem, Mofreh M.; Badawy, Mahmoud

2017-08-01

This paper investigates a novel architecture to the problem of quantum computer programming. A generalized architecture for a high-level quantum programming language has been proposed. Therefore, the programming evolution from the complicated quantum-based programming to the high-level quantum independent programming will be achieved. The proposed architecture receives the high-level source code and, automatically transforms it into the equivalent quantum representation. This architecture involves two layers which are the programmer layer and the compilation layer. These layers have been implemented in the state of the art of three main stages; pre-classification, classification, and post-classification stages respectively. The basic building block of each stage has been divided into subsequent phases. Each phase has been implemented to perform the required transformations from one representation to another. A verification process was exposed using a case study to investigate the ability of the compiler to perform all transformation processes. Experimental results showed that the efficacy of the proposed compiler achieves a correspondence correlation coefficient about R ≈ 1 between outputs and the targets. Also, an obvious achievement has been utilized with respect to the consumed time in the optimization process compared to other techniques. In the online optimization process, the consumed time has increased exponentially against the amount of accuracy needed. However, in the proposed offline optimization process has increased gradually.

Nozzle Mounting Method Optimization Based on Robot Kinematic Analysis

NASA Astrophysics Data System (ADS)

Chen, Chaoyue; Liao, Hanlin; Montavon, Ghislain; Deng, Sihao

2016-08-01

Nowadays, the application of industrial robots in thermal spray is gaining more and more importance. A desired coating quality depends on factors such as a balanced robot performance, a uniform scanning trajectory and stable parameters (e.g. nozzle speed, scanning step, spray angle, standoff distance). These factors also affect the mass and heat transfer as well as the coating formation. Thus, the kinematic optimization of all these aspects plays a key role in order to obtain an optimal coating quality. In this study, the robot performance was optimized from the aspect of nozzle mounting on the robot. An optimized nozzle mounting for a type F4 nozzle was designed, based on the conventional mounting method from the point of view of robot kinematics validated on a virtual robot. Robot kinematic parameters were obtained from the simulation by offline programming software and analyzed by statistical methods. The energy consumptions of different nozzle mounting methods were also compared. The results showed that it was possible to reasonably assign the amount of robot motion to each axis during the process, so achieving a constant nozzle speed. Thus, it is possible optimize robot performance and to economize robot energy.

Performance of arrays of direct-driven wave energy converters under optimal power take-off damping

NASA Astrophysics Data System (ADS)

Wang, Liguo; Engström, Jens; Leijon, Mats; Isberg, Jan

2016-08-01

It is well known that the total power converted by a wave energy farm is influenced by the hydrodynamic interactions between wave energy converters, especially when they are close to each other. Therefore, to improve the performance of a wave energy farm, the hydrodynamic interaction between converters must be considered, which can be influenced by the power take-off damping of individual converters. In this paper, the performance of arrays of wave energy converters under optimal hydrodynamic interaction and power take-off damping is investigated. This is achieved by coordinating the power take-off damping of individual converters, resulting in optimal hydrodynamic interaction as well as higher production of time-averaged power converted by the farm. Physical constraints on motion amplitudes are considered in the solution, which is required for the practical implementation of wave energy converters. Results indicate that the natural frequency of a wave energy converter under optimal damping will not vary with sea states, but the production performance of a wave energy farm can be improved significantly while satisfying the motion constraints.

Holistic Context-Sensitivity for Run-Time Optimization of Flexible Manufacturing Systems.

PubMed

Scholze, Sebastian; Barata, Jose; Stokic, Dragan

2017-02-24

Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to diverse parameters, e.g., efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach based on data streaming from high amount of sensors and other data sources. Cyber-physical systems play an important role as sources of information to achieve context sensitivity. Cyber-physical systems can be seen as complex intelligent sensors providing data needed to identify the current context under which the manufacturing system is operating. In this paper, it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of cyber-physical systems integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution encompasses run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes.

Optimizing the wireless power transfer over MIMO Channels

NASA Astrophysics Data System (ADS)

Wiedmann, Karsten; Weber, Tobias

2017-09-01

In this paper, the optimization of the power transfer over wireless channels having multiple-inputs and multiple-outputs (MIMO) is studied. Therefore, the transmitter, the receiver and the MIMO channel are modeled as multiports. The power transfer efficiency is described by a Rayleigh quotient, which is a function of the channel's scattering parameters and the incident waves from both transmitter and receiver side. This way, the power transfer efficiency can be maximized analytically by solving a generalized eigenvalue problem, which is deduced from the Rayleigh quotient. As a result, the maximum power transfer efficiency achievable over a given MIMO channel is obtained. This maximum can be used as a performance bound in order to benchmark wireless power transfer systems. Furthermore, the optimal operating point which achieves this maximum will be obtained. The optimal operating point will be described by the complex amplitudes of the optimal incident and reflected waves of the MIMO channel. This supports the design of the optimal transmitter and receiver multiports. The proposed method applies for arbitrary MIMO channels, taking transmitter-side and/or receiver-side cross-couplings in both near- and farfield scenarios into consideration. Special cases are briefly discussed in this paper in order to illustrate the method.

Holistic Context-Sensitivity for Run-Time Optimization of Flexible Manufacturing Systems

PubMed Central

Scholze, Sebastian; Barata, Jose; Stokic, Dragan

2017-01-01

Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to diverse parameters, e.g., efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach based on data streaming from high amount of sensors and other data sources. Cyber-physical systems play an important role as sources of information to achieve context sensitivity. Cyber-physical systems can be seen as complex intelligent sensors providing data needed to identify the current context under which the manufacturing system is operating. In this paper, it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of cyber-physical systems integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution encompasses run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes. PMID:28245564

Portable parallel stochastic optimization for the design of aeropropulsion components

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Rhodes, G. S.

1994-01-01

This report presents the results of Phase 1 research to develop a methodology for performing large-scale Multi-disciplinary Stochastic Optimization (MSO) for the design of aerospace systems ranging from aeropropulsion components to complete aircraft configurations. The current research recognizes that such design optimization problems are computationally expensive, and require the use of either massively parallel or multiple-processor computers. The methodology also recognizes that many operational and performance parameters are uncertain, and that uncertainty must be considered explicitly to achieve optimum performance and cost. The objective of this Phase 1 research was to initialize the development of an MSO methodology that is portable to a wide variety of hardware platforms, while achieving efficient, large-scale parallelism when multiple processors are available. The first effort in the project was a literature review of available computer hardware, as well as review of portable, parallel programming environments. The first effort was to implement the MSO methodology for a problem using the portable parallel programming language, Parallel Virtual Machine (PVM). The third and final effort was to demonstrate the example on a variety of computers, including a distributed-memory multiprocessor, a distributed-memory network of workstations, and a single-processor workstation. Results indicate the MSO methodology can be well-applied towards large-scale aerospace design problems. Nearly perfect linear speedup was demonstrated for computation of optimization sensitivity coefficients on both a 128-node distributed-memory multiprocessor (the Intel iPSC/860) and a network of workstations (speedups of almost 19 times achieved for 20 workstations). Very high parallel efficiencies (75 percent for 31 processors and 60 percent for 50 processors) were also achieved for computation of aerodynamic influence coefficients on the Intel. Finally, the multi-level parallelization strategy that will be needed for large-scale MSO problems was demonstrated to be highly efficient. The same parallel code instructions were used on both platforms, demonstrating portability. There are many applications for which MSO can be applied, including NASA's High-Speed-Civil Transport, and advanced propulsion systems. The use of MSO will reduce design and development time and testing costs dramatically.

Fuel consumption optimization for smart hybrid electric vehicle during a car-following process

NASA Astrophysics Data System (ADS)

Li, Liang; Wang, Xiangyu; Song, Jian

2017-03-01

Hybrid electric vehicles (HEVs) provide large potential to save energy and reduce emission, and smart vehicles bring out great convenience and safety for drivers. By combining these two technologies, vehicles may achieve excellent performances in terms of dynamic, economy, environmental friendliness, safety, and comfort. Hence, a smart hybrid electric vehicle (s-HEV) is selected as a platform in this paper to study a car-following process with optimizing the fuel consumption. The whole process is a multi-objective optimal problem, whose optimal solution is not just adding an energy management strategy (EMS) to an adaptive cruise control (ACC), but a deep fusion of these two methods. The problem has more restricted conditions, optimal objectives, and system states, which may result in larger computing burden. Therefore, a novel fuel consumption optimization algorithm based on model predictive control (MPC) is proposed and some search skills are adopted in receding horizon optimization to reduce computing burden. Simulations are carried out and the results indicate that the fuel consumption of proposed method is lower than that of the ACC+EMS method on the condition of ensuring car-following performances.

An evaluation of MPI message rate on hybrid-core processors

DOE PAGES

Barrett, Brian W.; Brightwell, Ron; Grant, Ryan; ...

2014-11-01

Power and energy concerns are motivating chip manufacturers to consider future hybrid-core processor designs that may combine a small number of traditional cores optimized for single-thread performance with a large number of simpler cores optimized for throughput performance. This trend is likely to impact the way in which compute resources for network protocol processing functions are allocated and managed. In particular, the performance of MPI match processing is critical to achieving high message throughput. In this paper, we analyze the ability of simple and more complex cores to perform MPI matching operations for various scenarios in order to gain insightmore » into how MPI implementations for future hybrid-core processors should be designed.« less

Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.

PubMed

Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo

2015-09-01

This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications.

Perspectives on MEMS in bioengineering: a novel capacitive position microsensor.

PubMed

Pedrocchi, A; Hoen, S; Ferrigno, G; Pedotti, A

2000-01-01

We describe a novel capacitive position sensor using micromachining to achieve high sensitivity and large range of motion. These sensors require a new theoretical framework to describe and optimize their performance. Employing a complete description of the electrical fields, the sensor should deviate from the standard geometries used for capacitive sensors. By this optimization, the sensor gains a twofold increase in sensitivity. Results on a PC board 10x model imply that the micromachined sensor should achieve a sensitivity of less than 10 nm over 500-micron range of travel. Some bioengineering applications are addressed, including positioning of micromirrors for laser surgery and dose control for implantable drug delivery systems.

Design issues for optimum solar cell configuration

NASA Astrophysics Data System (ADS)

Kumar, Atul; Thakur, Ajay D.

2018-05-01

A computer based simulation of solar cell structure is performed to study the optimization of pn junction configuration for photovoltaic action. The fundamental aspects of photovoltaic action viz, absorption, separation collection, and their dependence on material properties and deatails of device structures is discussed. Using SCAPS 1D we have simulated the ideal pn junction and shown the effect of band offset and carrier densities on solar cell performance. The optimum configuration can be achieved by optimizing transport of carriers in pn junction under effect of field dependent recombination (tunneling) and density dependent recombination (SRH, Auger) mechanisms.

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

Receding horizon online optimization for torque control of gasoline engines.

PubMed

Kang, Mingxin; Shen, Tielong

2016-11-01

This paper proposes a model-based nonlinear receding horizon optimal control scheme for the engine torque tracking problem. The controller design directly employs the nonlinear model exploited based on mean-value modeling principle of engine systems without any linearizing reformation, and the online optimization is achieved by applying the Continuation/GMRES (generalized minimum residual) approach. Several receding horizon control schemes are designed to investigate the effects of the integral action and integral gain selection. Simulation analyses and experimental validations are implemented to demonstrate the real-time optimization performance and control effects of the proposed torque tracking controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal design of a hybrid MR brake for haptic wrist application

NASA Astrophysics Data System (ADS)

Nguyen, Quoc Hung; Nguyen, Phuong Bac; Choi, Seung-Bok

2011-03-01

In this work, a new configuration of a magnetorheological (MR) brake is proposed and an optimal design of the proposed MR brake for haptic wrist application is performed considering the required braking torque, the zero-field friction torque, the size and mass of the brake. The proposed MR brake configuration is a combination of disc-type and drum-type which is referred as a hybrid configuration in this study. After the MR brake with the hybrid configuration is proposed, braking torque of the brake is analyzed based on Bingham rheological model of the MR fluid. The zero-field friction torque of the MR brake is also obtained. An optimization procedure based on finite element analysis integrated with an optimization tool is developed for the MR brake. The purpose of the optimal design is to find the optimal geometric dimensions of the MR brake structure that can produce the required braking torque and minimize the uncontrollable torque (passive torque) of the haptic wrist. Based on developed optimization procedure, optimal solution of the proposed MR brake is achieved. The proposed optimized hybrid brake is then compared with conventional types of MR brake and discussions on working performance of the proposed MR brake are described.

Planar junctionless phototransistor: A potential high-performance and low-cost device for optical-communications

NASA Astrophysics Data System (ADS)

Ferhati, H.; Djeffal, F.

2017-12-01

In this paper, a new junctionless optical controlled field effect transistor (JL-OCFET) and its comprehensive theoretical model is proposed to achieve high optical performance and low cost fabrication process. Exhaustive study of the device characteristics and comparison between the proposed junctionless design and the conventional inversion mode structure (IM-OCFET) for similar dimensions are performed. Our investigation reveals that the proposed design exhibits an outstanding capability to be an alternative to the IM-OCFET due to the high performance and the weak signal detection benefit offered by this design. Moreover, the developed analytical expressions are exploited to formulate the objective functions to optimize the device performance using Genetic Algorithms (GAs) approach. The optimized JL-OCFET not only demonstrates good performance in terms of derived drain current and responsivity, but also exhibits superior signal to noise ratio, low power consumption, high-sensitivity, high ION/IOFF ratio and high-detectivity as compared to the conventional IM-OCFET counterpart. These characteristics make the optimized JL-OCFET potentially suitable for developing low cost and ultrasensitive photodetectors for high-performance and low cost inter-chips data communication applications.

Broadband absorption enhancement in amorphous Si solar cells using metal gratings and surface texturing

NASA Astrophysics Data System (ADS)

Magdi, Sara; Swillam, Mohamed A.

2017-02-01

The efficiencies of thin film amorphous silicon (a-Si) solar cells are restricted by the small thickness required for efficient carrier collection. This thickness limitations result in poor light absorption. In this work, broadband absorption enhancement is theoretically achieved in a-Si solar cells by using nanostructured back electrode along with surface texturing. The back electrode is formed of Au nanogratings and the surface texturing consists of Si nanocones. The results were then compared to random texturing surfaces. Three dimensional finite difference time domain (FDTD) simulations are used to design and optimize the structure. The Au nanogratings achieved absorption enhancement in the long wavelengths due to sunlight coupling to surface plasmon polaritons (SPP) modes. High absorption enhancement was achieved at short wavelengths due to the decreased reflection and enhanced scattering inside the a-Si absorbing layer. Optimizations have been performed to obtain the optimal geometrical parameters for both the nanogratings and the periodic texturing. In addition, an enhancement factor (i.e. absorbed power in nanostructured device/absorbed power in reference device) was calculated to evaluate the enhancement obtained due to the incorporation of each nanostructure.

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Optimization of microwire/glass-fibre reinforced polymer composites for wind turbine application

NASA Astrophysics Data System (ADS)

Qin, F. X.; Peng, H. X.; Chen, Z.; Wang, H.; Zhang, J. W.; Hilton, G.

2013-11-01

We here report a comprehensive study of glass-fibre reinforced polymers (GFRP) incorporating ferromagnetic microwires for microwave absorption applications. With wire addition, a remarkable dependence of microwave absorption performance appears on the local properties of wires such as wire geometry and the mesostructure such as inter-wire spacing, as well as the embedded depth of the wires layer. The impact testing further demonstrates that the metallic microwires can to some extent improve the impact performance. Based on both the absorption and impact behavior, we propose an optimized design of the microwire/GFRP composites to achieve simultaneous best possible absorption and impact performance for multifunctional applications in aeronautical structures and wind turbines.

[Optimization of radiological scoliosis assessment].

PubMed

Enríquez, Goya; Piqueras, Joaquim; Catalá, Ana; Oliva, Glòria; Ruiz, Agustí; Ribas, Montserrat; Duran, Carmina; Rodrigo, Carlos; Rodríguez, Eugenia; Garriga, Victoria; Maristany, Teresa; García-Fontecha, César; Baños, Joan; Muchart, Jordi; Alava, Fernando

2014-07-01

Most scoliosis are idiopathic (80%) and occur more frequently in adolescent girls. Plain radiography is the imaging method of choice, both for the initial study and follow-up studies but has the disadvantage of using ionizing radiation. The breasts are exposed to x-ray along these repeated examinations. The authors present a range of recommendations in order to optimize radiographic exam technique for both conventional and digital x-ray settings to prevent unnecessary patients' radiation exposure and to reduce the risk of breast cancer in patients with scoliosis. With analogue systems, leaded breast protectors should always be used, and with any radiographic equipment, analog or digital radiography, the examination should be performed in postero-anterior projection and optimized low-dose techniques. The ALARA (as low as reasonable achievable) rule should always be followed to achieve diagnostic quality images with the lowest feasible dose. Copyright © 2014. Published by Elsevier Espana.

High-frequency AC/DC converter with unity power factor and minimum harmonic distortion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wernekinch, E.R.

1987-01-01

The power factor is controlled by adjusting the relative position of the fundamental component of an optimized PWM-type voltage with respect to the supply voltage. Current harmonic distortion is minimized by the use of optimized firing angles for the converter at a frequency where GTO's can be used. This feature makes this approach very attractive at power levels of 100 to 600 kW. To obtain the optimized PWM pattern, a steepest descent digital computer algorithm is used. Digital-computer simulations are performed and a low-power model is constructed and tested to verify the concepts and the behavior of the model. Experimentalmore » results show that unity power factor is achieved and that the distortion in the phase currents is 10.4% at 90% of full load. This is less than achievable with sinusoidal PWM, harmonic elimination, hysteresis control, and deadbeat control for the same switching frequency.« less

Analysis of torque transmitting behavior and wheel slip prevention control during regenerative braking for high speed EMU trains

NASA Astrophysics Data System (ADS)

Xu, Kun; Xu, Guo-Qing; Zheng, Chun-Hua

2016-04-01

The wheel-rail adhesion control for regenerative braking systems of high speed electric multiple unit trains is crucial to maintaining the stability, improving the adhesion utilization, and achieving deep energy recovery. There remain technical challenges mainly because of the nonlinear, uncertain, and varying features of wheel-rail contact conditions. This research analyzes the torque transmitting behavior during regenerative braking, and proposes a novel methodology to detect the wheel-rail adhesion stability. Then, applications to the wheel slip prevention during braking are investigated, and the optimal slip ratio control scheme is proposed, which is based on a novel optimal reference generation of the slip ratio and a robust sliding mode control. The proposed methodology achieves the optimal braking performance without the wheel-rail contact information. Numerical simulation results for uncertain slippery rails verify the effectiveness of the proposed methodology.

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

PubMed

Lee, Jong-Seok; Park, Cheol Hoon

2010-08-01

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

Investigating the optimal passive and active vibration controls of adjacent buildings based on performance indices using genetic algorithms

NASA Astrophysics Data System (ADS)

Hadi, Muhammad N. S.; Uz, Mehmet E.

2015-02-01

This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimization to minimize the H2 and H∞ norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H∞ norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control force between the buildings. The proposed method is more effective than other metaheuristic methods and more feasible, although the control force increased. The results in the active control system show that the response of adjacent buildings is reduced in an efficient manner.

A rapid method for optimization of the rocket propulsion system for single-stage-to-orbit vehicles

NASA Technical Reports Server (NTRS)

Eldred, C. H.; Gordon, S. V.

1976-01-01

A rapid analytical method for the optimization of rocket propulsion systems is presented for a vertical take-off, horizontal landing, single-stage-to-orbit launch vehicle. This method utilizes trade-offs between propulsion characteristics affecting flight performance and engine system mass. The performance results from a point-mass trajectory optimization program are combined with a linearized sizing program to establish vehicle sizing trends caused by propulsion system variations. The linearized sizing technique was developed for the class of vehicle systems studied herein. The specific examples treated are the optimization of nozzle expansion ratio and lift-off thrust-to-weight ratio to achieve either minimum gross mass or minimum dry mass. Assumed propulsion system characteristics are high chamber pressure, liquid oxygen and liquid hydrogen propellants, conventional bell nozzles, and the same fixed nozzle expansion ratio for all engines on a vehicle.

Design optimization of a high specific speed Francis turbine runner

NASA Astrophysics Data System (ADS)

Enomoto, Y.; Kurosawa, S.; Kawajiri, H.

2012-11-01

Francis turbine is used in many hydroelectric power stations. This paper presents the development of hydraulic performance in a high specific speed Francis turbine runner. In order to achieve the improvements of turbine efficiency throughout a wide operating range, a new runner design method which combines the latest Computational Fluid Dynamics (CFD) and a multi objective optimization method with an existing design system was applied in this study. The validity of the new design system was evaluated by model performance tests. As the results, it was confirmed that the optimized runner presented higher efficiency compared with an originally designed runner. Besides optimization of runner, instability vibration which occurred at high part load operating condition was investigated by model test and gas-liquid two-phase flow analysis. As the results, it was confirmed that the instability vibration was caused by oval cross section whirl which was caused by recirculation flow near runner cone wall.

The universal scissor component: Optimization of a reconfigurable component for deployable scissor structures

NASA Astrophysics Data System (ADS)

Alegria Mira, Lara; Thrall, Ashley P.; De Temmerman, Niels

2016-02-01

Deployable scissor structures are well equipped for temporary and mobile applications since they are able to change their form and functionality. They are structural mechanisms that transform from a compact state to an expanded, fully deployed configuration. A barrier to the current design and reuse of scissor structures, however, is that they are traditionally designed for a single purpose. Alternatively, a universal scissor component (USC)-a generalized element which can achieve all traditional scissor types-introduces an opportunity for reuse in which the same component can be utilized for different configurations and spans. In this article, the USC is optimized for structural performance. First, an optimized length for the USC is determined based on a trade-off between component weight and structural performance (measured by deflections). Then, topology optimization, using the simulated annealing algorithm, is implemented to determine a minimum weight layout of beams within a single USC component.

Multi-objective Optimization Strategies Using Adjoint Method and Game Theory in Aerodynamics

NASA Astrophysics Data System (ADS)

Tang, Zhili

2006-08-01

There are currently three different game strategies originated in economics: (1) Cooperative games (Pareto front), (2) Competitive games (Nash game) and (3) Hierarchical games (Stackelberg game). Each game achieves different equilibria with different performance, and their players play different roles in the games. Here, we introduced game concept into aerodynamic design, and combined it with adjoint method to solve multi-criteria aerodynamic optimization problems. The performance distinction of the equilibria of these three game strategies was investigated by numerical experiments. We computed Pareto front, Nash and Stackelberg equilibria of the same optimization problem with two conflicting and hierarchical targets under different parameterizations by using the deterministic optimization method. The numerical results show clearly that all the equilibria solutions are inferior to the Pareto front. Non-dominated Pareto front solutions are obtained, however the CPU cost to capture a set of solutions makes the Pareto front an expensive tool to the designer.

Initial Ares I Bending Filter Design

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Bedrossian, Nazareth; Hall, Robert; Norris, H. Lee; Hall, Charles; Jackson, Mark

2007-01-01

The Ares-I launch vehicle represents a challenging flex-body structural environment for control system design. Software filtering of the inertial sensor output will be required to ensure control system stability and adequate performance. This paper presents a design methodology employing numerical optimization to develop the Ares-I bending filters. The filter design methodology was based on a numerical constrained optimization approach to maximize stability margins while meeting performance requirements. The resulting bending filter designs achieved stability by adding lag to the first structural frequency and hence phase stabilizing the first Ares-I flex mode. To minimize rigid body performance impacts, a priority was placed via constraints in the optimization algorithm to minimize bandwidth decrease with the addition of the bending filters. The bending filters provided here have been demonstrated to provide a stable first stage control system in both the frequency domain and the MSFC MAVERIC time domain simulation.

New Enhanced Artificial Bee Colony (JA-ABC5) Algorithm with Application for Reactive Power Optimization

PubMed Central

2015-01-01

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement. PMID:25879054

Parameter optimization of electrochemical machining process using black hole algorithm

NASA Astrophysics Data System (ADS)

Singh, Dinesh; Shukla, Rajkamal

2017-12-01

Advanced machining processes are significant as higher accuracy in machined component is required in the manufacturing industries. Parameter optimization of machining processes gives optimum control to achieve the desired goals. In this paper, electrochemical machining (ECM) process is considered to evaluate the performance of the considered process using black hole algorithm (BHA). BHA considers the fundamental idea of a black hole theory and it has less operating parameters to tune. The two performance parameters, material removal rate (MRR) and overcut (OC) are considered separately to get optimum machining parameter settings using BHA. The variations of process parameters with respect to the performance parameters are reported for better and effective understanding of the considered process using single objective at a time. The results obtained using BHA are found better while compared with results of other metaheuristic algorithms, such as, genetic algorithm (GA), artificial bee colony (ABC) and bio-geography based optimization (BBO) attempted by previous researchers.

New enhanced artificial bee colony (JA-ABC5) algorithm with application for reactive power optimization.

PubMed

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-01-01

The standard artificial bee colony (ABC) algorithm involves exploration and exploitation processes which need to be balanced for enhanced performance. This paper proposes a new modified ABC algorithm named JA-ABC5 to enhance convergence speed and improve the ability to reach the global optimum by balancing exploration and exploitation processes. New stages have been proposed at the earlier stages of the algorithm to increase the exploitation process. Besides that, modified mutation equations have also been introduced in the employed and onlooker-bees phases to balance the two processes. The performance of JA-ABC5 has been analyzed on 27 commonly used benchmark functions and tested to optimize the reactive power optimization problem. The performance results have clearly shown that the newly proposed algorithm has outperformed other compared algorithms in terms of convergence speed and global optimum achievement.

Statistical model based iterative reconstruction in clinical CT systems. Part III. Task-based kV/mAs optimization for radiation dose reduction

PubMed Central

Li, Ke; Gomez-Cardona, Daniel; Hsieh, Jiang; Lubner, Meghan G.; Pickhardt, Perry J.; Chen, Guang-Hong

2015-01-01

Purpose: For a given imaging task and patient size, the optimal selection of x-ray tube potential (kV) and tube current-rotation time product (mAs) is pivotal in achieving the maximal radiation dose reduction while maintaining the needed diagnostic performance. Although contrast-to-noise (CNR)-based strategies can be used to optimize kV/mAs for computed tomography (CT) imaging systems employing the linear filtered backprojection (FBP) reconstruction method, a more general framework needs to be developed for systems using the nonlinear statistical model-based iterative reconstruction (MBIR) method. The purpose of this paper is to present such a unified framework for the optimization of kV/mAs selection for both FBP- and MBIR-based CT systems. Methods: The optimal selection of kV and mAs was formulated as a constrained optimization problem to minimize the objective function, Dose(kV,mAs), under the constraint that the achievable detectability index d′(kV,mAs) is not lower than the prescribed value of d℞′ for a given imaging task. Since it is difficult to analytically model the dependence of d′ on kV and mAs for the highly nonlinear MBIR method, this constrained optimization problem is solved with comprehensive measurements of Dose(kV,mAs) and d′(kV,mAs) at a variety of kV–mAs combinations, after which the overlay of the dose contours and d′ contours is used to graphically determine the optimal kV–mAs combination to achieve the lowest dose while maintaining the needed detectability for the given imaging task. As an example, d′ for a 17 mm hypoattenuating liver lesion detection task was experimentally measured with an anthropomorphic abdominal phantom at four tube potentials (80, 100, 120, and 140 kV) and fifteen mA levels (25 and 50–700) with a sampling interval of 50 mA at a fixed rotation time of 0.5 s, which corresponded to a dose (CTDIvol) range of [0.6, 70] mGy. Using the proposed method, the optimal kV and mA that minimized dose for the prescribed detectability level of d℞′=16 were determined. As another example, the optimal kV and mA for an 8 mm hyperattenuating liver lesion detection task were also measured using the developed framework. Both an in vivo animal and human subject study were used as demonstrations of how the developed framework can be applied to the clinical work flow. Results: For the first task, the optimal kV and mAs were measured to be 100 and 500, respectively, for FBP, which corresponded to a dose level of 24 mGy. In comparison, the optimal kV and mAs for MBIR were 80 and 150, respectively, which corresponded to a dose level of 4 mGy. The topographies of the iso-d′ map and the iso-CNR map were the same for FBP; thus, the use of d′- and CNR-based optimization methods generated the same results for FBP. However, the topographies of the iso-d′ and iso-CNR map were significantly different in MBIR; the CNR-based method overestimated the performance of MBIR, predicting an overly aggressive dose reduction factor. For the second task, the developed framework generated the following optimization results: for FBP, kV = 140, mA = 350, dose = 37.5 mGy; for MBIR, kV = 120, mA = 250, dose = 18.8 mGy. Again, the CNR-based method overestimated the performance of MBIR. Results of the preliminary in vivo studies were consistent with those of the phantom experiments. Conclusions: A unified and task-driven kV/mAs optimization framework has been developed in this work. The framework is applicable to both linear and nonlinear CT systems such as those using the MBIR method. As expected, the developed framework can be reduced to the conventional CNR-based kV/mAs optimization frameworks if the system is linear. For MBIR-based nonlinear CT systems, however, the developed task-based kV/mAs optimization framework is needed to achieve the maximal dose reduction while maintaining the desired diagnostic performance. PMID:26328971

Striving for Excellence Sometimes Hinders High Achievers: Performance-Approach Goals Deplete Arithmetical Performance in Students with High Working Memory Capacity

PubMed Central

Crouzevialle, Marie; Smeding, Annique; Butera, Fabrizio

2015-01-01

We tested whether the goal to attain normative superiority over other students, referred to as performance-approach goals, is particularly distractive for high-Working Memory Capacity (WMC) students—that is, those who are used to being high achievers. Indeed, WMC is positively related to high-order cognitive performance and academic success, a record of success that confers benefits on high-WMC as compared to low-WMC students. We tested whether such benefits may turn out to be a burden under performance-approach goal pursuit. Indeed, for high achievers, aiming to rise above others may represent an opportunity to reaffirm their positive status—a stake susceptible to trigger disruptive outcome concerns that interfere with task processing. Results revealed that with performance-approach goals—as compared to goals with no emphasis on social comparison—the higher the students’ WMC, the lower their performance at a complex arithmetic task (Experiment 1). Crucially, this pattern appeared to be driven by uncertainty regarding the chances to outclass others (Experiment 2). Moreover, an accessibility measure suggested the mediational role played by status-related concerns in the observed disruption of performance. We discuss why high-stake situations can paradoxically lead high-achievers to sub-optimally perform when high-order cognitive performance is at play. PMID:26407097

Design optimization of piezoresistive cantilevers for force sensing in air and water

PubMed Central

Doll, Joseph C.; Park, Sung-Jin; Pruitt, Beth L.

2009-01-01

Piezoresistive cantilevers fabricated from doped silicon or metal films are commonly used for force, topography, and chemical sensing at the micro- and macroscales. Proper design is required to optimize the achievable resolution by maximizing sensitivity while simultaneously minimizing the integrated noise over the bandwidth of interest. Existing analytical design methods are insufficient for modeling complex dopant profiles, design constraints, and nonlinear phenomena such as damping in fluid. Here we present an optimization method based on an analytical piezoresistive cantilever model. We use an existing iterative optimizer to minimimize a performance goal, such as minimum detectable force. The design tool is available as open source software. Optimal cantilever design and performance are found to strongly depend on the measurement bandwidth and the constraints applied. We discuss results for silicon piezoresistors fabricated by epitaxy and diffusion, but the method can be applied to any dopant profile or material which can be modeled in a similar fashion or extended to other microelectromechanical systems. PMID:19865512

Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Ouyang, Huei-Tau

2017-07-01

Three types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive model with exogenous inputs (LARX), the nonlinear autoregressive model with exogenous inputs with wavelet function (NLARX-W) and the nonlinear autoregressive model with exogenous inputs with sigmoid function (NLARX-S). The forecast performance was evaluated by three indices: coefficient of efficiency, error in peak water level and relative time shift. Historical typhoon data were used to establish water-level forecasting models that satisfy all three objectives. A multi-objective genetic algorithm was employed to search for the Pareto-optimal model set that satisfies all three objectives and select the ideal models for the three indices. Findings showed that the optimized nonlinear models (NLARX-W and NLARX-S) outperformed the linear model (LARX). Among the nonlinear models, the optimized NLARX-W model achieved a more balanced performance on the three indices than the NLARX-S models and is recommended for inundation forecasting during typhoons.

Performance of InGaAs short wave infrared avalanche photodetector for low flux imaging

NASA Astrophysics Data System (ADS)

Singh, Anand; Pal, Ravinder

2017-11-01

Opto-electronic performance of the InGaAs/i-InGaAs/InP short wavelength infrared focal plane array suitable for high resolution imaging under low flux conditions and ranging is presented. More than 85% quantum efficiency is achieved in the optimized detector structure. Isotropic nature of the wet etching process poses a challenge in maintaining the required control in the small pitch high density detector array. Etching process is developed to achieve low dark current density of 1 nA/cm2 in the detector array with 25 µm pitch at 298 K. Noise equivalent photon performance less than one is achievable showing single photon detection capability. The reported photodiode with low photon flux is suitable for active cum passive imaging, optical information processing and quantum computing applications.

HPF Implementation of ARC3D

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Yan, Jerry

1999-01-01

We present an HPF (High Performance Fortran) implementation of ARC3D code along with the profiling and performance data on SGI Origin 2000. Advantages and limitations of HPF as a parallel programming language for CFD applications are discussed. For achieving good performance results we used the data distributions optimized for implementation of implicit and explicit operators of the solver and boundary conditions. We compare the results with MPI and directive based implementations.

Optimal design of reverse osmosis module networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maskan, F.; Wiley, D.E.; Johnston, L.P.M.

2000-05-01

The structure of individual reverse osmosis modules, the configuration of the module network, and the operating conditions were optimized for seawater and brackish water desalination. The system model included simple mathematical equations to predict the performance of the reverse osmosis modules. The optimization problem was formulated as a constrained multivariable nonlinear optimization. The objective function was the annual profit for the system, consisting of the profit obtained from the permeate, capital cost for the process units, and operating costs associated with energy consumption and maintenance. Optimization of several dual-stage reverse osmosis systems were investigated and compared. It was found thatmore » optimal network designs are the ones that produce the most permeate. It may be possible to achieve economic improvements by refining current membrane module designs and their operating pressures.« less

Detailed design of a lattice composite fuselage structure by a mixed optimization method

NASA Astrophysics Data System (ADS)

Liu, D.; Lohse-Busch, H.; Toropov, V.; Hühne, C.; Armani, U.

2016-10-01

In this article, a procedure for designing a lattice fuselage barrel is developed. It comprises three stages: first, topology optimization of an aircraft fuselage barrel is performed with respect to weight and structural performance to obtain the conceptual design. The interpretation of the optimal result is given to demonstrate the development of this new lattice airframe concept for the fuselage barrel. Subsequently, parametric optimization of the lattice aircraft fuselage barrel is carried out using genetic algorithms on metamodels generated with genetic programming from a 101-point optimal Latin hypercube design of experiments. The optimal design is achieved in terms of weight savings subject to stability, global stiffness and strain requirements, and then verified by the fine mesh finite element simulation of the lattice fuselage barrel. Finally, a practical design of the composite skin complying with the aircraft industry lay-up rules is presented. It is concluded that the mixed optimization method, combining topology optimization with the global metamodel-based approach, allows the problem to be solved with sufficient accuracy and provides the designers with a wealth of information on the structural behaviour of the novel anisogrid composite fuselage design.

Optimal design study of high efficiency indium phosphide space solar cells

NASA Technical Reports Server (NTRS)

Jain, Raj K.; Flood, Dennis J.

1990-01-01

Recently indium phosphide solar cells have achieved beginning of life AMO efficiencies in excess of 19 pct. at 25 C. The high efficiency prospects along with superb radiation tolerance make indium phosphide a leading material for space power requirements. To achieve cost effectiveness, practical cell efficiencies have to be raised to near theoretical limits and thin film indium phosphide cells need to be developed. The optimal design study is described of high efficiency indium phosphide solar cells for space power applications using the PC-1D computer program. It is shown that cells with efficiencies over 22 pct. AMO at 25 C could be fabricated by achieving proper material and process parameters. It is observed that further improvements in cell material and process parameters could lead to experimental cell efficiencies near theoretical limits. The effect of various emitter and base parameters on cell performance was studied.

Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools

NASA Astrophysics Data System (ADS)

Ouyang, Qin; Chen, Quansheng; Zhao, Jiewen

2016-02-01

The approach presented herein reports the application of near infrared (NIR) spectroscopy, in contrast with human sensory panel, as a tool for estimating Chinese rice wine quality; concretely, to achieve the prediction of the overall sensory scores assigned by the trained sensory panel. Back propagation artificial neural network (BPANN) combined with adaptive boosting (AdaBoost) algorithm, namely BP-AdaBoost, as a novel nonlinear algorithm, was proposed in modeling. First, the optimal spectra intervals were selected by synergy interval partial least square (Si-PLS). Then, BP-AdaBoost model based on the optimal spectra intervals was established, called Si-BP-AdaBoost model. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient (Rp) and root mean square error of prediction (RMSEP) in prediction set. Si-BP-AdaBoost showed excellent performance in comparison with other models. The best Si-BP-AdaBoost model was achieved with Rp = 0.9180 and RMSEP = 2.23 in the prediction set. It was concluded that NIR spectroscopy combined with Si-BP-AdaBoost was an appropriate method for the prediction of the sensory quality in Chinese rice wine.

Process control systems: integrated for future process technologies

NASA Astrophysics Data System (ADS)

Botros, Youssry; Hajj, Hazem M.

2003-06-01

Process Control Systems (PCS) are becoming more crucial to the success of Integrated Circuit makers due to their direct impact on product quality, cost, and Fab output. The primary objective of PCS is to minimize variability by detecting and correcting non optimal performance. Current PCS implementations are considered disparate, where each PCS application is designed, deployed and supported separately. Each implementation targets a specific area of control such as equipment performance, wafer manufacturing, and process health monitoring. With Intel entering the nanometer technology era, tighter process specifications are required for higher yields and lower cost. This requires areas of control to be tightly coupled and integrated to achieve the optimal performance. This requirement can be achieved via consistent design and deployment of the integrated PCS. PCS integration will result in several benefits such as leveraging commonalities, avoiding redundancy, and facilitating sharing between implementations. This paper will address PCS implementations and focus on benefits and requirements of the integrated PCS. Intel integrated PCS Architecture will be then presented and its components will be briefly discussed. Finally, industry direction and efforts to standardize PCS interfaces that enable PCS integration will be presented.

Optimized flexible cover films for improved conversion efficiency in thin film flexible solar cells

NASA Astrophysics Data System (ADS)

Guterman, Sidney; Wen, Xin; Gudavalli, Ganesh; Rhajbhandari, Pravakar; Dhakal, Tara P.; Wilt, David; Klotzkin, David

2018-05-01

Thin film solar cell technologies are being developed for lower cost and flexible applications. For such technologies, it is desirable to have inexpensive, flexible cover strips. In this paper, we demonstrate that transparent silicone cover glass adhesive can be doped with TiO2 nanoparticles to achieve an optimal refractive index and maximize the performance of the cell. Cells covered with the film doped with nanoparticles at the optimal concentration demonstrated a ∼1% increase in photocurrent over the plain (undoped) film. In addition, fused silica beads can be incorporated into the flexible cover slip to realize a built-in pseudomorphic glass diffuser layer as well. This additional degree of freedom in engineering flexible solar cell covers allows maximal performance from a given cell for minimal increased cost.

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-12-01

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

On the Efficacy of Source Code Optimizations for Cache-Based Systems

NASA Technical Reports Server (NTRS)

VanderWijngaart, Rob F.; Saphir, William C.

1998-01-01

Obtaining high performance without machine-specific tuning is an important goal of scientific application programmers. Since most scientific processing is done on commodity microprocessors with hierarchical memory systems, this goal of "portable performance" can be achieved if a common set of optimization principles is effective for all such systems. It is widely believed, or at least hoped, that portable performance can be realized. The rule of thumb for optimization on hierarchical memory systems is to maximize temporal and spatial locality of memory references by reusing data and minimizing memory access stride. We investigate the effects of a number of optimizations on the performance of three related kernels taken from a computational fluid dynamics application. Timing the kernels on a range of processors, we observe an inconsistent and often counterintuitive impact of the optimizations on performance. In particular, code variations that have a positive impact on one architecture can have a negative impact on another, and variations expected to be unimportant can produce large effects. Moreover, we find that cache miss rates - as reported by a cache simulation tool, and confirmed by hardware counters - only partially explain the results. By contrast, the compiler-generated assembly code provides more insight by revealing the importance of processor-specific instructions and of compiler maturity, both of which strongly, and sometimes unexpectedly, influence performance. We conclude that it is difficult to obtain performance portability on modern cache-based computers, and comment on the implications of this result.

On the Efficacy of Source Code Optimizations for Cache-Based Systems

NASA Technical Reports Server (NTRS)

VanderWijngaart, Rob F.; Saphir, William C.; Saini, Subhash (Technical Monitor)

1998-01-01

Obtaining high performance without machine-specific tuning is an important goal of scientific application programmers. Since most scientific processing is done on commodity microprocessors with hierarchical memory systems, this goal of "portable performance" can be achieved if a common set of optimization principles is effective for all such systems. It is widely believed, or at least hoped, that portable performance can be realized. The rule of thumb for optimization on hierarchical memory systems is to maximize temporal and spatial locality of memory references by reusing data and minimizing memory access stride. We investigate the effects of a number of optimizations on the performance of three related kernels taken from a computational fluid dynamics application. Timing the kernels on a range of processors, we observe an inconsistent and often counterintuitive impact of the optimizations on performance. In particular, code variations that have a positive impact on one architecture can have a negative impact on another, and variations expected to be unimportant can produce large effects. Moreover, we find that cache miss rates-as reported by a cache simulation tool, and confirmed by hardware counters-only partially explain the results. By contrast, the compiler-generated assembly code provides more insight by revealing the importance of processor-specific instructions and of compiler maturity, both of which strongly, and sometimes unexpectedly, influence performance. We conclude that it is difficult to obtain performance portability on modern cache-based computers, and comment on the implications of this result.

Linear antenna array optimization using flower pollination algorithm.

PubMed

Saxena, Prerna; Kothari, Ashwin

2016-01-01

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

Optimization study on inductive-resistive circuit for broadband piezoelectric energy harvesters

NASA Astrophysics Data System (ADS)

Tan, Ting; Yan, Zhimiao

2017-03-01

The performance of cantilever-beam piezoelectric energy harvester is usually analyzed with pure resistive circuit. The optimal performance of such a vibration-based energy harvesting system is limited by narrow bandwidth around its modified natural frequency. For broadband piezoelectric energy harvesting, series and parallel inductive-resistive circuits are introduced. The electromechanical coupled distributed parameter models for such systems under harmonic base excitations are decoupled with modified natural frequency and electrical damping to consider the coupling effect. Analytical solutions of the harvested power and tip displacement for the electromechanical decoupled model are confirmed with numerical solutions for the coupled model. The optimal performance of piezoelectric energy harvesting with inductive-resistive circuits is revealed theoretically as constant maximal power at any excitation frequency. This is achieved by the scenarios of matching the modified natural frequency with the excitation frequency and equating the electrical damping to the mechanical damping. The inductance and load resistance should be simultaneously tuned to their optimal values, which may not be applicable for very high electromechanical coupling systems when the excitation frequency is higher than their natural frequencies. With identical optimal performance, the series inductive-resistive circuit is recommended for relatively small load resistance, while the parallel inductive-resistive circuit is suggested for relatively large load resistance. This study provides a simplified optimization method for broadband piezoelectric energy harvesters with inductive-resistive circuits.

A Multidisciplinary Performance Analysis of a Lifting-Body Single-Stage-to-Orbit Vehicle

NASA Technical Reports Server (NTRS)

Tartabini, Paul V.; Lepsch, Roger A.; Korte, J. J.; Wurster, Kathryn E.

2000-01-01

Lockheed Martin Skunk Works (LMSW) is currently developing a single-stage-to-orbit reusable launch vehicle called VentureStar(TM) A team at NASA Langley Research Center participated with LMSW in the screening and evaluation of a number of early VentureStar(TM) configurations. The performance analyses that supported these initial studies were conducted to assess the effect of a lifting body shape, linear aerospike engine and metallic thermal protection system (TPS) on the weight and performance of the vehicle. These performance studies were performed in a multidisciplinary fashion that indirectly linked the trajectory optimization with weight estimation and aerothermal analysis tools. This approach was necessary to develop optimized ascent and entry trajectories that met all vehicle design constraints. Significant improvements in ascent performance were achieved when the vehicle flew a lifting trajectory and varied the engine mixture ratio during flight. Also, a considerable reduction in empty weight was possible by adjusting the total oxidizer-to-fuel and liftoff thrust-to-weight ratios. However, the optimal ascent flight profile had to be altered to ensure that the vehicle could be trimmed in pitch using only the flow diverting capability of the aerospike engine. Likewise, the optimal entry trajectory had to be tailored to meet TPS heating rate and transition constraints while satisfying a crossrange requirement.

Development of a 4 K Separate Two-Stage Pulse Tube Refrigerator with High Efficiency

NASA Astrophysics Data System (ADS)

Qiu, L. M.; He, Y. L.; Gan, Z. H.; Chen, G. B.

2006-04-01

Compared to the traditional 4 K cryocoolers, the separate 4 K pulse tube refrigerator (PTR) consists of two independent PTRs, which are thermally connected between the cold end of the first stage and some middle position of the second stage regenerator. It is possible to use different frequency, valve timing, phase shifter and even compressor for each stage for better cooling performance. A 4 K separate two-stage PTR was designed and manufactured. The first stage was separately optimized. A minimum temperature of 12.6 K and cooling capacity of 59.0 W at 40 K was achieved for the first stage by adding some Er3Ni at the cold part of the regenerator. An experimental investigation of valve timing effects on the cooling performance of the 4 K separate two-stage PTR is reported. The experiments show that the optimization of valve timing can considerably improve the cooling performance of the PTR. Cooling capacity of 0.59 W at 4.2 K and 15.4 W at 37.0 K were achieved with an actual input power of 6.6 kW. Effect of frequency on the performance of the separate two-stage PTR is also presented.

Sequential Nonlinear Learning for Distributed Multiagent Systems via Extreme Learning Machines.

PubMed

Vanli, Nuri Denizcan; Sayin, Muhammed O; Delibalta, Ibrahim; Kozat, Suleyman Serdar

2017-03-01

We study online nonlinear learning over distributed multiagent systems, where each agent employs a single hidden layer feedforward neural network (SLFN) structure to sequentially minimize arbitrary loss functions. In particular, each agent trains its own SLFN using only the data that is revealed to itself. On the other hand, the aim of the multiagent system is to train the SLFN at each agent as well as the optimal centralized batch SLFN that has access to all the data, by exchanging information between neighboring agents. We address this problem by introducing a distributed subgradient-based extreme learning machine algorithm. The proposed algorithm provides guaranteed upper bounds on the performance of the SLFN at each agent and shows that each of these individual SLFNs asymptotically achieves the performance of the optimal centralized batch SLFN. Our performance guarantees explicitly distinguish the effects of data- and network-dependent parameters on the convergence rate of the proposed algorithm. The experimental results illustrate that the proposed algorithm achieves the oracle performance significantly faster than the state-of-the-art methods in the machine learning and signal processing literature. Hence, the proposed method is highly appealing for the applications involving big data.

Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms

DOE PAGES

Ibrahim, Khaled Z.; Madduri, Kamesh; Williams, Samuel; ...

2013-07-18

The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This paper presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Finally, our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2× speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.

Structural Tailoring of Advanced Turboprops (STAT)

NASA Technical Reports Server (NTRS)

Brown, Kenneth W.

1988-01-01

This interim report describes the progress achieved in the structural Tailoring of Advanced Turboprops (STAT) program which was developed to perform numerical optimizations on highly swept propfan blades. The optimization procedure seeks to minimize an objective function, defined as either direct operating cost or aeroelastic differences between a blade and its scaled model, by tuning internal and external geometry variables that must satisfy realistic blade design constraints. This report provides a detailed description of the input, optimization procedures, approximate analyses and refined analyses, as well as validation test cases for the STAT program. In addition, conclusions and recommendations are summarized.

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

Stochastic seismic response of building with super-elastic damper

NASA Astrophysics Data System (ADS)

Gur, Sourav; Mishra, Sudib Kumar; Roy, Koushik

2016-05-01

Hysteretic yield dampers are widely employed for seismic vibration control of buildings. An improved version of such damper has been proposed recently by exploiting the superelastic force-deformation characteristics of the Shape-Memory-Alloy (SMA). Although a number of studies have illustrated the performance of such damper, precise estimate of the optimal parameters and performances, along with the comparison with the conventional yield damper is lacking. Presently, the optimal parameters for the superelastic damper are proposed by conducting systematic design optimization, in which, the stochastic response serves as the objective function, evaluated through nonlinear random vibration analysis. These optimal parameters can be employed to establish an initial design for the SMA-damper. Further, a comparison among the optimal responses is also presented in order to assess the improvement that can be achieved by the superelastic damper over the yield damper. The consistency of the improvements is also checked by considering the anticipated variation in the system parameters as well as seismic loading condition. In spite of the improved performance of super-elastic damper, the available variant of SMA(s) is quite expensive to limit their applicability. However, recently developed ferrous SMA are expected to offer even superior performance along with improved cost effectiveness, that can be studied through a life cycle cost analysis in future work.

Paroxysmal atrial fibrillation prediction based on HRV analysis and non-dominated sorting genetic algorithm III.

PubMed

Boon, K H; Khalil-Hani, M; Malarvili, M B

2018-01-01

This paper presents a method that able to predict the paroxysmal atrial fibrillation (PAF). The method uses shorter heart rate variability (HRV) signals when compared to existing methods, and achieves good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to electrically stabilize and prevent the onset of atrial arrhythmias with different pacing techniques. We propose a multi-objective optimization algorithm based on the non-dominated sorting genetic algorithm III for optimizing the baseline PAF prediction system, that consists of the stages of pre-processing, HRV feature extraction, and support vector machine (SVM) model. The pre-processing stage comprises of heart rate correction, interpolation, and signal detrending. After that, time-domain, frequency-domain, non-linear HRV features are extracted from the pre-processed data in feature extraction stage. Then, these features are used as input to the SVM for predicting the PAF event. The proposed optimization algorithm is used to optimize the parameters and settings of various HRV feature extraction algorithms, select the best feature subsets, and tune the SVM parameters simultaneously for maximum prediction performance. The proposed method achieves an accuracy rate of 87.7%, which significantly outperforms most of the previous works. This accuracy rate is achieved even with the HRV signal length being reduced from the typical 30 min to just 5 min (a reduction of 83%). Furthermore, another significant result is the sensitivity rate, which is considered more important that other performance metrics in this paper, can be improved with the trade-off of lower specificity. Copyright © 2017 Elsevier B.V. All rights reserved.

Robust control of flexible space vehicles with minimum structural excitation: On-off pulse control of flexible space vehicles

NASA Technical Reports Server (NTRS)

Wie, Bong; Liu, Qiang

1992-01-01

Both feedback and feedforward control approaches for uncertain dynamical systems (in particular, with uncertainty in structural mode frequency) are investigated. The control objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant uncertainty. Preshaping of an ideal, time optimal control input using a tapped-delay filter is shown to provide a fast settling time with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. It is shown that a properly designed, feedback controller performs well, as compared with a time optimal open loop controller with special preshaping for performance robustness. Also included are two separate papers by the same authors on this subject.

Quantum cloning by cellular automata

NASA Astrophysics Data System (ADS)

D'Ariano, G. M.; Macchiavello, C.; Rossi, M.

2013-03-01

We introduce a quantum cellular automaton that achieves approximate phase-covariant cloning of qubits. The automaton is optimized for 1→2N economical cloning. The use of the automaton for cloning allows us to exploit different foliations for improving the performance with given resources.

Solar thermal collectors using planar reflector

NASA Technical Reports Server (NTRS)

Espy, P. N.

1978-01-01

Specular reflectors have been used successfully with flat-plate collectors to achieve exceptionally high operating temperatures and high delivered energy per unit collector area. Optimal orientation of collectors and reflectors can result in even higher performance with an improved relationship between energy demand and supply. This paper reports on a study providing first order optimization of collector-reflector arrays in which single- and multiple-faceted reflectors in fixed or singly adjustable configurations provide delivered energy maxima in either summer or winter.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

Midfield wireless powering of subwavelength autonomous devices.

PubMed

Kim, Sanghoek; Ho, John S; Poon, Ada S Y

2013-05-17

We obtain an analytical bound on the efficiency of wireless power transfer to a weakly coupled device. The optimal source is solved for a multilayer geometry in terms of a representation based on the field equivalence principle. The theory reveals that optimal power transfer exploits the properties of the midfield to achieve efficiencies far greater than conventional coil-based designs. As a physical realization of the source, we present a slot array structure whose performance closely approaches the theoretical bound.

Meta-heuristic algorithms as tools for hydrological science

NASA Astrophysics Data System (ADS)

Yoo, Do Guen; Kim, Joong Hoon

2014-12-01

In this paper, meta-heuristic optimization techniques are introduced and their applications to water resources engineering, particularly in hydrological science are introduced. In recent years, meta-heuristic optimization techniques have been introduced that can overcome the problems inherent in iterative simulations. These methods are able to find good solutions and require limited computation time and memory use without requiring complex derivatives. Simulation-based meta-heuristic methods such as Genetic algorithms (GAs) and Harmony Search (HS) have powerful searching abilities, which can occasionally overcome the several drawbacks of traditional mathematical methods. For example, HS algorithms can be conceptualized from a musical performance process and used to achieve better harmony; such optimization algorithms seek a near global optimum determined by the value of an objective function, providing a more robust determination of musical performance than can be achieved through typical aesthetic estimation. In this paper, meta-heuristic algorithms and their applications (focus on GAs and HS) in hydrological science are discussed by subject, including a review of existing literature in the field. Then, recent trends in optimization are presented and a relatively new technique such as Smallest Small World Cellular Harmony Search (SSWCHS) is briefly introduced, with a summary of promising results obtained in previous studies. As a result, previous studies have demonstrated that meta-heuristic algorithms are effective tools for the development of hydrological models and the management of water resources.

Robust Airfoil Optimization to Achieve Consistent Drag Reduction Over a Mach Range

NASA Technical Reports Server (NTRS)

Li, Wu; Huyse, Luc; Padula, Sharon; Bushnell, Dennis M. (Technical Monitor)

2001-01-01

We prove mathematically that in order to avoid point-optimization at the sampled design points for multipoint airfoil optimization, the number of design points must be greater than the number of free-design variables. To overcome point-optimization at the sampled design points, a robust airfoil optimization method (called the profile optimization method) is developed and analyzed. This optimization method aims at a consistent drag reduction over a given Mach range and has three advantages: (a) it prevents severe degradation in the off-design performance by using a smart descent direction in each optimization iteration, (b) there is no random airfoil shape distortion for any iterate it generates, and (c) it allows a designer to make a trade-off between a truly optimized airfoil and the amount of computing time consumed. For illustration purposes, we use the profile optimization method to solve a lift-constrained drag minimization problem for 2-D airfoil in Euler flow with 20 free-design variables. A comparison with other airfoil optimization methods is also included.

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

New reflective symmetry design capability in the JPL-IDEAS Structure Optimization Program

NASA Technical Reports Server (NTRS)

Strain, D.; Levy, R.

1986-01-01

The JPL-IDEAS antenna structure analysis and design optimization computer program was modified to process half structure models of symmetric structures subjected to arbitrary external static loads, synthesize the performance, and optimize the design of the full structure. Significant savings in computation time and cost (more than 50%) were achieved compared to the cost of full model computer runs. The addition of the new reflective symmetry analysis design capabilities to the IDEAS program allows processing of structure models whose size would otherwise prevent automated design optimization. The new program produced synthesized full model iterative design results identical to those of actual full model program executions at substantially reduced cost, time, and computer storage.

Control Parameters Optimization Based on Co-Simulation of a Mechatronic System for an UA-Based Two-Axis Inertially Stabilized Platform.

PubMed

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-08-14

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS(®); then, to analyze the system's kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB(®) SIMULINK(®) controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance.

Control Parameters Optimization Based on Co-Simulation of a Mechatronic System for an UA-Based Two-Axis Inertially Stabilized Platform

PubMed Central

Zhou, Xiangyang; Zhao, Beilei; Gong, Guohao

2015-01-01

This paper presents a method based on co-simulation of a mechatronic system to optimize the control parameters of a two-axis inertially stabilized platform system (ISP) applied in an unmanned airship (UA), by which high control performance and reliability of the ISP system are achieved. First, a three-dimensional structural model of the ISP is built by using the three-dimensional parametric CAD software SOLIDWORKS®; then, to analyze the system’s kinematic and dynamic characteristics under operating conditions, dynamics modeling is conducted by using the multi-body dynamics software ADAMS™, thus the main dynamic parameters such as displacement, velocity, acceleration and reaction curve are obtained, respectively, through simulation analysis. Then, those dynamic parameters were input into the established MATLAB® SIMULINK® controller to simulate and test the performance of the control system. By these means, the ISP control parameters are optimized. To verify the methods, experiments were carried out by applying the optimized parameters to the control system of a two-axis ISP. The results show that the co-simulation by using virtual prototyping (VP) is effective to obtain optimized ISP control parameters, eventually leading to high ISP control performance. PMID:26287210

A novel composite adaptive flap controller design by a high-efficient modified differential evolution identification approach.

PubMed

Li, Nailu; Mu, Anle; Yang, Xiyun; Magar, Kaman T; Liu, Chao

2018-05-01

The optimal tuning of adaptive flap controller can improve adaptive flap control performance on uncertain operating environments, but the optimization process is usually time-consuming and it is difficult to design proper optimal tuning strategy for the flap control system (FCS). To solve this problem, a novel adaptive flap controller is designed based on a high-efficient differential evolution (DE) identification technique and composite adaptive internal model control (CAIMC) strategy. The optimal tuning can be easily obtained by DE identified inverse of the FCS via CAIMC structure. To achieve fast tuning, a high-efficient modified adaptive DE algorithm is proposed with new mutant operator and varying range adaptive mechanism for the FCS identification. A tradeoff between optimized adaptive flap control and low computation cost is successfully achieved by proposed controller. Simulation results show the robustness of proposed method and its superiority to conventional adaptive IMC (AIMC) flap controller and the CAIMC flap controllers using other DE algorithms on various uncertain operating conditions. The high computation efficiency of proposed controller is also verified based on the computation time on those operating cases. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Realization of an ultrathin acoustic lens for subwavelength focusing in the megasonic range.

PubMed

Hyun, Jaeyub; Kim, Yong Tae; Doh, Il; Ahn, Bongyoung; Baik, Kyungmin; Kim, Se-Hwa

2018-06-14

In this study, we report the first experimental realization of an ultrathin (0.14λ, λ = 1.482 mm means wavelength at 1 MHz in the water medium) subwavelength focusing acoustic lens that can surpass the Rayleigh diffraction limit (0.61λ/NA, NA means numerical aperture). It is termed a Super-Oscillatory Acoustic Lens (SOAL), and it operates in the megasonic range. The SOAL represents an interesting feature allowing the achievement of subwavelength focusing without the need to operate in close proximity to the object to be imaged. The optimal layout of the SOAL is obtained by utilizing a systematic design approach, referred to here as topology optimization. To this end, the optimization formulation is newly defined. The optimized SOAL is fabricated using a photo-etching process and its subwavelength focusing performance is verified experimentally via an acoustic intensity measurement system. From these measurements, we found that the proposed optimized SOAL can achieve superior focusing features with a Full Width at Half Maximum (FWHM) of ~0.40λ/NA ≃ 0.84 mm (for our SOAL, NA = 0.707) with the transmission efficiency of 26.5%.

SU-G-JeP2-07: Fusion Optimization of Multi-Contrast MRI Scans for MR-Based Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, L; Yin, F; Liang, X

Purpose: To develop an image fusion method using multiple contrast MRI scans for MR-based treatment planning. Methods: T1 weighted (T1-w), T2 weighted (T2-w) and diffusion weighted images (DWI) were acquired from liver cancer patient with breath-holding. Image fade correction and deformable image registration were performed using VelocityAI (Varian Medical Systems, CA). Registered images were normalized to mean voxel intensity for each image dataset. Contrast to noise ratio (CNR) between tumor and liver was quantified. Tumor area was defined as the GTV contoured by physicians. Normal liver area with equivalent dimension was used as background. Noise was defined by the standardmore » deviation of voxel intensities in the same liver area. Linear weightings were applied to T1-w, T2-w and DWI images to generate composite image and CNR was calculated for each composite image. Optimization process were performed to achieve different clinical goals. Results: With a goal of maximizing tumor contrast, the composite image achieved a 7–12 fold increase in tumor CNR (142.8 vs. −2.3, 11.4 and 20.6 for T1-w, T2-w and DWI only, respectively), while anatomical details were largely invisible. With a weighting combination of 100%, −10% and −10%, respectively, tumor contrast was enhanced from −2.3 to −5.4, while the anatomical details were clear. With a weighting combination of 25%, 20% and 55%, balanced tumor contrast and anatomy was achieved. Conclusion: We have investigated the feasibility of performing image fusion optimization on multiple contrast MRI images. This mechanism could help utilize multiple contrast MRI scans to potentially facilitate future MR-based treatment planning.« less

High Performance, Robust Control of Flexible Space Structures: MSFC Center Director's Discretionary Fund

NASA Technical Reports Server (NTRS)

Whorton, M. S.

1998-01-01

Many spacecraft systems have ambitious objectives that place stringent requirements on control systems. Achievable performance is often limited because of difficulty of obtaining accurate models for flexible space structures. To achieve sufficiently high performance to accomplish mission objectives may require the ability to refine the control design model based on closed-loop test data and tune the controller based on the refined model. A control system design procedure is developed based on mixed H2/H(infinity) optimization to synthesize a set of controllers explicitly trading between nominal performance and robust stability. A homotopy algorithm is presented which generates a trajectory of gains that may be implemented to determine maximum achievable performance for a given model error bound. Examples show that a better balance between robustness and performance is obtained using the mixed H2/H(infinity) design method than either H2 or mu-synthesis control design. A second contribution is a new procedure for closed-loop system identification which refines parameters of a control design model in a canonical realization. Examples demonstrate convergence of the parameter estimation and improved performance realized by using the refined model for controller redesign. These developments result in an effective mechanism for achieving high-performance control of flexible space structures.

Towards Robust Designs Via Multiple-Objective Optimization Methods

NASA Technical Reports Server (NTRS)

Man Mohan, Rai

2006-01-01

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Optimal integration of daylighting and electric lighting systems using non-imaging optics

NASA Astrophysics Data System (ADS)

Scartezzini, J.-L.; Linhart, F.; Kaegi-Kolisnychenko, E.

2007-09-01

Electric lighting is responsible for a significant fraction of electricity consumption within non-residential buildings. Making daylight more available in office and commercial buildings can lead as a consequence to important electricity savings, as well as to the improvement of occupants' visual performance and wellbeing. Over the last decades, daylighting technologies have been developed for that purpose, some of them having proven to be highly efficient such as anidolic daylighting systems. Based on non-imaging optics these optical devices were designed to achieve an efficient collection and redistribution of daylight within deep office rooms. However in order to benefit from the substantial daylight provision obtained through these systems and convert it into effective electricity savings, novel electric lighting strategies are required. An optimal integration of high efficacy light sources and efficient luminaries based on non-imaging optics with anidolic daylighting systems can lead to such novel strategies. Starting from the experience gained through the development of an Anidolic Integrated Ceiling (AIC), this paper presents an optimal integrated daylighting and electric lighting system. Computer simulations based on ray-tracing techniques were used to achieve the integration of 36W fluorescent tubes and non-imaging reflectors with an advanced daylighting system. Lighting power densities lower than 4 W/m2 can be achieved in this way within the corresponding office room. On-site monitoring of an integrated daylighting and electric lighting system carried out on a solar experimental building confirmed the energy and visual performance of such a system: it showed that low lighting power densities can be achieved by combining an anidolic daylighting system with very efficient electric light sources and luminaries.

Tool Support for Software Lookup Table Optimization

DOE PAGES

Wilcox, Chris; Strout, Michelle Mills; Bieman, James M.

2011-01-01

A number of scientific applications are performance-limited by expressions that repeatedly call costly elementary functions. Lookup table (LUT) optimization accelerates the evaluation of such functions by reusing previously computed results. LUT methods can speed up applications that tolerate an approximation of function results, thereby achieving a high level of fuzzy reuse. One problem with LUT optimization is the difficulty of controlling the tradeoff between performance and accuracy. The current practice of manual LUT optimization adds programming effort by requiring extensive experimentation to make this tradeoff, and such hand tuning can obfuscate algorithms. In this paper we describe a methodology andmore » tool implementation to improve the application of software LUT optimization. Our Mesa tool implements source-to-source transformations for C or C++ code to automate the tedious and error-prone aspects of LUT generation such as domain profiling, error analysis, and code generation. We evaluate Mesa with five scientific applications. Our results show a performance improvement of 3.0× and 6.9× for two molecular biology algorithms, 1.4× for a molecular dynamics program, 2.1× to 2.8× for a neural network application, and 4.6× for a hydrology calculation. We find that Mesa enables LUT optimization with more control over accuracy and less effort than manual approaches.« less

Energy saving by using asymmetric aftbodies for merchant ships-design methodology, numerical simulation and validation

NASA Astrophysics Data System (ADS)

Dang, Jie; Chen, Hao

2016-12-01

The methodology and procedures are discussed on designing merchant ships to achieve fully-integrated and optimized hull-propulsion systems by using asymmetric aftbodies. Computational fluid dynamics (CFD) has been used to evaluate the powering performance through massive calculations with automatic deformation algorisms for the hull forms and the propeller blades. Comparative model tests of the designs to the optimized symmetric hull forms have been carried out to verify the efficiency gain. More than 6% improvement on the propulsive efficiency of an oil tanker has been measured during the model tests. Dedicated sea-trials show good agreement with the predicted performance from the test results.

The optimal operation of cooling tower systems with variable-frequency control

NASA Astrophysics Data System (ADS)

Cao, Yong; Huang, Liqing; Cui, Zhiguo; Liu, Jing

2018-02-01

This study investigates the energy performance of chiller and cooling tower systems integrated with variable-frequency control for cooling tower fans and condenser water pumps. With regard to an example chiller system serving an office building, Chiller and cooling towers models were developed to assess how different variable-frequency control methods of cooling towers fans and condenser water pumps influence the trade-off between the chiller power, pump power and fan power under various operating conditions. The matching relationship between the cooling tower fans frequency and condenser water pumps frequency at optimal energy consumption of the system is introduced to achieve optimum system performance.

A Case Study on the Application of a Structured Experimental Method for Optimal Parameter Design of a Complex Control System

NASA Technical Reports Server (NTRS)

Torres-Pomales, Wilfredo

2015-01-01

This report documents a case study on the application of Reliability Engineering techniques to achieve an optimal balance between performance and robustness by tuning the functional parameters of a complex non-linear control system. For complex systems with intricate and non-linear patterns of interaction between system components, analytical derivation of a mathematical model of system performance and robustness in terms of functional parameters may not be feasible or cost-effective. The demonstrated approach is simple, structured, effective, repeatable, and cost and time efficient. This general approach is suitable for a wide range of systems.

Genetics-based control of a mimo boiler-turbine plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dimeo, R.M.; Lee, K.Y.

1994-12-31

A genetic algorithm is used to develop an optimal controller for a non-linear, multi-input/multi-output boiler-turbine plant. The algorithm is used to train a control system for the plant over a wide operating range in an effort to obtain better performance. The results of the genetic algorithm`s controller designed from the linearized plant model at a nominal operating point. Because the genetic algorithm is well-suited to solving traditionally difficult optimization problems it is found that the algorithm is capable of developing the controller based on input/output information only. This controller achieves a performance comparable to the standard linear quadratic regulator.

Capacity of noncoherent MFSK channels

NASA Technical Reports Server (NTRS)

Bar-David, I.; Butman, S. A.; Klass, M. J.; Levitt, B. K.; Lyon, R. F.

1974-01-01

Performance limits theoretically achievable over noncoherent channels perturbed by additive Gaussian noise in hard decision, optimal, and soft decision receivers are computed as functions of the number of orthogonal signals and the predetection signal-to-noise ratio. Equations are derived for orthogonal signal capacity, the ultimate MFSK capacity, and the convolutional coding and decoding limit. It is shown that performance improves as the signal-to-noise ratio increases, provided the bandwidth can be increased, that the optimum number of signals is not infinite (except for the optimal receiver), and that the optimum number decreases as the signal-to-noise ratio decreases, but is never less than 7 for even the hard decision receiver.

Optimization of Tape Winding Process Parameters to Enhance the Performance of Solid Rocket Nozzle Throat Back Up Liners using Taguchi's Robust Design Methodology

NASA Astrophysics Data System (ADS)

Nath, Nayani Kishore

2017-08-01

The throat back up liners is used to protect the nozzle structural members from the severe thermal environment in solid rocket nozzles. The throat back up liners is made with E-glass phenolic prepregs by tape winding process. The objective of this work is to demonstrate the optimization of process parameters of tape winding process to achieve better insulative resistance using Taguchi's robust design methodology. In this method four control factors machine speed, roller pressure, tape tension, tape temperature that were investigated for the tape winding process. The presented work was to study the cogency and acceptability of Taguchi's methodology in manufacturing of throat back up liners. The quality characteristic identified was Back wall temperature. Experiments carried out using L 9 ' (34) orthogonal array with three levels of four different control factors. The test results were analyzed using smaller the better criteria for Signal to Noise ratio in order to optimize the process. The experimental results were analyzed conformed and successfully used to achieve the minimum back wall temperature of the throat back up liners. The enhancement in performance of the throat back up liners was observed by carrying out the oxy-acetylene tests. The influence of back wall temperature on the performance of throat back up liners was verified by ground firing test.

Histological evaluation and optimization of surgical vessel sealing systems

NASA Astrophysics Data System (ADS)

Lathrop, Robert; Ryan, Thomas; Gaspredes, Jonathan; Woloszko, Jean; Coad, James E.

2017-02-01

Surgical vessel sealing systems are widely used to achieve hemostasis and dissection in open surgery and minimally invasive, laparoscopic surgery. This enabling technology was developed about 17 years ago and continues to evolve with new devices and systems achieving improved outcomes. Histopathological assessment of thermally sealed tissues is a valuable tool for refining and comparing performance among surgical vessel sealing systems. Early work in this field typically assessed seal time, burst rate, and failure rate (in-situ). Later work compared histological staining methods with birefringence to assess the extent of thermal damage to tissues adjacent to the device. Understanding the microscopic architecture of a sealed vessel is crucial to optimizing the performance of power delivery algorithms and device design parameters. Manufacturers rely on these techniques to develop new products. A system for histopathological evaluation of vessels and sealing performance was established, to enable the direct assessment of a treatment's tissue effects. The parameters included the commonly used seal time, pressure burst rate and failure rate, as well as extensions of the assessment to include its likelihood to form steam vacuoles, adjacent thermal effect near the device, and extent of thermally affected tissue extruded back into the vessel lumen. This comprehensive assessment method provides an improved means of assessing the quality of a sealed vessel and understanding the exact mechanisms which create an optimally sealed vessel.

Taguchi's technique: an effective method for improving X-ray medical radiographic screen performance.

PubMed

Vlachogiannis, J G

2003-01-01

Taguchi's technique is a helpful tool to achieve experimental optimization of a large number of decision variables with a small number of off-line experiments. The technique appears to be an ideal tool for improving the performance of X-ray medical radiographic screens under a noise source. Currently there are very many guides available for improving the efficiency of X-ray medical radiographic screens. These guides can be refined using a second-stage parameter optimization. based on Taguchi's technique, selecting the optimum levels of controllable X-ray radiographic screen factors. A real example of the proposed technique is presented giving certain performance criteria. The present research proposes the reinforcement of X-ray radiography by Taguchi's technique as a novel hardware mechanism.

Improvement and analysis of the hydrogen-cerium redox flow cell

NASA Astrophysics Data System (ADS)

Tucker, Michael C.; Weiss, Alexandra; Weber, Adam Z.

2016-09-01

The H2-Ce redox flow cell is optimized using commercially-available cell materials. Cell performance is found to be sensitive to the upper charge cutoff voltage, membrane boiling pretreatment, methanesulfonic-acid concentration, (+) electrode surface area and flow pattern, and operating temperature. Performance is relatively insensitive to membrane thickness, Cerium concentration, and all features of the (-) electrode including hydrogen flow. Cell performance appears to be limited by mass transport and kinetics in the cerium (+) electrode. Maximum discharge power of 895 mW cm-2 was observed at 60 °C; an energy efficiency of 90% was achieved at 50 °C. The H2-Ce cell is promising for energy storage assuming one can optimize Ce reaction kinetics and electrolyte.

Exponential H ∞ Synchronization of Chaotic Cryptosystems Using an Improved Genetic Algorithm

PubMed Central

Hsiao, Feng-Hsiag

2015-01-01

This paper presents a systematic design methodology for neural-network- (NN-) based secure communications in multiple time-delay chaotic (MTDC) systems with optimal H ∞ performance and cryptography. On the basis of the Improved Genetic Algorithm (IGA), which is demonstrated to have better performance than that of a traditional GA, a model-based fuzzy controller is then synthesized to stabilize the MTDC systems. A fuzzy controller is synthesized to not only realize the exponential synchronization, but also achieve optimal H ∞ performance by minimizing the disturbance attenuation level. Furthermore, the error of the recovered message is stated by using the n-shift cipher and key. Finally, a numerical example with simulations is given to demonstrate the effectiveness of our approach. PMID:26366432

Optimization design and performance analysis of a miniature stirling engine

NASA Astrophysics Data System (ADS)

You, Zhanping; Yang, Bo; Pan, Lisheng; Hao, Changsheng

2017-10-01

Under given operation conditions, a stirling engine of 2 kW is designed which takes hydrogen as working medium. Through establishment of adiabatic model, the ways are achieved about performance improving. The ways are raising the temperature of hot terminal, lowering the temperature of cold end, increasing the average cycle pressure, speeding up the speed, phase angle being 90°, stroke volume ratio approximating to 1 and increasing the performance of regenerator.

Optimal Periodic Cooperative Spectrum Sensing Based on Weight Fusion in Cognitive Radio Networks

PubMed Central

Liu, Xin; Jia, Min; Gu, Xuemai; Tan, Xuezhi

2013-01-01

The performance of cooperative spectrum sensing in cognitive radio (CR) networks depends on the sensing mode, the sensing time and the number of cooperative users. In order to improve the sensing performance and reduce the interference to the primary user (PU), a periodic cooperative spectrum sensing model based on weight fusion is proposed in this paper. Moreover, the sensing period, the sensing time and the searching time are optimized, respectively. Firstly the sensing period is optimized to improve the spectrum utilization and reduce the interference, then the joint optimization algorithm of the local sensing time and the number of cooperative users, is proposed to obtain the optimal sensing time for improving the throughput of the cognitive radio user (CRU) during each period, and finally the water-filling principle is applied to optimize the searching time in order to make the CRU find an idle channel within the shortest time. The simulation results show that compared with the previous algorithms, the optimal sensing period can improve the spectrum utilization of the CRU and decrease the interference to the PU significantly, the optimal sensing time can make the CRU achieve the largest throughput, and the optimal searching time can make the CRU find an idle channel with the least time. PMID:23604027

Development of mathematical models and optimization of the process parameters of laser surface hardened EN25 steel using elitist non-dominated sorting genetic algorithm

NASA Astrophysics Data System (ADS)

Vignesh, S.; Dinesh Babu, P.; Surya, G.; Dinesh, S.; Marimuthu, P.

2018-02-01

The ultimate goal of all production entities is to select the process parameters that would be of maximum strength, minimum wear and friction. The friction and wear are serious problems in most of the industries which are influenced by the working set of parameters, oxidation characteristics and mechanism involved in formation of wear. The experimental input parameters such as sliding distance, applied load, and temperature are utilized in finding out the optimized solution for achieving the desired output responses such as coefficient of friction, wear rate, and volume loss. The optimization is performed with the help of a novel method, Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) based on an evolutionary algorithm. The regression equations obtained using Response Surface Methodology (RSM) are used in determining the optimum process parameters. Further, the results achieved through desirability approach in RSM are compared with that of the optimized solution obtained through NSGA-II. The results conclude that proposed evolutionary technique is much effective and faster than the desirability approach.

The Development of Lightweight Commercial Vehicle Wheels Using Microalloying Steel

NASA Astrophysics Data System (ADS)

Lu, Hongzhou; Zhang, Lilong; Wang, Jiegong; Xuan, Zhaozhi; Liu, Xiandong; Guo, Aimin; Wang, Wenjun; Lu, Guimin

Lightweight wheels can reduce weight about 100kg for commercial vehicles, and it can save energy and reduce emission, what's more, it can enhance the profits for logistics companies. The development of lightweight commercial vehicle wheels is achieved by the development of new steel for rim, the process optimization of flash butt welding, and structure optimization by finite element methods. Niobium micro-alloying technology can improve hole expansion rate, weldability and fatigue performance of wheel steel, and based on Niobium micro-alloying technology, a special wheel steel has been studied whose microstructure are Ferrite and Bainite, with high formability and high fatigue performance, and stable mechanical properties. The content of Nb in this new steel is 0.025% and the hole expansion rate is ≥ 100%. At the same time, welding parameters including electric upsetting time, upset allowance, upsetting pressure and flash allowance are optimized, and by CAE analysis, an optimized structure has been attained. As a results, the weight of 22.5in×8.25in wheel is up to 31.5kg, which is most lightweight comparing the same size wheels. And its functions including bending fatigue performance and radial fatigue performance meet the application requirements of truck makers and logistics companies.

Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.

PubMed

Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei

2015-06-25

Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm.

Optimizing feeding composition and carbon-nitrogen ratios for improved methane yield during anaerobic co-digestion of dairy, chicken manure and wheat straw.

PubMed

Wang, Xiaojiao; Yang, Gaihe; Feng, Yongzhong; Ren, Guangxin; Han, Xinhui

2012-09-01

This study investigated the possibilities of improving methane yield from anaerobic digestion of multi-component substrates, using a mixture of dairy manure (DM), chicken manure (CM) and wheat straw (WS), based on optimized feeding composition and the C/N ratio. Co-digestion of DM, CM and WS performed better in methane potential than individual digestion. A larger synergetic effect in co-digestion of DM, CM and WS was found than in mixtures of single manures with WS. As the C/N ratio increased, methane potential initially increased and then declined. C/N ratios of 25:1 and 30:1 had better digestion performance with stable pH and low concentrations of total ammonium nitrogen and free NH(3). Maximum methane potential was achieved with DM/CM of 40.3:59.7 and a C/N ratio of 27.2:1 after optimization using response surface methodology. The results suggested that better performance of anaerobic co-digestion can be fulfilled by optimizing feeding composition and the C/N ratio. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimal control of a hybrid rhythmic-discrete task: the bouncing ball revisited.

PubMed

Ronsse, Renaud; Wei, Kunlin; Sternad, Dagmar

2010-05-01

Rhythmically bouncing a ball with a racket is a hybrid task that combines continuous rhythmic actuation of the racket with the control of discrete impact events between racket and ball. This study presents experimental data and a two-layered modeling framework that explicitly addresses the hybrid nature of control: a first discrete layer calculates the state to reach at impact and the second continuous layer smoothly drives the racket to this desired state, based on optimality principles. The testbed for this hybrid model is task performance at a range of increasingly slower tempos. When slowing the rhythm of the bouncing actions, the continuous cycles become separated into a sequence of discrete movements interspersed by dwell times and directed to achieve the desired impact. Analyses of human performance show increasing variability of performance measures with slower tempi, associated with a change in racket trajectories from approximately sinusoidal to less symmetrical velocity profiles. Matching results of model simulations give support to a hybrid control model based on optimality, and therefore suggest that optimality principles are applicable to the sensorimotor control of complex movements such as ball bouncing.

Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files.

PubMed

Sun, Xiaobo; Gao, Jingjing; Jin, Peng; Eng, Celeste; Burchard, Esteban G; Beaty, Terri H; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen; Wang, Fusheng; Qin, Zhaohui S

2018-06-01

Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)-based high-performance computing (HPC) implementation, and the popular VCFTools. Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems.

Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files

PubMed Central

Gao, Jingjing; Jin, Peng; Eng, Celeste; Burchard, Esteban G; Beaty, Terri H; Ruczinski, Ingo; Mathias, Rasika A; Barnes, Kathleen; Wang, Fusheng

2018-01-01

Abstract Background Sorted merging of genomic data is a common data operation necessary in many sequencing-based studies. It involves sorting and merging genomic data from different subjects by their genomic locations. In particular, merging a large number of variant call format (VCF) files is frequently required in large-scale whole-genome sequencing or whole-exome sequencing projects. Traditional single-machine based methods become increasingly inefficient when processing large numbers of files due to the excessive computation time and Input/Output bottleneck. Distributed systems and more recent cloud-based systems offer an attractive solution. However, carefully designed and optimized workflow patterns and execution plans (schemas) are required to take full advantage of the increased computing power while overcoming bottlenecks to achieve high performance. Findings In this study, we custom-design optimized schemas for three Apache big data platforms, Hadoop (MapReduce), HBase, and Spark, to perform sorted merging of a large number of VCF files. These schemas all adopt the divide-and-conquer strategy to split the merging job into sequential phases/stages consisting of subtasks that are conquered in an ordered, parallel, and bottleneck-free way. In two illustrating examples, we test the performance of our schemas on merging multiple VCF files into either a single TPED or a single VCF file, which are benchmarked with the traditional single/parallel multiway-merge methods, message passing interface (MPI)–based high-performance computing (HPC) implementation, and the popular VCFTools. Conclusions Our experiments suggest all three schemas either deliver a significant improvement in efficiency or render much better strong and weak scalabilities over traditional methods. Our findings provide generalized scalable schemas for performing sorted merging on genetics and genomics data using these Apache distributed systems. PMID:29762754

Increased conception rates in beef cattle inseminated with nanopurified bull semen

USDA-ARS?s Scientific Manuscript database

Reproductive performance is of paramount importance to the cattle industry. Since recent progress has been achieved by optimizing estrus and ovulation synchronization protocols in cows, improvements are desired to increase the fertility of bulls enrolled in artificial insemination (AI) programs. Thi...

The CCM Model: A Management Approach to Performance Optimization

ERIC Educational Resources Information Center

Geroy, Gary D.; Bray, Amber; Venneberg, Donald L.

2005-01-01

Three leadership styles are frequently discussed in the literature today: transactional, transformational, and most recently--transcendental. Managers may be able to put transactional, transformational, and transcendental leadership style theories into practice without inventing a new set of processes and procedures to achieve individual follower…

Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method

NASA Astrophysics Data System (ADS)

Salajegheh, Eysa; Gholizadeh, Saeed; Khatibinia, Mohsen

2008-03-01

The optimal seismic design of structures requires that time history analyses (THA) be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function (RBF) neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization (BPSO) is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.

JPARSS: A Java Parallel Network Package for Grid Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Jie; Akers, Walter; Chen, Ying

2002-03-01

The emergence of high speed wide area networks makes grid computinga reality. However grid applications that need reliable data transfer still have difficulties to achieve optimal TCP performance due to network tuning of TCP window size to improve bandwidth and to reduce latency on a high speed wide area network. This paper presents a Java package called JPARSS (Java Parallel Secure Stream (Socket)) that divides data into partitions that are sent over several parallel Java streams simultaneously and allows Java or Web applications to achieve optimal TCP performance in a grid environment without the necessity of tuning TCP window size.more » This package enables single sign-on, certificate delegation and secure or plain-text data transfer using several security components based on X.509 certificate and SSL. Several experiments will be presented to show that using Java parallelstreams is more effective than tuning TCP window size. In addition a simple architecture using Web services« less

Precoded spatial multiplexing MIMO system with spatial component interleaver.

PubMed

Gao, Xiang; Wu, Zhanji

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

Study of series-connected polymer tandem solar cells based on a highly efficient donor material of PTB7-Th

NASA Astrophysics Data System (ADS)

Zang, Yue; Gao, Xiumin; Xin, Qing; Lin, Jun; Zhao, Jufeng

2017-06-01

A highly efficient donor polymer, PTB7-Th, combined with acceptor fullerene PC71BM was introduced as the subcell in the series-connected tandem devices to achieve high-performance polymer tandem solar cells. Design of the device architecture was investigated using modeling and simulation methods to identify the optimal structure and to predict performance of the tandem cells. To address the challenge of current matching between the constituent subcells, the effect of active layer thickness, different device structure, and use of ultrathin Ag film were analyzed. It was found that the distribution of optical intensity in the tandem structure can be optimized through the optical spacer effect of interfacial layers and micro-cavity effect derived from the embedded ultrathin Ag film. Our results indicate that the efficient light utilization with appropriate subcells can allow achievement of power conversion efficiency of 12%, which can be 25% higher than that of a single cell of PTB7-Th.

High Speed Civil Transport Design Using Collaborative Optimization and Approximate Models

NASA Technical Reports Server (NTRS)

Manning, Valerie Michelle

1999-01-01

The design of supersonic aircraft requires complex analysis in multiple disciplines, posing, a challenge for optimization methods. In this thesis, collaborative optimization, a design architecture developed to solve large-scale multidisciplinary design problems, is applied to the design of supersonic transport concepts. Collaborative optimization takes advantage of natural disciplinary segmentation to facilitate parallel execution of design tasks. Discipline-specific design optimization proceeds while a coordinating mechanism ensures progress toward an optimum and compatibility between disciplinary designs. Two concepts for supersonic aircraft are investigated: a conventional delta-wing design and a natural laminar flow concept that achieves improved performance by exploiting properties of supersonic flow to delay boundary layer transition. The work involves the development of aerodynamics and structural analyses, and integration within a collaborative optimization framework. It represents the most extensive application of the method to date.

Organizational transformation: a model for joint optimization of culture change and evidence-based design.

PubMed

Hamilton, D Kirk; Orr, Robin Diane; Raboin, W Ellen

2008-01-01

Healthcare organizations face continuous and accelerating external change and thus must be prepared to manage their own change initiatives proactively. Given that many believe that the U.S. healthcare system is broken and most healthcare organizations are dealing with pervasive problems, some organizations may choose to seek transformational change to achieve the six aims identified by the Institute of Medicine: healthcare that is safe, effective, patient-centered, timely, efficient, and equitable. Transformational change will almost certainly involve organizational culture. Culture change may be most effective when linked to other organizational change initiatives such as organizational strategy, structure, policies, procedures, and recruiting. Significant organizational change often requires accompanying facility change. There is an interdependent relationship between facility design and organizational culture. They affect each other and both impact organizational performance. Sociotechnical theory promotes joint optimization of the social (culture) and technical (facilities) aspects of an organization to achieve sustained positive change. To achieve organizational transformation and to sustain positive change, organizations must be prepared to adopt collaborative efforts in culture change and facility design. The authors propose a model for accomplishing joint optimization of culture change and evidence-based facility design.

Achieving minimum-error discrimination of an arbitrary set of laser-light pulses

NASA Astrophysics Data System (ADS)

da Silva, Marcus P.; Guha, Saikat; Dutton, Zachary

2013-05-01

Laser light is widely used for communication and sensing applications, so the optimal discrimination of coherent states—the quantum states of light emitted by an ideal laser—has immense practical importance. Due to fundamental limits imposed by quantum mechanics, such discrimination has a finite minimum probability of error. While concrete optical circuits for the optimal discrimination between two coherent states are well known, the generalization to larger sets of coherent states has been challenging. In this paper, we show how to achieve optimal discrimination of any set of coherent states using a resource-efficient quantum computer. Our construction leverages a recent result on discriminating multicopy quantum hypotheses [Blume-Kohout, Croke, and Zwolak, arXiv:1201.6625]. As illustrative examples, we analyze the performance of discriminating a ternary alphabet and show how the quantum circuit of a receiver designed to discriminate a binary alphabet can be reused in discriminating multimode hypotheses. Finally, we show that our result can be used to achieve the quantum limit on the rate of classical information transmission on a lossy optical channel, which is known to exceed the Shannon rate of all conventional optical receivers.

Reliability based design optimization: Formulations and methodologies

NASA Astrophysics Data System (ADS)

Agarwal, Harish

Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed. A trust region managed sequential approximate optimization methodology is employed for this purpose. Results from numerical test studies indicate that the methodology can be used for performing design optimization under severe uncertainty.

Do we perform surgical programming well? How can we improve it?

PubMed

Albareda, J; Clavel, D; Mahulea, C; Blanco, N; Ezquerra, L; Gómez, J; Silva, J M

The objective is to establish the duration of our interventions, intermediate times and surgical performance. This will create a virtual waiting list to apply a mathematical programme that performs programming with maximum performance. Retrospective review of 49 surgical sessions obtaining the delay in start time, intermediate time and surgical performance. Retrospective review of 4,045 interventions performed in the last 3 years to obtain the average duration of each type of surgery. Creation of a virtual waiting list of 700 patients in order to perform virtual programming through the MIQCP-P until achieving optimal performance. Our surgical performance with manual programming was 75.9%, ending 22.4% later than 3pm. The performance in the days without suspensions was 78.4%. The delay at start time was 9.7min. The optimum performance was 77.5% with a confidence of finishing before 15h of 80.6%. The waiting list has been scheduled in 254 sessions. Our manual surgical performance without suspensions (78.4%) was superior to the optimal (77.5%), generating days finished later than 3pm and suspensions. The possibilities for improvement are to achieve punctuality at the start time and adjust the schedule to the ideal performance. The virtual programming has allowed us to obtain our ideal performance and to establish the number of operating rooms necessary to solve the waiting list created. The data obtained in virtual mathematical programming are reliable enough to implement this model with guarantees. Copyright © 2017 SECOT. Publicado por Elsevier España, S.L.U. All rights reserved.

Optimized design of a low-resistance electrical conductor for the multimegahertz range

NASA Astrophysics Data System (ADS)

Kurs, André; Kesler, Morris; Johnson, Steven G.

2011-04-01

We propose a design for a conductive wire composed of several mutually insulated coaxial conducting shells. With the help of numerical optimization, it is possible to obtain electrical resistances significantly lower than those of a heavy-gauge copper wire or litz wire in the 2-20 MHz range. Moreover, much of the reduction in resistance can be achieved for just a few shells; in contrast, litz wire would need to contain ˜104 strands to perform comparably in this frequency range.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo

We analyze quantum algorithms for cloning of a quantum measurement. Our aim is to mimic two uses of a device performing an unknown von Neumann measurement with a single use of the device. When the unknown device has to be used before the bipartite state to be measured is available we talk about 1{yields}2 learning of the measurement, otherwise the task is called 1{yields}2 cloning of a measurement. We perform the optimization for both learning and cloning for arbitrary dimension d of the Hilbert space. For 1{yields}2 cloning we also propose a simple quantum network that achieves the optimal fidelity.more » The optimal fidelity for 1{yields}2 learning just slightly outperforms the estimate and prepare strategy in which one first estimates the unknown measurement and depending on the result suitably prepares the duplicate.« less

Optimal control model predictions of system performance and attention allocation and their experimental validation in a display design study

NASA Technical Reports Server (NTRS)

Johannsen, G.; Govindaraj, T.

1980-01-01

The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.

Interleaved segment correction achieves higher improvement factors in using genetic algorithm to optimize light focusing through scattering media

NASA Astrophysics Data System (ADS)

Li, Runze; Peng, Tong; Liang, Yansheng; Yang, Yanlong; Yao, Baoli; Yu, Xianghua; Min, Junwei; Lei, Ming; Yan, Shaohui; Zhang, Chunmin; Ye, Tong

2017-10-01

Focusing and imaging through scattering media has been proved possible with high resolution wavefront shaping. A completely scrambled scattering field can be corrected by applying a correction phase mask on a phase only spatial light modulator (SLM) and thereby the focusing quality can be improved. The correction phase is often found by global searching algorithms, among which Genetic Algorithm (GA) stands out for its parallel optimization process and high performance in noisy environment. However, the convergence of GA slows down gradually with the progression of optimization, causing the improvement factor of optimization to reach a plateau eventually. In this report, we propose an interleaved segment correction (ISC) method that can significantly boost the improvement factor with the same number of iterations comparing with the conventional all segment correction method. In the ISC method, all the phase segments are divided into a number of interleaved groups; GA optimization procedures are performed individually and sequentially among each group of segments. The final correction phase mask is formed by applying correction phases of all interleaved groups together on the SLM. The ISC method has been proved significantly useful in practice because of its ability to achieve better improvement factors when noise is present in the system. We have also demonstrated that the imaging quality is improved as better correction phases are found and applied on the SLM. Additionally, the ISC method lowers the demand of dynamic ranges of detection devices. The proposed method holds potential in applications, such as high-resolution imaging in deep tissue.

Systematic sparse matrix error control for linear scaling electronic structure calculations.

PubMed

Rubensson, Emanuel H; Sałek, Paweł

2005-11-30

Efficient truncation criteria used in multiatom blocked sparse matrix operations for ab initio calculations are proposed. As system size increases, so does the need to stay on top of errors and still achieve high performance. A variant of a blocked sparse matrix algebra to achieve strict error control with good performance is proposed. The presented idea is that the condition to drop a certain submatrix should depend not only on the magnitude of that particular submatrix, but also on which other submatrices that are dropped. The decision to remove a certain submatrix is based on the contribution the removal would cause to the error in the chosen norm. We study the effect of an accumulated truncation error in iterative algorithms like trace correcting density matrix purification. One way to reduce the initial exponential growth of this error is presented. The presented error control for a sparse blocked matrix toolbox allows for achieving optimal performance by performing only necessary operations needed to maintain the requested level of accuracy. Copyright 2005 Wiley Periodicals, Inc.

A multistage approach to improve performance of computer-aided detection of pulmonary embolisms depicted on CT images: preliminary investigation.

PubMed

Park, Sang Cheol; Chapman, Brian E; Zheng, Bin

2011-06-01

This study developed a computer-aided detection (CAD) scheme for pulmonary embolism (PE) detection and investigated several approaches to improve CAD performance. In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction; 4) false-positive (FP) reduction using an artificial neural network (ANN); and 5) a multifeature-based k-nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance: 1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete "redundant" features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination. The study suggested that performance of CAD schemes for PE detection depends on many factors that include 1) optimizing the 2-D region grouping and scoring methods; 2) selecting the optimal feature set; and 3) limiting the number of allowed cueing lesions per examination.

Catalog of Window Taper Functions for Sidelobe Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin W.

Window taper functions of finite apertures are well-known to control undesirable sidelobes, albeit with performance trades. A plethora of various taper functions have been developed over the years to achieve various optimizations. We herein catalog a number of window functions, and com pare principal characteristics.

Reliability centered maintenance : a case study of railway transit maintenance to achieve optimal performance.

DOT National Transportation Integrated Search

2010-12-01

The purpose of this qualitative case study was to identify the types of obstacles and patterns experienced by a single heavy rail transit agency located in North America that embedded a Reliability Centered Maintenance (RCM) Process. The outcome of t...

Investigation into Motor Carrier Practices to Achieve Optimal Commercial Motor Vehicle Driver Performance: Phase I

DOT National Transportation Integrated Search

2010-12-01

The objective of this research project was to determine the effectiveness of the 34-hour restart provision in the Hours-of-Service regulations governing property-carrying commercial motor vehicle drivers. A sample of 27 healthy subjects was studied i...

Optimizing the Dopant and Carrier Concentration of Ca5Al2Sb6 for High Thermoelectric Efficiency

PubMed Central

Yan, Yuli; Zhang, Guangbiao; Wang, Chao; Peng, Chengxiao; Zhang, Peihong; Wang, Yuanxu; Ren, Wei

2016-01-01

The effects of doping on the transport properties of Ca5Al2Sb6 are investigated using first-principles electronic structure methods and Boltzmann transport theory. The calculated results show that a maximum ZT value of 1.45 is achieved with an optimum carrier concentration at 1000 K. However, experimental studies have shown that the maximum ZT value is no more than 1 at 1000 K. By comparing the calculated Seebeck coefficient with experimental values, we find that the low dopant solubility in this material is not conductive to achieve the optimum carrier concentration, leading a smaller experimental value of the maximum ZT. Interestingly, the calculated dopant formation energies suggest that optimum carrier concentrations can be achieved when the dopants and Sb atoms have similar electronic configurations. Therefore, it might be possible to achieve a maximum ZT value of 1.45 at 1000 K with suitable dopants. These results provide a valuable theoretical guidance for the synthesis of high-performance bulk thermoelectric materials through dopants optimization. PMID:27406178

Addressing forecast uncertainty impact on CSP annual performance

NASA Astrophysics Data System (ADS)

Ferretti, Fabio; Hogendijk, Christopher; Aga, Vipluv; Ehrsam, Andreas

2017-06-01

This work analyzes the impact of weather forecast uncertainty on the annual performance of a Concentrated Solar Power (CSP) plant. Forecast time series has been produced by a commercial forecast provider using the technique of hindcasting for the full year 2011 in hourly resolution for Ouarzazate, Morocco. Impact of forecast uncertainty has been measured on three case studies, representing typical tariff schemes observed in recent CSP projects plus a spot market price scenario. The analysis has been carried out using an annual performance model and a standard dispatch optimization algorithm based on dynamic programming. The dispatch optimizer has been demonstrated to be a key requisite to maximize the annual revenues depending on the price scenario, harvesting the maximum potential out of the CSP plant. Forecasting uncertainty affects the revenue enhancement outcome of a dispatch optimizer depending on the error level and the price function. Results show that forecasting accuracy of direct solar irradiance (DNI) is important to make best use of an optimized dispatch but also that a higher number of calculation updates can partially compensate this uncertainty. Improvement in revenues can be significant depending on the price profile and the optimal operation strategy. Pathways to achieve better performance are presented by having more updates both by repeatedly generating new optimized trajectories but also more often updating weather forecasts. This study shows the importance of working on DNI weather forecasting for revenue enhancement as well as selecting weather services that can provide multiple updates a day and probabilistic forecast information.

Soft Snakes: Construction, Locomotion, and Control

NASA Astrophysics Data System (ADS)

Branyan, Callie; Courier, Taylor; Fleming, Chloe; Remaley, Jacquelin; Hatton, Ross; Menguc, Yigit

We fabricated modular bidirectional silicone pneumatic actuators to build a soft snake robot, applying geometric models of serpenoid swimmers to identify theoretically optimal gaits to realize serpentine locomotion. With the introduction of magnetic connections and elliptical cross-sections in fiber-reinforced modules, we can vary the number of continuum segments in the snake body to achieve more supple serpentine motion in a granular media. The performance of these gaits is observed using a motion capture system and efficiency is assessed in terms of pressure input and net displacement. These gaits are optimized using our geometric soap-bubble method of gait optimization, demonstrating the applicability of this tool to soft robot control and coordination.

Lattice Boltzmann Simulation Optimization on Leading Multicore Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Samuel; Carter, Jonathan; Oliker, Leonid

2008-02-01

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Clovertown, AMD Opteron X2, Sun Niagara2, STI Cell, as well as the single core Intel Itanium2. Rather than hand-tuning LBMHDmore » for each system, we develop a code generator that allows us identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned LBMHD application achieves up to a 14x improvement compared with the original code. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.« less

Lattice Boltzmann simulation optimization on leading multicore platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, S.; Carter, J.; Oliker, L.

2008-01-01

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of searchbased performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Clovertown, AMD Opteron X2, Sun Niagara2, STI Cell, as well as the single core Intel Itanium2. Rather than hand-tuning LBMHDmore » for each system, we develop a code generator that allows us identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our autotuned LBMHD application achieves up to a 14 improvement compared with the original code. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.« less

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian

1992-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip H.; Garg, Sanjay; Holowecky, Brian R.

1993-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

Using High Resolution Design Spaces for Aerodynamic Shape Optimization Under Uncertainty

NASA Technical Reports Server (NTRS)

Li, Wu; Padula, Sharon

2004-01-01

This paper explains why high resolution design spaces encourage traditional airfoil optimization algorithms to generate noisy shape modifications, which lead to inaccurate linear predictions of aerodynamic coefficients and potential failure of descent methods. By using auxiliary drag constraints for a simultaneous drag reduction at all design points and the least shape distortion to achieve the targeted drag reduction, an improved algorithm generates relatively smooth optimal airfoils with no severe off-design performance degradation over a range of flight conditions, in high resolution design spaces parameterized by cubic B-spline functions. Simulation results using FUN2D in Euler flows are included to show the capability of the robust aerodynamic shape optimization method over a range of flight conditions.

Optimal digital dynamical decoupling for general decoherence via Walsh modulation

NASA Astrophysics Data System (ADS)

Qi, Haoyu; Dowling, Jonathan P.; Viola, Lorenza

2017-11-01

We provide a general framework for constructing digital dynamical decoupling sequences based on Walsh modulation—applicable to arbitrary qubit decoherence scenarios. By establishing equivalence between decoupling design based on Walsh functions and on concatenated projections, we identify a family of optimal Walsh sequences, which can be exponentially more efficient, in terms of the required total pulse number, for fixed cancellation order, than known digital sequences based on concatenated design. Optimal sequences for a given cancellation order are highly non-unique—their performance depending sensitively on the control path. We provide an analytic upper bound to the achievable decoupling error and show how sequences within the optimal Walsh family can substantially outperform concatenated decoupling in principle, while respecting realistic timing constraints.

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Rui; Zhang, Yingchen

2016-08-01

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder andmore » results illustrate the superior control performance of the proposed approach.« less

Coordinated Optimization of Distributed Energy Resources and Smart Loads in Distribution Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Rui; Zhang, Yingchen

2016-11-14

Distributed energy resources (DERs) and smart loads have the potential to provide flexibility to the distribution system operation. A coordinated optimization approach is proposed in this paper to actively manage DERs and smart loads in distribution systems to achieve the optimal operation status. A three-phase unbalanced Optimal Power Flow (OPF) problem is developed to determine the output from DERs and smart loads with respect to the system operator's control objective. This paper focuses on coordinating PV systems and smart loads to improve the overall voltage profile in distribution systems. Simulations have been carried out in a 12-bus distribution feeder andmore » results illustrate the superior control performance of the proposed approach.« less

Thickness optimization of the ZnO based TCO layer in a CZTSSe solar cell. Evolution of its performance with thickness when external temperature changes.

NASA Astrophysics Data System (ADS)

Chadel, Meriem; Moustafa Bouzaki, Mohammed; Chadel, Asma; Aillerie, Michel; Benyoucef, Boumediene

2017-07-01

The influence of the thickness of a Zinc Oxide (ZnO) transparent conductive oxide (TCO) layer on the performance of the CZTSSe solar cell is shown in detail. In a photovoltaic cell, the thickness of each layer largely influence the performance of the solar cell and optimization of each layer constitutes a complete work. Here, using the Solar Cell Capacitance Simulation (SCAPS) software, we present simulation results obtained in the analyze of the influence of the TCO layer thickness on the performance of a CZTSSe solar cell, starting from performance of a CZTSSe solar cell commercialized in 2014 with an initial efficiency equal to 12.6%. In simulation, the temperature was considered as a functioning parameter and the evolution of tthe performance of the cell for various thickness of the TCO layer when the external temperature changes is simulated and discussed. The best efficiency of the solar cell based in CZTSSe is obtained with a ZnO thickness equal to 50 nm and low temperature. Based on the considered marketed cell, we show a technological possible increase of the global efficiency achieving 13% by optimization of ZnO based TCO layer.

New Side-Looking Rogowski Coil Sensor for Measuring Large-Magnitude Fast Impulse Currents

NASA Astrophysics Data System (ADS)

Metwally, I. A.

2015-12-01

This paper presents a new design of a side-looking "flat spiral" self-integrating Rogowski coil that is wound by twin coaxial cable with individual sheath. The coil is tested with different impulse current waveforms up to 7 kA peak value to improve its performance. The coil design is optimized to achieve bandwidth and sensitivity up to 7.854 MHz and 3.623 V/kA, respectively. The coil is calibrated versus two commercial impulse-current measurement devices at different coil-to-wire separations, coil inclination angles, and impulse current waveforms. Distortion of the coil output voltage waveform is examined by using the lumped-element model to optimize the connections of the four cable winding sheaths and the coil termination resistance. Finally, the coil frequency response is investigated to optimize the coil design parameters and achieve the desired bandwidth (large low-frequency time constant), high rate of rise, no overshoot, very small droop, high rate of fall, and no backswing.

Agreement Technologies for Energy Optimization at Home.

PubMed

González-Briones, Alfonso; Chamoso, Pablo; De La Prieta, Fernando; Demazeau, Yves; Corchado, Juan M

2018-05-19

Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.

Optimal Control Allocation with Load Sensor Feedback for Active Load Suppression, Experiment Development

NASA Technical Reports Server (NTRS)

Miller, Christopher J.; Goodrick, Dan

2017-01-01

The problem of control command and maneuver induced structural loads is an important aspect of any control system design. The aircraft structure and the control architecture must be designed to achieve desired piloted control responses while limiting the imparted structural loads. The classical approach is to utilize high structural margins, restrict control surface commands to a limited set of analyzed combinations, and train pilots to follow procedural maneuvering limitations. With recent advances in structural sensing and the continued desire to improve safety and vehicle fuel efficiency, it is both possible and desirable to develop control architectures that enable lighter vehicle weights while maintaining and improving protection against structural damage. An optimal control technique has been explored and shown to achieve desirable vehicle control performance while limiting sensed structural loads. The subject of this paper is the design of the optimal control architecture, and provides the reader with some techniques for tailoring the architecture, along with detailed simulation results.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues.

PubMed

Guo, Song; Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields.

A Multifeatures Fusion and Discrete Firefly Optimization Method for Prediction of Protein Tyrosine Sulfation Residues

PubMed Central

Liu, Chunhua; Zhou, Peng; Li, Yanling

2016-01-01

Tyrosine sulfation is one of the ubiquitous protein posttranslational modifications, where some sulfate groups are added to the tyrosine residues. It plays significant roles in various physiological processes in eukaryotic cells. To explore the molecular mechanism of tyrosine sulfation, one of the prerequisites is to correctly identify possible protein tyrosine sulfation residues. In this paper, a novel method was presented to predict protein tyrosine sulfation residues from primary sequences. By means of informative feature construction and elaborate feature selection and parameter optimization scheme, the proposed predictor achieved promising results and outperformed many other state-of-the-art predictors. Using the optimal features subset, the proposed method achieved mean MCC of 94.41% on the benchmark dataset, and a MCC of 90.09% on the independent dataset. The experimental performance indicated that our new proposed method could be effective in identifying the important protein posttranslational modifications and the feature selection scheme would be powerful in protein functional residues prediction research fields. PMID:27034949

Point spread function engineering for iris recognition system design.

PubMed

Ashok, Amit; Neifeld, Mark A

2010-04-01

Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

Staircase Quantum Dots Configuration in Nanowires for Optimized Thermoelectric Power

PubMed Central

Li, Lijie; Jiang, Jian-Hua

2016-01-01

The performance of thermoelectric energy harvesters can be improved by nanostructures that exploit inelastic transport processes. One prototype is the three-terminal hopping thermoelectric device where electron hopping between quantum-dots are driven by hot phonons. Such three-terminal hopping thermoelectric devices have potential in achieving high efficiency or power via inelastic transport and without relying on heavy-elements or toxic compounds. We show in this work how output power of the device can be optimized via tuning the number and energy configuration of the quantum-dots embedded in parallel nanowires. We find that the staircase energy configuration with constant energy-step can improve the power factor over a serial connection of a single pair of quantum-dots. Moreover, for a fixed energy-step, there is an optimal length for the nanowire. Similarly for a fixed number of quantum-dots there is an optimal energy-step for the output power. Our results are important for future developments of high-performance nanostructured thermoelectric devices. PMID:27550093

Theoretical and experimental investigations on the optimal match between compressor and cold finger of the Stirling-type pulse tube cryocooler

NASA Astrophysics Data System (ADS)

Dang, Haizheng; Tan, Jun; Zhang, Lei

2016-06-01

The match between the pulse tube cold finger (PTCF) and the linear compressor of the Stirling-type pulse tube cryocooler plays a vital role in optimizing the compressor efficiency and in improving the PTCF cooling performance as well. In this paper, the interaction of them has been analyzed in a detailed way to reveal the match mechanism, and systematic investigations on the two-way matching have been conducted. The design method of the PTCF to achieve the optimal matching for the given compressor and the counterpart design method of the compressor to achieve the optimal matching for the given PTCF are put forward. Specific experiments are then carried out to verify the conducted theoretical analyses and modeling. For a given linear compressor, a new in-line PTCF which seeks to achieve the optimal match is simulated, designed and tested. And for a given coaxial PTCF, a new dual-opposed moving-coil linear compressor is also developed to match with it. The simulated and experimental results are compared, and fairly good agreements are found between them in both cases. The matched in-line cooler with the newly-designed PTCF has capacities of 4-11.84 W at 80 K with higher than 17% of Carnot efficiency and the mean motor efficiency of 81.5%, and the matched coaxial cooler with the new-designed compressor can provide 2-5.5 W at 60 K with higher than 9.6% of Carnot efficiency and the mean motor efficiency of 83%, which verify the validity of the theoretical investigations on the optimal match and the proposed design methods.

Coevolutionary Free Lunches

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Macready, William G.

2005-01-01

Recent work on the mathematical foundations of optimization has begun to uncover its rich structure. In particular, the "No Free Lunch" (NFL) theorems state that any two algorithms are equivalent when their performance is averaged across all possible problems. This highlights the need for exploiting problem-specific knowledge to achieve better than random performance. In this paper we present a general framework covering more search scenarios. In addition to the optimization scenarios addressed in the NFL results, this framework covers multi-armed bandit problems and evolution of multiple co-evolving players. As a particular instance of the latter, it covers "self-play" problems. In these problems the set of players work together to produce a champion, who then engages one or more antagonists in a subsequent multi-player game. In contrast to the traditional optimization case where the NFL results hold, we show that in self-play there are free lunches: in coevolution some algorithms have better performance than other algorithms, averaged across all possible problems. We consider the implications of these results to biology where there is no champion.

Optimal Link Removal for Epidemic Mitigation: A Two-Way Partitioning Approach

PubMed Central

Enns, Eva A.; Mounzer, Jeffrey J.; Brandeau, Margaret L.

2011-01-01

The structure of the contact network through which a disease spreads may influence the optimal use of resources for epidemic control. In this work, we explore how to minimize the spread of infection via quarantining with limited resources. In particular, we examine which links should be removed from the contact network, given a constraint on the number of removable links, such that the number of nodes which are no longer at risk for infection is maximized. We show how this problem can be posed as a non-convex quadratically constrained quadratic program (QCQP), and we use this formulation to derive a link removal algorithm. The performance of our QCQP-based algorithm is validated on small Erdős-Renyi and small-world random graphs, and then tested on larger, more realistic networks, including a real-world network of injection drug use. We show that our approach achieves near optimal performance and out-perform so ther intuitive link removal algorithms, such as removing links in order of edge centrality. PMID:22115862

Local performance optimization for a class of redundant eight-degree-of-freedom manipulators

NASA Technical Reports Server (NTRS)

Williams, Robert L., II

1994-01-01

Local performance optimization for joint limit avoidance and manipulability maximization (singularity avoidance) is obtained by using the Jacobian matrix pseudoinverse and by projecting the gradient of an objective function into the Jacobian null space. Real-time redundancy optimization control is achieved for an eight-joint redundant manipulator having a three-axis spherical shoulder, a single elbow joint, and a four-axis spherical wrist. Symbolic solutions are used for both full-Jacobian and wrist-partitioned pseudoinverses, partitioned null-space projection matrices, and all objective function gradients. A kinematic limitation of this class of manipulators and the limitation's effect on redundancy resolution are discussed. Results obtained with graphical simulation are presented to demonstrate the effectiveness of local redundant manipulator performance optimization. Actual hardware experiments performed to verify the simulated results are also discussed. A major result is that the partitioned solution is desirable because of low computation requirements. The partitioned solution is suboptimal compared with the full solution because translational and rotational terms are optimized separately; however, the results show that the difference is not significant. Singularity analysis reveals that no algorithmic singularities exist for the partitioned solution. The partitioned and full solutions share the same physical manipulator singular conditions. When compared with the full solution, the partitioned solution is shown to be ill-conditioned in smaller neighborhoods of the shared singularities.

Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise

NASA Astrophysics Data System (ADS)

Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming

2017-11-01

Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real-world problems effectively, more robust superpixel algorithms must be developed.

Power-constrained supercomputing

NASA Astrophysics Data System (ADS)

Bailey, Peter E.

As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, achieving practical exascale computing will therefore rely on optimizing performance subject to a power constraint. However, this requirement should not add to the burden of application developers; optimizing the runtime environment given restricted power will primarily be the job of high-performance system software. In this dissertation, we explore this area and develop new techniques that extract maximum performance subject to a particular power constraint. These techniques include a method to find theoretical optimal performance, a runtime system that shifts power in real time to improve performance, and a node-level prediction model for selecting power-efficient operating points. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive message passing events. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41%. This demonstrates limitations of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target. We also introduce Conductor, a run-time system that intelligently distributes available power to nodes and cores to improve performance. The key techniques used are configuration space exploration and adaptive power balancing. Configuration exploration dynamically selects the optimal thread concurrency level and DVFS state subject to a hardware-enforced power bound. Adaptive power balancing efficiently predicts where critical paths are likely to occur and distributes power to those paths. Greater power, in turn, allows increased thread concurrency levels, CPU frequency/voltage, or both. We describe these techniques in detail and show that, compared to the state-of-the-art technique of using statically predetermined, per-node power caps, Conductor leads to a best-case performance improvement of up to 30%, and an average improvement of 19.1%. At the node level, an accurate power/performance model will aid in selecting the right configuration from a large set of available configurations. We present a novel approach to generate such a model offline using kernel clustering and multivariate linear regression. Our model requires only two iterations to select a configuration, which provides a significant advantage over exhaustive search-based strategies. We apply our model to predict power and performance for different applications using arbitrary configurations, and show that our model, when used with hardware frequency-limiting in a runtime system, selects configurations with significantly higher performance at a given power limit than those chosen by frequency-limiting alone. When applied to a set of 36 computational kernels from a range of applications, our model accurately predicts power and performance; our runtime system based on the model maintains 91% of optimal performance while meeting power constraints 88% of the time. When the runtime system violates a power constraint, it exceeds the constraint by only 6% in the average case, while simultaneously achieving 54% more performance than an oracle. Through the combination of the above contributions, we hope to provide guidance and inspiration to research practitioners working on runtime systems for power-constrained environments. We also hope this dissertation will draw attention to the need for software and runtime-controlled power management under power constraints at various levels, from the processor level to the cluster level.

Anaerobic treatment of complex chemical wastewater in a sequencing batch biofilm reactor: process optimization and evaluation of factor interactions using the Taguchi dynamic DOE methodology.

PubMed

Venkata Mohan, S; Chandrasekhara Rao, N; Krishna Prasad, K; Murali Krishna, P; Sreenivas Rao, R; Sarma, P N

2005-06-20

The Taguchi robust experimental design (DOE) methodology has been applied on a dynamic anaerobic process treating complex wastewater by an anaerobic sequencing batch biofilm reactor (AnSBBR). For optimizing the process as well as to evaluate the influence of different factors on the process, the uncontrollable (noise) factors have been considered. The Taguchi methodology adopting dynamic approach is the first of its kind for studying anaerobic process evaluation and process optimization. The designed experimental methodology consisted of four phases--planning, conducting, analysis, and validation connected sequence-wise to achieve the overall optimization. In the experimental design, five controllable factors, i.e., organic loading rate (OLR), inlet pH, biodegradability (BOD/COD ratio), temperature, and sulfate concentration, along with the two uncontrollable (noise) factors, volatile fatty acids (VFA) and alkalinity at two levels were considered for optimization of the anae robic system. Thirty-two anaerobic experiments were conducted with a different combination of factors and the results obtained in terms of substrate degradation rates were processed in Qualitek-4 software to study the main effect of individual factors, interaction between the individual factors, and signal-to-noise (S/N) ratio analysis. Attempts were also made to achieve optimum conditions. Studies on the influence of individual factors on process performance revealed the intensive effect of OLR. In multiple factor interaction studies, biodegradability with other factors, such as temperature, pH, and sulfate have shown maximum influence over the process performance. The optimum conditions for the efficient performance of the anaerobic system in treating complex wastewater by considering dynamic (noise) factors obtained are higher organic loading rate of 3.5 Kg COD/m3 day, neutral pH with high biodegradability (BOD/COD ratio of 0.5), along with mesophilic temperature range (40 degrees C), and low sulfate concentration (700 mg/L). The optimization resulted in enhanced anaerobic performance (56.7%) from a substrate degradation rate (SDR) of 1.99 to 3.13 Kg COD/m3 day. Considering the obtained optimum factors, further validation experiments were carried out, which showed enhanced process performance (3.04 Kg COD/m3-day from 1.99 Kg COD/m3 day) accounting for 52.13% improvement with the optimized process conditions. The proposed method facilitated a systematic mathematical approach to understand the complex multi-species manifested anaerobic process treating complex chemical wastewater by considering the uncontrollable factors. Copyright (c) 2005 Wiley Periodicals, Inc.

Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools.

PubMed

Ouyang, Qin; Chen, Quansheng; Zhao, Jiewen

2016-02-05

The approach presented herein reports the application of near infrared (NIR) spectroscopy, in contrast with human sensory panel, as a tool for estimating Chinese rice wine quality; concretely, to achieve the prediction of the overall sensory scores assigned by the trained sensory panel. Back propagation artificial neural network (BPANN) combined with adaptive boosting (AdaBoost) algorithm, namely BP-AdaBoost, as a novel nonlinear algorithm, was proposed in modeling. First, the optimal spectra intervals were selected by synergy interval partial least square (Si-PLS). Then, BP-AdaBoost model based on the optimal spectra intervals was established, called Si-BP-AdaBoost model. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient (Rp) and root mean square error of prediction (RMSEP) in prediction set. Si-BP-AdaBoost showed excellent performance in comparison with other models. The best Si-BP-AdaBoost model was achieved with Rp=0.9180 and RMSEP=2.23 in the prediction set. It was concluded that NIR spectroscopy combined with Si-BP-AdaBoost was an appropriate method for the prediction of the sensory quality in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

Improvement and analysis of the hydrogen-cerium redox flow cell

DOE PAGES

Tucker, Michael C.; Weiss, Alexandra; Weber, Adam Z.

2016-08-03

In this paper, the H 2-Ce redox flow cell is optimized using commercially-available cell materials. Cell performance is found to be sensitive to the upper charge cutoff voltage, membrane boiling pretreatment, methanesulfonic-acid concentration, (+) electrode surface area and flow pattern, and operating temperature. Performance is relatively insensitive to membrane thickness, Cerium concentration, and all features of the (-) electrode including hydrogen flow. Cell performance appears to be limited by mass transport and kinetics in the cerium (+) electrode. Maximum discharge power of 895 mW cm -2 was observed at 60 °C; an energy efficiency of 90% was achieved at 50more » °C. Finally, the H 2-Ce cell is promising for energy storage assuming one can optimize Ce reaction kinetics and electrolyte.« less

Trade Studies for a Manned High-Power Nuclear Electric Propulsion Vehicle

NASA Technical Reports Server (NTRS)

SanSoucie, Michael; Hull, Patrick V.; Irwin, Ryan W.; TInker, Michael L.; Patton, Bruce W.

2005-01-01

Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate vehicles must be identified through trade studies for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combines analysis codes for NEP subsystems with genetic algorithm-based optimization. Trade studies for a NEP reference mission to the asteroids were conducted to identify important trends, and to determine the effects of various technologies and subsystems on vehicle performance. It was found that the electric thruster type and thruster performance have a major impact on the achievable system performance, and that significant effort in thruster research and development is merited.

Solving Optimization Problems with Spreadsheets

ERIC Educational Resources Information Center

Beigie, Darin

2017-01-01

Spreadsheets provide a rich setting for first-year algebra students to solve problems. Individual spreadsheet cells play the role of variables, and creating algebraic expressions for a spreadsheet to perform a task allows students to achieve a glimpse of how mathematics is used to program a computer and solve problems. Classic optimization…

76 FR 33307 - Strengthen and Promote the Role of Local Health Departments in Retail Food Safety Regulation (U-50)

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-08

..., scientifically-based guidance, training, program evaluation, and technical assistance. B. Research/Cooperative... officials. NACCHO values guide staff and leadership in work to achieve optimal health for all through an... annual appropriations and successful performance. III. Paper Application, Registration, and Submission...

High density arrays of micromirrors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Folta, J. M.; Decker, J. Y.; Kolman, J.

We established and achieved our goal to (1) fabricate and evaluate test structures based on the micromirror design optimized for maskless lithography applications, (2) perform system analysis and code development for the maskless lithography concept, and (3) identify specifications for micromirror arrays (MMAs) for LLNL's adaptive optics (AO) applications and conceptualize new devices.

A permanent-magnet rotor for a high-temperature superconducting bearing

NASA Astrophysics Data System (ADS)

Mulcahy, T. M.; Hull, J. R.; Uherka, K. L.; Abboud, R. G.; Wise, J. H.; Carnegie, D. W.

1995-06-01

Design, fabrication, and performance, of a 1/3-m dia., 10-kg flywheel rotor with only one bearing is discussed. To achieve low-loss energy storage, the rotor's segmented-ring permanent-magnet (PM) is optimized for levitation and circumferential homogeneity. The magnet's carbon composite bands enable practical energy storage.

A Workstation Farm Optimized for Monte Carlo Shell Model Calculations : Alphleet

NASA Astrophysics Data System (ADS)

Watanabe, Y.; Shimizu, N.; Haruyama, S.; Honma, M.; Mizusaki, T.; Taketani, A.; Utsuno, Y.; Otsuka, T.

We have built a workstation farm named ``Alphleet" which consists of 140 COMPAQ's Alpha 21264 CPUs, for Monte Carlo Shell Model (MCSM) calculations. It has achieved more than 90 % scalable performance with 140 CPUs when the MCSM calculation with PVM and 61.2 Gflops of LINPACK.

Accelerating IMRT optimization by voxel sampling

NASA Astrophysics Data System (ADS)

Martin, Benjamin C.; Bortfeld, Thomas R.; Castañon, David A.

2007-12-01

This paper presents a new method for accelerating intensity-modulated radiation therapy (IMRT) optimization using voxel sampling. Rather than calculating the dose to the entire patient at each step in the optimization, the dose is only calculated for some randomly selected voxels. Those voxels are then used to calculate estimates of the objective and gradient which are used in a randomized version of a steepest descent algorithm. By selecting different voxels on each step, we are able to find an optimal solution to the full problem. We also present an algorithm to automatically choose the best sampling rate for each structure within the patient during the optimization. Seeking further improvements, we experimented with several other gradient-based optimization algorithms and found that the delta-bar-delta algorithm performs well despite the randomness. Overall, we were able to achieve approximately an order of magnitude speedup on our test case as compared to steepest descent.

Reliability-based design optimization using a generalized subset simulation method and posterior approximation

NASA Astrophysics Data System (ADS)

Ma, Yuan-Zhuo; Li, Hong-Shuang; Yao, Wei-Xing

2018-05-01

The evaluation of the probabilistic constraints in reliability-based design optimization (RBDO) problems has always been significant and challenging work, which strongly affects the performance of RBDO methods. This article deals with RBDO problems using a recently developed generalized subset simulation (GSS) method and a posterior approximation approach. The posterior approximation approach is used to transform all the probabilistic constraints into ordinary constraints as in deterministic optimization. The assessment of multiple failure probabilities required by the posterior approximation approach is achieved by GSS in a single run at all supporting points, which are selected by a proper experimental design scheme combining Sobol' sequences and Bucher's design. Sequentially, the transformed deterministic design optimization problem can be solved by optimization algorithms, for example, the sequential quadratic programming method. Three optimization problems are used to demonstrate the efficiency and accuracy of the proposed method.

[Not Available].

PubMed

Mokeddem, Diab; Khellaf, Abdelhafid

2009-01-01

Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to achieve fine tuning of variables in determining a set of non dominating solutions distributed along the Pareto front in a single run of the algorithm. The NSGA-II ability to identify a set of optimal solutions provides the decision-maker DM with a complete picture of the optimal solution space to gain better and appropriate choices. Then an outranking with PROMETHEE II helps the decision-maker to finalize the selection of a best compromise. The effectiveness of NSGA-II method with multiojective optimization problem is illustrated through two carefully referenced examples.

Aerodynamic optimization of wind turbine rotor using CFD/AD method

NASA Astrophysics Data System (ADS)

Cao, Jiufa; Zhu, Weijun; Wang, Tongguang; Ke, Shitang

2018-05-01

The current work describes a novel technique for wind turbine rotor optimization. The aerodynamic design and optimization of wind turbine rotor can be achieved with different methods, such as the semi-empirical engineering methods and more accurate computational fluid dynamic (CFD) method. The CFD method often provides more detailed aerodynamics features during the design process. However, high computational cost limits the application, especially for rotor optimization purpose. In this paper, a CFD-based actuator disc (AD) model is used to represent turbulent flow over a wind turbine rotor. The rotor is modeled as a permeable disc of equivalent area where the forces from the blades are distributed on the circular disc. The AD model is coupled with a Reynolds Averaged Navier-Stokes (RANS) solver such that the thrust and power are simulated. The design variables are the shape parameters comprising the chord, the twist and the relative thickness of the wind turbine rotor blade. The comparative aerodynamic performance is analyzed between the original and optimized reference wind turbine rotor. The results showed that the optimization framework can be effectively and accurately utilized in enhancing the aerodynamic performance of the wind turbine rotor.

Exploring Machine Learning Techniques For Dynamic Modeling on Future Exascale Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Shuaiwen; Tallent, Nathan R.; Vishnu, Abhinav

2013-09-23

Future exascale systems must be optimized for both power and performance at scale in order to achieve DOE’s goal of a sustained petaflop within 20 Megawatts by 2022 [1]. Massive parallelism of the future systems combined with complex memory hierarchies will form a barrier to efficient application and architecture design. These challenges are exacerbated with emerging complex architectures such as GPGPUs and Intel Xeon Phi as parallelism increases orders of magnitude and system power consumption can easily triple or quadruple. Therefore, we need techniques that can reduce the search space for optimization, isolate power-performance bottlenecks, identify root causes for software/hardwaremore » inefficiency, and effectively direct runtime scheduling.« less

High-speed prediction of crystal structures for organic molecules

NASA Astrophysics Data System (ADS)

Obata, Shigeaki; Goto, Hitoshi

2015-02-01

We developed a master-worker type parallel algorithm for allocating tasks of crystal structure optimizations to distributed compute nodes, in order to improve a performance of simulations for crystal structure predictions. The performance experiments were demonstrated on TUT-ADSIM supercomputer system (HITACHI HA8000-tc/HT210). The experimental results show that our parallel algorithm could achieve speed-ups of 214 and 179 times using 256 processor cores on crystal structure optimizations in predictions of crystal structures for 3-aza-bicyclo(3.3.1)nonane-2,4-dione and 2-diazo-3,5-cyclohexadiene-1-one, respectively. We expect that this parallel algorithm is always possible to reduce computational costs of any crystal structure predictions.

Global Optimization of N-Maneuver, High-Thrust Trajectories Using Direct Multiple Shooting

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob A.; Ellison, Donald H.

2016-01-01

The performance of impulsive, gravity-assist trajectories often improves with the inclusion of one or more maneuvers between flybys. However, grid-based scans over the entire design space can become computationally intractable for even one deep-space maneuver, and few global search routines are capable of an arbitrary number of maneuvers. To address this difficulty a trajectory transcription allowing for any number of maneuvers is developed within a multi-objective, global optimization framework for constrained, multiple gravity-assist trajectories. The formulation exploits a robust shooting scheme and analytic derivatives for computational efficiency. The approach is applied to several complex, interplanetary problems, achieving notable performance without a user-supplied initial guess.

High-Performance, Multi-Node File Copies and Checksums for Clustered File Systems

NASA Technical Reports Server (NTRS)

Kolano, Paul Z.; Ciotti, Robert B.

2012-01-01

Modern parallel file systems achieve high performance using a variety of techniques, such as striping files across multiple disks to increase aggregate I/O bandwidth and spreading disks across multiple servers to increase aggregate interconnect bandwidth. To achieve peak performance from such systems, it is typically necessary to utilize multiple concurrent readers/writers from multiple systems to overcome various singlesystem limitations, such as number of processors and network bandwidth. The standard cp and md5sum tools of GNU coreutils found on every modern Unix/Linux system, however, utilize a single execution thread on a single CPU core of a single system, and hence cannot take full advantage of the increased performance of clustered file systems. Mcp and msum are drop-in replacements for the standard cp and md5sum programs that utilize multiple types of parallelism and other optimizations to achieve maximum copy and checksum performance on clustered file systems. Multi-threading is used to ensure that nodes are kept as busy as possible. Read/write parallelism allows individual operations of a single copy to be overlapped using asynchronous I/O. Multinode cooperation allows different nodes to take part in the same copy/checksum. Split-file processing allows multiple threads to operate concurrently on the same file. Finally, hash trees allow inherently serial checksums to be performed in parallel. Mcp and msum provide significant performance improvements over standard cp and md5sum using multiple types of parallelism and other optimizations. The total speed-ups from all improvements are significant. Mcp improves cp performance over 27x, msum improves md5sum performance almost 19x, and the combination of mcp and msum improves verified copies via cp and md5sum by almost 22x. These improvements come in the form of drop-in replacements for cp and md5sum, so are easily used and are available for download as open source software at http://mutil.sourceforge.net.

Paying the right price for pharmaceuticals: a case study of why the comparator matters.

PubMed

Spinks, Jean M; Richardson, Jeff R J

2011-08-01

This article considers the pricing policy for pharmaceuticals in Australia, which is widely seen as having achieved low drug prices. However, compared to New Zealand, the evidence implies that Australia might have improved its performance significantly if it had proactively sought market best pricing. The Australian record suggests that the information sought by authorities may not be sufficient for optimal pricing and that the economic evaluation of pharmaceuticals may be neither necessary nor sufficient for achieving this goal.

[Rapid detection of caffeine in blood by freeze-out extraction].

PubMed

Bekhterev, V N; Gavrilova, S N; Kozina, E P; Maslakov, I V

2010-01-01

A new method for the detection of caffeine in blood has been proposed based on the combination of extraction and freezing-out to eliminate the influence of sample matrix. Metrological characteristics of the method are presented. Selectivity of detection is achieved by optimal conditions of analysis by high performance liquid chromatography. The method is technically simple and cost-efficient, it ensures rapid performance of the studies.

Unleashing elastic energy: dynamics of energy release in rubber bands and impulsive biological systems

NASA Astrophysics Data System (ADS)

Ilton, Mark; Cox, Suzanne; Egelmeers, Thijs; Patek, S. N.; Crosby, Alfred J.

Impulsive biological systems - which include mantis shrimp, trap-jaw ants, and venus fly traps - can reach high speeds by using elastic elements to store and rapidly release energy. The material behavior and shape changes critical to achieving rapid energy release in these systems are largely unknown due to limitations of materials testing instruments operating at high speed and large displacement. In this work, we perform fundamental, proof-of-concept measurements on the tensile retraction of elastomers. Using high speed imaging, the kinematics of retraction are measured for elastomers with varying mechanical properties and geometry. Based on the kinematics, the rate of energy dissipation in the material is determined as a function of strain and strain-rate, along with a scaling relation which describes the dependence of maximum velocity on material properties. Understanding this scaling relation along with the material failure limits of the elastomer allows the prediction of material properties required for optimal performance. We demonstrate this concept experimentally by optimizing for maximum velocity in our synthetic model system, and achieve retraction velocities that exceed those in biological impulsive systems. This model system provides a foundation for future work connecting continuum performance to molecular architecture in impulsive systems.

Running with horizontal pulling forces: the benefits of towing.

PubMed

Grabowski, Alena M; Kram, Rodger

2008-10-01

Towing, or running with a horizontal pulling force, is a common technique used by adventure racing teams. During an adventure race, the slowest person on a team determines the team's overall performance. To improve overall performance, a faster runner tows a slower runner with an elastic cord attached to their waists. Our purpose was to create and validate a model that predicts the optimal towing force needed by two runners to achieve their best overall performance. We modeled the effects of towing forces between two runners that differ in solo 10-km performance time and/or body mass. We calculated the overall time that could be saved with towing for running distances of 10, 20, and 42.2-km based on equations from previous research. Then, we empirically tested our 10-km model on 15 runners. Towing improved overall running performance considerably and our model accurately predicted this performance improvement. For example, if two runners (a 70 kg runner with a 35 min solo 10-km time and a 70-kg runner with a 50-min solo 10-km time) maintain an optimal towing force throughout a 10-km race, they can improve overall performance by 15%, saving almost 8 min. Ultimately, the race performance time and body mass of each runner determine the optimal towing force.

Emerging Techniques for Dose Optimization in Abdominal CT

PubMed Central

Platt, Joel F.; Goodsitt, Mitchell M.; Al-Hawary, Mahmoud M.; Maturen, Katherine E.; Wasnik, Ashish P.; Pandya, Amit

2014-01-01

Recent advances in computed tomographic (CT) scanning technique such as automated tube current modulation (ATCM), optimized x-ray tube voltage, and better use of iterative image reconstruction have allowed maintenance of good CT image quality with reduced radiation dose. ATCM varies the tube current during scanning to account for differences in patient attenuation, ensuring a more homogeneous image quality, although selection of the appropriate image quality parameter is essential for achieving optimal dose reduction. Reducing the x-ray tube voltage is best suited for evaluating iodinated structures, since the effective energy of the x-ray beam will be closer to the k-edge of iodine, resulting in a higher attenuation for the iodine. The optimal kilovoltage for a CT study should be chosen on the basis of imaging task and patient habitus. The aim of iterative image reconstruction is to identify factors that contribute to noise on CT images with use of statistical models of noise (statistical iterative reconstruction) and selective removal of noise to improve image quality. The degree of noise suppression achieved with statistical iterative reconstruction can be customized to minimize the effect of altered image quality on CT images. Unlike with statistical iterative reconstruction, model-based iterative reconstruction algorithms model both the statistical noise and the physical acquisition process, allowing CT to be performed with further reduction in radiation dose without an increase in image noise or loss of spatial resolution. Understanding these recently developed scanning techniques is essential for optimization of imaging protocols designed to achieve the desired image quality with a reduced dose. © RSNA, 2014 PMID:24428277

Comparison of fan beam, slit-slat and multi-pinhole collimators for molecular breast tomosynthesis.

PubMed

van Roosmalen, Jarno; Beekman, Freek J; Goorden, Marlies C

2018-05-16

Recently, we proposed and optimized dedicated multi-pinhole molecular breast tomosynthesis (MBT) that images a lightly compressed breast. As MBT may also be performed with other types of collimators, the aim of this paper is to optimize MBT with fan beam and slit-slat collimators and to compare its performance to that of multi-pinhole MBT to arrive at a truly optimized design. Using analytical expressions, we first optimized fan beam and slit-slat collimator parameters to reach maximum sensitivity at a series of given system resolutions. Additionally, we performed full system simulations of a breast phantom containing several tumours for the optimized designs. We found that at equal system resolution the maximum achievable sensitivity increases from pinhole to slit-slat to fan beam collimation with fan beam and slit-slat MBT having on average a 48% and 20% higher sensitivity than multi-pinhole MBT. Furthermore, by inspecting simulated images and applying a tumour-to-background contrast-to-noise (TB-CNR) analysis, we found that slit-slat collimators underperform with respect to the other collimator types. The fan beam collimators obtained a similar TB-CNR as the pinhole collimators, but the optimum was reached at different system resolutions. For fan beam collimators, a 6-8 mm system resolution was optimal in terms of TB-CNR, while with pinhole collimation highest TB-CNR was reached in the 7-10 mm range.

A stochastic optimal feedforward and feedback control methodology for superagility

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.

1992-01-01

A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

Spectroscopic Ellipsometry Studies of Thin Film a-Si:H Solar Cell Fabrication by Multichamber Deposition in the n-i-p Substrate Configuration

NASA Astrophysics Data System (ADS)

Dahal, Lila Raj

Real time spectroscopic ellipsometry (RTSE), and ex-situ mapping spectroscopic ellipsometry (SE) are powerful characterization techniques capable of performance optimization and scale-up evaluation of thin film solar cells used in various photovoltaics technologies. These non-invasive optical probes employ multichannel spectral detection for high speed and provide high precision parameters that describe (i) thin film structure, such as layer thicknesses, and (ii) thin film optical properties, such as oscillator variables in analytical expressions for the complex dielectric function. These parameters are critical for evaluating the electronic performance of materials in thin film solar cells and also can be used as inputs for simulating their multilayer optical performance. In this Thesis, the component layers of thin film hydrogenated silicon (Si:H) solar cells in the n-i-p or substrate configuration on rigid and flexible substrate materials have been studied by RTSE and ex-situ mapping SE. Depositions were performed by magnetron sputtering for the metal and transparent conducting oxide contacts and by plasma enhanced chemical vapor deposition (PECVD) for the semiconductor doped contacts and intrinsic absorber layers. The motivations are first to optimize the thin film Si:H solar cell in n-i-p substrate configuration for single-junction small-area dot cells and ultimately to scale-up the optimized process to larger areas with minimum loss in device performance. Deposition phase diagrams for both i- and p -layers on 2" x 2" rigid borosilicate glass substrate were developed as functions of the hydrogen-to-silane flow ratio in PECVD. These phase diagrams were correlated with the performance parameters of the corresponding solar cells, fabricated in the Cr/Ag/ZnO/n/i/ p/ITO structure. In both cases, optimization was achieved when the layers were deposited in the protocrystalline phase. Identical solar cell structures were fabricated on 6" x 6" borosilicate glass with 256 cells followed by ex-situ mapping SE on each cell to achieve better statistics for solar cell optimization by correlating local structural parameters with solar cell parameters. Solar cells of similar structure were also fabricated on flexible polymer substrates in the roll-to-roll configuration. In this configuration as well, RTSE was demonstrated as an effective process monitoring and control tool for thin film photovoltaics.

Optimization design of wireless charging system for autonomous robots based on magnetic resonance coupling

NASA Astrophysics Data System (ADS)

Wang, Junhua; Hu, Meilin; Cai, Changsong; Lin, Zhongzheng; Li, Liang; Fang, Zhijian

2018-05-01

Wireless charging is the key technology to realize real autonomy of mobile robots. As the core part of wireless power transfer system, coupling mechanism including coupling coils and compensation topology is analyzed and optimized through simulations, to achieve stable and practical wireless charging suitable for ordinary robots. Multi-layer coil structure, especially double-layer coil is explored and selected to greatly enhance coupling performance, while shape of ferrite shielding goes through distributed optimization to guarantee coil fault tolerance and cost effectiveness. On the basis of optimized coils, primary compensation topology is analyzed to adopt composite LCL compensation, to stabilize operations of the primary side under variations of mutual inductance. Experimental results show the optimized system does make sense for wireless charging application for robots based on magnetic resonance coupling, to realize long-term autonomy of robots.

Noise Figure Optimization of Fully Integrated Inductively Degenerated Silicon Germanium HBT LNAs

NASA Astrophysics Data System (ADS)

Ibrahim, Mohamed Farhat

Silicon germanium (SiGe) heterojunction bipolar transistors (HBTs) have the properties of producing very low noise and high gain over a wide bandwidth. Because of these properties, SiGe HBTs have continually improved and now compete with InP and GaAs HEMTs for low-noise amplification. This thesis investigates the theoretical characterizations and optimizations of SiGe HBT low noise amplifiers (LNAs) for low-noise low-power applications, using SiGe BiCMOS (bipolar complementary metal-oxide-semiconductor) technology. The theoretical characterization of SiGe HBT transistors is investigated by a comprehensive study of the DC and small-signal transistor modeling. Based on a selected small-signal model, a noise model for the SiGe HBT transistor is produced. This noise model is used to build a cascode inductively degenerated SiGe HBT LNA circuit. The noise figure (NF) equation for this LNA is derived. This NF equation shows better than 94.4% agreement with the simulation results. With the small-signal model verification, a new analytical method for optimizing the noise figure of the SiGe HBT LNA circuits is presented. The novelty feature of this optimization is the inclusion of the noise contributions of the base inductor parasitic resistance, the emitter inductor parasitic resistance and the bond-wire inductor parasitic resistances. The optimization is performed by reducing the number of design variables as possible. This improved theoretical optimization results in LNA designs that achieve better noise figure performance compared to previously published results in bipolar and BiCMOS technologies. Different design constraints are discussed for the LNA optimization techniques. Three different LNAs are designed. The three designs are fully integrated and fabricated in a single chip to achieve a fully monolithic realization. The LNA designs are experimentally verified. The low noise design produced a NF of 1.5dB, S21 of 15dB, and power consumption of 15mW. The three LNA designs occupied 1.4mum 2 in 130 nm BiCMOS technology.

Understanding and optimizing the dual excipient functionality of sodium lauryl sulfate in tablet formulation of poorly water soluble drug: wetting and lubrication.

PubMed

Aljaberi, Ahmad; Chatterji, Ashish; Dong, Zedong; Shah, Navnit H; Malick, Waseem; Singhal, Dharmendra; Sandhu, Harpreet K

2013-01-01

To evaluate and optimize sodium lauryl sulfate (SLS) and magnesium stearate (Mg.St) levels, with respect to dissolution and compaction, in a high dose, poorly soluble drug tablet formulation. A model poorly soluble drug was formulated using high shear aqueous granulation. A D-optimal design was used to evaluate and model the effect of granulation conditions, size of milling screen, SLS and Mg.St levels on tablet compaction and ejection. The compaction profiles were generated using a Presster(©) compaction simulator. Dissolution of the kernels was performed using a USP dissolution apparatus II and intrinsic dissolution was determined using a stationary disk system. Unlike kernels dissolution which failed to discriminate between tablets prepared with various SLS contents, the intrinsic dissolution rate showed that a SLS level of 0.57% was sufficient to achieve the required release profile while having minimal effect on compaction. The formulation factors that affect tablet compaction and ejection were identified and satisfactorily modeled. The design space of best factor setting to achieve optimal compaction and ejection properties was successfully constructed by RSM analysis. A systematic study design helped identify the critical factors and provided means to optimize the functionality of key excipient to design robust drug product.

Optimization of the sources in local hyperthermia using a combined finite element-genetic algorithm method.

PubMed

Siauve, N; Nicolas, L; Vollaire, C; Marchal, C

2004-12-01

This article describes an optimization process specially designed for local and regional hyperthermia in order to achieve the desired specific absorption rate in the patient. It is based on a genetic algorithm coupled to a finite element formulation. The optimization method is applied to real human organs meshes assembled from computerized tomography scans. A 3D finite element formulation is used to calculate the electromagnetic field in the patient, achieved by radiofrequency or microwave sources. Space discretization is performed using incomplete first order edge elements. The sparse complex symmetric matrix equation is solved using a conjugate gradient solver with potential projection pre-conditionning. The formulation is validated by comparison of calculated specific absorption rate distributions in a phantom to temperature measurements. A genetic algorithm is used to optimize the specific absorption rate distribution to predict the phases and amplitudes of the sources leading to the best focalization. The objective function is defined as the specific absorption rate ratio in the tumour and healthy tissues. Several constraints, regarding the specific absorption rate in tumour and the total power in the patient, may be prescribed. Results obtained with two types of applicators (waveguides and annular phased array) are presented and show the faculties of the developed optimization process.

Stochastic injection-strategy optimization for the preliminary assessment of candidate geological storage sites

NASA Astrophysics Data System (ADS)

Cody, Brent M.; Baù, Domenico; González-Nicolás, Ana

2015-09-01

Geological carbon sequestration (GCS) has been identified as having the potential to reduce increasing atmospheric concentrations of carbon dioxide (CO2). However, a global impact will only be achieved if GCS is cost-effectively and safely implemented on a massive scale. This work presents a computationally efficient methodology for identifying optimal injection strategies at candidate GCS sites having uncertainty associated with caprock permeability, effective compressibility, and aquifer permeability. A multi-objective evolutionary optimization algorithm is used to heuristically determine non-dominated solutions between the following two competing objectives: (1) maximize mass of CO2 sequestered and (2) minimize project cost. A semi-analytical algorithm is used to estimate CO2 leakage mass rather than a numerical model, enabling the study of GCS sites having vastly different domain characteristics. The stochastic optimization framework presented herein is applied to a feasibility study of GCS in a brine aquifer in the Michigan Basin (MB), USA. Eight optimization test cases are performed to investigate the impact of decision-maker (DM) preferences on Pareto-optimal objective-function values and carbon-injection strategies. This analysis shows that the feasibility of GCS at the MB test site is highly dependent upon the DM's risk-adversity preference and degree of uncertainty associated with caprock integrity. Finally, large gains in computational efficiency achieved using parallel processing and archiving are discussed.

Adaptive time-sequential binary sensing for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Hu, Chenhui; Lu, Yue M.

2012-06-01

We present a novel image sensor for high dynamic range imaging. The sensor performs an adaptive one-bit quantization at each pixel, with the pixel output switched from 0 to 1 only if the number of photons reaching that pixel is greater than or equal to a quantization threshold. With an oracle knowledge of the incident light intensity, one can pick an optimal threshold (for that light intensity) and the corresponding Fisher information contained in the output sequence follows closely that of an ideal unquantized sensor over a wide range of intensity values. This observation suggests the potential gains one may achieve by adaptively updating the quantization thresholds. As the main contribution of this work, we propose a time-sequential threshold-updating rule that asymptotically approaches the performance of the oracle scheme. With every threshold mapped to a number of ordered states, the dynamics of the proposed scheme can be modeled as a parametric Markov chain. We show that the frequencies of different thresholds converge to a steady-state distribution that is concentrated around the optimal choice. Moreover, numerical experiments show that the theoretical performance measures (Fisher information and Craḿer-Rao bounds) can be achieved by a maximum likelihood estimator, which is guaranteed to find globally optimal solution due to the concavity of the log-likelihood functions. Compared with conventional image sensors and the strategy that utilizes a constant single-photon threshold considered in previous work, the proposed scheme attains orders of magnitude improvement in terms of sensor dynamic ranges.

Compliant flow designs for optimum lift control of wind turbine rotors

NASA Astrophysics Data System (ADS)

Williams, Theodore J. H.

An optimization approach was formulated to determine geometric designs that are most compliant to flow control devices. Single dielectric barrier discharge (SDBD) plasma actuators are used in the flow control design optimization as they are able to be incorporated into CFD simulations. An adjoint formulation was derived in order to have a numerically efficient way of calculating the shape derivatives on the surface of the geometric design. The design of a wind turbine blade retrofit for the JIMP 25kW wind turbine at Notre Dame is used to motivate analyses that utilize the optimization approach. The CFD simulations of the existing wind turbine blade were validated against wind tunnel testing. A one-parameter optimization was performed in order to design a trailing edge addition for the current wind turbine blade. The trailing edge addition was designed to meet a desired lift target while maximizing the lift-to-drag ratio. This analysis was performed at seven radial locations on the wind turbine blade. The new trailing edge retrofits were able to achieve the lift target for the outboard radial locations. The designed geometry has been fabricated and is currently being validated on a full-scale turbine and it is predicted to have an increase in annual energy production of 4.30%. The design of a trailing edge retrofit that includes the use of a SDBD plasma actuator was performed using a two-parameter optimization. The objective of this analysis was to meet the lift target and maximize the controllability of the design. The controllability is defined as the difference in lift between plasma on and plasma off cases. A trailing edge retrofit with the plasma actuator located on the pressure side was able to achieve the target passive lift increase while using plasma flow control to reduce the lift to below the original design. This design resulted in a highly compliant flow.

Design of double gate vertical tunnel field effect transistor using HDB and its performance estimation

NASA Astrophysics Data System (ADS)

Seema; Chauhan, Sudakar Singh

2018-05-01

In this paper, we demonstrate the double gate vertical tunnel field-effect transistor using homo/hetero dielectric buried oxide (HDB) to obtain the optimized device characteristics. In this concern, the existence of double gate, HDB and electrode work-function engineering enhances DC performance and Analog/RF performance. The use of electrostatic doping helps to achieve higher on-current owing to occurrence of higher tunneling generation rate of charge carriers at the source/epitaxial interface. Further, lightly doped drain region and high- k dielectric below channel and drain region are responsible to suppress the ambipolar current. Simulated results clarifies that proposed device have achieved the tremendous performance in terms of driving current capability, steeper subthreshold slope (SS), drain induced barrier lowering (DIBL), hot carrier effects (HCEs) and high frequency parameters for better device reliability.

The CF6 Jet Engine Performance Improvement - Low Pressure Turbine Active Clearance Control

NASA Technical Reports Server (NTRS)

Beck, B. D.; Fasching, W. A.

1982-01-01

A low pressure turbine (LPT) active clearance control (ACC) cooling system was developed to reduce the fuel consumption of current CF6-50 turbofan engines for wide bodied commercial aircraft. The program performance improvement goal of 0.3% delta sfc was determined to be achievable with an improved impingement cooling system. The technology enables the design of an optimized manifold and piping system which is capable of a performance gain of 0.45% delta sfc.

Effect of intake swirl on the performance of single cylinder direct injection diesel engine

NASA Astrophysics Data System (ADS)

Sharma, Vinod Kumar; Mohan, Man; Mouli, Chandra

2017-11-01

In the present work, the effect of inlet manifold geometry and swirl intensity on the direct injection (DI) diesel engine performance was investigated experimentally. Modifications in inlet manifold geometry have been suggested to achieve optimized swirl for the better mixing of fuel with air. The intake swirl intensities of modified cylinder head were measured in swirl test rig at different valve lifts. Later, the overall performance of 435 CC DI diesel engine was measured using modified cylinder head. In addition, the performance of engine was compared for both modified and old cylinder head. For same operating conditions, the brake power and brake specific fuel consumption was improved by 6% and 7% respectively with modified cylinder head compared to old cylinder head. The maximum brake power of 9 HP was achieved for modified cylinder head. The results revealed that the intake swirl has great influence on engine performance.

The influence of optimism and pessimism on student achievement in mathematics

NASA Astrophysics Data System (ADS)

Yates, Shirley M.

2002-11-01

Students' causal attributions are not only fundamental motivational variables but are also critical motivators of their persistence in learning. Optimism, pessimism, and achievement in mathematics were measured in a sample of primary and lower secondary students on two occasions. Although achievement in mathematics was most strongly related to prior achievement and grade level, optimism and pessimism were significant factors. In particular, students with a more generally pessimistic outlook on life had a lower level of achievement in mathematics over time. Gender was not a significant factor in achievement. The implications of these findings are discussed.

Delivery of compression therapy for venous leg ulcers.

PubMed

Zarchi, Kian; Jemec, Gregor B E

2014-07-01

Despite the documented effect of compression therapy in clinical studies and its widespread prescription, treatment of venous leg ulcers is often prolonged and recurrence rates high. Data on provided compression therapy are limited. To assess whether home care nurses achieve adequate subbandage pressure when treating patients with venous leg ulcers and the factors that predict the ability to achieve optimal pressure. We performed a cross-sectional study from March 1, 2011, through March 31, 2012, in home care centers in 2 Danish municipalities. Sixty-eight home care nurses who managed wounds in their everyday practice were included. Participant-masked measurements of subbandage pressure achieved with an elastic, long-stretch, single-component bandage; an inelastic, short-stretch, single-component bandage; and a multilayer, 2-component bandage, as well as, association between achievement of optimal pressure and years in the profession, attendance at wound care educational programs, previous work experience, and confidence in bandaging ability. A substantial variation in the exerted pressure was found: subbandage pressures ranged from 11 mm Hg exerted by an inelastic bandage to 80 mm Hg exerted by a 2-component bandage. The optimal subbandage pressure range, defined as 30 to 50 mm Hg, was achieved by 39 of 62 nurses (63%) applying the 2-component bandage, 28 of 68 nurses (41%) applying the elastic bandage, and 27 of 68 nurses (40%) applying the inelastic bandage. More than half the nurses applying the inelastic (38 [56%]) and elastic (36 [53%]) bandages obtained pressures less than 30 mm Hg. At best, only 17 of 62 nurses (27%) using the 2-component bandage achieved subbandage pressure within the range they aimed for. In this study, none of the investigated factors was associated with the ability to apply a bandage with optimal pressure. This study demonstrates the difficulty of achieving the desired subbandage pressure and indicates that a substantial proportion of patients with venous leg ulcers do not receive adequate compression therapy. Training programs that focus on practical bandaging skills should be implemented to improve management of venous leg ulcers.

Optimization of primary printed batteries based on Zn/MnO2

NASA Astrophysics Data System (ADS)

Madej, E.; Espig, M.; Baumann, R. R.; Schuhmann, W.; La Mantia, F.

2014-09-01

Thin-film batteries based on zinc/manganese dioxide chemistry with gel ZnCl2 electrolyte were manufactured as single (1.5 V) and double (3.0 V) cells from electrodes printed on paper substrates covered with different polymeric insulating coatings. Their properties were evaluated by means of electrochemical impedance spectroscopy and chronopotentiometry. Best performing cells achieved capacities in the range of 3 mAh cm-2 during discharge with 100 μA current, corresponding approximately to C/100 discharge rate. The influence of the cell elements on the overvoltage was examined and suggestions for the optimization of their performance were postulated. In particular, it was observed that limitations in the delivered power were governed by the poor conductivity of the carbon current collector. An optimized cell was built and showed a 4-fold improvement in the power delivered at 1 mA.

Sensitivity analysis, approximate analysis, and design optimization for internal and external viscous flows

NASA Technical Reports Server (NTRS)

Taylor, Arthur C., III; Hou, Gene W.; Korivi, Vamshi M.

1991-01-01

A gradient-based design optimization strategy for practical aerodynamic design applications is presented, which uses the 2D thin-layer Navier-Stokes equations. The strategy is based on the classic idea of constructing different modules for performing the major tasks such as function evaluation, function approximation and sensitivity analysis, mesh regeneration, and grid sensitivity analysis, all driven and controlled by a general-purpose design optimization program. The accuracy of aerodynamic shape sensitivity derivatives is validated on two viscous test problems: internal flow through a double-throat nozzle and external flow over a NACA 4-digit airfoil. A significant improvement in aerodynamic performance has been achieved in both cases. Particular attention is given to a consistent treatment of the boundary conditions in the calculation of the aerodynamic sensitivity derivatives for the classic problems of external flow over an isolated lifting airfoil on 'C' or 'O' meshes.

Blind Channel Equalization Using Constrained Generalized Pattern Search Optimization and Reinitialization Strategy

NASA Astrophysics Data System (ADS)

Zaouche, Abdelouahib; Dayoub, Iyad; Rouvaen, Jean Michel; Tatkeu, Charles

2008-12-01

We propose a global convergence baud-spaced blind equalization method in this paper. This method is based on the application of both generalized pattern optimization and channel surfing reinitialization. The potentially used unimodal cost function relies on higher- order statistics, and its optimization is achieved using a pattern search algorithm. Since the convergence to the global minimum is not unconditionally warranted, we make use of channel surfing reinitialization (CSR) strategy to find the right global minimum. The proposed algorithm is analyzed, and simulation results using a severe frequency selective propagation channel are given. Detailed comparisons with constant modulus algorithm (CMA) are highlighted. The proposed algorithm performances are evaluated in terms of intersymbol interference, normalized received signal constellations, and root mean square error vector magnitude. In case of nonconstant modulus input signals, our algorithm outperforms significantly CMA algorithm with full channel surfing reinitialization strategy. However, comparable performances are obtained for constant modulus signals.

Meeting the challenges of developing LED-based projection displays

NASA Astrophysics Data System (ADS)

Geißler, Enrico

2006-04-01

The main challenge in developing a LED-based projection system is to meet the brightness requirements of the market. Therefore a balanced combination of optical, electrical and thermal parameters must be reached to achieve these performance and cost targets. This paper describes the system design methodology for a digital micromirror display (DMD) based optical engine using LEDs as the light source, starting at the basic physical and geometrical parameters of the DMD and other optical elements through characterization of the LEDs to optimizing the system performance by determining optimal driving conditions. LEDs have a luminous flux density which is just at the threshold of acceptance in projection systems and thus only a fully optimized optical system with a matched set of LEDs can be used. This work resulted in two projection engines, one for a compact pocket projector and the other for a rear projection television, both of which are currently in commercialization.

Achieving Optimal Self-Adaptivity for Dynamic Tuning of Organic Semiconductors through Resonance Engineering.

PubMed

Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei

2016-08-03

Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.

Genetic algorithm approaches for conceptual design of spacecraft systems including multi-objective optimization and design under uncertainty

NASA Astrophysics Data System (ADS)

Hassan, Rania A.

In the design of complex large-scale spacecraft systems that involve a large number of components and subsystems, many specialized state-of-the-art design tools are employed to optimize the performance of various subsystems. However, there is no structured system-level concept-architecting process. Currently, spacecraft design is heavily based on the heritage of the industry. Old spacecraft designs are modified to adapt to new mission requirements, and feasible solutions---rather than optimal ones---are often all that is achieved. During the conceptual phase of the design, the choices available to designers are predominantly discrete variables describing major subsystems' technology options and redundancy levels. The complexity of spacecraft configurations makes the number of the system design variables that need to be traded off in an optimization process prohibitive when manual techniques are used. Such a discrete problem is well suited for solution with a Genetic Algorithm, which is a global search technique that performs optimization-like tasks. This research presents a systems engineering framework that places design requirements at the core of the design activities and transforms the design paradigm for spacecraft systems to a top-down approach rather than the current bottom-up approach. To facilitate decision-making in the early phases of the design process, the population-based search nature of the Genetic Algorithm is exploited to provide computationally inexpensive---compared to the state-of-the-practice---tools for both multi-objective design optimization and design optimization under uncertainty. In terms of computational cost, those tools are nearly on the same order of magnitude as that of standard single-objective deterministic Genetic Algorithm. The use of a multi-objective design approach provides system designers with a clear tradeoff optimization surface that allows them to understand the effect of their decisions on all the design objectives under consideration simultaneously. Incorporating uncertainties avoids large safety margins and unnecessary high redundancy levels. The focus on low computational cost for the optimization tools stems from the objective that improving the design of complex systems should not be achieved at the expense of a costly design methodology.

Role of medical, technical, and administrative leadership in the human resource management life cycle: a team approach to laboratory management.

PubMed

Wilkinson, D S; Dilts, T J

1999-01-01

We believe the team approach to laboratory management achieves the best outcomes. Laboratory management requires the integration of medical, technical, and administrative expertise to achieve optimal service, quality, and cost performance. Usually, a management team of two or more individuals must be assembled to achieve all of these critical leadership functions. The individual members of the management team must possess the requisite expertise in clinical medicine, laboratory science, technology management, and administration. They also must work together in a unified and collaborative manner, regardless of where individual team members appear on the organizational chart. The management team members share in executing the entire human resource management life cycle, creating the proper environment to maximize human performance. Above all, the management team provides visionary and credible leadership.

Development and Evaluation of a Sandia Cooler-based Refrigerator Condenser

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Terry A.; Kariya, Harumichi Arthur; Leick, Michael T.

This report describes the first design of a refrigerator condenser using the Sandia Cooler, i.e. air - bearing supported rotating heat - sink impeller. The project included ba seline performance testing of a residential refrigerator, analysis and design development of a Sandia Cooler condenser assembly including a spiral channel baseplate, and performance measurement and validation of this condenser system as incorporated into the residential refrigerator. Comparable performance was achieved in a 60% smaller volume package. The improved modeling parameters can now be used to guide more optimized designs and more accurately predict performance.

Direct Methods for Predicting Movement Biomechanics Based Upon Optimal Control Theory with Implementation in OpenSim.

PubMed

Porsa, Sina; Lin, Yi-Chung; Pandy, Marcus G

2016-08-01

The aim of this study was to compare the computational performances of two direct methods for solving large-scale, nonlinear, optimal control problems in human movement. Direct shooting and direct collocation were implemented on an 8-segment, 48-muscle model of the body (24 muscles on each side) to compute the optimal control solution for maximum-height jumping. Both algorithms were executed on a freely-available musculoskeletal modeling platform called OpenSim. Direct collocation converged to essentially the same optimal solution up to 249 times faster than direct shooting when the same initial guess was assumed (3.4 h of CPU time for direct collocation vs. 35.3 days for direct shooting). The model predictions were in good agreement with the time histories of joint angles, ground reaction forces and muscle activation patterns measured for subjects jumping to their maximum achievable heights. Both methods converged to essentially the same solution when started from the same initial guess, but computation time was sensitive to the initial guess assumed. Direct collocation demonstrates exceptional computational performance and is well suited to performing predictive simulations of movement using large-scale musculoskeletal models.

Study on key technologies of optimization of big data for thermal power plant performance

NASA Astrophysics Data System (ADS)

Mao, Mingyang; Xiao, Hong

2018-06-01

Thermal power generation accounts for 70% of China's power generation, the pollutants accounted for 40% of the same kind of emissions, thermal power efficiency optimization needs to monitor and understand the whole process of coal combustion and pollutant migration, power system performance data show explosive growth trend, The purpose is to study the integration of numerical simulation of big data technology, the development of thermal power plant efficiency data optimization platform and nitrogen oxide emission reduction system for the thermal power plant to improve efficiency, energy saving and emission reduction to provide reliable technical support. The method is big data technology represented by "multi-source heterogeneous data integration", "large data distributed storage" and "high-performance real-time and off-line computing", can greatly enhance the energy consumption capacity of thermal power plants and the level of intelligent decision-making, and then use the data mining algorithm to establish the boiler combustion mathematical model, mining power plant boiler efficiency data, combined with numerical simulation technology to find the boiler combustion and pollutant generation rules and combustion parameters of boiler combustion and pollutant generation Influence. The result is to optimize the boiler combustion parameters, which can achieve energy saving.

A Bandwidth-Optimized Multi-Core Architecture for Irregular Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

This paper presents an architecture template for next-generation high performance computing systems specifically targeted to irregular applications. We start our work by considering that future generation interconnection and memory bandwidth full-system numbers are expected to grow by a factor of 10. In order to keep up with such a communication capacity, while still resorting to fine-grained multithreading as the main way to tolerate unpredictable memory access latencies of irregular applications, we show how overall performance scaling can benefit from the multi-core paradigm. At the same time, we also show how such an architecture template must be coupled with specific techniquesmore » in order to optimize bandwidth utilization and achieve the maximum scalability. We propose a technique based on memory references aggregation, together with the related hardware implementation, as one of such optimization techniques. We explore the proposed architecture template by focusing on the Cray XMT architecture and, using a dedicated simulation infrastructure, validate the performance of our template with two typical irregular applications. Our experimental results prove the benefits provided by both the multi-core approach and the bandwidth optimization reference aggregation technique.« less

LDRD Report: Topological Design Optimization of Convolutes in Next Generation Pulsed Power Devices.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cyr, Eric C.; von Winckel, Gregory John; Kouri, Drew Philip

This LDRD project was developed around the ambitious goal of applying PDE-constrained opti- mization approaches to design Z-machine components whose performance is governed by elec- tromagnetic and plasma models. This report documents the results of this LDRD project. Our differentiating approach was to use topology optimization methods developed for structural design and extend them for application to electromagnetic systems pertinent to the Z-machine. To achieve this objective a suite of optimization algorithms were implemented in the ROL library part of the Trilinos framework. These methods were applied to standalone demonstration problems and the Drekar multi-physics research application. Out of thismore » exploration a new augmented Lagrangian approach to structural design problems was developed. We demonstrate that this approach has favorable mesh-independent performance. Both the final design and the algorithmic performance were independent of the size of the mesh. In addition, topology optimization formulations for the design of conducting networks were developed and demonstrated. Of note, this formulation was used to develop a design for the inner magnetically insulated transmission line on the Z-machine. The resulting electromagnetic device is compared with theoretically postulated designs.« less

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

Optimized universal color palette design for error diffusion

NASA Astrophysics Data System (ADS)

Kolpatzik, Bernd W.; Bouman, Charles A.

1995-04-01

Currently, many low-cost computers can only simultaneously display a palette of 256 color. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L*AL*B*, but also accounts for the lowpass characteristic of human contrast sensitivity.

Combined design of structures and controllers for optimal maneuverability

NASA Technical Reports Server (NTRS)

Ling, Jer; Kabamba, Pierre; Taylor, John

1990-01-01

Approaches to the combined design of structures and controllers for achieving optimal maneuverability are presented. A maneuverability index which directly reflects the minimum time required to perform a given set of maneuvers is introduced. By designing the flexible appendages, the maneuver time of the spacecraft is minimized under the constraints of structural properties, and post maneuver spillover is kept within a specified bound. The spillover reduction is achieved by making use of an appropriate reduced order model. The distributed parameter design problem is approached using assumed shape functions, and finite element analysis with dynamic reduction. Solution procedures have been investigated. Approximate design methods have been developed to overcome the computational difficulties. Some new constraints on the modal frequencies of the spacecraft are introduced in the original optimization problem to facilitate the solution process. It is shown that the global optimal design may be obtained by tuning the natural frequencies to satisfy specific constraints. Researchers quantify the difference between a lower bound to the solution for maneuver time associated with the original problem and the estimate obtained from the modified problem, for a specified application requirement. Numerical examples are presented to demonstrate the capability of this approach.

LAMMPS strong scaling performance optimization on Blue Gene/Q

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coffman, Paul; Jiang, Wei; Romero, Nichols A.

2014-11-12

LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using anmore » 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.« less

mdtmFTP and its evaluation on ESNET SDN testbed

DOE PAGES

Zhang, Liang; Wu, Wenji; DeMar, Phil; ...

2017-04-21

In this paper, to address the high-performance challenges of data transfer in the big data era, we are developing and implementing mdtmFTP: a high-performance data transfer tool for big data. mdtmFTP has four salient features. First, it adopts an I/O centric architecture to execute data transfer tasks. Second, it more efficiently utilizes the underlying multicore platform through optimized thread scheduling. Third, it implements a large virtual file mechanism to address the lots-of-small-files (LOSF) problem. In conclusion, mdtmFTP integrates multiple optimization mechanisms, including–zero copy, asynchronous I/O, pipelining, batch processing, and pre-allocated buffer pools–to enhance performance. mdtmFTP has been extensively tested andmore » evaluated within the ESNET 100G testbed. Evaluations show that mdtmFTP can achieve higher performance than existing data transfer tools, such as GridFTP, FDT, and BBCP.« less

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Physical and mechanical metallurgy of high purity Nb accelerator cavities.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wright, N. T.; Bieler, T. R.; Pourgoghart , F.

2010-01-01

In the past decade, high Q values have been achieved in high purity Nb superconducting radio frequency (SRF) cavities. Fundamental understanding of the physical metallurgy of Nb that enables these achievements is beginning to reveal what challenges remain to establish reproducible and cost-effective production of high performance SRF cavities. Recent studies of dislocation substructure development and effects of recrystallization arising from welding and heat treatments and their correlations with cavity performance are considered. With better fundamental understanding of the effects of dislocation substructure evolution and recrystallization on electron and phonon conduction, as well as the interior and surface states, itmore » will be possible to design optimal processing paths for cost-effective performance using approaches such as hydroforming, which minimizes or eliminates welds in a cavity.« less

Physical and mechanical metallurgy of high purity Nb for accelerator cavities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bieler, T. R.; Wright, N. T.; Pourboghrat, F.

2010-01-01

In the past decade, high Q values have been achieved in high purity Nb superconducting radio frequency (SRF) cavities. Fundamental understanding of the physical metallurgy of Nb that enables these achievements is beginning to reveal what challenges remain to establish reproducible and cost-effective production of high performance SRF cavities. Recent studies of dislocation substructure development and effects of recrystallization arising from welding and heat treatments and their correlations with cavity performance are considered. With better fundamental understanding of the effects of dislocation substructure evolution and recrystallization on electron and phonon conduction, as well as the interior and surface states, itmore » will be possible to design optimal processing paths for cost-effective performance using approaches such as hydroforming, which minimizes or eliminates welds in a cavity.« less

Design of pilot studies to inform the construction of composite outcome measures.

PubMed

Edland, Steven D; Ard, M Colin; Li, Weiwei; Jiang, Lingjing

2017-06-01

Composite scales have recently been proposed as outcome measures for clinical trials. For example, the Prodromal Alzheimer's Cognitive Composite (PACC) is the sum of z-score normed component measures assessing episodic memory, timed executive function, and global cognition. Alternative methods of calculating composite total scores using the weighted sum of the component measures that maximize signal-to-noise of the resulting composite score have been proposed. Optimal weights can be estimated from pilot data, but it is an open question how large a pilot trial is required to calculate reliably optimal weights. In this manuscript, we describe the calculation of optimal weights, and use large-scale computer simulations to investigate the question of how large a pilot study sample is required to inform the calculation of optimal weights. The simulations are informed by the pattern of decline observed in cognitively normal subjects enrolled in the Alzheimer's Disease Cooperative Study (ADCS) Prevention Instrument cohort study, restricting to n=75 subjects age 75 and over with an ApoE E4 risk allele and therefore likely to have an underlying Alzheimer neurodegenerative process. In the context of secondary prevention trials in Alzheimer's disease, and using the components of the PACC, we found that pilot studies as small as 100 are sufficient to meaningfully inform weighting parameters. Regardless of the pilot study sample size used to inform weights, the optimally weighted PACC consistently outperformed the standard PACC in terms of statistical power to detect treatment effects in a clinical trial. Pilot studies of size 300 produced weights that achieved near-optimal statistical power, and reduced required sample size relative to the standard PACC by more than half. These simulations suggest that modestly sized pilot studies, comparable to that of a phase 2 clinical trial, are sufficient to inform the construction of composite outcome measures. Although these findings apply only to the PACC in the context of prodromal AD, the observation that weights only have to approximate the optimal weights to achieve near-optimal performance should generalize. Performing a pilot study or phase 2 trial to inform the weighting of proposed composite outcome measures is highly cost-effective. The net effect of more efficient outcome measures is that smaller trials will be required to test novel treatments. Alternatively, second generation trials can use prior clinical trial data to inform weighting, so that greater efficiency can be achieved as we move forward.

Cognitive, Parent and Teacher Rating Measures of Executive Functioning: Shared and Unique Influences on School Achievement

PubMed Central

Dekker, Marielle C.; Ziermans, Tim B.; Spruijt, Andrea M.; Swaab, Hanna

2017-01-01

Very little is known about the relative influence of cognitive performance-based executive functioning (EF) measures and behavioral EF ratings in explaining differences in children's school achievement. This study examined the shared and unique influence of these different EF measures on math and spelling outcome for a sample of 84 first and second graders. Parents and teachers completed the Behavior Rating Inventory of Executive Function (BRIEF), and children were tested with computer-based performance tests from the Amsterdam Neuropsychological Tasks (ANT). Mixed-model hierarchical regression analyses, including intelligence level and age, showed that cognitive performance and teacher's ratings of working memory and shifting concurrently explained differences in spelling. However, teacher's behavioral EF ratings did not explain any additional variance in math outcome above cognitive EF performance. Parent's behavioral EF ratings did not add any unique information for either outcome measure. This study provides support for the ecological validity of performance- and teacher rating-based EF measures, and shows that both measures could have a complementary role in identifying EF processes underlying spelling achievement problems. The early identification of strengths and weaknesses of a child's working memory and shifting capabilities, might help teachers to broaden their range of remedial intervention options to optimize school achievement. PMID:28194121

Non-destructive determination of Malondialdehyde (MDA) distribution in oilseed rape leaves by laboratory scale NIR hyperspectral imaging

NASA Astrophysics Data System (ADS)

Kong, Wenwen; Liu, Fei; Zhang, Chu; Zhang, Jianfeng; Feng, Hailin

2016-10-01

The feasibility of hyperspectral imaging with 400-1000 nm was investigated to detect malondialdehyde (MDA) content in oilseed rape leaves under herbicide stress. After comparing the performance of different preprocessing methods, linear and nonlinear calibration models, the optimal prediction performance was achieved by extreme learning machine (ELM) model with only 23 wavelengths selected by competitive adaptive reweighted sampling (CARS), and the result was RP = 0.929 and RMSEP = 2.951. Furthermore, MDA distribution map was successfully achieved by partial least squares (PLS) model with CARS. This study indicated that hyperspectral imaging technology provided a fast and nondestructive solution for MDA content detection in plant leaves.

Optimization of spatiotemporally fractionated radiotherapy treatments with bounds on the achievable benefit

NASA Astrophysics Data System (ADS)

Gaddy, Melissa R.; Yıldız, Sercan; Unkelbach, Jan; Papp, Dávid

2018-01-01

Spatiotemporal fractionation schemes, that is, treatments delivering different dose distributions in different fractions, can potentially lower treatment side effects without compromising tumor control. This can be achieved by hypofractionating parts of the tumor while delivering approximately uniformly fractionated doses to the surrounding tissue. Plan optimization for such treatments is based on biologically effective dose (BED); however, this leads to computationally challenging nonconvex optimization problems. Optimization methods that are in current use yield only locally optimal solutions, and it has hitherto been unclear whether these plans are close to the global optimum. We present an optimization framework to compute rigorous bounds on the maximum achievable normal tissue BED reduction for spatiotemporal plans. The approach is demonstrated on liver tumors, where the primary goal is to reduce mean liver BED without compromising any other treatment objective. The BED-based treatment plan optimization problems are formulated as quadratically constrained quadratic programming (QCQP) problems. First, a conventional, uniformly fractionated reference plan is computed using convex optimization. Then, a second, nonconvex, QCQP model is solved to local optimality to compute a spatiotemporally fractionated plan that minimizes mean liver BED, subject to the constraints that the plan is no worse than the reference plan with respect to all other planning goals. Finally, we derive a convex relaxation of the second model in the form of a semidefinite programming problem, which provides a rigorous lower bound on the lowest achievable mean liver BED. The method is presented on five cases with distinct geometries. The computed spatiotemporal plans achieve 12-35% mean liver BED reduction over the optimal uniformly fractionated plans. This reduction corresponds to 79-97% of the gap between the mean liver BED of the uniform reference plans and our lower bounds on the lowest achievable mean liver BED. The results indicate that spatiotemporal treatments can achieve substantial reductions in normal tissue dose and BED, and that local optimization techniques provide high-quality plans that are close to realizing the maximum potential normal tissue dose reduction.

Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

PubMed

Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

2014-01-01

The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Team performance and collective efficacy in the dynamic psychology of competitive team: a Bayesian network analysis.

PubMed

Fuster-Parra, P; García-Mas, A; Ponseti, F J; Leo, F M

2015-04-01

The purpose of this paper was to discover the relationships among 22 relevant psychological features in semi-professional football players in order to study team's performance and collective efficacy via a Bayesian network (BN). The paper includes optimization of team's performance and collective efficacy using intercausal reasoning pattern which constitutes a very common pattern in human reasoning. The BN is used to make inferences regarding our problem, and therefore we obtain some conclusions; among them: maximizing the team's performance causes a decrease in collective efficacy and when team's performance achieves the minimum value it causes an increase in moderate/high values of collective efficacy. Similarly, we may reason optimizing team collective efficacy instead. It also allows us to determine the features that have the strongest influence on performance and which on collective efficacy. From the BN two different coaching styles were differentiated taking into account the local Markov property: training leadership and autocratic leadership. Copyright © 2014 Elsevier B.V. All rights reserved.

Fundamentals of Free-Space Optical Communications

NASA Technical Reports Server (NTRS)

Dolinar, Sam; Moision, Bruce; Erkmen, Baris

2012-01-01

Free-space optical communication systems potentially gain many dBs over RF systems. There is no upper limit on the theoretically achievable photon efficiency when the system is quantum-noise-limited: a) Intensity modulations plus photon counting can achieve arbitrarily high photon efficiency, but with sub-optimal spectral efficiency. b) Quantum-ideal number states can achieve the ultimate capacity in the limit of perfect transmissivity. Appropriate error correction codes are needed to communicate reliably near the capacity limits. Poisson-modeled noises, detector losses, and atmospheric effects must all be accounted for: a) Theoretical models are used to analyze performance degradations. b) Mitigation strategies derived from this analysis are applied to minimize these degradations.

Optimal port-based teleportation

NASA Astrophysics Data System (ADS)

Mozrzymas, Marek; Studziński, Michał; Strelchuk, Sergii; Horodecki, Michał

2018-05-01

Deterministic port-based teleportation (dPBT) protocol is a scheme where a quantum state is guaranteed to be transferred to another system without unitary correction. We characterise the best achievable performance of the dPBT when both the resource state and the measurement is optimised. Surprisingly, the best possible fidelity for an arbitrary number of ports and dimension of the teleported state is given by the largest eigenvalue of a particular matrix—Teleportation Matrix. It encodes the relationship between a certain set of Young diagrams and emerges as the optimal solution to the relevant semidefinite programme.

High-efficiency hybrid solar cells based on polymer/PbSx Se1-x nanocrystals benefiting from vertical phase segregation.

PubMed

Liu, Zeke; Sun, Yaxiang; Yuan, Jianyu; Wei, Huaixin; Huang, Xiaodong; Han, Lu; Wang, Weiwei; Wang, Haiqiao; Ma, Wanli

2013-10-25

Solution-processed hybrid solar cells employing a low band-gap polymer and PbSx Se1-x alloy nanocrystals, achieving a record high PCE of 5.50% and an optimal FF of 67% are presented. The remarkable device efficiency can be attributed to the high-performance active materials, the optimal polymer/NCs ratio and, more importantly, the vertical donor/(donor:acceptor)/acceptor structure which benefits charge dissociation and transport. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gradient-based adaptation of general gaussian kernels.

PubMed

Glasmachers, Tobias; Igel, Christian

2005-10-01

Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

Parametric optimization of the MVC desalination plant with thermomechanical compressor

NASA Astrophysics Data System (ADS)

Blagin, E. V.; Biryuk, V. V.; Anisimov, M. Y.; Shimanov, A. A.; Gorshkalev, A. A.

2018-03-01

This article deals with parametric optimization of the Mechanical Vapour Compression (MVC) desalination plant with thermomechanical compressor. In this plants thermocompressor is used instead of commonly used centrifugal compressor. Influence of two main parameters was studied. These parameters are: inlet pressure and number of stages. Analysis shows that it is possible to achieve better plant performance in comparison with traditional MVC plant. But is required reducing the number of stages and utilization of low or high initial pressure with power consumption maximum at approximately 20-30 kPa.

On optimization of energy harvesting from base-excited vibration

NASA Astrophysics Data System (ADS)

Tai, Wei-Che; Zuo, Lei

2017-12-01

This paper re-examines and clarifies the long-believed optimization conditions of electromagnetic and piezoelectric energy harvesting from base-excited vibration. In terms of electromagnetic energy harvesting, it is typically believed that the maximum power is achieved when the excitation frequency and electrical damping equal the natural frequency and mechanical damping of the mechanical system respectively. We will show that this optimization condition is only valid when the acceleration amplitude of base excitation is constant and an approximation for small mechanical damping when the excitation displacement amplitude is constant. To this end, a two-variable optimization analysis, involving the normalized excitation frequency and electrical damping ratio, is performed to derive the exact optimization condition of each case. When the excitation displacement amplitude is constant, we analytically show that, in contrast to the long-believed optimization condition, the optimal excitation frequency and electrical damping are always larger than the natural frequency and mechanical damping ratio respectively. In particular, when the mechanical damping ratio exceeds a critical value, the optimization condition is no longer valid. Instead, the average power generally increases as the excitation frequency and electrical damping ratio increase. Furthermore, the optimization analysis is extended to consider parasitic electrical losses, which also shows different results when compared with existing literature. When the excitation acceleration amplitude is constant, on the other hand, the exact optimization condition is identical to the long-believed one. In terms of piezoelectric energy harvesting, it is commonly believed that the optimal power efficiency is achieved when the excitation and the short or open circuit frequency of the harvester are equal. Via a similar two-variable optimization analysis, we analytically show that the optimal excitation frequency depends on the mechanical damping ratio and does not equal the short or open circuit frequency. Finally, the optimal excitation frequencies and resistive loads are derived in closed-form.

Hydraulic analysis and optimization design in Guri rehabilitation project

NASA Astrophysics Data System (ADS)

Cheng, H.; Zhou, L. J.; Gong, L.; Wang, Z. N.; Wen, Q.; Zhao, Y. Z.; Wang, Y. L.

2016-11-01

Recently Dongfang was awarded the contract for rehabilitation of 6 units in Guri power plant, the biggest hydro power project in Venezuela. The rehabilitation includes, but not limited to, the extension of output capacity by about 50% and enhancement of efficiency level. To achieve the targets the runner and the guide vanes will be replaced by the newly optimized designs. In addition, the out-of-date stay vanes with straight plate shape will be modified into proper profiles after considering the application feasibility in field. The runner and vane profiles were optimized by using state-of-the-art flow simulation techniques. And the hydraulic performances were confirmed by the following model tests. This paper describes the flow analysis during the optimization procedure and the comparison between various technical concepts.

Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design

NASA Astrophysics Data System (ADS)

Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro

2018-06-01

A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.

Optimal Solutions of Multiproduct Batch Chemical Process Using Multiobjective Genetic Algorithm with Expert Decision System

PubMed Central

Mokeddem, Diab; Khellaf, Abdelhafid

2009-01-01

Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to achieve fine tuning of variables in determining a set of non dominating solutions distributed along the Pareto front in a single run of the algorithm. The NSGA-II ability to identify a set of optimal solutions provides the decision-maker DM with a complete picture of the optimal solution space to gain better and appropriate choices. Then an outranking with PROMETHEE II helps the decision-maker to finalize the selection of a best compromise. The effectiveness of NSGA-II method with multiojective optimization problem is illustrated through two carefully referenced examples. PMID:19543537

Two Blades-Up Runs Using the JetStream Navitus Atherectomy Device Achieve Optimal Tissue Debulking of Nonocclusive In-Stent Restenosis: Observations From a Porcine Stent/Balloon Injury Model.

PubMed

Shammas, Nicolas W; Aasen, Nicole; Bailey, Lynn; Budrewicz, Jay; Farago, Trent; Jarvis, Gary

2015-08-01

To determine the number of runs with blades up (BU) using the JetStream Navitus to achieving optimal debulking in a porcine model of femoropopliteal artery in-stent restenosis (ISR). In this porcine model, 8 limbs were implanted with overlapping nitinol self-expanding stents. ISR was treated initially with 2 blades-down (BD) runs followed by 4 BU runs (BU1 to BU4). Quantitative vascular angiography (QVA) was performed at baseline, after 2 BD runs, and after each BU run. Plaque surface area and percent stenosis within the treated stented segment were measured. Intravascular ultrasound (IVUS) was used to measure minimum lumen area (MLA) and determine IVUS-derived plaque surface area. QVA showed that plaque surface area was significantly reduced between baseline (83.9%±14.8%) and 2 BD (67.7%±17.0%, p=0.005) and BU1 (55.4%±9.0%, p=0.005) runs, and between BU1 and BU2 runs (50.7%±9.7%, p<0.05). Percent stenosis behaved similarly with no further reduction after BU2. There were no further reductions in plaque surface area or percent stenosis with BU 3 and 4 runs (p=0.10). Similarly, IVUS (24 lesions) confirmed optimal results with BU2 runs and no additional gain in MLA or reduction in plaque surface area with BU3 and 4. IVUS confirmed no orbital cutting with JetStream Navitus. There were no stent strut discontinuities on high-resolution radiographs following atherectomy. JetStream Navitus achieved optimal tissue debulking after 2 BD and 2 BU runs with no further statistical gain in debulking after the BU2 run. Operators treating ISR with JetStream Navitus may be advised to limit their debulking to 2 BD and 2 BU runs to achieve optimal debulking. © The Author(s) 2015.

Dose-mass inverse optimization for minimally moving thoracic lesions

NASA Astrophysics Data System (ADS)

Mihaylov, I. B.; Moros, E. G.

2015-05-01

In the past decade, several different radiotherapy treatment plan evaluation and optimization schemes have been proposed as viable approaches, aiming for dose escalation or an increase of healthy tissue sparing. In particular, it has been argued that dose-mass plan evaluation and treatment plan optimization might be viable alternatives to the standard of care, which is realized through dose-volume evaluation and optimization. The purpose of this investigation is to apply dose-mass optimization to a cohort of lung cancer patients and compare the achievable healthy tissue sparing to that one achievable through dose-volume optimization. Fourteen non-small cell lung cancer (NSCLC) patient plans were studied retrospectively. The range of tumor motion was less than 0.5 cm and motion management in the treatment planning process was not considered. For each case, dose-volume (DV)-based and dose-mass (DM)-based optimization was performed. Nine-field step-and-shoot IMRT was used, with all of the optimization parameters kept the same between DV and DM optimizations. Commonly used dosimetric indices (DIs) such as dose to 1% the spinal cord volume, dose to 50% of the esophageal volume, and doses to 20 and 30% of healthy lung volumes were used for cross-comparison. Similarly, mass-based indices (MIs), such as doses to 20 and 30% of healthy lung masses, 1% of spinal cord mass, and 33% of heart mass, were also tallied. Statistical equivalence tests were performed to quantify the findings for the entire patient cohort. Both DV and DM plans for each case were normalized such that 95% of the planning target volume received the prescribed dose. DM optimization resulted in more organs at risk (OAR) sparing than DV optimization. The average sparing of cord, heart, and esophagus was 23, 4, and 6%, respectively. For the majority of the DIs, DM optimization resulted in lower lung doses. On average, the doses to 20 and 30% of healthy lung were lower by approximately 3 and 4%, whereas lung volumes receiving 2000 and 3000 cGy were lower by 3 and 2%, respectively. The behavior of MIs was very similar. The statistical analyses of the results again indicated better healthy anatomical structure sparing with DM optimization. The presented findings indicate that dose-mass-based optimization results in statistically significant OAR sparing as compared to dose-volume-based optimization for NSCLC. However, the sparing is case-dependent and it is not observed for all tallied dosimetric endpoints.

Ensemble engineering and statistical modeling for parameter calibration towards optimal design of microbial fuel cells

NASA Astrophysics Data System (ADS)

Sun, Hongyue; Luo, Shuai; Jin, Ran; He, Zhen

2017-07-01

Mathematical modeling is an important tool to investigate the performance of microbial fuel cell (MFC) towards its optimized design. To overcome the shortcoming of traditional MFC models, an ensemble model is developed through integrating both engineering model and statistical analytics for the extrapolation scenarios in this study. Such an ensemble model can reduce laboring effort in parameter calibration and require fewer measurement data to achieve comparable accuracy to traditional statistical model under both the normal and extreme operation regions. Based on different weight between current generation and organic removal efficiency, the ensemble model can give recommended input factor settings to achieve the best current generation and organic removal efficiency. The model predicts a set of optimal design factors for the present tubular MFCs including the anode flow rate of 3.47 mL min-1, organic concentration of 0.71 g L-1, and catholyte pumping flow rate of 14.74 mL min-1 to achieve the peak current at 39.2 mA. To maintain 100% organic removal efficiency, the anode flow rate and organic concentration should be controlled lower than 1.04 mL min-1 and 0.22 g L-1, respectively. The developed ensemble model can be potentially modified to model other types of MFCs or bioelectrochemical systems.

Self-tuning bistable parametric feedback oscillator: Near-optimal amplitude maximization without model information

NASA Astrophysics Data System (ADS)

Braun, David J.; Sutas, Andrius; Vijayakumar, Sethu

2017-01-01

Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.

Topology-optimization-based design method of flexures for mounting the primary mirror of a large-aperture space telescope.

PubMed

Hu, Rui; Liu, Shutian; Li, Quhao

2017-05-20

For the development of a large-aperture space telescope, one of the key techniques is the method for designing the flexures for mounting the primary mirror, as the flexures are the key components. In this paper, a topology-optimization-based method for designing flexures is presented. The structural performances of the mirror system under multiple load conditions, including static gravity and thermal loads, as well as the dynamic vibration, are considered. The mirror surface shape error caused by gravity and the thermal effect is treated as the objective function, and the first-order natural frequency of the mirror structural system is taken as the constraint. The pattern repetition constraint is added, which can ensure symmetrical material distribution. The topology optimization model for flexure design is established. The substructuring method is also used to condense the degrees of freedom (DOF) of all the nodes of the mirror system, except for the nodes that are linked to the mounting flexures, to reduce the computation effort during the optimization iteration process. A potential optimized configuration is achieved by solving the optimization model and post-processing. A detailed shape optimization is subsequently conducted to optimize its dimension parameters. Our optimization method deduces new mounting structures that significantly enhance the optical performance of the mirror system compared to the traditional methods, which only focus on the parameters of existing structures. Design results demonstrate the effectiveness of the proposed optimization method.

Enablers and barriers for women with gestational diabetes mellitus to achieve optimal glycaemic control - a qualitative study using the theoretical domains framework.

PubMed

Martis, Ruth; Brown, Julie; McAra-Couper, Judith; Crowther, Caroline A

2018-04-11

Glycaemic target recommendations vary widely between international professional organisations for women with gestational diabetes mellitus (GDM). Some studies have reported women's experiences of having GDM, but little is known how this relates to their glycaemic targets. The aim of this study was to identify enablers and barriers for women with GDM to achieve optimal glycaemic control. Women with GDM were recruited from two large, geographically different, hospitals in New Zealand to participate in a semi-structured interview to explore their views and experiences focusing on enablers and barriers to achieving optimal glycaemic control. Final thematic analysis was performed using the Theoretical Domains Framework. Sixty women participated in the study. Women reported a shift from their initial negative response to accepting their diagnosis but disliked the constant focus on numbers. Enablers and barriers were categorised into ten domains across the three study questions. Enablers included: the ability to attend group teaching sessions with family and hear from women who have had GDM; easy access to a diabetes dietitian with diet recommendations tailored to a woman's context including ethnic food and financial considerations; free capillary blood glucose (CBG) monitoring equipment, health shuttles to take women to appointments; child care when attending clinic appointments; and being taught CBG testing by a community pharmacist. Barriers included: lack of health information, teaching sessions, consultations, and food diaries in a woman's first language; long waiting times at clinic appointments; seeing a different health professional every clinic visit; inconsistent advice; no tailored physical activities assessments; not knowing where to access appropriate information on the internet; unsupportive partners, families, and workplaces; and unavailability of social media or support groups for women with GDM. Perceived judgement by others led some women only to share their GDM diagnosis with their partners. This created social isolation. Women with GDM report multiple enablers and barriers to achieving optimal glycaemic control. The findings of this study may assist health professionals and diabetes in pregnancy services to improve their care for women with GDM and support them to achieve optimal glycaemic control.

Infrared and visible image fusion based on visual saliency map and weighted least square optimization

NASA Astrophysics Data System (ADS)

Ma, Jinlei; Zhou, Zhiqiang; Wang, Bo; Zong, Hua

2017-05-01

The goal of infrared (IR) and visible image fusion is to produce a more informative image for human observation or some other computer vision tasks. In this paper, we propose a novel multi-scale fusion method based on visual saliency map (VSM) and weighted least square (WLS) optimization, aiming to overcome some common deficiencies of conventional methods. Firstly, we introduce a multi-scale decomposition (MSD) using the rolling guidance filter (RGF) and Gaussian filter to decompose input images into base and detail layers. Compared with conventional MSDs, this MSD can achieve the unique property of preserving the information of specific scales and reducing halos near edges. Secondly, we argue that the base layers obtained by most MSDs would contain a certain amount of residual low-frequency information, which is important for controlling the contrast and overall visual appearance of the fused image, and the conventional "averaging" fusion scheme is unable to achieve desired effects. To address this problem, an improved VSM-based technique is proposed to fuse the base layers. Lastly, a novel WLS optimization scheme is proposed to fuse the detail layers. This optimization aims to transfer more visual details and less irrelevant IR details or noise into the fused image. As a result, the fused image details would appear more naturally and be suitable for human visual perception. Experimental results demonstrate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

Distributed Wireless Power Transfer With Energy Feedback

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Zhang, Rui

2017-04-01

Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve an EB gain that scales with the number of ETs. However, the optimal design of EB waveforms requires accurate channel state information (CSI) at the ETs, which is challenging to obtain practically, especially in a distributed system with ETs at separate locations. In this paper, we study practical and efficient channel training methods to achieve optimal EB in a distributed WET system. We propose two protocols with and without centralized coordination, respectively, where distributed ETs either sequentially or in parallel adapt their transmit phases based on a low-complexity energy feedback from the ER. The energy feedback only depends on the received power level at the ER, where each feedback indicates one particular transmit phase that results in the maximum harvested power over a set of previously used phases. Simulation results show that the two proposed training protocols converge very fast in practical WET systems even with a large number of distributed ETs, while the protocol with sequential ET phase adaptation is also analytically shown to converge to the optimal EB design with perfect CSI by increasing the training time. Numerical results are also provided to evaluate the performance of the proposed distributed EB and training designs as compared to other benchmark schemes.

Detection of mitotic nuclei in breast histopathology images using localized ACM and Random Kitchen Sink based classifier.

PubMed

Beevi, K Sabeena; Nair, Madhu S; Bindu, G R

2016-08-01

The exact measure of mitotic nuclei is a crucial parameter in breast cancer grading and prognosis. This can be achieved by improving the mitotic detection accuracy by careful design of segmentation and classification techniques. In this paper, segmentation of nuclei from breast histopathology images are carried out by Localized Active Contour Model (LACM) utilizing bio-inspired optimization techniques in the detection stage, in order to handle diffused intensities present along object boundaries. Further, the application of a new optimal machine learning algorithm capable of classifying strong non-linear data such as Random Kitchen Sink (RKS), shows improved classification performance. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for MITOS-ATYPIA CONTEST 2014. The proposed framework achieved 95% recall, 98% precision and 96% F-score.

Designing with non-linear viscoelastic fluids

NASA Astrophysics Data System (ADS)

Schuh, Jonathon; Lee, Yong Hoon; Allison, James; Ewoldt, Randy

2017-11-01

Material design is typically limited to hard materials or simple fluids; however, design with more complex materials can provide ways to enhance performance. Using the Criminale-Ericksen-Filbey (CEF) constitutive model in the thin film lubrication limit, we derive a modified Reynolds Equation (based on asymptotic analysis) that includes shear thinning, first normal stress, and terminal regime viscoelastic effects. This allows for designing non-linear viscoelastic fluids in thin-film creeping flow scenarios, i.e. optimizing the shape of rheological material properties to achieve different design objectives. We solve the modified Reynolds equation using the pseudo-spectral method, and describe a case study in full-film lubricated sliding where optimal fluid properties are identified. These material-agnostic property targets can then guide formulation of complex fluids which may use polymeric, colloidal, or other creative approaches to achieve the desired non-Newtonian properties.

Optimized design of total energy systems: The RETE project

NASA Astrophysics Data System (ADS)

Alia, P.; Dallavalle, F.; Denard, C.; Sanson, F.; Veneziani, S.; Spagni, G.

1980-05-01

The RETE (Reggio Emilia Total Energy) project is discussed. The total energy system (TES) was developed to achieve the maximum quality matching on the thermal energy side between plant and user and perform an open scheme on the electrical energy side by connection with the Italian electrical network. The most significant qualitative considerations at the basis of the plant economic energy optimization and the selection of the operating criterion most fitting the user consumption characteristics and the external system constraints are reported. The design methodology described results in a TES that: in energy terms achieves a total efficiency evaluated on a yearly basis to be equal to about 78 percent and a fuel saving of about 28 percent and in economic terms allows a recovery of the investment required as to conventional solutions, in about seven years.

Open-loop-feedback control of serum drug concentrations: pharmacokinetic approaches to drug therapy.

PubMed

Jelliffe, R W

1983-01-01

Recent developments to optimize open-loop-feedback control of drug dosage regimens, generally applicable to pharmacokinetically oriented therapy with many drugs, involve computation of patient-individualized strategies for obtaining desired serum drug concentrations. Analyses of past therapy are performed by least squares, extended least squares, and maximum a posteriori probability Bayesian methods of fitting pharmacokinetic models to serum level data. Future possibilities for truly optimal open-loop-feedback therapy with full Bayesian methods, and conceivably for optimal closed-loop therapy in such data-poor clinical situations, are also discussed. Implementation of these various therapeutic strategies, using automated, locally controlled infusion devices, has also been achieved in prototype form.

Optimizing point-of-care testing in clinical systems management.

PubMed

Kost, G J

1998-01-01

The goal of improving medical and economic outcomes calls for leadership based on fundamental principles. The manager of clinical systems works collaboratively within the acute care center to optimize point-of-care testing through systematic approaches such as integrative strategies, algorithms, and performance maps. These approaches are effective and efficacious for critically ill patients. Optimizing point-of-care testing throughout the entire health-care system is inherently more difficult. There is potential to achieve high-quality testing, integrated disease management, and equitable health-care delivery. Despite rapid change and economic uncertainty, a macro-strategic, information-integrated, feedback-systems, outcomes-oriented approach is timely, challenging, effective, and uplifting to the creative human spirit.

Optimal Scheduling and Fair Service Policy for STDMA in Underwater Networks with Acoustic Communications

PubMed Central

2018-01-01

In this work, a multi-hop string network with a single sink node is analyzed. A periodic optimal scheduling for TDMA operation that considers the characteristic long propagation delay of the underwater acoustic channel is presented. This planning of transmissions is obtained with the help of a new geometrical method based on a 2D lattice in the space-time domain. In order to evaluate the performance of this optimal scheduling, two service policies have been compared: FIFO and Round-Robin. Simulation results, including achievable throughput, packet delay, and queue length, are shown. The network fairness has also been quantified with the Gini index. PMID:29462966

Stochastic simulation and robust design optimization of integrated photonic filters

NASA Astrophysics Data System (ADS)

Weng, Tsui-Wei; Melati, Daniele; Melloni, Andrea; Daniel, Luca

2017-01-01

Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic coupled ring resonator filters are considered as an example of significant interest. The sparsity structure in photonic circuits is exploited to construct a sparse combined generalized polynomial chaos model, which is then used to analyze related statistics and perform robust design optimization. Simulation results show that the optimized circuits are more robust to fabrication process variations and achieve a reduction of 11%-35% in the mean square errors of the 3 dB bandwidth compared to unoptimized nominal designs.

Study on Pyroelectric Harvesters with Various Geometry

PubMed Central

Siao, An-Shen; Chao, Ching-Kong; Hsiao, Chun-Ching

2015-01-01

Pyroelectric harvesters convert time-dependent temperature variations into electric current. The appropriate geometry of the pyroelectric cells, coupled with the optimal period of temperature fluctuations, is key to driving the optimal load resistance, which enhances the performance of pyroelectric harvesters. The induced charge increases when the thickness of the pyroelectric cells decreases. Moreover, the induced charge is extremely reduced for the thinner pyroelectric cell when not used for the optimal period. The maximum harvested power is achieved when a 100 μm-thick PZT (Lead zirconate titanate) cell is used to drive the optimal load resistance of about 40 MΩ. Moreover, the harvested power is greatly reduced when the working resistance diverges even slightly from the optimal load resistance. The stored voltage generated from the 75 μm-thick PZT cell is less than that from the 400 μm-thick PZT cell for a period longer than 64 s. Although the thinner PZT cell is advantageous in that it enhances the efficiency of the pyroelectric harvester, the much thinner 75 μm-thick PZT cell and the divergence from the optimal period further diminish the performance of the pyroelectric cell. Therefore, the designers of pyroelectric harvesters need to consider the coupling effect between the geometry of the pyroelectric cells and the optimal period of temperature fluctuations to drive the optimal load resistance. PMID:26270666

Adaptive infinite impulse response system identification using modified-interior search algorithm with Lèvy flight.

PubMed

Kumar, Manjeet; Rawat, Tarun Kumar; Aggarwal, Apoorva

2017-03-01

In this paper, a new meta-heuristic optimization technique, called interior search algorithm (ISA) with Lèvy flight is proposed and applied to determine the optimal parameters of an unknown infinite impulse response (IIR) system for the system identification problem. ISA is based on aesthetics, which is commonly used in interior design and decoration processes. In ISA, composition phase and mirror phase are applied for addressing the nonlinear and multimodal system identification problems. System identification using modified-ISA (M-ISA) based method involves faster convergence, single parameter tuning and does not require derivative information because it uses a stochastic random search using the concepts of Lèvy flight. A proper tuning of control parameter has been performed in order to achieve a balance between intensification and diversification phases. In order to evaluate the performance of the proposed method, mean square error (MSE), computation time and percentage improvement are considered as the performance measure. To validate the performance of M-ISA based method, simulations has been carried out for three benchmarked IIR systems using same order and reduced order system. Genetic algorithm (GA), particle swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search algorithm (CSA), differential evolution using wavelet mutation (DEWM), firefly algorithm (FFA), craziness based particle swarm optimization (CRPSO), harmony search (HS) algorithm, opposition based harmony search (OHS) algorithm, hybrid particle swarm optimization-gravitational search algorithm (HPSO-GSA) and ISA are also used to model the same examples and simulation results are compared. Obtained results confirm the efficiency of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Biomechanical and Psychological Analysis of High School, Intercollegiate, and Elite Long-Distance Runners

ERIC Educational Resources Information Center

Solorio, Claribel; Hickey, Ann

2015-01-01

It is undeniable that efficiency and mentality are crucial to achieving optimal athletic performance during competition. However, development of psychological skills is often neglected, particularly in lower levels of competition. The purpose of this study was to analyze and compare the biomechanical efficiency and psychological skills use among…

The High-Performance Mind: Mastering Brainwaves for Insight, Healing, and Creativity.

ERIC Educational Resources Information Center

Wise, Anna

This book aims to enlighten its readers on how to achieve optimal human efficiency, well-being, and balance through "brainwave training." According to the book, the 4 kinds of brainwaves--beta, alpha, theta, and delta--communicate with each other to pass information between conscious and unconscious mind. Mastering these brainwaves…

A closed-form solution to tensor voting: theory and applications.

PubMed

Wu, Tai-Pang; Yeung, Sai-Kit; Jia, Jiaya; Tang, Chi-Keung; Medioni, Gérard

2012-08-01

We prove a closed-form solution to tensor voting (CFTV): Given a point set in any dimensions, our closed-form solution provides an exact, continuous, and efficient algorithm for computing a structure-aware tensor that simultaneously achieves salient structure detection and outlier attenuation. Using CFTV, we prove the convergence of tensor voting on a Markov random field (MRF), thus termed as MRFTV, where the structure-aware tensor at each input site reaches a stationary state upon convergence in structure propagation. We then embed structure-aware tensor into expectation maximization (EM) for optimizing a single linear structure to achieve efficient and robust parameter estimation. Specifically, our EMTV algorithm optimizes both the tensor and fitting parameters and does not require random sampling consensus typically used in existing robust statistical techniques. We performed quantitative evaluation on its accuracy and robustness, showing that EMTV performs better than the original TV and other state-of-the-art techniques in fundamental matrix estimation for multiview stereo matching. The extensions of CFTV and EMTV for extracting multiple and nonlinear structures are underway.

Nonlinear Control of a Reusable Rocket Engine for Life Extension

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Holmes, Michael S.; Ray, Asok

1998-01-01

This paper presents the conceptual development of a life-extending control system where the objective is to achieve high performance and structural durability of the plant. A life-extending controller is designed for a reusable rocket engine via damage mitigation in both the fuel (H2) and oxidizer (O2) turbines while achieving high performance for transient responses of the combustion chamber pressure and the O2/H2 mixture ratio. The design procedure makes use of a combination of linear and nonlinear controller synthesis techniques and also allows adaptation of the life-extending controller module to augment a conventional performance controller of the rocket engine. The nonlinear aspect of the design is achieved using non-linear parameter optimization of a prescribed control structure. Fatigue damage in fuel and oxidizer turbine blades is primarily caused by stress cycling during start-up, shutdown, and transient operations of a rocket engine. Fatigue damage in the turbine blades is one of the most serious causes for engine failure.

Pushing the MAX IV 3 GeV storage ring brightness and coherence towards the limit of its magnetic lattice

NASA Astrophysics Data System (ADS)

Leemann, S. C.; Wurtz, W. A.

2018-03-01

The MAX IV 3 GeV storage ring is presently being commissioned and crucial parameters such as machine functions, emittance, and stored current have either already been reached or are approaching their design specifications. Once the baseline performance has been achieved, a campaign will be launched to further improve the brightness and coherence of this storage ring for typical X-ray users. During recent years, several such improvements have been designed. Common to these approaches is that they attempt to improve the storage ring performance using existing hardware provided for the baseline design. Such improvements therefore present more short-term upgrades. In this paper, however, we investigate medium-term improvements assuming power supplies can be exchanged in an attempt to push the brightness and coherence of the storage ring to the limit of what can be achieved without exchanging the magnetic lattice itself. We outline optics requirements, the optics optimization process, and summarize achievable parameters and expected performance.

The Motivation-Cognition Interface in Learning and Decision-Making.

PubMed

Maddox, W Todd; Markman, Arthur B

2010-04-01

In this article we discuss how incentive motivations and task demands affect performance. We present a three-factor framework that suggests that performance is determined from the interaction of global incentives, local incentives, and the psychological processes needed to achieve optimal task performance. We review work that examines the implications of the motivation-cognition interface in classification, choice and on phenomena such as stereotype threat and performance pressure. We show that under some conditions stereotype threat and pressure accentuate performance. We discuss the implications of this work for neuropsychological assessment, and outline a number of challenges for future research.

A perspective on future directions in aerospace propulsion system simulation

NASA Technical Reports Server (NTRS)

Miller, Brent A.; Szuch, John R.; Gaugler, Raymond E.; Wood, Jerry R.

1989-01-01

The design and development of aircraft engines is a lengthy and costly process using today's methodology. This is due, in large measure, to the fact that present methods rely heavily on experimental testing to verify the operability, performance, and structural integrity of components and systems. The potential exists for achieving significant speedups in the propulsion development process through increased use of computational techniques for simulation, analysis, and optimization. This paper outlines the concept and technology requirements for a Numerical Propulsion Simulation System (NPSS) that would provide capabilities to do interactive, multidisciplinary simulations of complete propulsion systems. By combining high performance computing hardware and software with state-of-the-art propulsion system models, the NPSS will permit the rapid calculation, assessment, and optimization of subcomponent, component, and system performance, durability, reliability and weight-before committing to building hardware.

Magnetic hyperthermia performance of magnetite nanoparticle assemblies under different driving fields

NASA Astrophysics Data System (ADS)

Wu, Kai; Wang, Jian-Ping

2017-05-01

The heating performance of magnetic nanoparticles (MNPs) under an alternating magnetic field (AMF) is dependent on several factors. Optimizing these factors improves the heating efficiency for cancer therapy and meanwhile lowers the MNP treatment dosage. AMF is one of the most easily controllable variables to enhance the efficiency of heat generation. This paper investigated the optimal magnetic field strength and frequency for an assembly of magnetite nanoparticles. For hyperthermia treatment in clinical applications, monodispersed NPs are forming nanoclusters in target regions where a strong magnetically interactive environment is anticipated, which leads to a completely different situation than MNPs in ferrofluids. Herein, the energy barrier model is revisited and Néel relaxation time is tailored for high MNP packing densities. AMF strength and frequency are customized for different magnetite NPs to achieve the highest power generation and the best hyperthermia performance.

Decision Fusion with Channel Errors in Distributed Decode-Then-Fuse Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Zhong, Xionghu

2015-01-01

Decision fusion for distributed detection in sensor networks under non-ideal channels is investigated in this paper. Usually, the local decisions are transmitted to the fusion center (FC) and decoded, and a fusion rule is then applied to achieve a global decision. We propose an optimal likelihood ratio test (LRT)-based fusion rule to take the uncertainty of the decoded binary data due to modulation, reception mode and communication channel into account. The average bit error rate (BER) is employed to characterize such an uncertainty. Further, the detection performance is analyzed under both non-identical and identical local detection performance indices. In addition, the performance of the proposed method is compared with the existing optimal and suboptimal LRT fusion rules. The results show that the proposed fusion rule is more robust compared to these existing ones. PMID:26251908

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Kuo -Ling; Mehrotra, Sanjay

We present a homogeneous algorithm equipped with a modified potential function for the monotone complementarity problem. We show that this potential function is reduced by at least a constant amount if a scaled Lipschitz condition (SLC) is satisfied. A practical algorithm based on this potential function is implemented in a software package named iOptimize. The implementation in iOptimize maintains global linear and polynomial time convergence properties, while achieving practical performance. It either successfully solves the problem, or concludes that the SLC is not satisfied. When compared with the mature software package MOSEK (barrier solver version 6.0.0.106), iOptimize solves convex quadraticmore » programming problems, convex quadratically constrained quadratic programming problems, and general convex programming problems in fewer iterations. Moreover, several problems for which MOSEK fails are solved to optimality. In addition, we also find that iOptimize detects infeasibility more reliably than the general nonlinear solvers Ipopt (version 3.9.2) and Knitro (version 8.0).« less

Optimization of Progressive Freeze Concentration on Apple Juice via Response Surface Methodology

NASA Astrophysics Data System (ADS)

Samsuri, S.; Amran, N. A.; Jusoh, M.

2018-05-01

In this work, a progressive freeze concentration (PFC) system was developed to concentrate apple juice and was optimized by response surface methodology (RSM). The effects of various operating conditions such as coolant temperature, circulation flowrate, circulation time and shaking speed to effective partition constant (K) were investigated. Five different level of central composite design (CCD) was employed to search for optimal concentration of concentrated apple juice. A full quadratic model for K was established by using method of least squares. A coefficient of determination (R2) of this model was found to be 0.7792. The optimum conditions were found to be coolant temperature = -10.59 °C, circulation flowrate = 3030.23 mL/min, circulation time = 67.35 minutes and shaking speed = 30.96 ohm. A validation experiment was performed to evaluate the accuracy of the optimization procedure and the best K value of 0.17 was achieved under the optimized conditions.

Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

2009-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

Fast globally optimal segmentation of 3D prostate MRI with axial symmetry prior.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

Enhanced index tracking modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin

2013-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Optimal Control Modification for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-05-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Experimental validation of 3D printed material behaviors and their influence on the structural topology design

NASA Astrophysics Data System (ADS)

Yang, Kai Ke; Zhu, Ji Hong; Wang, Chuang; Jia, Dong Sheng; Song, Long Long; Zhang, Wei Hong

2018-02-01

The purpose of this paper is to investigate the structures achieved by topology optimization and their fabrications by 3D printing considering the particular features of material microstructures and macro mechanical performances. Combining Digital Image Correlation and Optical Microscope, this paper experimentally explored the anisotropies of stiffness and strength existing in the 3D printed polymer material using Stereolithography (SLA) and titanium material using Selective Laser Melting (SLM). The standard specimens and typical structures obtained by topology optimization were fabricated along different building directions. On the one hand, the experimental results of these SLA produced structures showed stable properties and obviously anisotropic rules in stiffness, ultimate strengths and places of fractures. Further structural designs were performed using topology optimization when the particular mechanical behaviors of SLA printed materials were considered, which resulted in better structural performances compared to the optimized designs using `ideal' isotropic material model. On the other hand, this paper tested the mechanical behaviors of SLM printed multiscale lattice structures which were fabricated using the same metal powder and the same machine. The structural stiffness values are generally similar while the strength behaviors show a difference, which are mainly due to the irregular surface quality of the tiny structural branches of the lattice. The above evidences clearly show that the consideration of the particular behaviors of 3D printed materials is therefore indispensable for structural design and optimization in order to improve the structural performance and strengthen their practical significance.

Norm-Optimal ILC Applied to a High-Speed Rack Feeder

NASA Astrophysics Data System (ADS)

Schindele, Dominik; Aschemann, Harald; Ritzke, Jöran

2010-09-01

Rack feeders as automated conveying systems for high bay rackings are of high practical importance. To shorten the transport times by using trajectories with increased kinematic values accompanying control measures for a reduction of the excited structural vibrations are necessary. In this contribution, the model-based design of a norm-optimal iterative learning control structure is presented. The rack feeder is modelled as an elastic multibody system. For the mathematical description of the bending deflections a Ritz ansatz is introduced. The tracking control design is performed separately for both axes using decentralised state space representations. Both the achievable performance and the resulting tracking accuracy of the proposed control concept are shown by measurement results from the experimental set-up.

Numerical Modeling and Optimization of Warm-water Heat Sinks

NASA Astrophysics Data System (ADS)

Hadad, Yaser; Chiarot, Paul

2015-11-01

For cooling in large data-centers and supercomputers, water is increasingly replacing air as the working fluid in heat sinks. Utilizing water provides unique capabilities; for example: higher heat capacity, Prandtl number, and convection heat transfer coefficient. The use of warm, rather than chilled, water has the potential to provide increased energy efficiency. The geometric and operating parameters of the heat sink govern its performance. Numerical modeling is used to examine the influence of geometry and operating conditions on key metrics such as thermal and flow resistance. This model also facilitates studies on cooling of electronic chip hot spots and failure scenarios. We report on the optimal parameters for a warm-water heat sink to achieve maximum cooling performance.

Optimal control theory investigation of proprotor/wing response to vertical gust

NASA Technical Reports Server (NTRS)

Frick, J. K. D.; Johnson, W.

1974-01-01

Optimal control theory is used to design linear state variable feedback to improve the dynamic characteristics of a rotor and cantilever wing representing the tilting proprotor aircraft in cruise flight. The response to a vertical gust and system damping are used as criteria for the open and closed loop performance. The improvement in the dynamic characteristics achievable is examined for a gimballed rotor and for a hingeless rotor design. Several features of the design process are examined, including: (1) using only the wing or only the rotor dynamics in the control system design; (2) the use of a wing flap as well as the rotor controls for inputs; (3) and the performance of the system designed for one velocity at other forward speeds.

Administrator Leadership Styles and Their Impact on School Nursing Part II. A High-Performance School Nurse-Building Administrator Relationship Model.

PubMed

Davis, Charles R; Lynch, Erik J

2018-06-01

There is a significant disparity in roles, responsibilities, education, training, and expertise between the school nurse and building administrator. Because of this disparity, a natural chasm must be bridged to optimize student health, safety, well-being, and achievement in the classroom while meeting the individual needs of both professionals. This article constructs and presents a new school nurse-building administrator relationship model, the foundation of which is formed from the pioneering and seminal work on high-performance professional relationships and outcomes of Lewin and Drucker. The authors posit that this new model provides the framework for successful school nurse-building administrator interactions that will lead to optimal student outcomes.

DYNAMIC NEUROMUSCULAR STABILIZATION & SPORTS REHABILITATION

PubMed Central

Kobesova, Alena; Kolar, Pavel

2013-01-01

Dynamic neuromuscular (core) stability is necessary for optimal athletic performance and is not achieved purely by adequate strength of abdominals, spinal extensors, gluteals or any other musculature; rather, core stabilization is accomplished through precise coordination of these muscles and intra‐abdominal pressure regulation by the central nervous system. Understanding developmental kinesiology provides a framework to appreciate the regional interdependence and the inter‐linking of the skeleton, joints, musculature during movement and the importance of training both the dynamic and stabilizing function of muscles in the kinetic chain. The Dynamic Neuromuscular Stabilization (DNS) approach provides functional tools to assess and activate the intrinsic spinal stabilizers in order to optimize the movement system for both pre‐habilitation and rehabilitation of athletic injuries and performance. Level of Evidence: 5 PMID:23439921

Analysis of antimycin A by reversed-phase liquid chromatography/nuclear magnetic-resonance spectrometry

USGS Publications Warehouse

Ha, Steven T.K.; Wilkins, Charles L.; Abidi, Sharon L.

1989-01-01

A mixture of closely related streptomyces fermentation products, antimycin A, Is separated, and the components are identified by using reversed-phase high-performance liquid chromatography with directly linked 400-MHz proton nuclear magnetic resonance detection. Analyses of mixtures of three amino acids, alanine, glycine, and valine, are used to determine optimal measurement conditions. Sensitivity increases of as much as a factor of 3 are achieved, at the expense of some loss in chromatographic resolution, by use of an 80-μL NMR cell, Instead of a smaller 14-μL cell. Analysis of the antimycin A mixture, using the optimal analytical high performance liquid chromatography/nuclear magnetic resonance conditions, reveals it to consist of at least 10 closely related components.

Task-Driven Tube Current Modulation and Regularization Design in Computed Tomography with Penalized-Likelihood Reconstruction.

PubMed

Gang, G J; Siewerdsen, J H; Stayman, J W

2016-02-01

This work applies task-driven optimization to design CT tube current modulation and directional regularization in penalized-likelihood (PL) reconstruction. The relative performance of modulation schemes commonly adopted for filtered-backprojection (FBP) reconstruction were also evaluated for PL in comparison. We adopt a task-driven imaging framework that utilizes a patient-specific anatomical model and information of the imaging task to optimize imaging performance in terms of detectability index ( d' ). This framework leverages a theoretical model based on implicit function theorem and Fourier approximations to predict local spatial resolution and noise characteristics of PL reconstruction as a function of the imaging parameters to be optimized. Tube current modulation was parameterized as a linear combination of Gaussian basis functions, and regularization was based on the design of (directional) pairwise penalty weights for the 8 in-plane neighboring voxels. Detectability was optimized using a covariance matrix adaptation evolutionary strategy algorithm. Task-driven designs were compared to conventional tube current modulation strategies for a Gaussian detection task in an abdomen phantom. The task-driven design yielded the best performance, improving d' by ~20% over an unmodulated acquisition. Contrary to FBP, PL reconstruction using automatic exposure control and modulation based on minimum variance (in FBP) performed worse than the unmodulated case, decreasing d' by 16% and 9%, respectively. This work shows that conventional tube current modulation schemes suitable for FBP can be suboptimal for PL reconstruction. Thus, the proposed task-driven optimization provides additional opportunities for improved imaging performance and dose reduction beyond that achievable with conventional acquisition and reconstruction.

Progress towards an Optimization Methodology for Combustion-Driven Portable Thermoelectric Power Generation Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, Shankar; Karri, Naveen K.; Gogna, Pawan K.

2012-03-13

Enormous military and commercial interests exist in developing quiet, lightweight, and compact thermoelectric (TE) power generation systems. This paper investigates design integration and analysis of an advanced TE power generation system implementing JP-8 fueled combustion and thermal recuperation. Design and development of a portable TE power system using a JP-8 combustor as a high temperature heat source and optimal process flows depend on efficient heat generation, transfer, and recovery within the system are explored. Design optimization of the system required considering the combustion system efficiency and TE conversion efficiency simultaneously. The combustor performance and TE sub-system performance were coupled directlymore » through exhaust temperatures, fuel and air mass flow rates, heat exchanger performance, subsequent hot-side temperatures, and cold-side cooling techniques and temperatures. Systematic investigation of this system relied on accurate thermodynamic modeling of complex, high-temperature combustion processes concomitantly with detailed thermoelectric converter thermal/mechanical modeling. To this end, this work reports on design integration of systemlevel process flow simulations using commercial software CHEMCADTM with in-house thermoelectric converter and module optimization, and heat exchanger analyses using COMSOLTM software. High-performance, high-temperature TE materials and segmented TE element designs are incorporated in coupled design analyses to achieve predicted TE subsystem level conversion efficiencies exceeding 10%. These TE advances are integrated with a high performance microtechnology combustion reactor based on recent advances at the Pacific Northwest National Laboratory (PNNL). Predictions from this coupled simulation established a basis for optimal selection of fuel and air flow rates, thermoelectric module design and operating conditions, and microtechnology heat-exchanger design criteria. This paper will discuss this simulation process that leads directly to system efficiency power maps defining potentially available optimal system operating conditions and regimes. This coupled simulation approach enables pathways for integrated use of high-performance combustor components, high performance TE devices, and microtechnologies to produce a compact, lightweight, combustion driven TE power system prototype that operates on common fuels.« less

Optimization of a Lattice Boltzmann Computation on State-of-the-Art Multicore Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Samuel; Carter, Jonathan; Oliker, Leonid

2009-04-10

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to a lattice Boltzmann application (LBMHD) that historically has made poor use of scalar microprocessors due to its complex data structures and memory access patterns. We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon E5345 (Clovertown), AMD Opteron 2214 (Santa Rosa), AMD Opteron 2356 (Barcelona), Sun T5140 T2+ (Victoria Falls), as well asmore » a QS20 IBM Cell Blade. Rather than hand-tuning LBMHD for each system, we develop a code generator that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned LBMHD application achieves up to a 15x improvement compared with the original code at a given concurrency. Additionally, we present detailed analysis of each optimization, which reveal surprising hardware bottlenecks and software challenges for future multicore systems and applications.« less

Blue light hazard optimization for white light-emitting diode sources with high luminous efficacy of radiation and high color rendering index

NASA Astrophysics Data System (ADS)

Zhang, Jingjing; Guo, Weihong; Xie, Bin; Yu, Xingjian; Luo, Xiaobing; Zhang, Tao; Yu, Zhihua; Wang, Hong; Jin, Xing

2017-09-01

Blue light hazard of white light-emitting diodes (LED) is a hidden risk for human's photobiological safety. Recent spectral optimization methods focus on maximizing luminous efficacy and improving color performances of LEDs, but few of them take blue hazard into account. Therefore, for healthy lighting, it's urgent to propose a spectral optimization method for white LED source to exhibit low blue light hazard, high luminous efficacy of radiation (LER) and high color performances. In this study, a genetic algorithm with penalty functions was proposed for realizing white spectra with low blue hazard, maximal LER and high color rendering index (CRI) values. By simulations, white spectra from LEDs with low blue hazard, high LER (≥297 lm/W) and high CRI (≥90) were achieved at different correlated color temperatures (CCTs) from 2013 K to 7845 K. Thus, the spectral optimization method can be used for guiding the fabrication of LED sources in line with photobiological safety. It is also found that the maximum permissible exposure duration of the optimized spectra increases by 14.9% than that of bichromatic phosphor-converted LEDs with equal CCT.

Comparison of fan beam, slit-slat and multi-pinhole collimators for molecular breast tomosynthesis

NASA Astrophysics Data System (ADS)

van Roosmalen, Jarno; Beekman, Freek J.; Goorden, Marlies C.

2018-05-01

Recently, we proposed and optimized dedicated multi-pinhole molecular breast tomosynthesis (MBT) that images a lightly compressed breast. As MBT may also be performed with other types of collimators, the aim of this paper is to optimize MBT with fan beam and slit-slat collimators and to compare its performance to that of multi-pinhole MBT to arrive at a truly optimized design. Using analytical expressions, we first optimized fan beam and slit-slat collimator parameters to reach maximum sensitivity at a series of given system resolutions. Additionally, we performed full system simulations of a breast phantom containing several tumours for the optimized designs. We found that at equal system resolution the maximum achievable sensitivity increases from pinhole to slit-slat to fan beam collimation with fan beam and slit-slat MBT having on average a 48% and 20% higher sensitivity than multi-pinhole MBT. Furthermore, by inspecting simulated images and applying a tumour-to-background contrast-to-noise (TB-CNR) analysis, we found that slit-slat collimators underperform with respect to the other collimator types. The fan beam collimators obtained a similar TB-CNR as the pinhole collimators, but the optimum was reached at different system resolutions. For fan beam collimators, a 6–8 mm system resolution was optimal in terms of TB-CNR, while with pinhole collimation highest TB-CNR was reached in the 7–10 mm range.

Saturation pulse design for quantitative myocardial T1 mapping.

PubMed

Chow, Kelvin; Kellman, Peter; Spottiswoode, Bruce S; Nielles-Vallespin, Sonia; Arai, Andrew E; Salerno, Michael; Thompson, Richard B

2015-10-01

Quantitative saturation-recovery based T1 mapping sequences are less sensitive to systematic errors than the Modified Look-Locker Inversion recovery (MOLLI) technique but require high performance saturation pulses. We propose to optimize adiabatic and pulse train saturation pulses for quantitative T1 mapping to have <1 % absolute residual longitudinal magnetization (|MZ/M0|) over ranges of B0 and [Formula: see text] (B1 scale factor) inhomogeneity found at 1.5 T and 3 T. Design parameters for an adiabatic BIR4-90 pulse were optimized for improved performance within 1.5 T B0 (±120 Hz) and [Formula: see text] (0.7-1.0) ranges. Flip angles in hard pulse trains of 3-6 pulses were optimized for 1.5 T and 3 T, with consideration of T1 values, field inhomogeneities (B0 = ±240 Hz and [Formula: see text]=0.4-1.2 at 3 T), and maximum achievable B1 field strength. Residual MZ/M0 was simulated and measured experimentally for current standard and optimized saturation pulses in phantoms and in-vivo human studies. T1 maps were acquired at 3 T in human subjects and a swine using a SAturation recovery single-SHot Acquisition (SASHA) technique with a standard 90°-90°-90° and an optimized 6-pulse train. Measured residual MZ/M0 in phantoms had excellent agreement with simulations over a wide range of B0 and [Formula: see text]. The optimized BIR4-90 reduced the maximum residual |MZ/M0| to <1 %, a 5.8× reduction compared to a reference BIR4-90. An optimized 3-pulse train achieved a maximum residual |MZ/M0| <1 % for the 1.5 T optimization range compared to 11.3 % for a standard 90°-90°-90° pulse train, while a 6-pulse train met this target for the wider 3 T ranges of B0 and [Formula: see text]. The 6-pulse train demonstrated more uniform saturation across both the myocardium and entire field of view than other saturation pulses in human studies. T1 maps were more spatially homogeneous with 6-pulse train SASHA than the reference 90°-90°-90° SASHA in both human and animal studies. Adiabatic and pulse train saturation pulses optimized for different constraints found at 1.5 T and 3 T achieved <1 % residual |MZ/M0| in phantom experiments, enabling greater accuracy in quantitative saturation recovery T1 imaging.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, C.

Almost every computer architect dreams of achieving high system performance with low implementation costs. A multigauge machine can reconfigure its data-path width, provide parallelism, achieve better resource utilization, and sometimes can trade computational precision for increased speed. A simple experimental method is used here to capture the main characteristics of multigauging. The measurements indicate evidence of near-optimal speedups. Adapting these ideas in designing parallel processors incurs low costs and provides flexibility. Several operational aspects of designing a multigauge machine are discussed as well. Thus, this research reports the technical, economical, and operational feasibility studies of multigauging.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the first two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-X510 network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Optimal Signal Processing of Frequency-Stepped CW Radar Data

NASA Technical Reports Server (NTRS)

Ybarra, Gary A.; Wu, Shawkang M.; Bilbro, Griff L.; Ardalan, Sasan H.; Hearn, Chase P.; Neece, Robert T.

1995-01-01

An optimal signal processing algorithm is derived for estimating the time delay and amplitude of each scatterer reflection using a frequency-stepped CW system. The channel is assumed to be composed of abrupt changes in the reflection coefficient profile. The optimization technique is intended to maximize the target range resolution achievable from any set of frequency-stepped CW radar measurements made in such an environment. The algorithm is composed of an iterative two-step procedure. First, the amplitudes of the echoes are optimized by solving an overdetermined least squares set of equations. Then, a nonlinear objective function is scanned in an organized fashion to find its global minimum. The result is a set of echo strengths and time delay estimates. Although this paper addresses the specific problem of resolving the time delay between the two echoes, the derivation is general in the number of echoes. Performance of the optimization approach is illustrated using measured data obtained from an HP-851O network analyzer. It is demonstrated that the optimization approach offers a significant resolution enhancement over the standard processing approach that employs an IFFT. Degradation in the performance of the algorithm due to suboptimal model order selection and the effects of additive white Gaussion noise are addressed.

Optimizing the Entrainment Geometry of a Dry Powder Inhaler: Methodology and Preliminary Results.

PubMed

Kopsch, Thomas; Murnane, Darragh; Symons, Digby

2016-11-01

For passive dry powder inhalers (DPIs) entrainment and emission of the aerosolized drug dose depends strongly on device geometry and the patient's inhalation manoeuvre. We propose a computational method for optimizing the entrainment part of a DPI. The approach assumes that the pulmonary delivery location of aerosol can be determined by the timing of dose emission into the tidal airstream. An optimization algorithm was used to iteratively perform computational fluid dynamic (CFD) simulations of the drug emission of a DPI. The algorithm seeks to improve performance by changing the device geometry. Objectives were to achieve drug emission that was: A) independent of inhalation manoeuvre; B) similar to a target profile. The simulations used complete inhalation flow-rate profiles generated dependent on the device resistance. The CFD solver was OpenFOAM with drug/air flow simulated by the Eulerian-Eulerian method. To demonstrate the method, a 2D geometry was optimized for inhalation independence (comparing two breath profiles) and an early-bolus delivery. Entrainment was both shear-driven and gas-assisted. Optimization for a delay in the bolus delivery was not possible with the chosen geometry. Computational optimization of a DPI geometry for most similar drug delivery has been accomplished for an example entrainment geometry.

50% duty cycle may be inappropriate to achieve a sufficient chest compression depth when cardiopulmonary resuscitation is performed by female or light rescuers.

PubMed

Lee, Chang Jae; Chung, Tae Nyoung; Bae, Jinkun; Kim, Eui Chung; Choi, Sung Wook; Kim, Ok Jun

2015-03-01

Current guidelines for cardiopulmonary resuscitation recommend chest compressions (CC) during 50% of the duty cycle (DC) in part because of the ease with which individuals may learn to achieve it with practice. However, no consideration has been given to a possible interaction between DC and depth of CC, which has been the subject of recent study. Our aim was to determine if 50% DC is inappropriate to achieve sufficient chest compression depth for female and light rescuers. Previously collected CC data, performed by senior medical students guided by metronome sounds with various down-stroke patterns and rates, were included in the analysis. Multiple linear regression analysis was performed to determine the association between average compression depth (ACD) with average compression rate (ACR), DC, and physical characteristics of the performers. Expected ACD was calculated for various settings. DC, ACR, body weight, male sex, and self-assessed physical strength were significantly associated with ACD in multivariate analysis. Based on our calculations, with 50% of DC, only men with ACR of 140/min or faster or body weight over 74 kg with ACR of 120/min can achieve sufficient ACD. A shorter DC is independently correlated with deeper CC during simulated cardiopulmonary resuscitation. The optimal DC recommended in current guidelines may be inappropriate for achieving sufficient CD, especially for female or lighter-weight rescuers.

New Optimizations of Microcalorimeter Arrays for High-Resolution Imaging X-ray Spectroscopy

NASA Astrophysics Data System (ADS)

Kilbourne, Caroline

We propose to continue our successful research program in developing arrays of superconducting transition-edge sensors (TES) for x-ray astrophysics. Our standard 0.3 mm TES pixel achieves better than 2.5-eV resolution, and we now make 32x32 arrays of such pixels. We have also achieved better than 1-eV resolution in smaller pixels, and promising performance in a range of position-sensitive designs. We propose to continue to advance the designs of both the single-pixel and position-sensitive microcalorimeters so that we can produce arrays suitable for several x-ray spectroscopy observatories presently in formulation. We will also investigate various array and pixel optimizations such as would be needed for large arrays for surveys, large- pixel arrays for diffuse soft x-ray measurements, or sub-arrays of fast pixels optimized for neutron-star burst spectroscopy. In addition, we will develop fabrication processes for integrating sub-arrays with very different pixel designs into a monolithic focal-plane array to simplify the design of the focal-plane assembly and make feasible new detector configurations such as the one currently baselined for AXSIO. Through a series of measurements on test devices, we have improved our understanding of the weak-link physics governing the observed resistive transitions in TES detectors. We propose to build on that work and ultimately use the results to improve the immunity of the detector to environmental magnetic fields, as well as its fundamental performance, in each of the targeted optimizations we are developing.

Scout: high-performance heterogeneous computing made simple

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jablin, James; Mc Cormick, Patrick; Herlihy, Maurice

2011-01-26

Researchers must often write their own simulation and analysis software. During this process they simultaneously confront both computational and scientific problems. Current strategies for aiding the generation of performance-oriented programs do not abstract the software development from the science. Furthermore, the problem is becoming increasingly complex and pressing with the continued development of many-core and heterogeneous (CPU-GPU) architectures. To acbieve high performance, scientists must expertly navigate both software and hardware. Co-design between computer scientists and research scientists can alleviate but not solve this problem. The science community requires better tools for developing, optimizing, and future-proofing codes, allowing scientists to focusmore » on their research while still achieving high computational performance. Scout is a parallel programming language and extensible compiler framework targeting heterogeneous architectures. It provides the abstraction required to buffer scientists from the constantly-shifting details of hardware while still realizing higb-performance by encapsulating software and hardware optimization within a compiler framework.« less

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Constraining neutron guide optimizations with phase-space considerations

NASA Astrophysics Data System (ADS)

Bertelsen, Mads; Lefmann, Kim

2016-09-01

We introduce a method named the Minimalist Principle that serves to reduce the parameter space for neutron guide optimization when the required beam divergence is limited. The reduced parameter space will restrict the optimization to guides with a minimal neutron intake that are still theoretically able to deliver the maximal possible performance. The geometrical constraints are derived using phase-space propagation from moderator to guide and from guide to sample, while assuming that the optimized guides will achieve perfect transport of the limited neutron intake. Guide systems optimized using these constraints are shown to provide performance close to guides optimized without any constraints, however the divergence received at the sample is limited to the desired interval, even when the neutron transport is not limited by the supermirrors used in the guide. As the constraints strongly limit the parameter space for the optimizer, two control parameters are introduced that can be used to adjust the selected subspace, effectively balancing between maximizing neutron transport and avoiding background from unnecessary neutrons. One parameter is needed to describe the expected focusing abilities of the guide to be optimized, going from perfectly focusing to no correlation between position and velocity. The second parameter controls neutron intake into the guide, so that one can select exactly how aggressively the background should be limited. We show examples of guides optimized using these constraints which demonstrates the higher signal to noise than conventional optimizations. Furthermore the parameter controlling neutron intake is explored which shows that the simulated optimal neutron intake is close to the analytically predicted, when assuming that the guide is dominated by multiple scattering events.

Analysis and design of a 3rd order velocity-controlled closed-loop for MEMS vibratory gyroscopes.

PubMed

Wu, Huan-ming; Yang, Hai-gang; Yin, Tao; Jiao, Ji-wei

2013-09-18

The time-average method currently available is limited to analyzing the specific performance of the automatic gain control-proportional and integral (AGC-PI) based velocity-controlled closed-loop in a micro-electro-mechanical systems (MEMS) vibratory gyroscope, since it is hard to solve nonlinear functions in the time domain when the control loop reaches to 3rd order. In this paper, we propose a linearization design approach to overcome this limitation by establishing a 3rd order linear model of the control loop and transferring the analysis to the frequency domain. Order reduction is applied on the built linear model's transfer function by constructing a zero-pole doublet, and therefore mathematical expression of each control loop's performance specification is obtained. Then an optimization methodology is summarized, which reveals that a robust, stable and swift control loop can be achieved by carefully selecting the system parameters following a priority order. Closed-loop drive circuits are designed and implemented using 0.35 μm complementary metal oxide semiconductor (CMOS) process, and experiments carried out on a gyroscope prototype verify the optimization methodology that an optimized stability of the control loop can be achieved by constructing the zero-pole doublet, and disturbance rejection capability (D.R.C) of the control loop can be improved by increasing the integral term.

Hybrid feedforward and feedback controller design for nuclear steam generators over wide range operation using genetic algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Y.; Edwards, R.M.; Lee, K.Y.

1997-03-01

In this paper, a simplified model with a lower order is first developed for a nuclear steam generator system and verified against some realistic environments. Based on this simplified model, a hybrid multi-input and multi-out (MIMO) control system, consisting of feedforward control (FFC) and feedback control (FBC), is designed for wide range conditions by using the genetic algorithm (GA) technique. The FFC control, obtained by the GA optimization method, injects an a priori command input into the system to achieve an optimal performance for the designed system, while the GA-based FBC control provides the necessary compensation for any disturbances ormore » uncertainties in a real steam generator. The FBC control is an optimal design of a PI-based control system which would be more acceptable for industrial practices and power plant control system upgrades. The designed hybrid MIMO FFC/FBC control system is first applied to the simplified model and then to a more complicated model with a higher order which is used as a substitute of the real system to test the efficacy of the designed control system. Results from computer simulations show that the designed GA-based hybrid MIMO FFC/FBC control can achieve good responses and robust performances. Hence, it can be considered as a viable alternative to the current control system upgrade.« less

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

Bringing High-Rate, CO2-Based Microbial Electrosynthesis Closer to Practical Implementation through Improved Electrode Design and Operating Conditions.

PubMed

Jourdin, Ludovic; Freguia, Stefano; Flexer, Victoria; Keller, Jurg

2016-02-16

The enhancement of microbial electrosynthesis (MES) of acetate from CO2 to performance levels that could potentially support practical implementations of the technology must go through the optimization of key design and operating conditions. We report that higher proton availability drastically increases the acetate production rate, with pH 5.2 found to be optimal, which will likely suppress methanogenic activity without inhibitor addition. Applied cathode potential as low as -1.1 V versus SHE still achieved 99% of electron recovery in the form of acetate at a current density of around -200 A m(-2). These current densities are leading to an exceptional acetate production rate of up to 1330 g m(-2) day(-1) at pH 6.7. Using highly open macroporous reticulated vitreous carbon electrodes with macropore sizes of about 0.6 mm in diameter was found to be optimal for achieving a good balance between total surface area available for biofilm formation and effective mass transfer between the bulk liquid and the electrode and biofilm surface. Furthermore, we also successfully demonstrated the use of a synthetic biogas mixture as carbon dioxide source, yielding similarly high MES performance as pure CO2. This would allow this process to be used effectively for both biogas quality improvement and conversion of the available CO2 to acetate.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

Elimination of Bimodal Size in InAs/GaAs Quantum Dots for Preparation of 1.3-μm Quantum Dot Lasers

NASA Astrophysics Data System (ADS)

Su, Xiang-Bin; Ding, Ying; Ma, Ben; Zhang, Ke-Lu; Chen, Ze-Sheng; Li, Jing-Lun; Cui, Xiao-Ran; Xu, Ying-Qiang; Ni, Hai-Qiao; Niu, Zhi-Chuan

2018-02-01

The device characteristics of semiconductor quantum dot lasers have been improved with progress in active layer structures. Self-assembly formed InAs quantum dots grown on GaAs had been intensively promoted in order to achieve quantum dot lasers with superior device performances. In the process of growing high-density InAs/GaAs quantum dots, bimodal size occurs due to large mismatch and other factors. The bimodal size in the InAs/GaAs quantum dot system is eliminated by the method of high-temperature annealing and optimized the in situ annealing temperature. The annealing temperature is taken as the key optimization parameters, and the optimal annealing temperature of 680 °C was obtained. In this process, quantum dot growth temperature, InAs deposition, and arsenic (As) pressure are optimized to improve quantum dot quality and emission wavelength. A 1.3-μm high-performance F-P quantum dot laser with a threshold current density of 110 A/cm2 was demonstrated.

Engine performance analysis and optimization of a dual-mode scramjet with varied inlet conditions

NASA Astrophysics Data System (ADS)

Tian, Lu; Chen, Li-Hong; Chen, Qiang; Zhong, Feng-Quan; Chang, Xin-Yu

2016-02-01

A dual-mode scramjet can operate in a wide range of flight conditions. Higher thrust can be generated by adopting suitable combustion modes. Based on the net thrust, an analysis and preliminary optimal design of a kerosene-fueled parameterized dual-mode scramjet at a crucial flight Mach number of 6 were investigated by using a modified quasi-one-dimensional method and simulated annealing strategy. Engine structure and heat release distributions, affecting the engine thrust, were chosen as analytical parameters for varied inlet conditions (isolator entrance Mach number: 1.5-3.5). Results show that different optimal heat release distributions and structural conditions can be obtained at five different inlet conditions. The highest net thrust of the parameterized dual-mode engine can be achieved by a subsonic combustion mode at an isolator entrance Mach number of 2.5. Additionally, the effects of heat release and scramjet structure on net thrust have been discussed. The present results and the developed analytical method can provide guidance for the design and optimization of high-performance dual-mode scramjets.

Elimination of Bimodal Size in InAs/GaAs Quantum Dots for Preparation of 1.3-μm Quantum Dot Lasers.

PubMed

Su, Xiang-Bin; Ding, Ying; Ma, Ben; Zhang, Ke-Lu; Chen, Ze-Sheng; Li, Jing-Lun; Cui, Xiao-Ran; Xu, Ying-Qiang; Ni, Hai-Qiao; Niu, Zhi-Chuan

2018-02-21

The device characteristics of semiconductor quantum dot lasers have been improved with progress in active layer structures. Self-assembly formed InAs quantum dots grown on GaAs had been intensively promoted in order to achieve quantum dot lasers with superior device performances. In the process of growing high-density InAs/GaAs quantum dots, bimodal size occurs due to large mismatch and other factors. The bimodal size in the InAs/GaAs quantum dot system is eliminated by the method of high-temperature annealing and optimized the in situ annealing temperature. The annealing temperature is taken as the key optimization parameters, and the optimal annealing temperature of 680 °C was obtained. In this process, quantum dot growth temperature, InAs deposition, and arsenic (As) pressure are optimized to improve quantum dot quality and emission wavelength. A 1.3-μm high-performance F-P quantum dot laser with a threshold current density of 110 A/cm 2 was demonstrated.

Holistic, model-based optimization of edge leveling as an enabler for lithographic focus control: application to a memory use case

NASA Astrophysics Data System (ADS)

Hasan, T.; Kang, Y.-S.; Kim, Y.-J.; Park, S.-J.; Jang, S.-Y.; Hu, K.-Y.; Koop, E. J.; Hinnen, P. C.; Voncken, M. M. A. J.

2016-03-01

Advancement of the next generation technology nodes and emerging memory devices demand tighter lithographic focus control. Although the leveling performance of the latest-generation scanners is state of the art, challenges remain at the wafer edge due to large process variations. There are several customer configurable leveling control options available in ASML scanners, some of which are application specific in their scope of leveling improvement. In this paper, we assess the usability of leveling non-correctable error models to identify yield limiting edge dies. We introduce a novel dies-inspec based holistic methodology for leveling optimization to guide tool users in selecting an optimal configuration of leveling options. Significant focus gain, and consequently yield gain, can be achieved with this integrated approach. The Samsung site in Hwaseong observed an improved edge focus performance in a production of a mid-end memory product layer running on an ASML NXT 1960 system. 50% improvement in focus and a 1.5%p gain in edge yield were measured with the optimized configurations.

Fabrication and Optimization of Stable, Optically Transparent, and Reusable pH-Responsive Silk Membranes

PubMed Central

Toytziaridis, Andreas; Dicko, Cedric

2016-01-01

The fabrication of silk-based membranes that are stable, optically transparent and reusable is yet to be achieved. To address this bottleneck we have developed a method to produce transparent chromogenic silk patches that are optically responsive to pH. The patches were produced by blending regenerated silk fibroin (RSF), Laponite RD (nano clay) and the organic dyes neutral red and Thionine acetate. The Laponite RD played a central role in the patch mechanical integrity and prevention of dye leaching. The process was optimized using a factorial design to maximize the patch response to pH by UV absorbance and fluorescence emission. New patches of the optimized protocol, made from solutions containing 125 μM neutral red or 250 μM of Thionine and 15 mg/mL silk, were further tested for operational stability over several cycles of pH altering. Stability, performance, and reusability were achieved over the tested cycles. The approach could be extended to other reporting molecules or enzymes able to bind to Laponite. PMID:27854303

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

PubMed Central

Xu, Gaochao; Hu, Liang; Fu, Xiaodong

2013-01-01

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful. PMID:24385877

A novel artificial bee colony approach of live virtual machine migration policy using Bayes theorem.

PubMed

Xu, Gaochao; Ding, Yan; Zhao, Jia; Hu, Liang; Fu, Xiaodong

2013-01-01

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.

Ridge filter design and optimization for the broad-beam three-dimensional irradiation system for heavy-ion radiotherapy.

PubMed

Schaffner, B; Kanai, T; Futami, Y; Shimbo, M; Urakabe, E

2000-04-01

The broad-beam three-dimensional irradiation system under development at National Institute of Radiological Sciences (NIRS) requires a small ridge filter to spread the initially monoenergetic heavy-ion beam to a small spread-out Bragg peak (SOBP). A large SOBP covering the target volume is then achieved by a superposition of differently weighted and displaced small SOBPs. Two approaches were studied for the definition of a suitable ridge filter and experimental verifications were performed. Both approaches show a good agreement between the calculated and measured dose and lead to a good homogeneity of the biological dose in the target. However, the ridge filter design that produces a Gaussian-shaped spectrum of the particle ranges was found to be more robust to small errors and uncertainties in the beam application. Furthermore, an optimization procedure for two fields was applied to compensate for the missing dose from the fragmentation tail for the case of a simple-geometry target. The optimized biological dose distributions show that a very good homogeneity is achievable in the target.

Agreement Technologies for Energy Optimization at Home

PubMed Central

2018-01-01

Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%. PMID:29783768

Modelling and multi-parametric control for delivery of anaesthetic agents.

PubMed

Dua, Pinky; Dua, Vivek; Pistikopoulos, Efstratios N

2010-06-01

This article presents model predictive controllers (MPCs) and multi-parametric model-based controllers for delivery of anaesthetic agents. The MPC can take into account constraints on drug delivery rates and state of the patient but requires solving an optimization problem at regular time intervals. The multi-parametric controller has all the advantages of the MPC and does not require repetitive solution of optimization problem for its implementation. This is achieved by obtaining the optimal drug delivery rates as a set of explicit functions of the state of the patient. The derivation of the controllers relies on using detailed models of the system. A compartmental model for the delivery of three drugs for anaesthesia is developed. The key feature of this model is that mean arterial pressure, cardiac output and unconsciousness of the patient can be simultaneously regulated. This is achieved by using three drugs: dopamine (DP), sodium nitroprusside (SNP) and isoflurane. A number of dynamic simulation experiments are carried out for the validation of the model. The model is then used for the design of model predictive and multi-parametric controllers, and the performance of the controllers is analyzed.

Processing technology for high efficiency silicon solar cells

NASA Technical Reports Server (NTRS)

Spitzer, M. B.; Keavney, C. J.

1985-01-01

Recent advances in silicon solar cell processing have led to attainment of conversion efficiency approaching 20%. The basic cell design is investigated and features of greatest importance to achievement of 20% efficiency are indicated. Experiments to separately optimize high efficiency design features in test structures are discussed. The integration of these features in a high efficiency cell is examined. Ion implantation has been used to achieve optimal concentrations of emitter dopant and junction depth. The optimization reflects the trade-off between high sheet conductivity, necessary for high fill factor, and heavy doping effects, which must be minimized for high open circuit voltage. A second important aspect of the design experiments is the development of a passivation process to minimize front surface recombination velocity. The manner in which a thin SiO2 layer may be used for this purpose is indicated without increasing reflection losses, if the antireflection coating is properly designed. Details are presented of processing intended to reduce recombination at the contact/Si interface. Data on cell performance (including CZ and ribbon) and analysis of loss mechanisms are also presented.

Real-time PCR probe optimization using design of experiments approach.

PubMed

Wadle, S; Lehnert, M; Rubenwolf, S; Zengerle, R; von Stetten, F

2016-03-01

Primer and probe sequence designs are among the most critical input factors in real-time polymerase chain reaction (PCR) assay optimization. In this study, we present the use of statistical design of experiments (DOE) approach as a general guideline for probe optimization and more specifically focus on design optimization of label-free hydrolysis probes that are designated as mediator probes (MPs), which are used in reverse transcription MP PCR (RT-MP PCR). The effect of three input factors on assay performance was investigated: distance between primer and mediator probe cleavage site; dimer stability of MP and target sequence (influenza B virus); and dimer stability of the mediator and universal reporter (UR). The results indicated that the latter dimer stability had the greatest influence on assay performance, with RT-MP PCR efficiency increased by up to 10% with changes to this input factor. With an optimal design configuration, a detection limit of 3-14 target copies/10 μl reaction could be achieved. This improved detection limit was confirmed for another UR design and for a second target sequence, human metapneumovirus, with 7-11 copies/10 μl reaction detected in an optimum case. The DOE approach for improving oligonucleotide designs for real-time PCR not only produces excellent results but may also reduce the number of experiments that need to be performed, thus reducing costs and experimental times.

Improving the performance of surgery-based clinical pathways: a simulation-optimization approach.

PubMed

Ozcan, Yasar A; Tànfani, Elena; Testi, Angela

2017-03-01

This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients' clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives-meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.