Science.gov

Sample records for adaptive performance optimization

  1. Design optimization of system level adaptive optical performance

    NASA Astrophysics Data System (ADS)

    Michels, Gregory J.; Genberg, Victor L.; Doyle, Keith B.; Bisson, Gary R.

    2005-09-01

    By linking predictive methods from multiple engineering disciplines, engineers are able to compute more meaningful predictions of a product's performance. By coupling mechanical and optical predictive techniques mechanical design can be performed to optimize optical performance. This paper demonstrates how mechanical design optimization using system level optical performance can be used in the development of the design of a high precision adaptive optical telescope. While mechanical design parameters are treated as the design variables, the objective function is taken to be the adaptively corrected optical imaging performance of an orbiting two-mirror telescope.

  2. Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Long, Theresa W.

    1995-01-01

    Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

  3. Optimizing aircraft performance with adaptive, integrated flight/propulsion control

    NASA Technical Reports Server (NTRS)

    Smith, R. H.; Chisholm, J. D.; Stewart, J. F.

    1991-01-01

    The Performance-Seeking Control (PSC) integrated flight/propulsion adaptive control algorithm presented was developed in order to optimize total aircraft performance during steady-state engine operation. The PSC multimode algorithm minimizes fuel consumption at cruise conditions, while maximizing excess thrust during aircraft accelerations, climbs, and dashes, and simultaneously extending engine service life through reduction of fan-driving turbine inlet temperature upon engagement of the extended-life mode. The engine models incorporated by the PSC are continually upgraded, using a Kalman filter to detect anomalous operations. The PSC algorithm will be flight-demonstrated by an F-15 at NASA-Dryden.

  4. Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

    2017-01-01

    This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

  5. A concept for adaptive performance optimization on commercial transport aircraft

    NASA Technical Reports Server (NTRS)

    Jackson, Michael R.; Enns, Dale F.

    1995-01-01

    An adaptive control method is presented for the minimization of drag during flight for transport aircraft. The minimization of drag is achieved by taking advantage of the redundant control capability available in the pitch axis, with the horizontal tail used as the primary surface and symmetric deflection of the ailerons and cruise flaps used as additional controls. The additional control surfaces are excited with sinusoidal signals, while the altitude and velocity loops are closed with guidance and control laws. A model of the throttle response as a function of the additional control surfaces is formulated and the parameters in the model are estimated from the sensor measurements using a least squares estimation method. The estimated model is used to determine the minimum drag positions of the control surfaces. The method is presented for the optimization of one and two additional control surfaces. The adaptive control method is extended to optimize rate of climb with the throttle fixed. Simulations that include realistic disturbances are presented, as well as the results of a Monte Carlo simulation analysis that shows the effects of changing the disturbance environment and the excitation signal parameters.

  6. Direct adaptive performance optimization of subsonic transports: A periodic perturbation technique

    NASA Technical Reports Server (NTRS)

    Espana, Martin D.; Gilyard, Glenn

    1995-01-01

    Aircraft performance can be optimized at the flight condition by using available redundancy among actuators. Effective use of this potential allows improved performance beyond limits imposed by design compromises. Optimization based on nominal models does not result in the best performance of the actual aircraft at the actual flight condition. An adaptive algorithm for optimizing performance parameters, such as speed or fuel flow, in flight based exclusively on flight data is proposed. The algorithm is inherently insensitive to model inaccuracies and measurement noise and biases and can optimize several decision variables at the same time. An adaptive constraint controller integrated into the algorithm regulates the optimization constraints, such as altitude or speed, without requiring and prior knowledge of the autopilot design. The algorithm has a modular structure which allows easy incorporation (or removal) of optimization constraints or decision variables to the optimization problem. An important part of the contribution is the development of analytical tools enabling convergence analysis of the algorithm and the establishment of simple design rules. The fuel-flow minimization and velocity maximization modes of the algorithm are demonstrated on the NASA Dryden B-720 nonlinear flight simulator for the single- and multi-effector optimization cases.

  7. Design and Performance Optimization of GeoFEST for Adaptive Geophysical Modeling on High Performance Computers

    NASA Astrophysics Data System (ADS)

    Norton, C. D.; Parker, J. W.; Lyzenga, G. A.; Glasscoe, M. T.; Donnellan, A.

    2006-12-01

    The Geophysical Finite Element Simulation Tool (GeoFEST) and the PYRAMID parallel adaptive mesh refinement library have been integrated to provide high performance and high resolution modeling of 3D Earth crustal deformation under tectonic loading associated with the Earthquake cycle. This includes co-seismic and post-seismic modeling capabilities as well as other problems of geophysical interest. The use of the PYRAMID AMR library has allowed simulations of tens of millions of elements on various parallel computers where strain energy is applied as the error estimation criterion. This has allowed for improved generation of time-dependent simulations where the computational effort can be localized to geophysical regions of most activity. This talk will address techniques including conversion of the sequential GeoFEST software to a parallel version using PYRAMID, performance optimization and various lessons learned as part of porting such software to various parallel systems including Linux Clusters, SGI Altix systems, and Apple G5 XServe systems. We will also describe how the software has been applied in modeling of post-seismic deformation studies of the Landers and Northridge earthquake events.

  8. Optimal nutrition for athletic performance, with emphasis on fat adaptation in dogs and horses.

    PubMed

    Kronfeld, D S; Ferrante, P L; Grandjean, D

    1994-12-01

    Four mathematical approaches are proposed to determine optimal ranges of nutrients for specified purposes. For exercise, the diet must provide optimal mixtures of fuels, also optimal amounts of nutrients conducive to a sound structure, a desired power/weight ratio, a water-electrolyte system that resists dehydration and buffers hydrogen ions, a tolerance to the cumulative stress of repetitive competition and tractable attitude. The nutritional strategy of carbohydrate loading risks a variety of abnormalities in dogs and horses. An alternative strategy of fat adaptation (the combination of fat feeding and training) was found to improve aerobic performance in dogs and horses and to spare glycogen utilization and reduce lactate accumulation. Surprisingly, improved anaerobic performance has also been confirmed in fat-adapted horses that have been sprint trained. Fat adaptation increased the blood lactate responses to incremental tests and repeated sprints. Blood lactate accumulation during repeated sprints was affected synergistically by the combination of fat adaptation and sodium bicarbonate supplementation. Fat adaptation in horses appears to facilitate metabolic regulation to achieve power needs, with glycolysis decreasing during aerobic work but increasing during anaerobic work and with blood lactate changes following accordingly. Interactions between fat adaptation and dietary cation-anion balance need further investigation.

  9. In-flight adaptive performance optimization (APO) control using redundant control effectors of an aircraft

    NASA Technical Reports Server (NTRS)

    Gilyard, Glenn B. (Inventor)

    1999-01-01

    Practical application of real-time (or near real-time) Adaptive Performance Optimization (APO) is provided for a transport aircraft in steady climb, cruise, turn descent or other flight conditions based on measurements and calculations of incremental drag from a forced response maneuver of one or more redundant control effectors defined as those in excess of the minimum set of control effectors required to maintain the steady flight condition in progress. The method comprises the steps of applying excitation in a raised-cosine form over an interval of from 100 to 500 sec. at the rate of 1 to 10 sets/sec of excitation, and data for analysis is gathered in sets of measurements made during the excitation to calculate lift and drag coefficients C.sub.L and C.sub.D from two equations, one for each coefficient. A third equation is an expansion of C.sub.D as a function of parasitic drag, induced drag, Mach and altitude drag effects, and control effector drag, and assumes a quadratic variation of drag with positions .delta..sub.i of redundant control effectors i=1 to n. The third equation is then solved for .delta..sub.iopt the optimal position of redundant control effector i, which is then used to set the control effector i for optimum performance during the remainder of said steady flight or until monitored flight conditions change by some predetermined amount as determined automatically or a predetermined minimum flight time has elapsed.

  10. Statistical evaluation of the performance of an optimized adaptive optics arm for retinal imaging flood system

    NASA Astrophysics Data System (ADS)

    Magaña Chávez, J. L.; Medina-Márquez, J.; Valdivieso-González, L. G.; Balderas-Mata, S. E.

    2016-09-01

    In the last decade, Adaptive Optics has been used to compensate the aberrations of the eye in order to acquire high resolution retinal images. The use of high speed deformable mirrors (DMs) to accomplish this compensation in real time is of great importance. But, sometimes DMs are overused, compensating the aberrations inherent in the optical systems. In this work the evaluation of the performance of an adaptive optics system together with the imaging system will be evaluated in order to know in advance the aberrations inherent in them in order to compensate them prior the use of a DM.

  11. Lockheed L-1011 TriStar to support Adaptive Performance Optimization study with NASA F-18 chase plan

    NASA Technical Reports Server (NTRS)

    1995-01-01

    This Lockheed L-1011 Tristar, seen here June 1995, is currently the subject of a new flight research experiment developed by NASA's Dryden Flight Research Center, Edwards, California, to improve the effiecency of large transport aircraft. Shown with a NASA F-18 chase plane over California's Sierra Nevada mountains during an earlier baseline flight, the jetliner operated by Oribtal Sciences Corp., recently flew its first data-gathering mission in the Adaptive Performance Optimization project. The experiment seeks to reduce fuel comsumption of large jetliners by improving the aerodynamic efficiency of their wings at cruise conditions. A research computer employing a sophisticated software program adapts to changing flight conditions by commanding small movements of the L-1011's outboard ailerons to give its wings the most efficient - or optimal - airfoil. Up to a dozen research flights will be flown in the current and follow-on phases of the project over the next couple years.

  12. On the estimation algorithm used in adaptive performance optimization of turbofan engines

    NASA Technical Reports Server (NTRS)

    Espana, Martin D.; Gilyard, Glenn B.

    1993-01-01

    The performance seeking control algorithm is designed to continuously optimize the performance of propulsion systems. The performance seeking control algorithm uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters characterizing the engine deviations with respect to nominal conditions. In practice, because of measurement biases and/or model uncertainties, the estimated engine deviation parameters may not reflect the engine's actual off-nominal condition. This factor has a necessary impact on the overall performance seeking control scheme exacerbated by the open-loop character of the algorithm. The effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the performance seeking control algorithm to an F100 engine. An equivalence relation between the biases and engine deviation parameters stems from an observability study; therefore, it is undecided whether the estimated engine deviation parameters represent the actual engine deviation or whether they simply reflect the measurement biases. A new algorithm, based on the engine's (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of the onboard computer.

  13. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance.

    PubMed

    Aston-Jones, Gary; Cohen, Jonathan D

    2005-01-01

    Historically, the locus coeruleus-norepinephrine (LC-NE) system has been implicated in arousal, but recent findings suggest that this system plays a more complex and specific role in the control of behavior than investigators previously thought. We review neurophysiological and modeling studies in monkey that support a new theory of LC-NE function. LC neurons exhibit two modes of activity, phasic and tonic. Phasic LC activation is driven by the outcome of task-related decision processes and is proposed to facilitate ensuing behaviors and to help optimize task performance (exploitation). When utility in the task wanes, LC neurons exhibit a tonic activity mode, associated with disengagement from the current task and a search for alternative behaviors (exploration). Monkey LC receives prominent, direct inputs from the anterior cingulate (ACC) and orbitofrontal cortices (OFC), both of which are thought to monitor task-related utility. We propose that these frontal areas produce the above patterns of LC activity to optimize utility on both short and long timescales.

  14. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  15. Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives.

    PubMed

    Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P

    2015-07-01

    Model Based Control (MBC) is one of the energy optimal controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor dynamic performance of the drive. This study investigates the opportunity for improving dynamic performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The dynamic performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor dynamics improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions.

  16. Progress Toward Adaptive Integration and Optimization of Automated and Neural Processing Systems: Establishing Neural and Behavioral Benchmarks of Optimized Performance

    DTIC Science & Technology

    2014-11-01

    into more-realistic multitasking environments. Behind the work are basic questions about the utility of rapid serial visual presentation (RSVP) and... multitasking simulator with integrated real-time electroencephalogram (EEG) processing, RSVP performance was measured. Figure 2a shows the display for the...classification of their neural signals, all within the multitasking simulation environment. These studies and the results are described in the following

  17. Adaptive Integration and Optimization of Automated and Neural Processing Systems - Establishing Neural and Behavioral Benchmarks of Optimized Performance

    DTIC Science & Technology

    2012-07-01

    2.1 SAIC Applied and Transitional Research In contrast to the basic research developed at ICB, SAIC’s applied research and neurotechnology is based...application, a much higher level of performance is required. Under the Defense Advanced Research Project Agency’s (DARPA)’s Neurotechnology for...Biotechnologies LDA linear discriminant analysis MGV manned ground vehicles NIA Neurotechnology for Intelligence Analysts NTG non-target P3 P300

  18. Adaptive Cuckoo Search Algorithm for Unconstrained Optimization

    PubMed Central

    2014-01-01

    Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases. PMID:25298971

  19. Adaptive cuckoo search algorithm for unconstrained optimization.

    PubMed

    Ong, Pauline

    2014-01-01

    Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases.

  20. Adaptive control based on retrospective cost optimization

    NASA Astrophysics Data System (ADS)

    Santillo, Mario A.

    This dissertation studies adaptive control of multi-input, multi-output, linear, time-invariant, discrete-time systems that are possibly unstable and nonminimum phase. We consider both gradient-based adaptive control as well as retrospective-cost-based adaptive control. Retrospective cost optimization is a measure of performance at the current time based on a past window of data and without assumptions about the command or disturbance signals. In particular, retrospective cost optimization acts as an inner loop to the adaptive control algorithm by modifying the performance variables based on the difference between the actual past control inputs and the recomputed past control inputs based on the current control law. We develop adaptive control algorithms that are effective for systems that are nonminimum phase. We consider discrete-time adaptive control since these control laws can be implemented directly in embedded code without requiring an intermediate discretization step. Furthermore, the adaptive controllers in this dissertation are developed under minimal modeling assumptions. In particular, the adaptive controllers require knowledge of the sign of the high-frequency gain and a sufficient number of Markov parameters to approximate the nonminimum-phase zeros (if any). No additional modeling information is necessary. The adaptive controllers presented in this dissertation are developed for full-state-feedback stabilization, static-output-feedback stabilization, as well as dynamic compensation for stabilization, command following, disturbance rejection, and model reference adaptive control. Lyapunov-based stability and convergence proofs are provided for special cases. We present numerical examples to illustrate the algorithms' effectiveness in handling systems that are unstable and/or nonminimum phase and to provide insight into the modeling information required for controller implementation.

  1. An adaptive multi-swarm optimizer for dynamic optimization problems.

    PubMed

    Li, Changhe; Yang, Shengxiang; Yang, Ming

    2014-01-01

    The multipopulation method has been widely used to solve dynamic optimization problems (DOPs) with the aim of maintaining multiple populations on different peaks to locate and track multiple changing optima simultaneously. However, to make this approach effective for solving DOPs, two challenging issues need to be addressed. They are how to adapt the number of populations to changes and how to adaptively maintain the population diversity in a situation where changes are complicated or hard to detect or predict. Tracking the changing global optimum in dynamic environments is difficult because we cannot know when and where changes occur and what the characteristics of changes would be. Therefore, it is necessary to take these challenging issues into account in designing such adaptive algorithms. To address the issues when multipopulation methods are applied for solving DOPs, this paper proposes an adaptive multi-swarm algorithm, where the populations are enabled to be adaptive in dynamic environments without change detection. An experimental study is conducted based on the moving peaks problem to investigate the behavior of the proposed method. The performance of the proposed algorithm is also compared with a set of algorithms that are based on multipopulation methods from different research areas in the literature of evolutionary computation.

  2. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1990-09-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. This quarter, an empirical model for predicting pressure drop across a cyclone was developed through a statistical analysis of pressure drop data for 98 cyclone designs. The model is shown to perform better than the pressure drop models of First (1950), Alexander (1949), Barth (1956), Stairmand (1949), and Shepherd-Lapple (1940). This model is used with the efficiency model of Iozia and Leith (1990) to develop an optimization curve which predicts the minimum pressure drop and the dimension rations of the optimized cyclone for a given aerodynamic cut diameter, d{sub 50}. The effect of variation in cyclone height, cyclone diameter, and flow on the optimization curve is determined. The optimization results are used to develop a design procedure for optimized cyclones. 37 refs., 10 figs., 4 tabs.

  3. Implementing Adaptive Performance Management in Server Applications

    SciTech Connect

    Liu, Yan; Gorton, Ian

    2007-06-11

    Performance and scalability are critical quality attributes for server applications in Internet-facing business systems. These applications operate in dynamic environments with rapidly fluctuating user loads and resource levels, and unpredictable system faults. Adaptive (autonomic) systems research aims to augment such server applications with intelligent control logic that can detect and react to sudden environmental changes. However, developing this adaptive logic is complex in itself. In addition, executing the adaptive logic consumes processing resources, and hence may (paradoxically) adversely affect application performance. In this paper we describe an approach for developing high-performance adaptive server applications and the supporting technology. The Adaptive Server Framework (ASF) is built on standard middleware services, and can be used to augment legacy systems with adaptive behavior without needing to change the application business logic. Crucially, ASF provides built-in control loop components to optimize the overall application performance, which comprises both the business and adaptive logic. The control loop is based on performance models and allows systems designers to tune the performance levels simply by modifying high level declarative policies. We demonstrate the use of ASF in a case study.

  4. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1990-06-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. During the past quarter, we have nearly completed modeling work that employs the flow field measurements made during the past six months. In addition, we have begun final work using the results of this project to develop improved design methods for cyclones. This work involves optimization using the Iozia-Leith efficiency model and the Dirgo pressure drop model. This work will be completed this summer. 9 figs.

  5. Russian Loanword Adaptation in Persian; Optimal Approach

    ERIC Educational Resources Information Center

    Kambuziya, Aliye Kord Zafaranlu; Hashemi, Eftekhar Sadat

    2011-01-01

    In this paper we analyzed some of the phonological rules of Russian loanword adaptation in Persian, on the view of Optimal Theory (OT) (Prince & Smolensky, 1993/2004). It is the first study of phonological process on Russian loanwords adaptation in Persian. By gathering about 50 current Russian loanwords, we selected some of them to analyze. We…

  6. Adaptive approximation models in optimization

    SciTech Connect

    Voronin, A.N.

    1995-05-01

    The paper proposes a method for optimization of functions of several variables that substantially reduces the number of objective function evaluations compared to traditional methods. The method is based on the property of iterative refinement of approximation models of the optimand function in approximation domains that contract to the extremum point. It does not require subjective specification of the starting point, step length, or other parameters of the search procedure. The method is designed for efficient optimization of unimodal functions of several (not more than 10-15) variables and can be applied to find the global extremum of polymodal functions and also for optimization of scalarized forms of vector objective functions.

  7. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1989-06-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. We have now received all the equipment necessary for the flow visualization studies described over the last two progress reports. We have begun more detailed studies of the gas flow pattern within cyclones as detailed below. Third, we have begun studies of the effect of particle concentration on cyclone performance. This work is critical to application of our results to commercial operations. 1 fig.

  8. Dynamic optimization and adaptive controller design

    NASA Astrophysics Data System (ADS)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  9. Optimal Hops-Based Adaptive Clustering Algorithm

    NASA Astrophysics Data System (ADS)

    Xuan, Xin; Chen, Jian; Zhen, Shanshan; Kuo, Yonghong

    This paper proposes an optimal hops-based adaptive clustering algorithm (OHACA). The algorithm sets an energy selection threshold before the cluster forms so that the nodes with less energy are more likely to go to sleep immediately. In setup phase, OHACA introduces an adaptive mechanism to adjust cluster head and load balance. And the optimal distance theory is applied to discover the practical optimal routing path to minimize the total energy for transmission. Simulation results show that OHACA prolongs the life of network, improves utilizing rate and transmits more data because of energy balance.

  10. Adaptation and optimization of biological transport networks.

    PubMed

    Hu, Dan; Cai, David

    2013-09-27

    It has been hypothesized that topological structures of biological transport networks are consequences of energy optimization. Motivated by experimental observation, we propose that adaptation dynamics may underlie this optimization. In contrast to the global nature of optimization, our adaptation dynamics responds only to local information and can naturally incorporate fluctuations in flow distributions. The adaptation dynamics minimizes the global energy consumption to produce optimal networks, which may possess hierarchical loop structures in the presence of strong fluctuations in flow distribution. We further show that there may exist a new phase transition as there is a critical open probability of sinks, above which there are only trees for network structures whereas below which loops begin to emerge.

  11. RLV Turbine Performance Optimization

    NASA Technical Reports Server (NTRS)

    Griffin, Lisa W.; Dorney, Daniel J.

    2001-01-01

    A task was developed at NASA/Marshall Space Flight Center (MSFC) to improve turbine aerodynamic performance through the application of advanced design and analysis tools. There are four major objectives of this task: 1) to develop, enhance, and integrate advanced turbine aerodynamic design and analysis tools; 2) to develop the methodology for application of the analytical techniques; 3) to demonstrate the benefits of the advanced turbine design procedure through its application to a relevant turbine design point; and 4) to verify the optimized design and analysis with testing. Final results of the preliminary design and the results of the two-dimensional (2D) detailed design of the first-stage vane of a supersonic turbine suitable for a reusable launch vehicle (R-LV) are presented. Analytical techniques for obtaining the results are also discussed.

  12. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1989-03-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. This quarter, we have been hampered somewhat by flow delivery of the bubble generation system and arc lighting system placed on order last fall. This equipment is necessary to map the flow field within cyclones using the techniques described in last quarter's report. Using the bubble generator, we completed this quarter a study of the natural length'' of cyclones of 18 different configurations, each configuration operated at five different gas flows. Results suggest that the equation by Alexander for natural length is incorrect; natural length as measured with the bubble generation system is always below the bottom of the cyclones regardless of the cyclone configuration or gas flow, within the limits of the experimental cyclones tested. This finding is important because natural length is a term in equations used to predict cyclone efficiency. 1 tab.

  13. Optimized micromirror arrays for adaptive optics

    NASA Astrophysics Data System (ADS)

    Michalicek, M. Adrian; Comtois, John H.; Hetherington, Dale L.

    1999-01-01

    This paper describes the design, layout, fabrication, and surface characterization of highly optimized surface micromachined micromirror devices. Design considerations and fabrication capabilities are presented. These devices are fabricated in the state-of-the-art, four-level, planarized, ultra-low-stress polysilicon process available at Sandia National Laboratories known as the Sandia Ultra-planar Multi-level MEMS Technology (SUMMiT). This enabling process permits the development of micromirror devices with near-ideal characteristics that have previously been unrealizable in standard three-layer polysilicon processes. The reduced 1 μm minimum feature sizes and 0.1 μm mask resolution make it possible to produce dense wiring patterns and irregularly shaped flexures. Likewise, mirror surfaces can be uniquely distributed and segmented in advanced patterns and often irregular shapes in order to minimize wavefront error across the pupil. The ultra-low-stress polysilicon and planarized upper layer allow designers to make larger and more complex micromirrors of varying shape and surface area within an array while maintaining uniform performance of optical surfaces. Powerful layout functions of the AutoCAD editor simplify the design of advanced micromirror arrays and make it possible to optimize devices according to the capabilities of the fabrication process. Micromirrors fabricated in this process have demonstrated a surface variance across the array from only 2-3 nm to a worst case of roughly 25 nm while boasting active surface areas of 98% or better. Combining the process planarization with a ``planarized-by-design'' approach will produce micromirror array surfaces that are limited in flatness only by the surface deposition roughness of the structural material. Ultimately, the combination of advanced process and layout capabilities have permitted the fabrication of highly optimized micromirror arrays for adaptive optics.

  14. Optimal adaptive sequential designs for crossover bioequivalence studies.

    PubMed

    Xu, Jialin; Audet, Charles; DiLiberti, Charles E; Hauck, Walter W; Montague, Timothy H; Parr, Alan F; Potvin, Diane; Schuirmann, Donald J

    2016-01-01

    In prior works, this group demonstrated the feasibility of valid adaptive sequential designs for crossover bioequivalence studies. In this paper, we extend the prior work to optimize adaptive sequential designs over a range of geometric mean test/reference ratios (GMRs) of 70-143% within each of two ranges of intra-subject coefficient of variation (10-30% and 30-55%). These designs also introduce a futility decision for stopping the study after the first stage if there is sufficiently low likelihood of meeting bioequivalence criteria if the second stage were completed, as well as an upper limit on total study size. The optimized designs exhibited substantially improved performance characteristics over our previous adaptive sequential designs. Even though the optimized designs avoided undue inflation of type I error and maintained power at ≥ 80%, their average sample sizes were similar to or less than those of conventional single stage designs.

  15. An Adaptive Unified Differential Evolution Algorithm for Global Optimization

    SciTech Connect

    Qiang, Ji; Mitchell, Chad

    2014-11-03

    In this paper, we propose a new adaptive unified differential evolution algorithm for single-objective global optimization. Instead of the multiple mutation strate- gies proposed in conventional differential evolution algorithms, this algorithm employs a single equation unifying multiple strategies into one expression. It has the virtue of mathematical simplicity and also provides users the flexibility for broader exploration of the space of mutation operators. By making all control parameters in the proposed algorithm self-adaptively evolve during the process of optimization, it frees the application users from the burden of choosing appro- priate control parameters and also improves the performance of the algorithm. In numerical tests using thirteen basic unimodal and multimodal functions, the proposed adaptive unified algorithm shows promising performance in compari- son to several conventional differential evolution algorithms.

  16. Adaptive Wing Camber Optimization: A Periodic Perturbation Approach

    NASA Technical Reports Server (NTRS)

    Espana, Martin; Gilyard, Glenn

    1994-01-01

    Available redundancy among aircraft control surfaces allows for effective wing camber modifications. As shown in the past, this fact can be used to improve aircraft performance. To date, however, algorithm developments for in-flight camber optimization have been limited. This paper presents a perturbational approach for cruise optimization through in-flight camber adaptation. The method uses, as a performance index, an indirect measurement of the instantaneous net thrust. As such, the actual performance improvement comes from the integrated effects of airframe and engine. The algorithm, whose design and robustness properties are discussed, is demonstrated on the NASA Dryden B-720 flight simulator.

  17. Direct aperture optimization for online adaptive radiation therapy

    SciTech Connect

    Mestrovic, Ante; Milette, Marie-Pierre; Nichol, Alan; Clark, Brenda G.; Otto, Karl

    2007-05-15

    This paper is the first investigation of using direct aperture optimization (DAO) for online adaptive radiation therapy (ART). A geometrical model representing the anatomy of a typical prostate case was created. To simulate interfractional deformations, four different anatomical deformations were created by systematically deforming the original anatomy by various amounts (0.25, 0.50, 0.75, and 1.00 cm). We describe a series of techniques where the original treatment plan was adapted in order to correct for the deterioration of dose distribution quality caused by the anatomical deformations. We found that the average time needed to adapt the original plan to arrive at a clinically acceptable plan is roughly half of the time needed for a complete plan regeneration, for all four anatomical deformations. Furthermore, through modification of the DAO algorithm the optimization search space was reduced and the plan adaptation was significantly accelerated. For the first anatomical deformation (0.25 cm), the plan adaptation was six times more efficient than the complete plan regeneration. For the 0.50 and 0.75 cm deformations, the optimization efficiency was increased by a factor of roughly 3 compared to the complete plan regeneration. However, for the anatomical deformation of 1.00 cm, the reduction of the optimization search space during plan adaptation did not result in any efficiency improvement over the original (nonmodified) plan adaptation. The anatomical deformation of 1.00 cm demonstrates the limit of this approach. We propose an innovative approach to online ART in which the plan adaptation and radiation delivery are merged together and performed concurrently--adaptive radiation delivery (ARD). A fundamental advantage of ARD is the fact that radiation delivery can start almost immediately after image acquisition and evaluation. Most of the original plan adaptation is done during the radiation delivery, so the time spent adapting the original plan does not

  18. Optimal Bayesian Adaptive Design for Test-Item Calibration.

    PubMed

    van der Linden, Wim J; Ren, Hao

    2015-06-01

    An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the current posterior distributions of the field-test parameters. Different criteria of optimality based on the two types of posterior distributions are possible. The design can be implemented using an MCMC scheme with alternating stages of sampling from the posterior distributions of the test takers' ability parameters and the parameters of the field-test items while reusing samples from earlier posterior distributions of the other parameters. Results from a simulation study demonstrated the feasibility of the proposed MCMC implementation for operational item calibration. A comparison of performances for different optimality criteria showed faster calibration of substantial numbers of items for the criterion of D-optimality relative to A-optimality, a special case of c-optimality, and random assignment of items to the test takers.

  19. Motion management with phase-adapted 4D-optimization

    NASA Astrophysics Data System (ADS)

    Nohadani, Omid; Seco, Joao; Bortfeld, Thomas

    2010-09-01

    Cancer treatment with ionizing radiation is often compromised by organ motion, in particular for lung cases. Motion uncertainties can significantly degrade an otherwise optimized treatment plan. We present a spatiotemporal optimization method, which takes into account all phases of breathing via the corresponding 4D-CTs and provides a 4D-optimal plan that can be delivered throughout all breathing phases. Monte Carlo dose calculations are employed to warrant for highest dosimetric accuracy, as pertinent to study motion effects in lung. We demonstrate the performance of this optimization method with clinical lung cancer cases and compare the outcomes to conventional gating techniques. We report significant improvements in target coverage and in healthy tissue sparing at a comparable computational expense. Furthermore, we show that the phase-adapted 4D-optimized plans are robust against irregular breathing, as opposed to gating. This technique has the potential to yield a higher delivery efficiency and a decisively shorter delivery time.

  20. 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.

  1. Optimizing rotary drill performance

    SciTech Connect

    Schivley, G.P. Jr.

    1995-12-31

    Data is presented showing Penetration Rate (PR) versus Force-on-the-Bit (FB) and Bit Angular Speed (N). Using this data, it is shown how FB and N each uniquely contribute to the PR for any particular drilling situation. This data represents many mining situations; including coal, copper, gold, iron ore and limestone quarrying. The important relationship between Penetration per Revolution (P/R) and the height of the cutting elements of the bit (CH) is discussed. Drill performance is then reviewed, considering the effect of FB and N on bit life. All this leads to recommendations for the operating values of FB and N for drilling situations where the rock is not highly abrasive and bit replacements are because of catastrophic failure of the bit cone bearings. The contribution of compressed air to the drilling process is discussed. It is suggested that if the air issuing from the bit jets is supersonic that may enhance the sweeping of the hole bottom. Also, it is shown that not just uphole air velocity is enough to provide adequate transport of the rock cuttings up the annulus of a drilled hole. In addition, air volume flow rate must be considered to assure there is adequate particle spacing so the mechanism of aerodynamic drag can effectively lift the cuttings up and out of the hole annulus.

  2. An adaptive penalty method for DIRECT algorithm in engineering optimization

    NASA Astrophysics Data System (ADS)

    Vilaça, Rita; Rocha, Ana Maria A. C.

    2012-09-01

    The most common approach for solving constrained optimization problems is based on penalty functions, where the constrained problem is transformed into a sequence of unconstrained problem by penalizing the objective function when constraints are violated. In this paper, we analyze the implementation of an adaptive penalty method, within the DIRECT algorithm, in which the constraints that are more difficult to be satisfied will have relatively higher penalty values. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

  3. Performance Optimization and Auto-Tuning

    SciTech Connect

    Howison, Mark

    2012-10-01

    In the broader computational research community, one subject of recent research is the problem of adapting algorithms to make effective use of multi- and many-core processors. Effective use of these architectures, which have complex memory hierarchies with many layers of cache, typically involves a careful examination of how an algorithm moves data through the memory hierarchy. Unfortunately, there is often a non-obvious relationship between algorithmic parameters like blocking strategies, and their impact on memory utilization, and, in turn, the relationship with runtime performance. Auto-tuning is an empirical method used to discover optimal values for tunable algorithmic parameters under such circumstances. The challenge is compounded by the fact that the settings that produce the best performance for a given problem and a given platform may not be the best for a different problem on the same platform, or the same problem on a different platform. The high performance visualization research community has begun to explore and adapt the principles of auto-tuning for the purpose of optimizing codes on modern multi- and many-core processors. This report focuses on how performance optimization studies reveal a dramatic variation in performance for two fundamental visualization algorithms: one based on a stencil operation having structured, uniform memory access, and the other is ray casting volume rendering, which uses unstructured memory access patterns. The two case studies highlighted in this report show the extra effort required to optimize such codes by adjusting the tunable algorithmic parameters can return substantial gains in performance. Additionally, these case studies also explore the potential impact of and the interaction between algorithmic optimizations and tunable algorithmic parameters, along with the potential performance gains resulting from leveraging architecture-specific features.

  4. 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.

  5. Optimal Pid Tuning for Power System Stabilizers Using Adaptive Particle Swarm Optimization Technique

    NASA Astrophysics Data System (ADS)

    Oonsivilai, Anant; Marungsri, Boonruang

    2008-10-01

    An application of the intelligent search technique to find optimal parameters of power system stabilizer (PSS) considering proportional-integral-derivative controller (PID) for a single-machine infinite-bus system is presented. Also, an efficient intelligent search technique, adaptive particle swarm optimization (APSO), is engaged to express usefulness of the intelligent search techniques in tuning of the PID—PSS parameters. Improve damping frequency of system is optimized by minimizing an objective function with adaptive particle swarm optimization. At the same operating point, the PID—PSS parameters are also tuned by the Ziegler-Nichols method. The performance of proposed controller compared to the conventional Ziegler-Nichols PID tuning controller. The results reveal superior effectiveness of the proposed APSO based PID controller.

  6. High-performance thresholding with adaptive equalization

    NASA Astrophysics Data System (ADS)

    Lam, Ka Po

    1998-09-01

    The ability to simplify an image whilst retaining such crucial information as shapes and geometric structures is of great importance for real-time image analysis applications. Here the technique of binary thresholding which reduces the image complexity has generally been regarded as one of the most valuable methods, primarily owing to its ease of design and analysis. This paper studies the state of developments in the field, and describes a radically different approach of adaptive thresholding. The latter employs the analytical technique of histogram normalization for facilitating an optimal `contrast level' of the image under consideration. A suitable criterion is also developed to determine the applicability of the adaptive processing procedure. In terms of performance and computational complexity, the proposed algorithm compares favorably to five established image thresholding methods selected for this study. Experimental results have shown that the new algorithm outperforms these methods in terms of a number of important errors measures, including a consistently low visual classification error performance. The simplicity of design of the algorithm also lends itself to efficient parallel implementations.

  7. A Tutorial on Adaptive Design Optimization

    PubMed Central

    Myung, Jay I.; Cavagnaro, Daniel R.; Pitt, Mark A.

    2013-01-01

    Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond. PMID:23997275

  8. Adaptive Mallow's optimization for weighted median filters

    NASA Astrophysics Data System (ADS)

    Rachuri, Raghu; Rao, Sathyanarayana S.

    2002-05-01

    This work extends the idea of spectral optimization for the design of Weighted Median filters and employ adaptive filtering that updates the coefficients of the FIR filter from which the weights of the median filters are derived. Mallows' theory of non-linear smoothers [1] has proven to be of great theoretical significance providing simple design guidelines for non-linear smoothers. It allows us to find a set of positive weights for a WM filter whose sample selection probabilities (SSP's) are as close as possible to a SSP set predetermined by Mallow's. Sample selection probabilities have been used as a basis for designing stack smoothers as they give a measure of the filter's detail preserving ability and give non-negative filter weights. We will extend this idea to design weighted median filters admitting negative weights. The new method first finds the linear FIR filter coefficients adaptively, which are then used to determine the weights of the median filter. WM filters can be designed to have band-pass, high-pass as well as low-pass frequency characteristics. Unlike the linear filters, however, the weighted median filters are robust in the presence of impulsive noise, as shown by the simulation results.

  9. Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

    SciTech Connect

    Yan Di; Liang Jian

    2013-02-15

    Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect to the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications. Conclusions

  10. Rate-distortion optimized adaptive transform coding

    NASA Astrophysics Data System (ADS)

    Lim, Sung-Chang; Kim, Dae-Yeon; Jeong, Seyoon; Choi, Jin Soo; Choi, Haechul; Lee, Yung-Lyul

    2009-08-01

    We propose a rate-distortion optimized transform coding method that adaptively employs either integer cosine transform that is an integer-approximated version of discrete cosine transform (DCT) or integer sine transform (IST) in a rate-distortion sense. The DCT that has been adopted in most video-coding standards is known as a suboptimal substitute for the Karhunen-Loève transform. However, according to the correlation of a signal, an alternative transform can achieve higher coding efficiency. We introduce a discrete sine transform (DST) that achieves the high-energy compactness in a correlation coefficient range of -0.5 to 0.5 and is applied to the current design of H.264/AVC (advanced video coding). Moreover, to avoid the encoder and decoder mismatch and make the implementation simple, an IST that is an integer-approximated version of the DST is developed. The experimental results show that the proposed method achieves a Bjøntegaard Delta-RATE gain up to 5.49% compared to Joint model 11.0.

  11. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    NASA Technical Reports Server (NTRS)

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  12. Adaptive, predictive controller for optimal process control

    SciTech Connect

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  13. Optimal performance of regenerative cryocoolers

    NASA Astrophysics Data System (ADS)

    de Boer, P. C. T.

    2011-02-01

    The key component of a regenerative cryocooler is its regenerative heat exchanger. This device is subject to losses due to imperfect heat transfer between the regenerator material and the gas, as well as due to viscous dissipation. The relative magnitudes of these losses can be characterized by the ratio of the Stanton number St to the Fanning friction factor f. Using available data for the ratio St/ f, results are developed for the optimal cooling rate and Carnot efficiency. The variations of pressure and temperature are taken to be sinusoidal in time, and to have small amplitudes. The results are applied to the case of the Stirling cryocooler, with flow being generated by pistons at both sides of the regenerator. The performance is found to be close to optimal at large ratio of the warm space volume to the regenerator void volume. The results are also applied to the Orifice Pulse Tube Refrigerator. In this case, optimal performance additionally requires a large ratio of the regenerator void volume to the cold space volume.

  14. Cockpit Adaptive Automation and Pilot Performance

    NASA Technical Reports Server (NTRS)

    Parasuraman, Raja

    2001-01-01

    The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals

  15. Spacecraft Component Adaptive Layout Environment (SCALE): An efficient optimization tool

    NASA Astrophysics Data System (ADS)

    Fakoor, Mahdi; Ghoreishi, Seyed Mohammad Navid; Sabaghzadeh, Hossein

    2016-11-01

    For finding the optimum layout of spacecraft subsystems, important factors such as the center of gravity, moments of inertia, thermal distribution, natural frequencies, etc. should be taken into account. This large number of effective parameters makes the optimum layout process of spacecraft subsystems complex and time consuming. In this paper, an automatic tool, based on multi-objective optimization methods, is proposed for a three dimensional layout of spacecraft subsystems. In this regard, an efficient Spacecraft Component Adaptive Layout Environment (SCALE) is produced by integration of some modeling, FEM, and optimization software. SCALE automatically provides optimal solutions for a three dimensional layout of spacecraft subsystems with considering important constraints such as center of gravity, moment of inertia, thermal distribution, natural frequencies and structural strength. In order to show the superiority and efficiency of SCALE, layout of a telecommunication spacecraft and a remote sensing spacecraft are performed. The results show that, the objective functions values for obtained layouts by using SCALE are in a much better condition than traditional one i.e. Reference Baseline Solution (RBS) which is proposed by the engineering system team. This indicates the good performance and ability of SCALE for finding the optimal layout of spacecraft subsystems.

  16. A forward method for optimal stochastic nonlinear and adaptive control

    NASA Technical Reports Server (NTRS)

    Bayard, David S.

    1988-01-01

    A computational approach is taken to solve the optimal nonlinear stochastic control problem. The approach is to systematically solve the stochastic dynamic programming equations forward in time, using a nested stochastic approximation technique. Although computationally intensive, this provides a straightforward numerical solution for this class of problems and provides an alternative to the usual dimensionality problem associated with solving the dynamic programming equations backward in time. It is shown that the cost degrades monotonically as the complexity of the algorithm is reduced. This provides a strategy for suboptimal control with clear performance/computation tradeoffs. A numerical study focusing on a generic optimal stochastic adaptive control example is included to demonstrate the feasibility of the method.

  17. Optimal Stratification of Item Pools in a-Stratified Computerized Adaptive Testing.

    ERIC Educational Resources Information Center

    Chang, Hua-Hua; van der Linden, Wim J.

    2003-01-01

    Developed a method based on 0-1 linear programming to stratify an item pool optimally for use in alpha-stratified adaptive testing. Applied the method to a previous item pool from the computerized adaptive test of the Graduate Record Examinations. Results show the new method performs well in practical situations. (SLD)

  18. Optimizing Reservoir Operation to Adapt to the Climate Change

    NASA Astrophysics Data System (ADS)

    Madadgar, S.; Jung, I.; Moradkhani, H.

    2010-12-01

    Climate change and upcoming variation in flood timing necessitates the adaptation of current rule curves developed for operation of water reservoirs as to reduce the potential damage from either flood or draught events. This study attempts to optimize the current rule curves of Cougar Dam on McKenzie River in Oregon addressing some possible climate conditions in 21th century. The objective is to minimize the failure of operation to meet either designated demands or flood limit at a downstream checkpoint. A simulation/optimization model including the standard operation policy and a global optimization method, tunes the current rule curve upon 8 GCMs and 2 greenhouse gases emission scenarios. The Precipitation Runoff Modeling System (PRMS) is used as the hydrology model to project the streamflow for the period of 2000-2100 using downscaled precipitation and temperature forcing from 8 GCMs and two emission scenarios. An ensemble of rule curves, each associated with an individual scenario, is obtained by optimizing the reservoir operation. The simulation of reservoir operation, for all the scenarios and the expected value of the ensemble, is conducted and performance assessment using statistical indices including reliability, resilience, vulnerability and sustainability is made.

  19. Optimal mirror deformation for multi conjugate adaptive optics systems

    NASA Astrophysics Data System (ADS)

    Raffetseder, S.; Ramlau, R.; Yudytskiy, M.

    2016-02-01

    Multi conjugate adaptive optics (MCAO) is a system planned for all future extremely large telescopes to compensate in real-time for the optical distortions caused by atmospheric turbulence over a wide field of view. The principles of MCAO are based on two inverse problems: a stable tomographic reconstruction of the turbulence profile followed by the optimal alignment of multiple deformable mirrors (DMs), conjugated to different altitudes in the atmosphere. We present a novel method to treat the optimal mirror deformation problem for MCAO. Contrary to the standard approach where the problem is formulated over a discrete set of optimization directions we focus on the solution of the continuous optimization problem. In the paper we study the existence and uniqueness of the solution and present a Tikhonov based regularization method. This approach gives us the flexibility to apply quadrature rules for a more sophisticated discretization scheme. Using numerical simulations in the context of the European extremely large telescope we show that our method leads to a significant improvement in the reconstruction quality over the standard approach and allows to reduce the numerical burden on the computer performing the computations.

  20. An optimized index of human cardiovascular adaptation to simulated weightlessness

    NASA Technical Reports Server (NTRS)

    Wang, M.; Hassebrook, L.; Evans, J.; Varghese, T.; Knapp, C.

    1996-01-01

    Prolonged exposure to weightlessness is known to produce a variety of cardiovascular changes, some of which may influence the astronaut's performance during a mission. In order to find a reliable indicator of cardiovascular adaptation to weightlessness, we analyzed data from nine male subjects after a 24-hour period of normal activity and after a period of simulated weightlessness produced by two hours in a launch position followed by 20 hours of 6 degrees head-down tilt plus pharmacologically induced diuresis (furosemide). Heart rate, arterial pressure, thoracic fluid index, and radial flow were analyzed. Autoregressive spectral estimation and decomposition were used to obtain the spectral components of each variable from the subjects in the supine position during pre- and post-simulated weightlessness. We found a significant decrease in heart rate power and an increase in thoracic fluid index power in the high frequency region (0.2-0.45 Hz) and significant increases in radial flow and arterial pressure powers in the low frequency region (<0.2 Hz) in response to simulated weightlessness. However, due to the variability among subjects, any single variable appeared limited as a dependable index of cardiovascular adaptation to weightlessness. The backward elimination algorithm was then used to select the best discriminatory features from these spectral components. Fisher's linear discriminant and Bayes' quadratic discriminant were used to combine the selected features to obtain an optimal index of adaptation to simulated weightlessness. Results showed that both techniques provided improved discriminant performance over any single variable and thus have the potential for use as an index to track adaptation and prescribe countermeasures to the effects of weightlessness.

  1. Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection

    ERIC Educational Resources Information Center

    Mulder, Joris; van der Linden, Wim J.

    2009-01-01

    Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the…

  2. Adaptive-optics performance of Antarctic telescopes.

    PubMed

    Lawrence, Jon S

    2004-02-20

    The performance of natural guide star adaptive-optics systems for telescopes located on the Antarctic plateau is evaluated and compared with adaptive-optics systems operated with the characteristic mid-latitude atmosphere found at Mauna Kea. A 2-m telescope with tip-tilt correction and an 8-m telescope equipped with a high-order adaptive-optics system are considered. Because of the large isoplanatic angle of the South Pole atmosphere, the anisoplanatic error associated with an adaptive-optics correction is negligible, and the achievable resolution is determined only by the fitting error associated with the number of corrected wave-front modes, which depends on the number of actuators on the deformable mirror. The usable field of view of an adaptive-optics equipped Antarctic telescope is thus orders of magnitude larger than for a similar telescope located at a mid-latitude site; this large field of view obviates the necessity for multiconjugate adaptive-optics systems that use multiple laser guide stars. These results, combined with the low infrared sky backgrounds, indicate that the Antarctic plateau is the best site on Earth at which to perform high-resolution imaging with large telescopes, either over large fields of view or with appreciable sky coverage. Preliminary site-testing results obtained recently from the Dome Concordia station indicate that this site is far superior to even the South Pole.

  3. Reliability Optimization Design for Contact Springs of AC Contactors Based on Adaptive Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Zhao, Sheng; Su, Xiuping; Wu, Ziran; Xu, Chengwen

    The paper illustrates the procedure of reliability optimization modeling for contact springs of AC contactors under nonlinear multi-constraint conditions. The adaptive genetic algorithm (AGA) is utilized to perform reliability optimization on the contact spring parameters of a type of AC contactor. A method that changes crossover and mutation rates at different times in the AGA can effectively avoid premature convergence, and experimental tests are performed after optimization. The experimental result shows that the mass of each optimized spring is reduced by 16.2%, while the reliability increases to 99.9% from 94.5%. The experimental result verifies the correctness and feasibility of this reliability optimization designing method.

  4. Adaptive optimization and control using neural networks

    SciTech Connect

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  5. A Model for Optimal Constrained Adaptive Testing.

    ERIC Educational Resources Information Center

    van der Linden, Wim J.; Reese, Lynda M.

    1998-01-01

    Proposes a model for constrained computerized adaptive testing in which the information in the test at the trait level (theta) estimate is maximized subject to the number of possible constraints on the content of the test. Test assembly relies on a linear-programming approach. Illustrates the approach through simulation with items from the Law…

  6. Adaptation and optimal chemotactic strategy for {ital E. coli}

    SciTech Connect

    Strong, S.P.; Bialek, William; Koberle, R. Freedman, B.

    1998-04-01

    Extending the classic works of Berg and Purcell on the biophysics of bacterial chemotaxis, we find the optimal chemotactic strategy for the peritrichous bacterium {ital E. coli} in the high and low signal to noise ratio limits. The optimal strategy depends on properties of the environment and properties of the individual bacterium, and is therefore highly adaptive. We review experiments relevant to testing both the form of the proposed strategy and its adaptability, and propose extensions of them which could test the limits of the adaptability in this simplest sensory processing system. {copyright} {ital 1998} {ital The American Physical Society}

  7. Camelina: Adaptation and performance of genotypes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Camelina (Camelina sativa L. Crantz) has shown potential as an alternative and biofuel crop in cereal-based cropping systems. Our study investigated the adaption, performance, and yield stability among camelina genotypes across diverse US Pacific Northwest (PNW) environments. Seven named camelina ge...

  8. Adaptive control based on retrospective cost optimization

    NASA Technical Reports Server (NTRS)

    Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)

    2012-01-01

    A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

  9. Extragalactic Fields Optimized for Adaptive Optics

    DTIC Science & Technology

    2011-03-01

    observatories (including those on Mauna Kea ). Before proceeding with a detailed analysis, it is instructive to note that many positions in the sky likely...4Gemini Observatory , Southern Operations Center, c/o AURA, Casilla 603,La Serena, Chile. sObservatories of the Carnegie Institution of Washington...United States Naval Observatory , 3450 Massachusetts Avenue, NW, Washington, DC 20392-5420. 348 galaxies in these fields require adaptive optics (AO

  10. Distributed Adaptive Particle Swarm Optimizer in Dynamic Environment

    SciTech Connect

    Cui, Xiaohui; Potok, Thomas E

    2007-01-01

    In the real world, we have to frequently deal with searching and tracking an optimal solution in a dynamical and noisy environment. This demands that the algorithm not only find the optimal solution but also track the trajectory of the changing solution. Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique, which can find an optimal, or near optimal, solution to a numerical and qualitative problem. In PSO algorithm, the problem solution emerges from the interactions between many simple individual agents called particles, which make PSO an inherently distributed algorithm. However, the traditional PSO algorithm lacks the ability to track the optimal solution in a dynamic and noisy environment. In this paper, we present a distributed adaptive PSO (DAPSO) algorithm that can be used for tracking a non-stationary optimal solution in a dynamically changing and noisy environment.

  11. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  12. On-sky demonstration of optimal control for adaptive optics at Palomar Observatory.

    PubMed

    Tesch, Jonathan; Truong, Tuan; Burruss, Rick; Gibson, Steve

    2015-04-01

    High-order adaptive optics systems often suffer from significant computational latency, which ultimately limits the temporal error rejection bandwidth when classical controllers are employed. This Letter presents results from an on-sky, real-time implementation of an optimal controller on the PALM-3000 adaptive optics system at Palomar Observatory. The optimal controller is computed directly from open-loop wavefront measurements using a multichannel subspace system identification algorithm, and mitigates latency by explicitly predicting incident turbulence. Experimental results show a significant reduction in the residual wavefront error over the controlled spatial modes, illustrating the superior performance of the optimal control approach versus the nominal integral control architecture.

  13. A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy.

    PubMed

    Wen, Hui; Xie, Weixin; Pei, Jihong

    2016-01-01

    This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms.

  14. A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

    PubMed Central

    Wen, Hui; Xie, Weixin; Pei, Jihong

    2016-01-01

    This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

  15. Sootblowing optimization for improved boiler performance

    DOEpatents

    James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J

    2013-07-30

    A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

  16. Sootblowing optimization for improved boiler performance

    DOEpatents

    James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.

    2012-12-25

    A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

  17. A hybrid method for optimization of the adaptive Goldstein filter

    NASA Astrophysics Data System (ADS)

    Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue

    2014-12-01

    The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.

  18. Performance predictions for the Keck telescope adaptive optics system

    SciTech Connect

    Gavel, D.T.; Olivier, S.S.

    1995-08-07

    The second Keck ten meter telescope (Keck-11) is slated to have an infrared-optimized adaptive optics system in the 1997--1998 time frame. This system will provide diffraction-limited images in the 1--3 micron region and the ability to use a diffraction-limited spectroscopy slit. The AO system is currently in the preliminary design phase and considerable analysis has been performed in order to predict its performance under various seeing conditions. In particular we have investigated the point-spread function, energy through a spectroscopy slit, crowded field contrast, object limiting magnitude, field of view, and sky coverage with natural and laser guide stars.

  19. An adaptive precision gradient method for optimal control.

    NASA Technical Reports Server (NTRS)

    Klessig, R.; Polak, E.

    1973-01-01

    This paper presents a gradient algorithm for unconstrained optimal control problems. The algorithm is stated in terms of numerical integration formulas, the precision of which is controlled adaptively by a test that ensures convergence. Empirical results show that this algorithm is considerably faster than its fixed precision counterpart.-

  20. Optimal Design of Item Banks for Computerized Adaptive Tests.

    ERIC Educational Resources Information Center

    Stocking, Martha L.; Swanson, Len

    1998-01-01

    Applied optimal design methods to the item-bank design of adaptive testing for continuous testing situations using a version of the weighted-deviations model (M. Stocking and L. Swanson, 1993) in a simulation. Independent and overlapping item banks used items more efficiently than did a large item bank. (SLD)

  1. Adaptive and Optimal Control of Stochastic Dynamical Systems

    DTIC Science & Technology

    2015-09-14

    control and stochastic differential games . Stochastic linear-quadratic, continuous time, stochastic control problems are solved for systems with noise...control problems for systems with arbitrary correlated n 15. SUBJECT TERMS Adaptive control, optimal control, stochastic differential games 16. SECURITY...explicit results have been obtained for problems of stochastic control and stochastic differential games . Stochastic linear- quadratic, continuous time

  2. Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

    NASA Astrophysics Data System (ADS)

    Zirkohi, Majid Moradi

    2015-04-01

    The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.

  3. Performance of adaptive optics at Lick Observatory

    SciTech Connect

    Olivier, S.S.; An, J.; Avicola, K.

    1994-03-01

    A prototype adaptive optics system has been developed at Lawrence Livermore National Laboratory (LLNL) for use at Lick Observatory. This system is based on an ITEX 69-actuator continuous-surface deformable mirror, a Kodak fast-framing intensified CCD camera, and a Mercury VME board containing four Intel i860 processors. The system has been tested using natural reference stars on the 40-inch Nickel telescope at Lick Observatory yielding up to a factor of 10 increase in image peak intensity and a factor of 6 reduction in image full width at half maximum (FWHM). These results are consistent with theoretical expectations. In order to improve performance, the intensified CCD camera will be replaced by a high-quantum-efficiency low-noise fast CCD camera built for LLNL by Adaptive Optics Associates using a chip developed by Lincoln Laboratory, and the 69-actuator deformable mirror will be replaced by a 127-actuator deformable mirror developed at LLNL. With these upgrades, the system should perform well in median seeing conditions on the 120-inch Shane telescope for observing wavelengths longer than {approximately}1 {mu}m and using natural reference stars brighter than m{sub R} {approximately} 10 or using the laser currently being developed at LLNL for use at Lick Observatory to generate a sodium-layer reference star.

  4. Optimizing Input/Output Using Adaptive File System Policies

    NASA Technical Reports Server (NTRS)

    Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

    1996-01-01

    Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

  5. Topology optimization of pressure adaptive honeycomb for a morphing flap

    NASA Astrophysics Data System (ADS)

    Vos, Roelof; Scheepstra, Jan; Barrett, Ron

    2011-03-01

    The paper begins with a brief historical overview of pressure adaptive materials and structures. By examining avian anatomy, it is seen that pressure-adaptive structures have been used successfully in the Natural world to hold structural positions for extended periods of time and yet allow for dynamic shape changes from one flight state to the next. More modern pneumatic actuators, including FAA certified autopilot servoactuators are frequently used by aircraft around the world. Pneumatic artificial muscles (PAM) show good promise as aircraft actuators, but follow the traditional model of load concentration and distribution commonly found in aircraft. A new system is proposed which leaves distributed loads distributed and manipulates structures through a distributed actuator. By using Pressure Adaptive Honeycomb (PAH), it is shown that large structural deformations in excess of 50% strains can be achieved while maintaining full structural integrity and enabling secondary flight control mechanisms like flaps. The successful implementation of pressure-adaptive honeycomb in the trailing edge of a wing section sparked the motivation for subsequent research into the optimal topology of the pressure adaptive honeycomb within the trailing edge of a morphing flap. As an input for the optimization two known shapes are required: a desired shape in cruise configuration and a desired shape in landing configuration. In addition, the boundary conditions and load cases (including aerodynamic loads and internal pressure loads) should be specified for each condition. Finally, a set of six design variables is specified relating to the honeycomb and upper skin topology of the morphing flap. A finite-element model of the pressure-adaptive honeycomb structure is developed specifically tailored to generate fast but reliable results for a given combination of external loading, input variables, and boundary conditions. Based on two bench tests it is shown that this model correlates well

  6. 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.

  7. An optimized, universal hardware-based adaptive correlation receiver architecture

    NASA Astrophysics Data System (ADS)

    Zhu, Zaidi; Suarez, Hernan; Zhang, Yan; Wang, Shang

    2014-05-01

    The traditional radar RF transceivers, similar to communication transceivers, have the basic elements such as baseband waveform processing, IF/RF up-down conversion, transmitter power circuits, receiver front-ends, and antennas, which are shown in the upper half of Figure 1. For modern radars with diversified and sophisticated waveforms, we can frequently observe that the transceiver behaviors, especially nonlinear behaviors, are depending on the waveform amplitudes, frequency contents and instantaneous phases. Usually, it is a troublesome process to tune an RF transceiver to optimum when different waveforms are used. Another issue arises from the interference caused by the waveforms - for example, the range side-lobe (RSL) caused by the waveforms, once the signals pass through the entire transceiver chain, may be further increased due to distortions. This study is inspired by the two existing solutions from commercial communication industry, digital pre-distortion (DPD) and adaptive channel estimation and Interference Mitigation (AIM), while combining these technologies into a single chip or board that can be inserted into the existing transceiver system. This device is then named RF Transceiver Optimizer (RTO). The lower half of Figure 1 shows the basic element of RTO. With RTO, the digital baseband processing does not need to take into account the transceiver performance with diversified waveforms, such as the transmitter efficiency and chain distortion (and the intermodulation products caused by distortions). Neither does it need to concern the pulse compression (or correlation receiver) process and the related mitigation. The focus is simply the information about the ground truth carried by the main peak of correlation receiver outputs. RTO can be considered as an extension of the existing calibration process, while it has the benefits of automatic, adaptive and universal. Currently, the main techniques to implement the RTO are the digital pre- or -post

  8. Adaptation to optimal cell growth through self-organized criticality.

    PubMed

    Furusawa, Chikara; Kaneko, Kunihiko

    2012-05-18

    A simple cell model consisting of a catalytic reaction network is studied to show that cellular states are self-organized in a critical state for achieving optimal growth; we consider the catalytic network dynamics over a wide range of environmental conditions, through the spontaneous regulation of nutrient transport into the cell. Furthermore, we find that the adaptability of cellular growth to reach a critical state depends only on the extent of environmental changes, while all chemical species in the cell exhibit correlated partial adaptation. These results are in remarkable agreement with the recent experimental observations of the present cells.

  9. Individually designed PALs vs. power optimized PALs adaptation comparison.

    PubMed

    Muždalo, Nataša Vujko; Mihelčič, Matjaž

    2015-03-01

    The practice shows that in everyday life we encounter ever-growing demand for better visual acuity at all viewing distances. The presbyopic population needs correction to far, near and intermediate distance with different dioptric powers. PAL lenses seem to be a comfortable solution. The object of the present study is the analysis of the factors determining adaptation to progressive addition lenses (PAL) of the first-time users. Only novice test persons were chosen in order to avoid the bias of previously worn particular lens design. For optimal results with this type of lens, several individual parameters must be considered: correct refraction, precise ocular and facial measures, and proper mounting of lenses into the frame. Nevertheless, first time wearers encounter various difficulties in the process of adapting to this type of glasses and adaptation time differs greatly between individual users. The question that arises is how much the individual parameters really affect the ease of adaptation and comfort when wearing progressive glasses. To clarify this, in the present study, the individual PAL lenses--Rodenstock's Impression FreeSign (with inclusion of all parameters related to the user's eye and spectacle frame: prescription, pupillary distance, fitting height, back vertex distance, pantoscopic angle and curvature of the frame) were compared to power optimized PAL--Rodenstock's Multigressiv MyView (respecting only prescription power and pupillary distance). Adaptation process was monitored over a period of four weeks. The collected results represent scores of user's subjective impressions, where the users themselves rated their adaptation to new progressive glasses and the degree of subjective visual impression. The results show that adaptation time to fully individually fit PAL is easier and quickly. The information obtained from users is valuable in everyday optometry practice because along with the manufacturer's specifications, the user's experience can

  10. An Adaptive Cauchy Differential Evolution Algorithm for Global Numerical Optimization

    PubMed Central

    Choi, Tae Jong; Ahn, Chang Wook; An, Jinung

    2013-01-01

    Adaptation of control parameters, such as scaling factor (F), crossover rate (CR), and population size (NP), appropriately is one of the major problems of Differential Evolution (DE) literature. Well-designed adaptive or self-adaptive parameter control method can highly improve the performance of DE. Although there are many suggestions for adapting the control parameters, it is still a challenging task to properly adapt the control parameters for problem. In this paper, we present an adaptive parameter control DE algorithm. In the proposed algorithm, each individual has its own control parameters. The control parameters of each individual are adapted based on the average parameter value of successfully evolved individuals' parameter values by using the Cauchy distribution. Through this, the control parameters of each individual are assigned either near the average parameter value or far from that of the average parameter value which might be better parameter value for next generation. The experimental results show that the proposed algorithm is more robust than the standard DE algorithm and several state-of-the-art adaptive DE algorithms in solving various unimodal and multimodal problems. PMID:23935445

  11. An adaptive Cauchy differential evolution algorithm for global numerical optimization.

    PubMed

    Choi, Tae Jong; Ahn, Chang Wook; An, Jinung

    2013-01-01

    Adaptation of control parameters, such as scaling factor (F), crossover rate (CR), and population size (NP), appropriately is one of the major problems of Differential Evolution (DE) literature. Well-designed adaptive or self-adaptive parameter control method can highly improve the performance of DE. Although there are many suggestions for adapting the control parameters, it is still a challenging task to properly adapt the control parameters for problem. In this paper, we present an adaptive parameter control DE algorithm. In the proposed algorithm, each individual has its own control parameters. The control parameters of each individual are adapted based on the average parameter value of successfully evolved individuals' parameter values by using the Cauchy distribution. Through this, the control parameters of each individual are assigned either near the average parameter value or far from that of the average parameter value which might be better parameter value for next generation. The experimental results show that the proposed algorithm is more robust than the standard DE algorithm and several state-of-the-art adaptive DE algorithms in solving various unimodal and multimodal problems.

  12. Adaptive Estimation of Intravascular Shear Rate Based on Parameter Optimization

    NASA Astrophysics Data System (ADS)

    Nitta, Naotaka; Takeda, Naoto

    2008-05-01

    The relationships between the intravascular wall shear stress, controlled by flow dynamics, and the progress of arteriosclerosis plaque have been clarified by various studies. Since the shear stress is determined by the viscosity coefficient and shear rate, both factors must be estimated accurately. In this paper, an adaptive method for improving the accuracy of quantitative shear rate estimation was investigated. First, the parameter dependence of the estimated shear rate was investigated in terms of the differential window width and the number of averaged velocity profiles based on simulation and experimental data, and then the shear rate calculation was optimized. The optimized result revealed that the proposed adaptive method of shear rate estimation was effective for improving the accuracy of shear rate calculation.

  13. Optimal design of an unsupervised adaptive classifier with unknown priors

    NASA Technical Reports Server (NTRS)

    Kazakos, D.

    1974-01-01

    An adaptive detection scheme for M hypotheses was analyzed. It was assumed that the probability density function under each hypothesis was known, and that the prior probabilities of the M hypotheses were unknown and sequentially estimated. Each observation vector was classified using the current estimate of the prior probabilities. Using a set of nonlinear transformations, and applying stochastic approximation theory, an optimally converging adaptive detection and estimation scheme was designed. The optimality of the scheme lies in the fact that convergence to the true prior probabilities is ensured, and that the asymptotic error variance is minimum, for the class of nonlinear transformations considered. An expression for the asymptotic mean square error variance of the scheme was also obtained.

  14. Optimal and adaptive methods of processing hydroacoustic signals (review)

    NASA Astrophysics Data System (ADS)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  15. Adaptive particle swarm optimization for optimal orbital elements of binary stars

    NASA Astrophysics Data System (ADS)

    Attia, Abdel-Fattah

    2016-12-01

    The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.

  16. On l(1): Optimal decentralized performance

    NASA Technical Reports Server (NTRS)

    Sourlas, Dennis; Manousiouthakis, Vasilios

    1993-01-01

    In this paper, the Manousiouthakis parametrization of all decentralized stabilizing controllers is employed in mathematically formulating the l(sup 1) optimal decentralized controller synthesis problem. The resulting optimization problem is infinite dimensional and therefore not directly amenable to computations. It is shown that finite dimensional optimization problems that have value arbitrarily close to the infinite dimensional one can be constructed. Based on this result, an algorithm that solves the l(sup 1) decentralized performance problems is presented. A global optimization approach to the solution of the infinite dimensional approximating problems is also discussed.

  17. Implementation and Performance Issues in Collaborative Optimization

    NASA Technical Reports Server (NTRS)

    Braun, Robert; Gage, Peter; Kroo, Ilan; Sobieski, Ian

    1996-01-01

    Collaborative optimization is a multidisciplinary design architecture that is well-suited to large-scale multidisciplinary optimization problems. This paper compares this approach with other architectures, examines the details of the formulation, and some aspects of its performance. A particular version of the architecture is proposed to better accommodate the occurrence of multiple feasible regions. The use of system level inequality constraints is shown to increase the convergence rate. A series of simple test problems, demonstrated to challenge related optimization architectures, is successfully solved with collaborative optimization.

  18. A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment

    NASA Astrophysics Data System (ADS)

    Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir

    2015-07-01

    This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0-238 N s m-1 through the viscous and electromagnetic components, respectively.

  19. Performance optimization of helicopter rotor blades

    NASA Technical Reports Server (NTRS)

    Walsh, Joanne L.

    1991-01-01

    As part of a center-wide activity at NASA Langley Research Center to develop multidisciplinary design procedures by accounting for discipline interactions, a performance design optimization procedure is developed. The procedure optimizes the aerodynamic performance of rotor blades by selecting the point of taper initiation, root chord, taper ratio, and maximum twist which minimize hover horsepower while not degrading forward flight performance. The procedure uses HOVT (a strip theory momentum analysis) to compute the horse power required for hover and the comprehensive helicopter analysis program CAMRAD to compute the horsepower required for forward flight and maneuver. The optimization algorithm consists of the general purpose optimization program CONMIN and approximate analyses. Sensitivity analyses consisting of derivatives of the objective function and constraints are carried out by forward finite differences. The procedure is applied to a test problem which is an analytical model of a wind tunnel model of a utility rotor blade.

  20. Pulsed Inductive Plasma Acceleration: Performance Optimization Criteria

    NASA Technical Reports Server (NTRS)

    Polzin, Kurt A.

    2014-01-01

    Optimization criteria for pulsed inductive plasma acceleration are developed using an acceleration model consisting of a set of coupled circuit equations describing the time-varying current in the thruster and a one-dimensional momentum equation. The model is nondimensionalized, resulting in the identification of several scaling parameters that are varied to optimize the performance of the thruster. The analysis reveals the benefits of underdamped current waveforms and leads to a performance optimization criterion that requires the matching of the natural period of the discharge and the acceleration timescale imposed by the inertia of the working gas. In addition, the performance increases when a greater fraction of the propellant is initially located nearer to the inductive acceleration coil. While the dimensionless model uses a constant temperature formulation in calculating performance, the scaling parameters that yield the optimum performance are shown to be relatively invariant if a self-consistent description of energy in the plasma is instead used.

  1. Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

    NASA Astrophysics Data System (ADS)

    Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

    2016-10-01

    Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

  2. A novel adaptive Cuckoo search for optimal query plan generation.

    PubMed

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  3. Adaptive Multi-Agent Systems for Constrained Optimization

    NASA Technical Reports Server (NTRS)

    Macready, William; Bieniawski, Stefan; Wolpert, David H.

    2004-01-01

    Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

  4. In-flight performance optimization for rotorcraft with redundant controls

    NASA Astrophysics Data System (ADS)

    Ozdemir, Gurbuz Taha

    A conventional helicopter has limits on performance at high speeds because of the limitations of main rotor, such as compressibility issues on advancing side or stall issues on retreating side. Auxiliary lift and thrust components have been suggested to improve performance of the helicopter substantially by reducing the loading on the main rotor. Such a configuration is called the compound rotorcraft. Rotor speed can also be varied to improve helicopter performance. In addition to improved performance, compound rotorcraft and variable RPM can provide a much larger degree of control redundancy. This additional redundancy gives the opportunity to further enhance performance and handling qualities. A flight control system is designed to perform in-flight optimization of redundant control effectors on a compound rotorcraft in order to minimize power required and extend range. This "Fly to Optimal" (FTO) control law is tested in simulation using the GENHEL model. A model of the UH-60, a compound version of the UH-60A with lifting wing and vectored thrust ducted propeller (VTDP), and a generic compound version of the UH-60A with lifting wing and propeller were developed and tested in simulation. A model following dynamic inversion controller is implemented for inner loop control of roll, pitch, yaw, heave, and rotor RPM. An outer loop controller regulates airspeed and flight path during optimization. A Golden Section search method was used to find optimal rotor RPM on a conventional helicopter, where the single redundant control effector is rotor RPM. The FTO builds off of the Adaptive Performance Optimization (APO) method of Gilyard by performing low frequency sweeps on a redundant control for a fixed wing aircraft. A method based on the APO method was used to optimize trim on a compound rotorcraft with several redundant control effectors. The controller can be used to optimize rotor RPM and compound control effectors through flight test or simulations in order to

  5. Optimal control law for classical and multiconjugate adaptive optics.

    PubMed

    Le Roux, Brice; Conan, Jean-Marc; Kulcsár, Caroline; Raynaud, Henri-François; Mugnier, Laurent M; Fusco, Thierry

    2004-07-01

    Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems.

  6. Modeling for deformable mirrors and the adaptive optics optimization program

    SciTech Connect

    Henesian, M.A.; Haney, S.W.; Trenholme, J.B.; Thomas, M.

    1997-03-18

    We discuss aspects of adaptive optics optimization for large fusion laser systems such as the 192-arm National Ignition Facility (NIF) at LLNL. By way of example, we considered the discrete actuator deformable mirror and Hartmann sensor system used on the Beamlet laser. Beamlet is a single-aperture prototype of the 11-0-5 slab amplifier design for NIF, and so we expect similar optical distortion levels and deformable mirror correction requirements. We are now in the process of developing a numerically efficient object oriented C++ language implementation of our adaptive optics and wavefront sensor code, but this code is not yet operational. Results are based instead on the prototype algorithms, coded-up in an interpreted array processing computer language.

  7. Adaptive Optimal Control Using Frequency Selective Information of the System Uncertainty With Application to Unmanned Aircraft.

    PubMed

    Maity, Arnab; Hocht, Leonhard; Heise, Christian; Holzapfel, Florian

    2016-11-28

    A new efficient adaptive optimal control approach is presented in this paper based on the indirect model reference adaptive control (MRAC) architecture for improvement of adaptation and tracking performance of the uncertain system. The system accounts here for both matched and unmatched unknown uncertainties that can act as plant as well as input effectiveness failures or damages. For adaptation of the unknown parameters of these uncertainties, the frequency selective learning approach is used. Its idea is to compute a filtered expression of the system uncertainty using multiple filters based on online instantaneous information, which is used for augmentation of the update law. It is capable of adjusting a sudden change in system dynamics without depending on high adaptation gains and can satisfy exponential parameter error convergence under certain conditions in the presence of structured matched and unmatched uncertainties as well. Additionally, the controller of the MRAC system is designed using a new optimal control method. This method is a new linear quadratic regulator-based optimal control formulation for both output regulation and command tracking problems. It provides a closed-form control solution. The proposed overall approach is applied in a control of lateral dynamics of an unmanned aircraft problem to show its effectiveness.

  8. Hybrid Self-Adaptive Evolution Strategies Guided by Neighborhood Structures for Combinatorial Optimization Problems.

    PubMed

    Coelho, V N; Coelho, I M; Souza, M J F; Oliveira, T A; Cota, L P; Haddad, M N; Mladenovic, N; Silva, R C P; Guimarães, F G

    2016-01-01

    This article presents an Evolution Strategy (ES)--based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration-exploitation balance. To validate the proposal, this framework is applied to solve three different [Formula: see text]-Hard combinatorial optimization problems: an Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks, an Unrelated Parallel Machine Scheduling Problem with Setup Times, and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results point out the convergence of the proposed model and highlight its ability in combining the application of move operations from distinct neighborhood structures along the optimization. The results gathered and reported in this article represent a collective evidence of the performance of the method in challenging combinatorial optimization problems from different application domains. The proposed evolution strategy demonstrates an ability of adapting the strength of the mutation disturbance during the generations of its evolution process. The effectiveness of the proposal motivates the application of this novel evolutionary framework for solving other combinatorial optimization problems.

  9. Performance optimization of digital VLSI circuits

    SciTech Connect

    Marple, D.P.

    1987-01-01

    Designers of digital VLSI circuits have virtually no computer tools available for the optimization of circuit performance. Instead, a designer relies extensively on circuit-analysis tools, such as circuit simulation (SPICE) and/or critical-delay-path analysis. A circuit-analysis approach to digital design is very labor-intensive and seldom produces a circuit with optimum area/delay or power/delay trade off. The goal of this research is to provide a synthesis approach to the design of digital circuits by finding the sizes of transistors that optimize circuits by finding the sizes of transistors that optimize circuit performance (delay, area, power). Solutions are found that are optimum for all possible delay paths of a given circuit and not for just a single path. The approach of this research is to formulate the problem of area/delay or power/delay optimization as a nonlinear program. Conditions for optimality are then established using graph theory and Kuhn-Tucker conditions. Finally, the use of augmented-Lagrangian and projected-Lagrangian algorithms are reviewed for the solution of the nonlinear programs. Two computer programs, PLATO and COP, were developed by the author to optimize CMOS PLA's (PLATO) and general CMOS circuits (COP). These tools provably find the globally optimum transistor sizes for a given circuit. Results are presented for PLA's and small- to medium-sized cells.

  10. A Computational Model of Optimal Vein Graft Adaptation in an Arterial Environment

    NASA Astrophysics Data System (ADS)

    Ramachandra, Abhay B.; Sankaran, Sethuraman; Humphrey, Jay; Marsden, Alison

    2012-11-01

    In coronary artery disease, surgical revascularization using venous bypass grafts is performed to relieve symptoms and prolong life. Coronary bypass graft surgery is performed on approximately 500,000 people every year in the United States, with graft failure rates as high as 50% within 5 years. When a vein graft is implanted in the arterial system it adapts to the high flow rate and high pressure of the arterial environment by changing composition and geometry, and thus stiffness. Hemodynamic loads, resulting in altered wall shear and intramural stresses, are major factors impacting vein graft remodeling. Here, a constrained mixture theory of growth and remodeling for arteries is extended to model the evolution of a vein graft subjected to arterial flow and pressure conditions. A derivative-free optimization method is used to estimate the optimal set of constitutive parameters that best match passive biaxial mouse inferior vena cava data from experiments. Optimization is performed using surrogate management framework, a pattern search method with established convergence theory. The resulting parameter set is used to predict optimal vein adaptation in an arterial environment for two illustrative cases: a) Step change b) Gradual change in loading. Results are compared against vein graft data from the literature and a possible set of mechanisms for sub-optimal vein graft remodeling is suggested.

  11. Performance evaluation of a sensorless adaptive optics multiphoton microscope.

    PubMed

    Skorsetz, Martin; Artal, Pablo; Bueno, Juan M

    2016-03-01

    A wavefront sensorless adaptive optics technique was combined with a custom-made multiphoton microscope to correct for specimen-induced aberrations. A liquid-crystal-on-silicon (LCoS) modulator was used to systematically generate Zernike modes during image recording. The performance of the instrument was evaluated in samples providing different nonlinear signals and the benefit of correcting higher order aberrations was always noticeable (in both contrast and resolution). The optimum aberration pattern was stable in time for the samples here involved. For a particular depth location within the sample, the wavefront to be precompensated was independent on the size of the imaged area (up to ∼ 360 × 360 μm(2)). The mode combination optimizing the recorded image depended on the Zernike correction control sequence; however, the final images hardly differed. At deeper locations, a noticeable dominance of spherical aberration was found. The influence of other aberration terms was also compared to the effect of the spherical aberration.

  12. Optimal performance of a quantum Otto refrigerator

    NASA Astrophysics Data System (ADS)

    Abah, Obinna; Lutz, Eric

    2016-03-01

    We consider a quantum Otto refrigerator cycle of a time-dependent harmonic oscillator. We investigate the coefficient of performance at maximum figure of merit for adiabatic and nonadiabatic frequency modulations. We obtain analytical expressions for the optimal performance both in the high-temperature (classical) regime and in the low-temperature (quantum) limit. We moreover analyze the breakdown of the cooling cycle for strongly nonadiabatic driving protocols and derive analytical estimates for the minimal driving time allowed for cooling.

  13. Efficient retrieval of landscape Hessian: Forced optimal covariance adaptive learning

    NASA Astrophysics Data System (ADS)

    Shir, Ofer M.; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

    2014-06-01

    Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳104). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

  14. Efficient retrieval of landscape Hessian: forced optimal covariance adaptive learning.

    PubMed

    Shir, Ofer M; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

    2014-06-01

    Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳10^{4}). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

  15. Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

    NASA Technical Reports Server (NTRS)

    Shiao, Michael C.; Chamis, Christos C.

    1994-01-01

    The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

  16. Optimizing Satellite Communications With Adaptive and Phased Array Antennas

    NASA Technical Reports Server (NTRS)

    Ingram, Mary Ann; Romanofsky, Robert; Lee, Richard Q.; Miranda, Felix; Popovic, Zoya; Langley, John; Barott, William C.; Ahmed, M. Usman; Mandl, Dan

    2004-01-01

    A new adaptive antenna array architecture for low-earth-orbiting satellite ground stations is being investigated. These ground stations are intended to have no moving parts and could potentially be operated in populated areas, where terrestrial interference is likely. The architecture includes multiple, moderately directive phased arrays. The phased arrays, each steered in the approximate direction of the satellite, are adaptively combined to enhance the Signal-to-Noise and Interference-Ratio (SNIR) of the desired satellite. The size of each phased array is to be traded-off with the number of phased arrays, to optimize cost, while meeting a bit-error-rate threshold. Also, two phased array architectures are being prototyped: a spacefed lens array and a reflect-array. If two co-channel satellites are in the field of view of the phased arrays, then multi-user detection techniques may enable simultaneous demodulation of the satellite signals, also known as Space Division Multiple Access (SDMA). We report on Phase I of the project, in which fixed directional elements are adaptively combined in a prototype to demodulate the S-band downlink of the EO-1 satellite, which is part of the New Millennium Program at NASA.

  17. Optimal spectral tracking--adapting to dynamic regime change.

    PubMed

    Brittain, John-Stuart; Halliday, David M

    2011-01-30

    Real world data do not always obey the statistical restraints imposed upon them by sophisticated analysis techniques. In spectral analysis for instance, an ergodic process--the interchangeability of temporal for spatial averaging--is assumed for a repeat-trial design. Many evolutionary scenarios, such as learning and motor consolidation, do not conform to such linear behaviour and should be approached from a more flexible perspective. To this end we previously introduced the method of optimal spectral tracking (OST) in the study of trial-varying parameters. In this extension to our work we modify the OST routines to provide an adaptive implementation capable of reacting to dynamic transitions in the underlying system state. In so doing, we generalise our approach to characterise both slow-varying and rapid fluctuations in time-series, simultaneously providing a metric of system stability. The approach is first applied to a surrogate dataset and compared to both our original non-adaptive solution and spectrogram approaches. The adaptive OST is seen to display fast convergence and desirable statistical properties. All three approaches are then applied to a neurophysiological recording obtained during a study on anaesthetic monitoring. Local field potentials acquired from the posterior hypothalamic region of a deep brain stimulation patient undergoing anaesthesia were analysed. The characterisation of features such as response delay, time-to-peak and modulation brevity are considered.

  18. Sleep As A Strategy For Optimizing Performance.

    PubMed

    Yarnell, Angela M; Deuster, Patricia

    2016-01-01

    Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance.

  19. Policy iteration optimal tracking control for chaotic systems by using an adaptive dynamic programming approach

    NASA Astrophysics Data System (ADS)

    Wei, Qing-Lai; Liu, De-Rong; Xu, Yan-Cai

    2015-03-01

    A policy iteration algorithm of adaptive dynamic programming (ADP) is developed to solve the optimal tracking control for a class of discrete-time chaotic systems. By system transformations, the optimal tracking problem is transformed into an optimal regulation one. The policy iteration algorithm for discrete-time chaotic systems is first described. Then, the convergence and admissibility properties of the developed policy iteration algorithm are presented, which show that the transformed chaotic system can be stabilized under an arbitrary iterative control law and the iterative performance index function simultaneously converges to the optimum. By implementing the policy iteration algorithm via neural networks, the developed optimal tracking control scheme for chaotic systems is verified by a simulation. Project supported by the National Natural Science Foundation of China (Grant Nos. 61034002, 61233001, 61273140, 61304086, and 61374105) and the Beijing Natural Science Foundation, China (Grant No. 4132078).

  20. An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

    PubMed

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

  1. Comparison of several stochastic parallel optimization algorithms for adaptive optics system without a wavefront sensor

    NASA Astrophysics Data System (ADS)

    Yang, Huizhen; Li, Xinyang

    2011-04-01

    Optimizing the system performance metric directly is an important method for correcting wavefront aberrations in an adaptive optics (AO) system where wavefront sensing methods are unavailable or ineffective. An appropriate "Deformable Mirror" control algorithm is the key to successful wavefront correction. Based on several stochastic parallel optimization control algorithms, an adaptive optics system with a 61-element Deformable Mirror (DM) is simulated. Genetic Algorithm (GA), Stochastic Parallel Gradient Descent (SPGD), Simulated Annealing (SA) and Algorithm Of Pattern Extraction (Alopex) are compared in convergence speed and correction capability. The results show that all these algorithms have the ability to correct for atmospheric turbulence. Compared with least squares fitting, they almost obtain the best correction achievable for the 61-element DM. SA is the fastest and GA is the slowest in these algorithms. The number of perturbation by GA is almost 20 times larger than that of SA, 15 times larger than SPGD and 9 times larger than Alopex.

  2. Performance of keck adaptive optics with sodium laser guide star

    SciTech Connect

    Gavel, D.T.; Olivier, S.; Brase, J.

    1996-03-08

    The Keck telescope adaptive optics system is designed to optimize performance in he 1 to 3 micron region of observation wavelengths (J, H, and K astronomical bands). The system uses a 249 degree of freedom deformable mirror, so that the interactuator spacing is 56 cm as mapped onto the 10 meter aperture. 56 cm is roughly equal to r0 at 1.4 microns, which implies the wavefront fitting error is 0.52 ({lambda}/2{pi})({ital d}/{ital r}{sub 0}){sup 5/6} = 118 nm rms. This is sufficient to produce a system Strehl of 0.74 at 1.4 microns if all other sources of error are negligible, which would be the case with a bright natural guidestar and very high control bandwidth. Other errors associated with the adaptive optics will however contribute to Strehl degradation, namely, servo bandwidth error due to inability to reject all temporal frequencies of the aberrated wavefront, wavefront measurement error due to finite signal-to-noise ratio in the wavefront sensor, and, in the case of a laser guidestar, the so-called cone effect where rays from the guidestar beacon fail to sample some of the upper atmosphere turbulence. Cone effect is mitigated considerably by the use of the very high altitude sodium laser guidestar (90 km altitude), as opposed to Rayleigh beacons at 20 km. However, considering the Keck telescope`s large aperture, this is still the dominating wavefront error contributor in the current adaptive optics system design.

  3. Pursuing optimal electric machines transient diagnosis: The adaptive slope transform

    NASA Astrophysics Data System (ADS)

    Pons-Llinares, Joan; Riera-Guasp, Martín; Antonino-Daviu, Jose A.; Habetler, Thomas G.

    2016-12-01

    The aim of this paper is to introduce a new linear time-frequency transform to improve the detection of fault components in electric machines transient currents. Linear transforms are analysed from the perspective of the atoms used. A criterion to select the atoms at every point of the time-frequency plane is proposed, taking into account the characteristics of the searched component at each point. This criterion leads to the definition of the Adaptive Slope Transform, which enables a complete and optimal capture of the different components evolutions in a transient current. A comparison with conventional linear transforms (Short-Time Fourier Transform and Wavelet Transform) is carried out, showing their inherent limitations. The approach is tested with laboratory and field motors, and the Lower Sideband Harmonic is captured for the first time during an induction motor startup and subsequent load oscillations, accurately tracking its evolution.

  4. Error sensitivity to refinement: a criterion for optimal grid adaptation

    NASA Astrophysics Data System (ADS)

    Luchini, Paolo; Giannnetti, Flavio; Citro, Vincenzo

    2016-11-01

    Most indicators used for automatic grid refinement are suboptimal, in the sense that they do not really minimize the global solution error. This paper concerns with a new indicator, related to the sensitivity map of global stability problems, suitable for an optimal grid refinement that minimizes the global solution error. The new criterion is derived from the properties of the adjoint operator and provides a map of the sensitivity of the global error (or its estimate) to a local mesh refinement. Examples are presented for both a scalar partial differential equation and for the system of Navier-Stokes equations. In the last case, we also present a grid-adaptation algorithm based on the new estimator and on the FreeFem++ software that improves the accuracy of the solution of almost two order of magnitude by redistributing the nodes of the initial computational mesh.

  5. Lossless image compression based on optimal prediction, adaptive lifting, and conditional arithmetic coding.

    PubMed

    Boulgouris, N V; Tzovaras, D; Strintzis, M G

    2001-01-01

    The optimal predictors of a lifting scheme in the general n-dimensional case are obtained and applied for the lossless compression of still images using first quincunx sampling and then simple row-column sampling. In each case, the efficiency of the linear predictors is enhanced nonlinearly. Directional postprocessing is used in the quincunx case, and adaptive-length postprocessing in the row-column case. Both methods are seen to perform well. The resulting nonlinear interpolation schemes achieve extremely efficient image decorrelation. We further investigate context modeling and adaptive arithmetic coding of wavelet coefficients in a lossless compression framework. Special attention is given to the modeling contexts and the adaptation of the arithmetic coder to the actual data. Experimental evaluation shows that the best of the resulting coders produces better results than other known algorithms for multiresolution-based lossless image coding.

  6. Aircraft design optimization with multidisciplinary performance criteria

    NASA Technical Reports Server (NTRS)

    Morris, Stephen; Kroo, Ilan

    1989-01-01

    The method described here for aircraft design optimization with dynamic response considerations provides an inexpensive means of integrating dynamics into aircraft preliminary design. By defining a dynamic performance index that can be added to a conventional objective function, a designer can investigate the trade-off between performance and handling (as measured by the vehicle's unforced response). The procedure is formulated to permit the use of control system gains as design variables, but does not require full-state feedback. The examples discussed here show how such an approach can lead to significant improvements in the design as compared with the more common sequential design of system and control law.

  7. Cognitive radio adaptation for power consumption minimization using biogeography-based optimization

    NASA Astrophysics Data System (ADS)

    Qi, Pei-Han; Zheng, Shi-Lian; Yang, Xiao-Niu; Zhao, Zhi-Jin

    2016-12-01

    Adaptation is one of the key capabilities of cognitive radio, which focuses on how to adjust the radio parameters to optimize the system performance based on the knowledge of the radio environment and its capability and characteristics. In this paper, we consider the cognitive radio adaptation problem for power consumption minimization. The problem is formulated as a constrained power consumption minimization problem, and the biogeography-based optimization (BBO) is introduced to solve this optimization problem. A novel habitat suitability index (HSI) evaluation mechanism is proposed, in which both the power consumption minimization objective and the quality of services (QoS) constraints are taken into account. The results show that under different QoS requirement settings corresponding to different types of services, the algorithm can minimize power consumption while still maintaining the QoS requirements. Comparison with particle swarm optimization (PSO) and cat swarm optimization (CSO) reveals that BBO works better, especially at the early stage of the search, which means that the BBO is a better choice for real-time applications. Project supported by the National Natural Science Foundation of China (Grant No. 61501356), the Fundamental Research Funds of the Ministry of Education, China (Grant No. JB160101), and the Postdoctoral Fund of Shaanxi Province, China.

  8. Performance-optimized clinical IMRT planning on modern CPUs

    NASA Astrophysics Data System (ADS)

    Ziegenhein, Peter; Kamerling, Cornelis Ph; Bangert, Mark; Kunkel, Julian; Oelfke, Uwe

    2013-06-01

    Intensity modulated treatment plan optimization is a computationally expensive task. The feasibility of advanced applications in intensity modulated radiation therapy as every day treatment planning, frequent re-planning for adaptive radiation therapy and large-scale planning research severely depends on the runtime of the plan optimization implementation. Modern computational systems are built as parallel architectures to yield high performance. The use of GPUs, as one class of parallel systems, has become very popular in the field of medical physics. In contrast we utilize the multi-core central processing unit (CPU), which is the heart of every modern computer and does not have to be purchased additionally. In this work we present an ultra-fast, high precision implementation of the inverse plan optimization problem using a quasi-Newton method on pre-calculated dose influence data sets. We redefined the classical optimization algorithm to achieve a minimal runtime and high scalability on CPUs. Using the proposed methods in this work, a total plan optimization process can be carried out in only a few seconds on a low-cost CPU-based desktop computer at clinical resolution and quality. We have shown that our implementation uses the CPU hardware resources efficiently with runtimes comparable to GPU implementations, at lower costs.

  9. Performance-optimized clinical IMRT planning on modern CPUs.

    PubMed

    Ziegenhein, Peter; Kamerling, Cornelis Ph; Bangert, Mark; Kunkel, Julian; Oelfke, Uwe

    2013-06-07

    Intensity modulated treatment plan optimization is a computationally expensive task. The feasibility of advanced applications in intensity modulated radiation therapy as every day treatment planning, frequent re-planning for adaptive radiation therapy and large-scale planning research severely depends on the runtime of the plan optimization implementation. Modern computational systems are built as parallel architectures to yield high performance. The use of GPUs, as one class of parallel systems, has become very popular in the field of medical physics. In contrast we utilize the multi-core central processing unit (CPU), which is the heart of every modern computer and does not have to be purchased additionally. In this work we present an ultra-fast, high precision implementation of the inverse plan optimization problem using a quasi-Newton method on pre-calculated dose influence data sets. We redefined the classical optimization algorithm to achieve a minimal runtime and high scalability on CPUs. Using the proposed methods in this work, a total plan optimization process can be carried out in only a few seconds on a low-cost CPU-based desktop computer at clinical resolution and quality. We have shown that our implementation uses the CPU hardware resources efficiently with runtimes comparable to GPU implementations, at lower costs.

  10. An adaptive /N-body algorithm of optimal order

    NASA Astrophysics Data System (ADS)

    Pruett, C. David; Rudmin, Joseph W.; Lacy, Justin M.

    2003-05-01

    Picard iteration is normally considered a theoretical tool whose primary utility is to establish the existence and uniqueness of solutions to first-order systems of ordinary differential equations (ODEs). However, in 1996, Parker and Sochacki [Neural, Parallel, Sci. Comput. 4 (1996)] published a practical numerical method for a certain class of ODEs, based upon modified Picard iteration, that generates the Maclaurin series of the solution to arbitrarily high order. The applicable class of ODEs consists of first-order, autonomous systems whose right-hand side functions (generators) are projectively polynomial; that is, they can be written as polynomials in the unknowns. The class is wider than might be expected. The method is ideally suited to the classical N-body problem, which is projectively polynomial. Here, we recast the N-body problem in polynomial form and develop a Picard-based algorithm for its solution. The algorithm is highly accurate, parameter-free, and simultaneously adaptive in time and order. Test cases for both benign and chaotic N-body systems reveal that optimal order is dynamic. That is, in addition to dependency upon N and the desired accuracy, optimal order depends upon the configuration of the bodies at any instant.

  11. Morphology optimization for enhanced performance in organic photovoltaics

    NASA Astrophysics Data System (ADS)

    Wodo, Olga; Zola, Jaroslaw; Ganapathysubramanian, Baskar

    2015-03-01

    Organic solar cells have the potential for widespread usage due to their low cost-per-watt and mechanical flexibility. Their wide spread use, however, is bottlenecked primarily by their low solar efficiencies. Experimental evidence suggests that a key property determining the solar efficiency of such devices is the final morphological distribution of the electron-donor and electron-acceptor constituents. By carefully designing the morphology of the device, one could potentially significantly enhance their performance. This is an area of intense experimental effort that is mostly trial-and-error based, and serves as a fertile area for introducing mechanics and computational thinking. In this work, we use optimization techniques coupled with computational modeling to identify the optimal structures for high efficiency solar cells. In particular, we use adaptive population-based incremental learning method linked to graph-based surrogate model to evaluate properties for given structure. We study several different criterions and find optimal structure that that improve the performance of currently hypothesized optimal structures by 29%.

  12. Improvement of Adaptive Cruise Control Performance

    NASA Astrophysics Data System (ADS)

    Miyata, Shigeharu; Nakagami, Takashi; Kobayashi, Sei; Izumi, Tomoji; Naito, Hisayoshi; Yanou, Akira; Nakamura, Hitomi; Takehara, Shin

    2010-12-01

    This paper describes the Adaptive Cruise Control system (ACC), a system which reduces the driving burden on the driver. The ACC system primarily supports four driving modes on the road and controls the acceleration and deceleration of the vehicle in order to maintain a set speed or to avoid a crash. This paper proposes more accurate methods of detecting the preceding vehicle by radar while cornering, with consideration for the vehicle sideslip angle, and also of controlling the distance between vehicles. By making full use of the proposed identification logic for preceding vehicles and path estimation logic, an improvement in driving stability was achieved.

  13. Optimized adaptation algorithm for HEVC/H.265 dynamic adaptive streaming over HTTP using variable segment duration

    NASA Astrophysics Data System (ADS)

    Irondi, Iheanyi; Wang, Qi; Grecos, Christos

    2016-04-01

    Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next

  14. Enhancing astronaut performance using sensorimotor adaptability training

    PubMed Central

    Bloomberg, Jacob J.; Peters, Brian T.; Cohen, Helen S.; Mulavara, Ajitkumar P.

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments—enhancing their ability to “learn to learn.” We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts. PMID:26441561

  15. Automated Cache Performance Analysis And Optimization

    SciTech Connect

    Mohror, Kathryn

    2013-12-23

    While there is no lack of performance counter tools for coarse-grained measurement of cache activity, there is a critical lack of tools for relating data layout to cache behavior to application performance. Generally, any nontrivial optimizations are either not done at all, or are done ”by hand” requiring significant time and expertise. To the best of our knowledge no tool available to users measures the latency of memory reference instructions for partic- ular addresses and makes this information available to users in an easy-to-use and intuitive way. In this project, we worked to enable the Open|SpeedShop performance analysis tool to gather memory reference latency information for specific instructions and memory ad- dresses, and to gather and display this information in an easy-to-use and intuitive way to aid performance analysts in identifying problematic data structures in their codes. This tool was primarily designed for use in the supercomputer domain as well as grid, cluster, cloud-based parallel e-commerce, and engineering systems and middleware. Ultimately, we envision a tool to automate optimization of application cache layout and utilization in the Open|SpeedShop performance analysis tool. To commercialize this soft- ware, we worked to develop core capabilities for gathering enhanced memory usage per- formance data from applications and create and apply novel methods for automatic data structure layout optimizations, tailoring the overall approach to support existing supercom- puter and cluster programming models and constraints. In this Phase I project, we focused on infrastructure necessary to gather performance data and present it in an intuitive way to users. With the advent of enhanced Precise Event-Based Sampling (PEBS) counters on recent Intel processor architectures and equivalent technology on AMD processors, we are now in a position to access memory reference information for particular addresses. Prior to the introduction of PEBS counters

  16. Modeling Cooperative Threads to Project GPU Performance for Adaptive Parallelism

    SciTech Connect

    Meng, Jiayuan; Uram, Thomas; Morozov, Vitali A.; Vishwanath, Venkatram; Kumaran, Kalyan

    2015-01-01

    Most accelerators, such as graphics processing units (GPUs) and vector processors, are particularly suitable for accelerating massively parallel workloads. On the other hand, conventional workloads are developed for multi-core parallelism, which often scale to only a few dozen OpenMP threads. When hardware threads significantly outnumber the degree of parallelism in the outer loop, programmers are challenged with efficient hardware utilization. A common solution is to further exploit the parallelism hidden deep in the code structure. Such parallelism is less structured: parallel and sequential loops may be imperfectly nested within each other, neigh boring inner loops may exhibit different concurrency patterns (e.g. Reduction vs. Forall), yet have to be parallelized in the same parallel section. Many input-dependent transformations have to be explored. A programmer often employs a larger group of hardware threads to cooperatively walk through a smaller outer loop partition and adaptively exploit any encountered parallelism. This process is time-consuming and error-prone, yet the risk of gaining little or no performance remains high for such workloads. To reduce risk and guide implementation, we propose a technique to model workloads with limited parallelism that can automatically explore and evaluate transformations involving cooperative threads. Eventually, our framework projects the best achievable performance and the most promising transformations without implementing GPU code or using physical hardware. We envision our technique to be integrated into future compilers or optimization frameworks for autotuning.

  17. Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.; Thompson, David R.; Hsiang, Kian

    2013-01-01

    This work was designed to find a way to optimally (or near optimally) sample spatiotemporal phenomena based on limited sensing capability, and to create a model that can be run to estimate uncertainties, as well as to estimate covariances. The goal was to maximize (or minimize) some function of the overall uncertainty. The uncertainties and covariances were modeled presuming a parametric distribution, and then the model was used to approximate the overall information gain, and consequently, the objective function from each potential sense. These candidate sensings were then crosschecked against operation costs and feasibility. Consequently, an operations plan was derived that combined both operational constraints/costs and sensing gain. Probabilistic modeling was used to perform an approximate inversion of the model, which enabled calculation of sensing gains, and subsequent combination with operational costs. This incorporation of operations models to assess cost and feasibility for specific classes of vehicles is unique.

  18. Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

    NASA Astrophysics Data System (ADS)

    Kmet', Tibor; Kmet'ov, Mria

    2010-09-01

    A neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints and open final time. The optimal control problem is transcribed into nonlinear programming problem, which is implemented with adaptive critic neural network [9] and recurrent neural network for solving nonlinear proprojection equations [10]. The proposed simulation methods is illustrated by the optimal control problem of feeding adaptation of filter feeders of Daphnia. Results show that adaptive critic based systematic approach and neural network solving of nonlinear equations hold promise for obtaining the optimal control with control and state constraints and open final time.

  19. Contemporary nutrition approaches to optimize elite marathon performance.

    PubMed

    Stellingwerff, Trent

    2013-09-01

    The professionalization of any sport must include an appreciation for how and where nutrition can positively affect training adaptation and/or competition performance. Furthermore, there is an ever-increasing importance of nutrition in sports that feature very high training volumes and are of a long enough duration that both glycogen and fluid balance can limit performance. Indeed, modern marathon training programs and racing satisfy these criteria and are uniquely suited to benefit from nutritional interventions. Given that muscle glycogen is limiting during a 2-h marathon, optimizing carbohydrate (CHO) intake and delivery is of maximal importance. Furthermore, the last 60 y of marathon performance have seen lighter and smaller marathoners, which enhances running economy and heat dissipation and increases CHO delivery per kg body mass. Finally, periodically training under conditions of low CHO availability (eg, low muscle glycogen) or periods of mild fluid restriction may actually further enhance the adaptive responses to training. Accordingly, this commentary highlights these key nutrition and hydration interventions that have emerged over the last several years and explores how they may assist in world-class marathon performance.

  20. Adaptive Flood Risk Management Under Climate Change Uncertainty Using Real Options and Optimization.

    PubMed

    Woodward, Michelle; Kapelan, Zoran; Gouldby, Ben

    2014-01-01

    It is well recognized that adaptive and flexible flood risk strategies are required to account for future uncertainties. Development of such strategies is, however, a challenge. Climate change alone is a significant complication, but, in addition, complexities exist trying to identify the most appropriate set of mitigation measures, or interventions. There are a range of economic and environmental performance measures that require consideration, and the spatial and temporal aspects of evaluating the performance of these is complex. All these elements pose severe difficulties to decisionmakers. This article describes a decision support methodology that has the capability to assess the most appropriate set of interventions to make in a flood system and the opportune time to make these interventions, given the future uncertainties. The flood risk strategies have been explicitly designed to allow for flexible adaptive measures by capturing the concepts of real options and multiobjective optimization to evaluate potential flood risk management opportunities. A state-of-the-art flood risk analysis tool is employed to evaluate the risk associated to each strategy over future points in time and a multiobjective genetic algorithm is utilized to search for the optimal adaptive strategies. The modeling system has been applied to a reach on the Thames Estuary (London, England), and initial results show the inclusion of flexibility is advantageous, while the outputs provide decisionmakers with supplementary knowledge that previously has not been considered.

  1. Adaptive aeroelastic composite wings - Control and optimization issues

    NASA Technical Reports Server (NTRS)

    Weisshaar, Terrence A.; Ehlers, Steven M.

    1992-01-01

    High-performance aircraft are adaptive machines composed of internal structural skeletons to which are attached control surfaces operated by hydraulic muscles to allow them to maneuver. The flight crew, avionic sensors and systems function as the brain and nervous system to adapt the machine to changing flight conditions, such as take-off, cruise and landing. The development of new materials that can expand or contract on command or change stiffness on demand will blur the now distinct boundaries between the structure, actuators and the control system. This paper discusses the use of imbedded active piezoelectric materials to change the aeroelastic stiffness of a lifting surface to allow this surface to control the aircraft. Expressions are developed for the piezoelectric material effectiveness when these active materials are combined with advanced composite structural materials for a swept, high-aspect-ratio wing. The interaction between advanced composite material properties and piezoelectric electromechanical properties is examined. The importance of choosing the proper active control laws is also illustrated.

  2. MACAO-VLTI adaptive optics systems performance

    NASA Astrophysics Data System (ADS)

    Arsenault, Robin; Donaldson, Rob; Dupuy, Christophe; Fedrigo, Enrico; Hubin, Norbert N.; Ivanescu, Liviu; Kasper, Markus E.; Oberti, Sylvain; Paufique, Jerome; Rossi, Silvio; Silber, Armin; Delabre, Bernhard; Lizon, Jean-Louis; Gigan, Pierre

    2004-10-01

    In April and August "03 two MACAO-VLTI curvature AO systems were installed on the VLT telescopes unit 2 and 3 in Paranal (Chile). These are 60 element systems using a 150mm bimorph deformable mirror and 60 APD"s as WFS detectors. Valuable integration & commissioning experience has been gained during these 2 missions. Several tests have been performed in order to evaluate system performance on the sky. The systems have proven to be extremely robust, performing in a stable fashion in extreme seeing condition (seeing up to 3"). Strehl ratio of 0.65 and residual tilt smaller than 10 mas have been obtained on the sky in 0.8" seeing condition. Weak guide source performance is also excellent with a strehl of 0.26 on a V~16 magnitude star. Several functionalities have been successfully tested including: chopping, off-axis guiding, atmospheric refraction compensation etc. The AO system can be used in a totally automatic fashion with a small overhead: the AO loop can be closed on the target less than 60 sec after star acquisition by the telescope. It includes reading the seeing value given by the site monitor, evaluate the guide star magnitude (cycling through neutral density filters) setting the close-loop AO parameters (system gain and vibrating membrane mirror stroke) including calculation of the command-matrix. The last 2 systems will be installed in August "04 and in the course of 2005.

  3. Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

    NASA Astrophysics Data System (ADS)

    Peng, Haijun; Wang, Wei

    2016-10-01

    An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

  4. Function-valued adaptive dynamics and optimal control theory.

    PubMed

    Parvinen, Kalle; Heino, Mikko; Dieckmann, Ulf

    2013-09-01

    In this article we further develop the theory of adaptive dynamics of function-valued traits. Previous work has concentrated on models for which invasion fitness can be written as an integral in which the integrand for each argument value is a function of the strategy value at that argument value only. For this type of models of direct effect, singular strategies can be found using the calculus of variations, with singular strategies needing to satisfy Euler's equation with environmental feedback. In a broader, more mechanistically oriented class of models, the function-valued strategy affects a process described by differential equations, and fitness can be expressed as an integral in which the integrand for each argument value depends both on the strategy and on process variables at that argument value. In general, the calculus of variations cannot help analyzing this much broader class of models. Here we explain how to find singular strategies in this class of process-mediated models using optimal control theory. In particular, we show that singular strategies need to satisfy Pontryagin's maximum principle with environmental feedback. We demonstrate the utility of this approach by studying the evolution of strategies determining seasonal flowering schedules.

  5. Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

    PubMed

    Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

    2016-08-01

    The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

  6. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

    PubMed Central

    Carmena, Jose M.

    2016-01-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to

  7. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    PubMed

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  8. Optimizing digital 8mm drive performance

    NASA Technical Reports Server (NTRS)

    Schadegg, Gerry

    1993-01-01

    The experience of attaching over 350,000 digital 8mm drives to 85-plus system platforms has uncovered many factors which can reduce cartridge capacity or drive throughput, reduce reliability, affect cartridge archivability and actually shorten drive life. Some are unique to an installation. Others result from how the system is set up to talk to the drive. Many stem from how applications use the drive, the work load that's present, the kind of media used and, very important, the kind of cleaning program in place. Digital 8mm drives record data at densities that rival those of disk technology. Even with technology this advanced, they are extremely robust and, given proper usage, care and media, should reward the user with a long productive life. The 8mm drive will give its best performance using high-quality 'data grade' media. Even though it costs more, good 'data grade' media can sustain the reliability and rigorous needs of a data storage environment and, with proper care, give users an archival life of 30 years or more. Various factors, taken individually, may not necessarily produce performance or reliability problems. Taken in combination, their effects can compound, resulting in rapid reductions in a drive's serviceable life, cartridge capacity, or drive performance. The key to managing media is determining the importance one places upon their recorded data and, subsequently, setting media usage guidelines that can deliver data reliability. Various options one can implement to optimize digital 8mm drive performance are explored.

  9. SSD-Optimized Workload Placement with Adaptive Learning and Classification in HPC Environments

    SciTech Connect

    Wan, Lipeng; Lu, Zheng; Cao, Qing; Wang, Feiyi; Oral, H Sarp; Settlemyer, Bradley W

    2014-01-01

    In recent years, non-volatile memory devices such as SSD drives have emerged as a viable storage solution due to their increasing capacity and decreasing cost. Due to the unique capability and capacity requirements in large scale HPC (High Performance Computing) storage environment, a hybrid config- uration (SSD and HDD) may represent one of the most available and balanced solutions considering the cost and performance. Under this setting, effective data placement as well as movement with controlled overhead become a pressing challenge. In this paper, we propose an integrated object placement and movement framework and adaptive learning algorithms to address these issues. Specifically, we present a method that shuffle data objects across storage tiers to optimize the data access performance. The method also integrates an adaptive learning algorithm where real- time classification is employed to predict the popularity of data object accesses, so that they can be placed on, or migrate between SSD or HDD drives in the most efficient manner. We discuss preliminary results based on this approach using a simulator we developed to show that the proposed methods can dynamically adapt storage placements and access pattern as workloads evolve to achieve the best system level performance such as throughput.

  10. Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2012-01-01

    This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

  11. Adaptable Learning Pathway Generation with Ant Colony Optimization

    ERIC Educational Resources Information Center

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2009-01-01

    One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with…

  12. Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.

  13. Optimal performance in a countermanding saccade task

    PubMed Central

    Wong-Lin, KongFatt; Eckhoff, Philip; Holmes, Philip; Cohen, Jonathan D.

    2010-01-01

    Countermanding an action is a fundamental form of cognitive control. In a saccade-countermanding task, subjects are instructed that, if a stop signal appears shortly after a target, they are to maintain fixation rather than to make a saccade to the target. In recent years, recordings in the frontal eye fields and superior colliculus of behaving non-human primates have found correlates of such countermanding behavior in movement and fixation neurons. In this work, we extend a previous neural network model of countermanding to account for the high pre-target activity of fixation neurons. We propose that this activity reflects the functioning of control mechanisms responsible for optimizing performance. We demonstrate, using computer simulations and mathematical analysis, that pre-target fixation neuronal activity supports countermanding behavior that maximizes reward rate as a function of the stop signal delay, fraction of stop signal trials, intertrial interval, duration of timeout, and relative reward value. We propose experiments to test these predictions regarding optimal behavior. PMID:20034481

  14. Optimizing the Adaptive Stochastic Resonance and Its Application in Fault Diagnosis

    NASA Astrophysics Data System (ADS)

    Liu, Xiaole; Yang, Jianhua; Liu, Houguang; Cheng, Gang; Chen, Xihui; Xu, Dan

    2015-10-01

    This paper presents an adaptive stochastic resonance method based on the improved artificial fish swarm algorithm. By this method, we can enhance the weak characteristic signal which is submerged in a heavy noise. We can also adaptively lead the stochastic resonance to be optimized to the greatest extent. The effectiveness of the proposed method is verified by both numerical simulation and lab experimental vibration signals including normal, a chipped tooth and a missing tooth of planetary gearboxes under the loaded condition. Both theoretical and experimental results show that this method can effectively extract weak characteristics in a heavy noise. In the experiment, each weak fault feature is extracted successfully from the fault planetary gear. When compared with the ensemble empirical mode decomposition (EEMD) method, the method proposed in this paper has been found to give remarkable performance.

  15. Adaptive use of interaction torque during arm reaching movement from the optimal control viewpoint

    PubMed Central

    Vu, Van Hoan; Isableu, Brice; Berret, Bastien

    2016-01-01

    The study aimed at investigating the extent to which the brain adaptively exploits or compensates interaction torque (IT) during movement control in various velocity and load conditions. Participants performed arm pointing movements toward a horizontal plane without a prescribed reach endpoint at slow, neutral and rapid speeds and with/without load attached to the forearm. Experimental results indicated that IT overall contributed to net torque (NT) to assist the movement, and that such contribution increased with limb inertia and instructed speed and led to hand trajectory variations. We interpreted these results within the (inverse) optimal control framework, assuming that the empirical arm trajectories derive from the minimization of a certain, possibly composite, cost function. Results indicated that mixing kinematic, energetic and dynamic costs was necessary to replicate the participants’ adaptive behavior at both kinematic and dynamic levels. Furthermore, the larger contribution of IT to NT was associated with an overall decrease of the kinematic cost contribution and an increase of its dynamic/energetic counterparts. Altogether, these results suggest that the adaptive use of IT might be tightly linked to the optimization of a composite cost which implicitly favors more the kinematic or kinetic aspects of movement depending on load and speed. PMID:27941920

  16. Adaptive Virtual Reality Training to Optimize Military Medical Skills Acquisition and Retention.

    PubMed

    Siu, Ka-Chun; Best, Bradley J; Kim, Jong Wook; Oleynikov, Dmitry; Ritter, Frank E

    2016-05-01

    The Department of Defense has pursued the integration of virtual reality simulation into medical training and applications to fulfill the need to train 100,000 military health care personnel annually. Medical personnel transitions, both when entering an operational area and returning to the civilian theater, are characterized by the need to rapidly reacquire skills that are essential but have decayed through disuse or infrequent use. Improved efficiency in reacquiring such skills is critical to avoid the likelihood of mistakes that may result in mortality and morbidity. We focus here on a study testing a theory of how the skills required for minimally invasive surgery for military surgeons are learned and retained. Our adaptive virtual reality surgical training system will incorporate an intelligent mechanism for tracking performance that will recognize skill deficiencies and generate an optimal adaptive training schedule. Our design is modeling skill acquisition based on a skill retention theory. The complexity of appropriate training tasks is adjusted according to the level of retention and/or surgical experience. Based on preliminary work, our system will improve the capability to interactively assess the level of skills learning and decay, optimizes skill relearning across levels of surgical experience, and positively impact skill maintenance. Our system could eventually reduce mortality and morbidity by providing trainees with the reexperience they need to help make a transition between operating theaters. This article reports some data that will support adaptive tutoring of minimally invasive surgery and similar surgical skills.

  17. Common spatial pattern patches - an optimized filter ensemble for adaptive brain-computer interfaces.

    PubMed

    Sannelli, Claudia; Vidaurre, Carmen; Muller, Klaus-Robert; Blankertz, Benjamin

    2010-01-01

    Laplacian filters are commonly used in Brain Computer Interfacing (BCI). When only data from few channels are available, or when, like at the beginning of an experiment, no previous data from the same user is available complex features cannot be used. In this case band power features calculated from Laplacian filtered channels represents an easy, robust and general feature to control a BCI, since its calculation does not involve any class information. For the same reason, the performance obtained with Laplacian features is poor in comparison to subject-specific optimized spatial filters, such as Common Spatial Patterns (CSP) analysis, which, on the other hand, can be used just in a later phase of the experiment, since they require a considerable amount of training data in order to enroll a stable and good performance. This drawback is particularly evident in case of poor performing BCI users, whose data is highly non-stationary and contains little class relevant information. Therefore, Laplacian filtering is preferred to CSP, e.g., in the initial period of co-adaptive calibration, a novel BCI paradigm designed to alleviate the problem of BCI illiteracy. In fact, in the co-adaptive calibration design the experiment starts with a subject-independent classifier and simple features are needed in order to obtain a fast adaptation of the classifier to the newly acquired user's data. Here, the use of an ensemble of local CSP patches (CSPP) is proposed, which can be considered as a compromise between Laplacians and CSP: CSPP needs less data and channels than CSP, while being superior to Laplacian filtering. This property is shown to be particularly useful for the co-adaptive calibration design and is demonstrated on off-line data from a previous co-adaptive BCI study.

  18. Research on web performance optimization principles and models

    NASA Astrophysics Data System (ADS)

    Wang, Xin

    2013-03-01

    The Internet high speed development, causes Web the optimized question to be getting more and more prominent, therefore the Web performance optimizes into inevitably. the first principle of Web Performance Optimization is to understand, to know that income will have to pay, and return is diminishing; Simultaneously the probability will decrease Web the performance, and will start from the highest level to optimize obtained biggest. Web Technical models to improve the performance are: sharing costs, high-speed caching, profiles, parallel processing, simplified treatment. Based on this study, given the crucial Web performance optimization recommendations, which improve the performance of Web usage, accelerate the efficient use of Internet has an important significance.

  19. Adaptation and fallibility in experts' judgments of novice performers.

    PubMed

    Larson, Jeffrey S; Billeter, Darron M

    2017-02-01

    Competition judges are often selected for their expertise, under the belief that a high level of performance expertise should enable accurate judgments of the competitors. Contrary to this assumption, we find evidence that expertise can reduce judgment accuracy. Adaptation level theory proposes that discriminatory capacity decreases with greater distance from one's adaptation level. Because experts' learning has produced an adaptation level close to ideal performance standards, they may be less able to discriminate among lower-level competitors. As a result, expertise increases judgment accuracy of high-level competitions but decreases judgment accuracy of low-level competitions. Additionally, we demonstrate that, consistent with an adaptation level theory account of expert judgment, experts systematically give more critical ratings than intermediates or novices. In summary, this work demonstrates a systematic change in human perception that occurs as task learning increases. (PsycINFO Database Record

  20. Monitoring the Performance of a Neuro-Adaptive Controller

    NASA Technical Reports Server (NTRS)

    Schumann, Johann; Gupta, Pramod

    2004-01-01

    Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

  1. Enhancing Functional Performance using Sensorimotor Adaptability Training Programs

    NASA Technical Reports Server (NTRS)

    Bloomberg, J. J.; Mulavara, A. P.; Peters, B. T.; Brady, R.; Audas, C.; Ruttley, T. M.; Cohen, H. S.

    2009-01-01

    During the acute phase of adaptation to novel gravitational environments, sensorimotor disturbances have the potential to disrupt the ability of astronauts to perform functional tasks. The goal of this project is to develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The project conducted a series of studies that investigated the efficacy of treadmill training combined with a variety of sensory challenges designed to increase adaptability including alterations in visual flow, body loading, and support surface stability.

  2. Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

    NASA Technical Reports Server (NTRS)

    Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.

    1999-01-01

    A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

  3. Modeling-Error-Driven Performance-Seeking Direct Adaptive Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John

    2008-01-01

    This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.

  4. 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.

  5. The 15-meter antenna performance optimization using an interdisciplinary approach

    NASA Technical Reports Server (NTRS)

    Grantham, William L.; Schroeder, Lyle C.; Bailey, Marion C.; Campbell, Thomas G.

    1988-01-01

    A 15-meter diameter deployable antenna has been built and is being used as an experimental test system with which to develop interdisciplinary controls, structures, and electromagnetics technology for large space antennas. The program objective is to study interdisciplinary issues important in optimizing large space antenna performance for a variety of potential users. The 15-meter antenna utilizes a hoop column structural concept with a gold-plated molybdenum mesh reflector. One feature of the design is the use of adjustable control cables to improve the paraboloid reflector shape. Manual adjustment of the cords after initial deployment improved surface smoothness relative to the build accuracy from 0.140 in. RMS to 0.070 in. Preliminary structural dynamics tests and near-field electromagnetic tests were made. The antenna is now being modified for further testing. Modifications include addition of a precise motorized control cord adjustment system to make the reflector surface smoother and an adaptive feed for electronic compensation of reflector surface distortions. Although the previous test results show good agreement between calculated and measured values, additional work is needed to study modelling limits for each discipline, evaluate the potential of adaptive feed compensation, and study closed-loop control performance in a dynamic environment.

  6. Optimizing Hydronic System Performance in Residential Applications

    SciTech Connect

    Arena, L.; Faakye, O.

    2013-10-01

    Even though new homes constructed with hydronic heat comprise only 3% of the market (US Census Bureau 2009), of the 115 million existing homes in the United States, almost 14 million of those homes (11%) are heated with steam or hot water systems according to 2009 US Census data. Therefore, improvements in hydronic system performance could result in significant energy savings in the US. When operating properly, the combination of a gas-fired condensing boiler with baseboard convectors and an indirect water heater is a viable option for high-efficiency residential space heating in cold climates. Based on previous research efforts, however, it is apparent that these types of systems are typically not designed and installed to achieve maximum efficiency. Furthermore, guidance on proper design and commissioning for heating contractors and energy consultants is hard to find and is not comprehensive. Through modeling and monitoring, CARB sought to determine the optimal combination(s) of components - pumps, high efficiency heat sources, plumbing configurations and controls - that result in the highest overall efficiency for a hydronic system when baseboard convectors are used as the heat emitter. The impact of variable-speed pumps on energy use and system performance was also investigated along with the effects of various control strategies and the introduction of thermal mass.

  7. Multimodal Optimization by Covariance Matrix Self-Adaptation Evolution Strategy with Repelling Subpopulations.

    PubMed

    Ahrari, Ali; Deb, Kalyanmoy; Preuss, Mike

    2016-04-12

    During the recent decades, many niching methods have been proposed and empirically verified on some available test problems. They often rely on some particular assumptions associated with the distribution, shape, and size of the basins, which can seldom be made in practical optimization problems. This study utilizes several existing concepts and techniques, such as taboo points, normalized Mahalanobis distance, and the Ursem's hill-valley function in order to develop a new tool for multimodal optimization, which does not make any of these assumptions. In the proposed method, several subpopulations explore the search space in parallel. Offspring of a subpopulation are forced to maintain a sufficient distance to the center of fitter subpopulations and the previously identified basins, which are marked as taboo points. The taboo points repel the subpopulation to prevent convergence to the same basin. A strategy to update the repelling power of the taboo points is proposed to address the challenge of basins of dissimilar size. The local shape of a basin is also approximated by the distribution of the subpopulation members converging to that basin. The proposed niching strategy is incorporated into the covariance matrix self-adaptation evolution strategy (CMSA-ES), a potent global optimization method. The resultant method, called the covariance matrix self-adaptation with repelling subpopulations (RS-CMSA), is assessed and compared to several state-of-the-art niching methods on a standard test suite for multimodal optimization. An organized procedure for parameter setting is followed which assumes a rough estimation of the desired/expected number of minima available. Performance sensitivity to the accuracy of this estimation is also studied by introducing the concept of robust mean peak ratio. Based on the numerical results using the available and the introduced performance measures, RS-CMSA emerges as the most successful method when robustness and efficiency are

  8. Skeletal muscle adaptations and muscle genomics of performance horses.

    PubMed

    Rivero, José-Luis L; Hill, Emmeline W

    2016-03-01

    Skeletal muscles in horses are characterised by specific adaptations, which are the result of the natural evolution of the horse as a grazing animal, centuries of selective breeding and the adaptability of this tissue in response to training. These adaptations include an increased muscle mass relative to body weight, a great locomotor efficiency based upon an admirable muscle-tendon architectural design and an adaptable fibre-type composition with intrinsic shortening velocities greater than would be predicted from an animal of comparable body size. Furthermore, equine skeletal muscles have a high mitochondrial volume that permits a higher whole animal aerobic capacity, as well as large intramuscular stores of energy substrates (glycogen in particular). Finally, high buffer and lactate transport capacities preserve muscles against fatigue during anaerobic exercise. Many of these adaptations can improve with training. The publication of the equine genome sequence in 2009 has provided a major advance towards an improved understanding of equine muscle physiology. Equine muscle genomics studies have revealed a number of genes associated with elite physical performance and have also identified changes in structural and metabolic genes following exercise and training. Genes involved in muscle growth, muscle contraction and specific metabolic pathways have been found to be functionally relevant for the early performance evaluation of elite athletic horses. The candidate genes discussed in this review are important for a healthy individual to improve performance. However, muscle performance limiting conditions are widespread in horses and many of these conditions are also genetically influenced.

  9. GASIFICATION PLANT COST AND PERFORMANCE OPTIMIZATION

    SciTech Connect

    Samuel S. Tam

    2002-05-01

    The goal of this series of design and estimating efforts was to start from the as-built design and actual operating data from the DOE sponsored Wabash River Coal Gasification Repowering Project and to develop optimized designs for several coal and petroleum coke IGCC power and coproduction projects. First, the team developed a design for a grass-roots plant equivalent to the Wabash River Coal Gasification Repowering Project to provide a starting point and a detailed mid-year 2000 cost estimate based on the actual as-built plant design and subsequent modifications (Subtask 1.1). This unoptimized plant has a thermal efficiency of 38.3% (HHV) and a mid-year 2000 EPC cost of 1,681 $/kW. This design was enlarged and modified to become a Petroleum Coke IGCC Coproduction Plant (Subtask 1.2) that produces hydrogen, industrial grade steam, and fuel gas for an adjacent Gulf Coast petroleum refinery in addition to export power. A structured Value Improving Practices (VIP) approach was applied to reduce costs and improve performance. The base case (Subtask 1.3) Optimized Petroleum Coke IGCC Coproduction Plant increased the power output by 16% and reduced the plant cost by 23%. The study looked at several options for gasifier sparing to enhance availability. Subtask 1.9 produced a detailed report on this availability analyses study. The Subtask 1.3 Next Plant, which retains the preferred spare gasification train approach, only reduced the cost by about 21%, but it has the highest availability (94.6%) and produces power at 30 $/MW-hr (at a 12% ROI). Thus, such a coke-fueled IGCC coproduction plant could fill a near term niche market. In all cases, the emissions performance of these plants is superior to the Wabash River project. Subtasks 1.5A and B developed designs for single-train coal and coke-fueled power plants. This side-by-side comparison of these plants, which contain the Subtask 1.3 VIP enhancements, showed their similarity both in design and cost (1,318 $/kW for the

  10. GASIFICATION PLANT COST AND PERFORMANCE OPTIMIZATION

    SciTech Connect

    Sheldon Kramer

    2003-09-01

    This project developed optimized designs and cost estimates for several coal and petroleum coke IGCC coproduction projects that produced hydrogen, industrial grade steam, and hydrocarbon liquid fuel precursors in addition to power. The as-built design and actual operating data from the DOE sponsored Wabash River Coal Gasification Repowering Project was the starting point for this study that was performed by Bechtel, Global Energy and Nexant under Department of Energy contract DE-AC26-99FT40342. First, the team developed a design for a grass-roots plant equivalent to the Wabash River Coal Gasification Repowering Project to provide a starting point and a detailed mid-year 2000 cost estimate based on the actual as-built plant design and subsequent modifications (Subtask 1.1). This non-optimized plant has a thermal efficiency to power of 38.3% (HHV) and a mid-year 2000 EPC cost of 1,681 $/kW.1 This design was enlarged and modified to become a Petroleum Coke IGCC Coproduction Plant (Subtask 1.2) that produces hydrogen, industrial grade steam, and fuel gas for an adjacent Gulf Coast petroleum refinery in addition to export power. A structured Value Improving Practices (VIP) approach was applied to reduce costs and improve performance. The base case (Subtask 1.3) Optimized Petroleum Coke IGCC Coproduction Plant increased the power output by 16% and reduced the plant cost by 23%. The study looked at several options for gasifier sparing to enhance availability. Subtask 1.9 produced a detailed report on this availability analyses study. The Subtask 1.3 Next Plant, which retains the preferred spare gasification train approach, only reduced the cost by about 21%, but it has the highest availability (94.6%) and produces power at 30 $/MW-hr (at a 12% ROI). Thus, such a coke-fueled IGCC coproduction plant could fill a near term niche market. In all cases, the emissions performance of these plants is superior to the Wabash River project. Subtasks 1.5A and B developed designs for

  11. Optical Design and Optimization of Translational Reflective Adaptive Optics Ophthalmoscopes

    NASA Astrophysics Data System (ADS)

    Sulai, Yusufu N. B.

    The retina serves as the primary detector for the biological camera that is the eye. It is composed of numerous classes of neurons and support cells that work together to capture and process an image formed by the eye's optics, which is then transmitted to the brain. Loss of sight due to retinal or neuro-ophthalmic disease can prove devastating to one's quality of life, and the ability to examine the retina in vivo is invaluable in the early detection and monitoring of such diseases. Adaptive optics (AO) ophthalmoscopy is a promising diagnostic tool in early stages of development, still facing significant challenges before it can become a clinical tool. The work in this thesis is a collection of projects with the overarching goal of broadening the scope and applicability of this technology. We begin by providing an optical design approach for AO ophthalmoscopes that reduces the aberrations that degrade the performance of the AO correction. Next, we demonstrate how to further improve image resolution through the use of amplitude pupil apodization and non-common path aberration correction. This is followed by the development of a viewfinder which provides a larger field of view for retinal navigation. Finally, we conclude with the development of an innovative non-confocal light detection scheme which improves the non-invasive visualization of retinal vasculature and reveals the cone photoreceptor inner segments in healthy and diseased eyes.

  12. Performance Benefits Associated with Context-Dependent Arm Pointing Adaptation

    NASA Technical Reports Server (NTRS)

    Seidler, R. D.; Bloomberg, J. J.; Stelmach, George E.

    2000-01-01

    Our previous work has demonstrated that head orientation can be used as a contextual cue to switch between mUltiple adaptive states. Subjects were assigned to one of three groups: the head orientation group tilted the head towards the right shoulder when drawing under a 0.5 gain of display and towards the left shoulder when drawing under a 1.5 gain of display; the target orientation group had the home & target positions rotated counterclockwise when drawing under the 0.5 gain and clockwise for the l.5 gain; the arm posture group changed the elbow angle of the arm they were not drawing with from full flexion to full extension with 0.5 and l.5 gain display changes. The head orientation cue was effectively associated with the multiple gains, in comparison to the control conditions. The purpose of the current investigation was to determine whether this context-dependent adaptation results in any savings in terms of performance measures such as movement duration and movement smoothness when subjects switch between multiple adaptive states. Subjects in the head adaptation group demonstrated reduced movement duration and increased movement smoothness (measured via normalized j erk scores) in comparison to the two control groups when switching between the 0.5 and 1.5 gain. of display. This work has demonstrated not only that subjects can acquire context-dependent adaptation, but also that it results in a significant savings of performance upon transfer between adaptive states

  13. Adaptive Performance Seeking Control Using Fuzzy Model Reference Learning Control and Positive Gradient Control

    NASA Technical Reports Server (NTRS)

    Kopasakis, George

    1997-01-01

    Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.

  14. Psychological adaptation after marital disruption: the effects of optimism and perceived control.

    PubMed

    Thuen, Frode; Rise, Jostein

    2006-04-01

    The present study explored the extent to which the two personality factors--perceived control and dispositional optimism--are related to psychological adaptation after marital disruption. A sample of 658 recently divorced individuals participated in the study by filling in an anonymous questionnaire. Bivariate findings revealed that perceived control and optimism were strongly related to psychological adaptation. However, when both predictors were included in a multiple regression analysis, optimism had a much larger effect than perceived control. The findings clearly indicate that personality factors account for a substantial proportion of the variance in adaptation to marital disruption.

  15. Performance Analysis of Adaptive Volterra Filters in the Finite-Alphabet Input Case

    NASA Astrophysics Data System (ADS)

    Besbes, Hichem; Jaïdane, Mériem; Ezzine, Jelel

    2004-12-01

    This paper deals with the analysis of adaptive Volterra filters, driven by the LMS algorithm, in the finite-alphabet inputs case. A tailored approach for the input context is presented and used to analyze the behavior of this nonlinear adaptive filter. Complete and rigorous mean square analysis is provided without any constraining independence assumption. Exact transient and steady-state performances expressed in terms of critical step size, rate of transient decrease, optimal step size, excess mean square error in stationary mode, and tracking nonstationarities are deduced.

  16. Stability and Performance Metrics for Adaptive Flight Control

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

    2009-01-01

    This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

  17. Is Adaptation to Task Complexity Really Beneficial for Performance?

    ERIC Educational Resources Information Center

    Pieschl, Stephanie; Stahl, Elmar; Murray, Tom; Bromme, Rainer

    2012-01-01

    Theories of self-regulated learning assume that learners flexibly adapt their learning process to external task demands and that this is positively related to performance. In this study, university students (n = 119) solved three tasks that greatly differed in complexity. Their learning processes were captured in detail by task-specific…

  18. Adaptation and Fallibility in Experts' Judgments of Novice Performers

    ERIC Educational Resources Information Center

    Larson, Jeffrey S.; Billeter, Darron M.

    2017-01-01

    Competition judges are often selected for their expertise, under the belief that a high level of performance expertise should enable accurate judgments of the competitors. Contrary to this assumption, we find evidence that expertise can reduce judgment accuracy. Adaptation level theory proposes that discriminatory capacity decreases with greater…

  19. An Adaptive Model of Student Performance Using Inverse Bayes

    ERIC Educational Resources Information Center

    Lang, Charles

    2014-01-01

    This article proposes a coherent framework for the use of Inverse Bayesian estimation to summarize and make predictions about student behaviour in adaptive educational settings. The Inverse Bayes Filter utilizes Bayes theorem to estimate the relative impact of contextual factors and internal student factors on student performance using time series…

  20. Adaptive Optics Performance at Lick and Keck Observatory

    NASA Astrophysics Data System (ADS)

    Max, C. E.; Olivier, S. S.; Avicola, K.; Bissinger, H. D.; Brase, J. M.; Friedman, H. W.; Gavel, D. T.; Salmon, J. T.; Waltjen, K. E.

    1993-12-01

    The performance of an adaptive optics system developed for the 40 inch Nickel and 120 inch Shane telescopes at Lick Observatory is discussed. The system is based on a 69 actuator continuous-surface deformable mirror and a Hartmann wavefront sensor equipped with a commercial intensified CCD fast-framing camera. Results from tests of this adaptive optics system using natural reference stars on the 40 inch Nickel telescope are presented. These results are compared to the performance predicted by simulations and analyses. Predictions for the system performance on the 120 inch Shane telescope and on the 10 meter Keck telescope using both natural and laser reference stars are also presented. Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract W-7405-Eng-48.

  1. Reduction of influence of gain errors on performance of adaptive sub-ranging A/D converters with simplified architecture

    NASA Astrophysics Data System (ADS)

    Jedrzejewski, Konrad; Malkiewicz, Łukasz

    2016-09-01

    The paper presents the results of studies pertaining to the influence of gain errors of inter-stage amplifiers on performance of adaptive sub-ranging analog-to-digital converters (ADCs). It focuses on adaptive sub-ranging ADCs with simplified architecture of the analog part - using only one amplifier and a low resolution digital-to-analog converter, that is identical to that of known conventional sub-ranging ADCs. The only difference between adaptive subranging ADCs with simplified architecture and conventional sub-ranging ADCs is the process of determination of output codes of converted samples. The adaptive sub-ranging ADCs calculate the output codes on the basis of sub-codes obtained in particular stages of conversion using an adaptive algorithm. Thanks to application of the optimal adaptive algorithm, adjusted to the parameters of possible components imperfections and internal noises, the adaptive ADCs outperform, in terms of effective resolution per cycle, conventional sub-ranging ADCs forming the output codes using simple lower-level bit operations. Optimization of the conversion algorithm used in adaptive ADCs leads however to high sensitivity of adaptive ADCs performance to the inter-stage gain error. An effective method for reduction of this sensitivity in adaptive sub-ranging ADCs with simplified architecture is proposed and discussed in the paper.

  2. Utilising pseudo-CT data for dose calculation and plan optimization in adaptive radiotherapy.

    PubMed

    Whelan, Brendan; Kumar, Shivani; Dowling, Jason; Begg, Jarrad; Lambert, Jonathan; Lim, Karen; Vinod, Shalini K; Greer, Peter B; Holloway, Lois

    2015-12-01

    To quantify the dose calculation error and resulting optimization uncertainty caused by performing inverse treatment planning on inaccurate electron density data (pseudo-CT) as needed for adaptive radiotherapy and Magnetic Resonance Imaging (MRI) based treatment planning. Planning Computer Tomography (CT) data from 10 cervix cancer patients was used to generate 4 pseudo-CT data sets. Each pseudo-CT was created based on an available method of assigning electron density to an anatomic image. An inversely modulated radiotherapy (IMRT) plan was developed on each planning CT. The dose calculation error caused by each pseudo-CT data set was quantified by comparing the dose calculated each pseudo-CT data set with that calculated on the original planning CT for the same IMRT plan. The optimization uncertainty introduced by the dose calculation error was quantified by re-optimizing the same optimization parameters on each pseudo-CT data set and comparing against the original planning CT. Dose differences were quantified by assessing the Equivalent Uniform Dose (EUD) for targets and relevant organs at risk. Across all pseudo-CT data sets and all organs, the absolute mean dose calculation error was 0.2 Gy, and was within 2 % of the prescription dose in 98.5 % of cases. Then absolute mean optimisation error was 0.3 Gy EUD, indicating that that inverse optimisation is impacted by the dose calculation error. However, the additional uncertainty introduced to plan optimisation is small compared the sources of variation which already exist. Use of inaccurate electron density data for inverse treatment planning results in a dose calculation error, which in turn introduces additional uncertainty into the plan optimization process. In this study, we showed that both of these effects are clinically acceptable for cervix cancer patients using four different pseudo-CT data sets. Dose calculation and inverse optimization on pseudo-CT is feasible for this patient cohort.

  3. An optimized locally adaptive non-local means denoising filter for cryo-electron microscopy data.

    PubMed

    Wei, Dai-Yu; Yin, Chang-Cheng

    2010-12-01

    Cryo-electron microscopy (cryo-EM) now plays an important role in structural analysis of macromolecular complexes, organelles and cells. However, the cryo-EM images obtained close to focus and under low dose conditions have a very high level of noise and a very low contrast, which hinders high-resolution structural analysis. Here, an optimized locally adaptive non-local (LANL) means filter, which can preserve signal details and simultaneously significantly suppress noise for cryo-EM data, is presented. This filter takes advantage of a wide range of pixels to estimate the denoised pixel values instead of the traditional filter that only uses pixels in the local neighborhood. The filter performed well on simulated data and showed promising results on raw cryo-EM images and tomograms. The predominant advantage of this optimized LANL-means filter is the structural signal and the background are clearly distinguishable. This locally adaptive non-local means filter may become a useful tool in the analysis of cryo-EM data, such as automatic particle picking, extracting structural features and segmentation of tomograms.

  4. Skeletal adaptation to external loads optimizes mechanical properties: fact or fiction

    NASA Technical Reports Server (NTRS)

    Turner, R. T.

    2001-01-01

    The skeleton adapts to a changing mechanical environment but the widely held concept that bone cells are programmed to respond to local mechanical loads to produce an optimal mechanical structure is not consistent with the high frequency of bone fractures. Instead, the author suggests that other important functions of bone compete with mechanical adaptation to determine structure. As a consequence of competing demands, bone architecture never achieves an optimal mechanical structure. c2001 Lippincott Williams & Wilkins, Inc.

  5. Optimization of an adaptive SPECT system with the scanning linear estimator

    NASA Astrophysics Data System (ADS)

    Ghanbari, Nasrin; Clarkson, Eric; Kupinski, Matthew A.; Li, Xin

    2015-08-01

    The adaptive single-photon emission computed tomography (SPECT) system studied here acquires an initial scout image to obtain preliminary information about the object. Then the configuration is adjusted by selecting the size of the pinhole and the magnification that optimize system performance on an ensemble of virtual objects generated to be consistent with the scout data. In this study the object is a lumpy background that contains a Gaussian signal with a variable width and amplitude. The virtual objects in the ensemble are imaged by all of the available configurations and the subsequent images are evaluated with the scanning linear estimator to obtain an estimate of the signal width and amplitude. The ensemble mean squared error (EMSE) on the virtual ensemble between the estimated and the true parameters serves as the performance figure of merit for selecting the optimum configuration. The results indicate that variability in the original object background, noise and signal parameters leads to a specific optimum configuration in each case. A statistical study carried out for a number of objects show that the adaptive system on average performs better than its nonadaptive counterpart.

  6. Automatic carrier landing system for V/STOL aircraft using L1 adaptive and optimal control

    NASA Astrophysics Data System (ADS)

    Hariharapura Ramesh, Shashank

    This thesis presents a framework for developing automatic carrier landing systems for aircraft with vertical or short take-off and landing capability using two different control strategies---gain-scheduled linear optimal control, and L1 adaptive control. The carrier landing sequence of V/STOL aircraft involves large variations in dynamic pressure and aerodynamic coefficients arising because of the transition from aerodynamic-supported to jet-borne flight, descent to the touchdown altitude, and turns performed to align with the runway. Consequently, the dynamics of the aircraft exhibit a highly non-linear dynamical behavior with variations in flight conditions prior to touchdown. Therefore, the implication is the need for non-linear control techniques to achieve automatic landing. Gain-scheduling has been one of the most widely employed techniques for control of aircraft, which involves designing linear controllers for numerous trimmed flight conditions, and interpolating them to achieve a global non-linear control. Adaptive control technique, on the other hand, eliminates the need to schedule the controller parameters as they adapt to changing flight conditions.

  7. Performance of the Gemini Planet Imager's adaptive optics system.

    PubMed

    Poyneer, Lisa A; Palmer, David W; Macintosh, Bruce; Savransky, Dmitry; Sadakuni, Naru; Thomas, Sandrine; Véran, Jean-Pierre; Follette, Katherine B; Greenbaum, Alexandra Z; Ammons, S Mark; Bailey, Vanessa P; Bauman, Brian; Cardwell, Andrew; Dillon, Daren; Gavel, Donald; Hartung, Markus; Hibon, Pascale; Perrin, Marshall D; Rantakyrö, Fredrik T; Sivaramakrishnan, Anand; Wang, Jason J

    2016-01-10

    The Gemini Planet Imager's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. A definitive description of the system's algorithms and technologies as built is given. 564 AO telemetry measurements from the Gemini Planet Imager Exoplanet Survey campaign are analyzed. The modal gain optimizer tracks changes in atmospheric conditions. Science observations show that image quality can be improved with the use of both the spatially filtered wavefront sensor and linear-quadratic-Gaussian control of vibration. The error budget indicates that for all targets and atmospheric conditions AO bandwidth error is the largest term.

  8. Adaptive arrival cost update for improving Moving Horizon Estimation performance.

    PubMed

    Sánchez, G; Murillo, M; Giovanini, L

    2017-03-01

    Moving horizon estimation is an efficient technique to estimate states and parameters of constrained dynamical systems. It relies on the solution of a finite horizon optimization problem to compute the estimates, providing a natural framework to handle bounds and constraints on estimates, noises and parameters. However, the approximation of the arrival cost and its updating mechanism are an active research topic. The arrival cost is very important because it provides a mean to incorporate information from previous measurements to the current estimates and it is difficult to estimate its true value. In this work, we exploit the features of adaptive estimation methods to update the parameters of the arrival cost. We show that, having a better approximation of the arrival cost, the size of the optimization problem can be significantly reduced guaranteeing the stability and convergence of the estimates. These properties are illustrated through simulation studies.

  9. Performance index and meta-optimization of a direct search optimization method

    NASA Astrophysics Data System (ADS)

    Krus, P.; Ölvander, J.

    2013-10-01

    Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

  10. Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

    NASA Technical Reports Server (NTRS)

    Ferrier, Yvonne L.; Nguyen, Nhan T.; Ting, Eric

    2016-01-01

    This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

  11. Adaptive Sensor Optimization and Cognitive Image Processing Using Autonomous Optical Neuroprocessors

    SciTech Connect

    CAMERON, STEWART M.

    2001-10-01

    Measurement and signal intelligence demands has created new requirements for information management and interoperability as they affect surveillance and situational awareness. Integration of on-board autonomous learning and adaptive control structures within a remote sensing platform architecture would substantially improve the utility of intelligence collection by facilitating real-time optimization of measurement parameters for variable field conditions. A problem faced by conventional digital implementations of intelligent systems is the conflict between a distributed parallel structure on a sequential serial interface functionally degrading bandwidth and response time. In contrast, optically designed networks exhibit the massive parallelism and interconnect density needed to perform complex cognitive functions within a dynamic asynchronous environment. Recently, all-optical self-organizing neural networks exhibiting emergent collective behavior which mimic perception, recognition, association, and contemplative learning have been realized using photorefractive holography in combination with sensory systems for feature maps, threshold decomposition, image enhancement, and nonlinear matched filters. Such hybrid information processors depart from the classical computational paradigm based on analytic rules-based algorithms and instead utilize unsupervised generalization and perceptron-like exploratory or improvisational behaviors to evolve toward optimized solutions. These systems are robust to instrumental systematics or corrupting noise and can enrich knowledge structures by allowing competition between multiple hypotheses. This property enables them to rapidly adapt or self-compensate for dynamic or imprecise conditions which would be unstable using conventional linear control models. By incorporating an intelligent optical neuroprocessor in the back plane of an imaging sensor, a broad class of high-level cognitive image analysis problems including geometric

  12. A note on the adaptive optimal control of ion accelerator facilities

    SciTech Connect

    Huang, T. )

    1990-06-01

    The application of optimal control theory to the computer control system of an ion accelerator facility is presented. The process is shown to consist of mathematical modeling of the underlying process, parameter identification, as well as some design methods of the optimal computer control and the techniques of realizing adaptive control.

  13. Gasification Plant Cost and Performance Optimization

    SciTech Connect

    Samuel Tam; Alan Nizamoff; Sheldon Kramer; Scott Olson; Francis Lau; Mike Roberts; David Stopek; Robert Zabransky; Jeffrey Hoffmann; Erik Shuster; Nelson Zhan

    2005-05-01

    As part of an ongoing effort of the U.S. Department of Energy (DOE) to investigate the feasibility of gasification on a broader level, Nexant, Inc. was contracted to perform a comprehensive study to provide a set of gasification alternatives for consideration by the DOE. Nexant completed the first two tasks (Tasks 1 and 2) of the ''Gasification Plant Cost and Performance Optimization Study'' for the DOE's National Energy Technology Laboratory (NETL) in 2003. These tasks evaluated the use of the E-GAS{trademark} gasification technology (now owned by ConocoPhillips) for the production of power either alone or with polygeneration of industrial grade steam, fuel gas, hydrocarbon liquids, or hydrogen. NETL expanded this effort in Task 3 to evaluate Gas Technology Institute's (GTI) fluidized bed U-GAS{reg_sign} gasifier. The Task 3 study had three main objectives. The first was to examine the application of the gasifier at an industrial application in upstate New York using a Southeastern Ohio coal. The second was to investigate the GTI gasifier in a stand-alone lignite-fueled IGCC power plant application, sited in North Dakota. The final goal was to train NETL personnel in the methods of process design and systems analysis. These objectives were divided into five subtasks. Subtasks 3.2 through 3.4 covered the technical analyses for the different design cases. Subtask 3.1 covered management activities, and Subtask 3.5 covered reporting. Conceptual designs were developed for several coal gasification facilities based on the fluidized bed U-GAS{reg_sign} gasifier. Subtask 3.2 developed two base case designs for industrial combined heat and power facilities using Southeastern Ohio coal that will be located at an upstate New York location. One base case design used an air-blown gasifier, and the other used an oxygen-blown gasifier in order to evaluate their relative economics. Subtask 3.3 developed an advanced design for an air-blown gasification combined heat and power

  14. Configuration optimization of laser guide stars and wavefront correctors for multi-conjugation adaptive optics

    NASA Astrophysics Data System (ADS)

    Xuan, Li; He, Bin; Hu, Li-Fa; Li, Da-Yu; Xu, Huan-Yu; Zhang, Xing-Yun; Wang, Shao-Xin; Wang, Yu-Kun; Yang, Cheng-Liang; Cao, Zhao-Liang; Mu, Quan-Quan; Lu, Xing-Hai

    2016-09-01

    Multi-conjugation adaptive optics (MCAOs) have been investigated and used in the large aperture optical telescopes for high-resolution imaging with large field of view (FOV). The atmospheric tomographic phase reconstruction and projection of three-dimensional turbulence volume onto wavefront correctors, such as deformable mirrors (DMs) or liquid crystal wavefront correctors (LCWCs), is a very important step in the data processing of an MCAO’s controller. In this paper, a method according to the wavefront reconstruction performance of MCAO is presented to evaluate the optimized configuration of multi laser guide stars (LGSs) and the reasonable conjugation heights of LCWCs. Analytical formulations are derived for the different configurations and are used to generate optimized parameters for MCAO. Several examples are given to demonstrate our LGSs configuration optimization method. Compared with traditional methods, our method has minimum wavefront tomographic error, which will be helpful to get higher imaging resolution at large FOV in MCAO. Project supported by the National Natural Science Foundation of China (Grant Nos. 11174274, 11174279, 61205021, 11204299, 61475152, and 61405194) and the State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences.

  15. Robust, integrated computational control of NMR experiments to achieve optimal assignment by ADAPT-NMR.

    PubMed

    Bahrami, Arash; Tonelli, Marco; Sahu, Sarata C; Singarapu, Kiran K; Eghbalnia, Hamid R; Markley, John L

    2012-01-01

    ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) represents a groundbreaking prototype for automated protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. With a [(13)C,(15)N]-labeled protein sample loaded into the NMR spectrometer, ADAPT-NMR delivers complete backbone resonance assignments and secondary structure in an optimal fashion without human intervention. ADAPT-NMR achieves this by implementing a strategy in which the goal of optimal assignment in each step determines the subsequent step by analyzing the current sum of available data. ADAPT-NMR is the first iterative and fully automated approach designed specifically for the optimal assignment of proteins with fast data collection as a byproduct of this goal. ADAPT-NMR evaluates the current spectral information, and uses a goal-directed objective function to select the optimal next data collection step(s) and then directs the NMR spectrometer to collect the selected data set. ADAPT-NMR extracts peak positions from the newly collected data and uses this information in updating the analysis resonance assignments and secondary structure. The goal-directed objective function then defines the next data collection step. The procedure continues until the collected data support comprehensive peak identification, resonance assignments at the desired level of completeness, and protein secondary structure. We present test cases in which ADAPT-NMR achieved results in two days or less that would have taken two months or more by manual approaches.

  16. Carrier phase estimation for optically coherent QPSK based on Wiener-optimal and adaptive Multi-Symbol Delay Detection (MSDD).

    PubMed

    Sigron, Netta; Tselniker, Igor; Nazarathy, Moshe

    2012-01-30

    The MSDD carrier phase estimation technique is derived here for optically coherent QPSK transmission, introducing the principle of operation while providing intuitive insight in terms of a multi-symbol extension of naïve delay-detection. We derive here for the first time Wiener-optimized and LMS-adapted versions of MSDD, introduce simplified hardware realizations, and evaluate complexity and numerical performance tradeoffs of this highly robust and low-complexity carrier phase recovery method. A multiplier-free carrier phase recovery version of the MSDD provides nearly optimal performance for linewidths up to ~0.5 MHz, whereas for wider linewidths, the Wiener or LMS versions provide optimal performance at about 9 taps, using 1 or 2 complex multipliers per tap.

  17. Adaptation of NASA technology for the optimization of orthopedic knee implants

    NASA Technical Reports Server (NTRS)

    Saravanos, D. A.; Mraz, P. J.; Hopkins, D. A.

    1991-01-01

    The NASA technology originally developed for the optimization of composite structures (engine blades) is adapted and applied to the optimization of orthopedic knee implants. A method is developed enabling the tailoring of the implant for optimal interaction with the environment of the tibia. The shape of the implant components are optimized, such that the stresses in the bone are favorably controlled to minimize bone degradation and prevent failures. A pilot tailoring system is developed and the feasibility of the concept is elevated. The optimization system is expected to provide the means for improving knee prosthesis and individual implant tailoring for each patient.

  18. Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

    2016-09-01

    In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

  19. Digital control of high performance aircraft using adaptive estimation techniques

    NASA Technical Reports Server (NTRS)

    Van Landingham, H. F.; Moose, R. L.

    1977-01-01

    In this paper, an adaptive signal processing algorithm is joined with gain-scheduling for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance STOL aircraft. The actual controller views the nonlinear behavior of the aircraft as equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. Nonlinear behavior is approximated by effective switching of the linear models at random times, with durations reflecting aircraft motion in response to pilot commands.

  20. Optimal control based on adaptive model reduction approach to control transfer phenomena

    NASA Astrophysics Data System (ADS)

    Oulghelou, Mourad; Allery, Cyrille

    2017-01-01

    The purpose of optimal control is to act on a set of parameters characterizing a dynamical system to achieve a target dynamics. In order to reduce CPU time and memory storage needed to perform control on evolution systems, it is possible to use reduced order models (ROMs). The mostly used one is the Proper Orthogonal Decomposition (POD). However the bases constructed in this way are sensitive to the configuration of the dynamical system. Consequently, the need of full simulations to build a basis for each configuration is time consuming and makes that approach still relatively expensive. In this paper, to overcome this difficulty we suggest to use an adequate bases interpolation method. It consists in computing the associated bases to a distribution of control parameters. These bases are afterwards called in the control algorithm to build a reduced basis adapted to a given control parameter. This interpolation method involves results of the calculus of Geodesics on Grassmann manifold.

  1. Statistical inference for response adaptive randomization procedures with adjusted optimal allocation proportions.

    PubMed

    Zhu, Hongjian

    2016-12-12

    Seamless phase II/III clinical trials have attracted increasing attention recently. They mainly use Bayesian response adaptive randomization (RAR) designs. There has been little research into seamless clinical trials using frequentist RAR designs because of the difficulty in performing valid statistical inference following this procedure. The well-designed frequentist RAR designs can target theoretically optimal allocation proportions, and they have explicit asymptotic results. In this paper, we study the asymptotic properties of frequentist RAR designs with adjusted target allocation proportions, and investigate statistical inference for this procedure. The properties of the proposed design provide an important theoretical foundation for advanced seamless clinical trials. Our numerical studies demonstrate that the design is ethical and efficient.

  2. Generalized Monge-Kantorovich optimization for grid generation and adaptation in LP

    SciTech Connect

    Delzanno, G L; Finn, J M

    2009-01-01

    The Monge-Kantorovich grid generation and adaptation scheme of is generalized from a variational principle based on L{sub 2} to a variational principle based on L{sub p}. A generalized Monge-Ampere (MA) equation is derived and its properties are discussed. Results for p > 1 are obtained and compared in terms of the quality of the resulting grid. We conclude that for the grid generation application, the formulation based on L{sub p} for p close to unity leads to serious problems associated with the boundary. Results for 1.5 {approx}< p {approx}< 2.5 are quite good, but there is a fairly narrow range around p = 2 where the results are close to optimal with respect to grid distortion. Furthermore, the Newton-Krylov methods used to solve the generalized MA equation perform best for p = 2.

  3. Sensorimotor Adaptability Training Improves Motor and Dual-Task Performance

    NASA Technical Reports Server (NTRS)

    Bloomberg, J.J.; Peters, B.T.; Mulavara, A.P.; Brady, R.; Batson, C.; Cohen, H.S.

    2009-01-01

    The overall objective of our project is to develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The goal of our current study was to determine if SA training using variation in visual flow and support surface motion produces improved performance in a novel sensory environment and demonstrate the retention characteristics of SA training.

  4. Optimality and adaptation of phenotypically switching cells in fluctuating environments

    NASA Astrophysics Data System (ADS)

    Belete, Merzu Kebede; Balázsi, Gábor

    2015-12-01

    Stochastic switching between alternative phenotypic states is a common cellular survival strategy during unforeseen environmental fluctuations. Cells can switch between different subpopulations that proliferate at different rates in different environments. Optimal population growth is typically assumed to occur when phenotypic switching rates match environmental switching rates. However, it is not well understood how this optimum behaves as a function of the growth rates of phenotypically different cells. In this study, we use mathematical and computational models to test how the actual parameters associated with optimal population growth differ from those assumed to be optimal. We find that the predicted optimum is practically always valid if the environmental durations are long. However, the regime of validity narrows as environmental durations shorten, especially if subpopulation growth rate differences differ from each other (are asymmetric) in two environments. Furthermore, we study the fate of mutants with switching rates previously predicted to be optimal. We find that mutants which match their phenotypic switching rates with the environmental ones can only sweep the population if the assumed optimum is valid, but not otherwise.

  5. Optimality and adaptation of phenotypically switching cells in fluctuating environments.

    PubMed

    Belete, Merzu Kebede; Balázsi, Gábor

    2015-12-01

    Stochastic switching between alternative phenotypic states is a common cellular survival strategy during unforeseen environmental fluctuations. Cells can switch between different subpopulations that proliferate at different rates in different environments. Optimal population growth is typically assumed to occur when phenotypic switching rates match environmental switching rates. However, it is not well understood how this optimum behaves as a function of the growth rates of phenotypically different cells. In this study, we use mathematical and computational models to test how the actual parameters associated with optimal population growth differ from those assumed to be optimal. We find that the predicted optimum is practically always valid if the environmental durations are long. However, the regime of validity narrows as environmental durations shorten, especially if subpopulation growth rate differences differ from each other (are asymmetric) in two environments. Furthermore, we study the fate of mutants with switching rates previously predicted to be optimal. We find that mutants which match their phenotypic switching rates with the environmental ones can only sweep the population if the assumed optimum is valid, but not otherwise.

  6. Quadratic performance index generation for optimal regular design.

    NASA Technical Reports Server (NTRS)

    Bullock, T. E.; Elder, J. M.

    1971-01-01

    Application of optimal control theory to practical problems has been limited by the difficulty of prescribing a performance index which accurately reflects design requirements. The task of deriving equivalent performance indices is considered in the present paper for a plant that is a completely controllable, scalar linear system with state feedback. A quadratic index is developed which leads to an optimal design performance satisfying some of the classical performance criteria.

  7. Tradeoff-based optimization criteria in clinical trials with multiple objectives and adaptive designs.

    PubMed

    Dmitrienko, Alex; Paux, Gautier; Pulkstenis, Erik; Zhang, Jianliang

    2016-01-01

    The article discusses clinical trial optimization problems in the context of mid- to late-stage drug development. Using the Clinical Scenario Evaluation approach, main objectives of clinical trial optimization are formulated, including selection of clinically relevant optimization criteria, identification of sets of optimal and nearly optimal values of the parameters of interest, and sensitivity assessments. The paper focuses on a class of optimization criteria arising in clinical trials with several competing goals, termed tradeoff-based optimization criteria, and discusses key considerations in constructing and applying tradeoff-based criteria. The clinical trial optimization framework considered in the paper is illustrated using two case studies based on a clinical trial with multiple objectives and a two-stage clinical trial which utilizes adaptive decision rules.

  8. Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.

    PubMed

    Wei, Qinglai; Liu, Derong; Lin, Hanquan

    2016-03-01

    In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.

  9. Program optimizations: The interplay between power, performance, and energy

    SciTech Connect

    Leon, Edgar A.; Karlin, Ian; Grant, Ryan E.; Dosanjh, Matthew

    2016-05-16

    Practical considerations for future supercomputer designs will impose limits on both instantaneous power consumption and total energy consumption. Working within these constraints while providing the maximum possible performance, application developers will need to optimize their code for speed alongside power and energy concerns. This paper analyzes the effectiveness of several code optimizations including loop fusion, data structure transformations, and global allocations. A per component measurement and analysis of different architectures is performed, enabling the examination of code optimizations on different compute subsystems. Using an explicit hydrodynamics proxy application from the U.S. Department of Energy, LULESH, we show how code optimizations impact different computational phases of the simulation. This provides insight for simulation developers into the best optimizations to use during particular simulation compute phases when optimizing code for future supercomputing platforms. Here, we examine and contrast both x86 and Blue Gene architectures with respect to these optimizations.

  10. Online optimal tracking control of continuous-time linear systems with unknown dynamics by using adaptive dynamic programming

    NASA Astrophysics Data System (ADS)

    Qin, Chunbin; Zhang, Huaguang; Luo, Yanhong

    2014-05-01

    In this paper, a novel theoretic formulation based on adaptive dynamic programming (ADP) is developed to solve online the optimal tracking problem of the continuous-time linear system with unknown dynamics. First, the original system dynamics and the reference trajectory dynamics are transformed into an augmented system. Then, under the same performance index with the original system dynamics, an augmented algebraic Riccati equation is derived. Furthermore, the solutions for the optimal control problem of the augmented system are proven to be equal to the standard solutions for the optimal tracking problem of the original system dynamics. Moreover, a new online algorithm based on the ADP technique is presented to solve the optimal tracking problem of the linear system with unknown system dynamics. Finally, simulation results are given to verify the effectiveness of the theoretic results.

  11. Mesh Adaptive Direct Search Methods for Constrained Nonsmooth Optimization

    DTIC Science & Technology

    2012-02-24

    presence will extend our collaboration circle to mechanical engineering researchers. • We have initiated a new collaboration with A.D. Pelton from chemi...Published: 1. A.E. Gheribi, C. Audet, S. Le Digabel, E. Blisle, C.W. Bale and A. D. Pelton . Calculating optimal conditions for alloy and process...Gheribi, C. Robelin, S. Le Digabel, C. Audet and A.D. Pelton . Calculating All Local Minima on Liquidus Surfaces Using the FactSage Software and Databases

  12. A Gradient Optimization Approach to Adaptive Multi-Robot Control

    DTIC Science & Technology

    2009-09-01

    optimization through the evolution of a dynamical system. Some existing approaches do not fit under the framework we propose in this chap- ter. A...parameters are coupled among robots, we must consider the evolution of all the robots’ parameters together. Let = [ a]. (4.39) be a concatenated...dynamics * Synchronous evolution of equa- tions * Exact Voronoi cells computed from exact positions of all Voronoi neighbors * Exact integrals over

  13. Adaptive optimal spectral range for dynamically changing scene

    NASA Astrophysics Data System (ADS)

    Pinsky, Ephi; Siman-tov, Avihay; Peles, David

    2012-06-01

    A novel multispectral video system that continuously optimizes both its spectral range channels and the exposure time of each channel autonomously, under dynamic scenes, varying from short range-clear scene to long range-poor visibility, is currently being developed. Transparency and contrast of high scattering medium of channels with spectral ranges in the near infrared is superior to the visible channels, particularly to the blue range. Longer wavelength spectral ranges that induce higher contrast are therefore favored. Images of 3 spectral channels are fused and displayed for (pseudo) color visualization, as an integrated high contrast video stream. In addition to the dynamic optimization of the spectral channels, optimal real-time exposure time is adjusted simultaneously and autonomously for each channel. A criterion of maximum average signal, derived dynamically from previous frames of the video stream is used (Patent Application - International Publication Number: WO2009/093110 A2, 30.07.2009). This configuration enables dynamic compatibility with the optimal exposure time of a dynamically changing scene. It also maximizes the signal to noise ratio and compensates each channel for the specified value of daylight reflections and sensors response for each spectral range. A possible implementation is a color video camera based on 4 synchronized, highly responsive, CCD imaging detectors, attached to a 4CCD dichroic prism and combined with a common, color corrected, lens. Principal Components Analysis (PCA) technique is then applied for real time "dimensional collapse" in color space, in order to select and fuse, for clear color visualization, the 3 most significant principal channels out of at least 4 characterized by high contrast and rich details in the image data.

  14. Adaptive Optimization Techniques for Large-Scale Stochastic Planning

    DTIC Science & Technology

    2011-06-28

    cannot be kept longer than a few weeks. The decision maker must decide on blood - type substitutions that minimize the chance of future shortage. Because...optimal blood - type substitution is a large stochastic problem. Another application is managing water reservoirs. In this domain, an operator needs to decide...compatibility constraints among blood types , blood inventory management does not fit well the standard inventory control framework. In reservoir management

  15. Optimization of heterogeneous Bin packing using adaptive genetic algorithm

    NASA Astrophysics Data System (ADS)

    Sridhar, R.; Chandrasekaran, M.; Sriramya, C.; Page, Tom

    2017-03-01

    This research is concentrates on a very interesting work, the bin packing using hybrid genetic approach. The optimal and feasible packing of goods for transportation and distribution to various locations by satisfying the practical constraints are the key points in this project work. As the number of boxes for packing can not be predicted in advance and the boxes may not be of same category always. It also involves many practical constraints that are why the optimal packing makes much importance to the industries. This work presents a combinational of heuristic Genetic Algorithm (HGA) for solving Three Dimensional (3D) Single container arbitrary sized rectangular prismatic bin packing optimization problem by considering most of the practical constraints facing in logistic industries. This goal was achieved in this research by optimizing the empty volume inside the container using genetic approach. Feasible packing pattern was achieved by satisfying various practical constraints like box orientation, stack priority, container stability, weight constraint, overlapping constraint, shipment placement constraint. 3D bin packing problem consists of ‘n’ number of boxes being to be packed in to a container of standard dimension in such a way to maximize the volume utilization and in-turn profit. Furthermore, Boxes to be packed may be of arbitrary sizes. The user input data are the number of bins, its size, shape, weight, and constraints if any along with standard container dimension. This user input were stored in the database and encoded to string (chromosomes) format which were normally acceptable by GA. GA operators were allowed to act over these encoded strings for finding the best solution.

  16. Optimal performance of a thermoelectric refrigerator

    SciTech Connect

    Goektun, S.

    1996-07-01

    By employing an externally and internally irreversible Carnot-like reversed heat engine model, the coefficient of performance and maximum cooling rate have been determined for a thermoelectric refrigerator. The irreversibilities can be characterized by a single parameter called the device-design parameter. The coefficient of performance and the cooling rate increase with an increase of the device-design parameter, which appears in the equations for maximum cooling rate and coefficient of performance.

  17. Active vibration control with optimized modified acceleration feedback equipped with adaptive line enhancer

    NASA Astrophysics Data System (ADS)

    Mahmoodi, S. Nima; Craft, Michael J.; Ahmadian, Mehdi

    2010-04-01

    Modified acceleration feedback (MAF) control, an active vibration control method that uses collocated piezoelectric actuator actuators and sensors is improved using an optimal controller. The controller consists of two main parts: 1) Frequency adaptation that uses Adaptive Line Enhancer (ALE), and 2) an optimal controller. Frequency adaptation tracks the frequency of vibrations using ALE. The obtained frequency is then fed to MPPF compensators and the optimal controller. This provides a unique feature for MAF, by extending its domain of capabilities from controlling tonal vibrations to broad band disturbances. The optimal controller consists of a set of optimal gains for wide range of frequencies that is provided, related to the characteristics of the system. Based on the tracked frequency, the optimal control system decides to use which set of gains for the MAF controller. The gains are optimal for the frequencies close to the tracked frequency. The numerical results show that the frequency tracking method that is derived has worked quite well. In addition, the frequency tracking is fast enough to be used in real-time controller. The results also indicate that the MAF can provide significant vibration reduction using the optimal controller.

  18. Active vibration control using optimized modified acceleration feedback with Adaptive Line Enhancer for frequency tracking

    NASA Astrophysics Data System (ADS)

    Nima Mahmoodi, S.; Craft, Michael J.; Southward, Steve C.; Ahmadian, Mehdi

    2011-03-01

    Modified acceleration feedback (MAF) control, an active vibration control method that uses collocated piezoelectric actuators and accelerometer is developed and its gains optimized using an optimal controller. The control system consists of two main parts: (1) frequency adaptation that uses Adaptive Line Enhancer (ALE) and (2) an optimized controller. Frequency adaptation method tracks the frequency of vibrations using ALE. The obtained frequency is then fed to MAF compensators. This provides a unique feature for MAF, by extending its domain of capabilities from controlling a certain mode of vibrations to any excited mode. The optimized MAF controller can provide optimal sets of gains for a wide range of frequencies, based on the characteristics of the system. The experimental results show that the frequency tracking method works quite well and fast enough to be used in a real-time controller. ALE parameters are numerically and experimentally investigated and tuned for optimized frequency tracking. The results also indicate that the MAF can provide significant vibration reduction using the optimized controller. The control power varies for vibration suppression at different resonance frequencies; however, it is always optimized.

  19. Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

    NASA Astrophysics Data System (ADS)

    Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

    2014-05-01

    Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

  20. Translation and adaptation of functional auditory performance indicators (FAPI)

    PubMed Central

    FERREIRA, Karina; MORET, Adriane Lima Mortari; BEVILACQUA, Maria Cecilia; JACOB, Regina de Souza Tangerino

    2011-01-01

    Work with deaf children has gained new attention since the expectation and goal of therapy has expanded to language development and subsequent language learning. Many clinical tests were developed for evaluation of speech sound perception in young children in response to the need for accurate assessment of hearing skills that developed from the use of individual hearing aids or cochlear implants. These tests also allow the evaluation of the rehabilitation program. However, few of these tests are available in Portuguese. Evaluation with the Functional Auditory Performance Indicators (FAPI) generates a child's functional auditory skills profile, which lists auditory skills in an integrated and hierarchical order. It has seven hierarchical categories, including sound awareness, meaningful sound, auditory feedback, sound source localizing, auditory discrimination, short-term auditory memory, and linguistic auditory processing. FAPI evaluation allows the therapist to map the child's hearing profile performance, determine the target for increasing the hearing abilities, and develop an effective therapeutic plan. Objective Since the FAPI is an American test, the inventory was adapted for application in the Brazilian population. Material and Methods The translation was done following the steps of translation and back translation, and reproducibility was evaluated. Four translated versions (two originals and two back-translated) were compared, and revisions were done to ensure language adaptation and grammatical and idiomatic equivalence. Results The inventory was duly translated and adapted. Conclusion Further studies about the application of the translated FAPI are necessary to make the test practicable in Brazilian clinical use. PMID:22230992

  1. Performance optimization of web-based medical simulation.

    PubMed

    Halic, Tansel; Ahn, Woojin; De, Suvranu

    2013-01-01

    This paper presents a technique for performance optimization of multimodal interactive web-based medical simulation. A web-based simulation framework is promising for easy access and wide dissemination of medical simulation. However, the real-time performance of the simulation highly depends on hardware capability on the client side. Providing consistent simulation in different hardware is critical for reliable medical simulation. This paper proposes a non-linear mixed integer programming model to optimize the performance of visualization and physics computation while considering hardware capability and application specific constraints. The optimization model identifies and parameterizes the rendering and computing capabilities of the client hardware using an exploratory proxy code. The parameters are utilized to determine the optimized simulation conditions including texture sizes, mesh sizes and canvas resolution. The test results show that the optimization model not only achieves a desired frame per second but also resolves visual artifacts due to low performance hardware.

  2. Development and implementation of a coupled computational muscle force optimization bone shape adaptation modeling method.

    PubMed

    Florio, C S

    2015-04-01

    Improved methods to analyze and compare the muscle-based influences that drive bone strength adaptation can aid in the understanding of the wide array of experimental observations about the effectiveness of various mechanical countermeasures to losses in bone strength that result from age, disuse, and reduced gravity environments. The coupling of gradient-based and gradientless numerical optimization routines with finite element methods in this work results in a modeling technique that determines the individual magnitudes of the muscle forces acting in a multisegment musculoskeletal system and predicts the improvement in the stress state uniformity and, therefore, strength, of a targeted bone through simulated local cortical material accretion and resorption. With a performance-based stopping criteria, no experimentally based or system-based parameters, and designed to include the direct and indirect effects of muscles attached to the targeted bone as well as to its neighbors, shape and strength alterations resulting from a wide range of boundary conditions can be consistently quantified. As demonstrated in a representative parametric study, the developed technique effectively provides a clearer foundation for the study of the relationships between muscle forces and the induced changes in bone strength. Its use can lead to the better control of such adaptive phenomena.

  3. Performance Trend of Different Algorithms for Structural Design Optimization

    NASA Technical Reports Server (NTRS)

    Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

    1996-01-01

    Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

  4. Optimization-based wavefront sensorless adaptive optics for multiphoton microscopy.

    PubMed

    Antonello, Jacopo; van Werkhoven, Tim; Verhaegen, Michel; Truong, Hoa H; Keller, Christoph U; Gerritsen, Hans C

    2014-06-01

    Optical aberrations have detrimental effects in multiphoton microscopy. These effects can be curtailed by implementing model-based wavefront sensorless adaptive optics, which only requires the addition of a wavefront shaping device, such as a deformable mirror (DM) to an existing microscope. The aberration correction is achieved by maximizing a suitable image quality metric. We implement a model-based aberration correction algorithm in a second-harmonic microscope. The tip, tilt, and defocus aberrations are removed from the basis functions used for the control of the DM, as these aberrations induce distortions in the acquired images. We compute the parameters of a quadratic polynomial that is used to model the image quality metric directly from experimental input-output measurements. Finally, we apply the aberration correction by maximizing the image quality metric using the least-squares estimate of the unknown aberration.

  5. Adaptive Edge Detection Using Adjusted ANT Colony Optimization

    NASA Astrophysics Data System (ADS)

    Davoodianidaliki, M.; Abedini, A.; Shankayi, M.

    2013-09-01

    Edges contain important information in image and edge detection can be considered a low level process in image processing. Among different methods developed for this purpose traditional methods are simple and rather efficient. In Swarm Intelligent methods developed in last decade, ACO is more capable in this process. This paper uses traditional edge detection operators such as Sobel and Canny as input to ACO and turns overall process adaptive to application. Magnitude matrix or edge image can be used for initial pheromone and ant distribution. Image size reduction is proposed as an efficient smoothing method. A few parameters such as area and diameter of travelled path by ants are converted into rules in pheromone update process. All rules are normalized and final value is acquired by averaging.

  6. A mathematical basis for the design optimization of adaptive trusses in precision control

    NASA Technical Reports Server (NTRS)

    Das, S. K.; Utku, S.; Chen, G. S.; Wada, B. K.

    1991-01-01

    Optimal actuator placement schemes are presently studied for cases of adaptive truss precision control and prestressing control, with a view to the maximization of actuator efficiencies. In statically indeterminate truss structures, the optimal placement criteria and techniques differ, depending on whether the primary determinate structure is known. A suboptimal actuator-placement solution to the global optimization problem which combines displacement control and prestressing control is suggested, by combining the separate displacement control and prestressing control optimization results. Attention is given to the results obtained for the illustrative case of a two-bay, three-dimensional precision truss structure.

  7. Issues in the design and optimization of adaptive optics and laser guide stars for the Keck Telescopes

    SciTech Connect

    Max, C.E.; Gavel, D.T.; Olivier, S.S.

    1994-03-01

    We discuss issues in optimizing the design of adaptive optics and laser guide star systems for the Keck Telescope. The initial tip-tilt system will use Keck`s chopping secondary mirror. We describe design constraints, choice of detector, and expected performance of this tip-tilt system as well as its sky coverage. The adaptive optics system is being optimized for wavelengths of I-2.2{mu}m. We are studying adaptive optics concepts which use a wavefront sensor with varying numbers of subapertures, so as to respond to changing turbulence conditions. The goal is to be able to ``gang together`` groups of deformable mirror subapertures under software control, when conditions call for larger subapertures. We present performance predictions as a function of sky coverage and the number of deformable mirror degrees of freedom. We analyze the predicted brightness several candidate laser guide star systems, as a function of laser power and pulse format. These predictions are used to examine the resulting Strehl as a function of observing wavelength and laser type. We discuss laser waste heat and thermal management issues, and conclude with an overview of instruments under design to take advantage of the Keck adaptive optics system.

  8. Single string based global optimizer for geometry optimization in strongly coupled finite clusters: An adaptive mutation-driven strategy.

    PubMed

    Sarkar, Kanchan; Bhattacharyya, S P

    2013-08-21

    We propose and implement a simple adaptive heuristic to optimize the geometries of clusters of point charges or ions with the ability to find the global minimum energy configurations. The approach uses random mutations of a single string encoding the geometry and accepts moves that decrease the energy. Mutation probability and mutation intensity are allowed to evolve adaptively on the basis of continuous evaluation of past explorations. The resulting algorithm has been called Completely Adaptive Random Mutation Hill Climbing method. We have implemented this method to search through the complex potential energy landscapes of parabolically confined 3D classical Coulomb clusters of hundreds or thousands of charges--usually found in high frequency discharge plasmas. The energy per particle (EN∕N) and its first and second differences, structural features, distribution of the oscillation frequencies of normal modes, etc., are analyzed as functions of confinement strength and the number of charges in the system. Certain magic numbers are identified. In order to test the feasibility of the algorithm in cluster geometry optimization on more complex energy landscapes, we have applied the algorithm for optimizing the geometries of MgO clusters, described by Coulomb-Born-Mayer potential and finding global minimum of some Lennard-Jones clusters. The convergence behavior of the algorithm compares favorably with those of other existing global optimizers.

  9. Single string based global optimizer for geometry optimization in strongly coupled finite clusters: An adaptive mutation-driven strategy

    NASA Astrophysics Data System (ADS)

    Sarkar, Kanchan; Bhattacharyya, S. P.

    2013-08-01

    We propose and implement a simple adaptive heuristic to optimize the geometries of clusters of point charges or ions with the ability to find the global minimum energy configurations. The approach uses random mutations of a single string encoding the geometry and accepts moves that decrease the energy. Mutation probability and mutation intensity are allowed to evolve adaptively on the basis of continuous evaluation of past explorations. The resulting algorithm has been called Completely Adaptive Random Mutation Hill Climbing method. We have implemented this method to search through the complex potential energy landscapes of parabolically confined 3D classical Coulomb clusters of hundreds or thousands of charges—usually found in high frequency discharge plasmas. The energy per particle (EN/N) and its first and second differences, structural features, distribution of the oscillation frequencies of normal modes, etc., are analyzed as functions of confinement strength and the number of charges in the system. Certain magic numbers are identified. In order to test the feasibility of the algorithm in cluster geometry optimization on more complex energy landscapes, we have applied the algorithm for optimizing the geometries of MgO clusters, described by Coulomb-Born-Mayer potential and finding global minimum of some Lennard-Jones clusters. The convergence behavior of the algorithm compares favorably with those of other existing global optimizers.

  10. Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

  11. Program optimizations: The interplay between power, performance, and energy

    DOE PAGES

    Leon, Edgar A.; Karlin, Ian; Grant, Ryan E.; ...

    2016-05-16

    Practical considerations for future supercomputer designs will impose limits on both instantaneous power consumption and total energy consumption. Working within these constraints while providing the maximum possible performance, application developers will need to optimize their code for speed alongside power and energy concerns. This paper analyzes the effectiveness of several code optimizations including loop fusion, data structure transformations, and global allocations. A per component measurement and analysis of different architectures is performed, enabling the examination of code optimizations on different compute subsystems. Using an explicit hydrodynamics proxy application from the U.S. Department of Energy, LULESH, we show how code optimizationsmore » impact different computational phases of the simulation. This provides insight for simulation developers into the best optimizations to use during particular simulation compute phases when optimizing code for future supercomputing platforms. Here, we examine and contrast both x86 and Blue Gene architectures with respect to these optimizations.« less

  12. The cost of model reference adaptive control - Analysis, experiments, and optimization

    NASA Technical Reports Server (NTRS)

    Messer, R. S.; Haftka, R. T.; Cudney, H. H.

    1993-01-01

    In this paper the performance of Model Reference Adaptive Control (MRAC) is studied in numerical simulations and verified experimentally with the objective of understanding how differences between the plant and the reference model affect the control effort. MRAC is applied analytically and experimentally to a single degree of freedom system and analytically to a MIMO system with controlled differences between the model and the plant. It is shown that the control effort is sensitive to differences between the plant and the reference model. The effects of increased damping in the reference model are considered, and it is shown that requiring the controller to provide increased damping actually decreases the required control effort when differences between the plant and reference model exist. This result is useful because one of the first attempts to counteract the increased control effort due to differences between the plant and reference model might be to require less damping, however, this would actually increase the control effort. Optimization of weighting matrices is shown to help reduce the increase in required control effort. However, it was found that eventually the optimization resulted in a design that required an extremely high sampling rate for successful realization.

  13. Optimized tuner selection for engine performance estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

    2013-01-01

    A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

  14. Business owners' optimism and business performance after a natural disaster.

    PubMed

    Bronson, James W; Faircloth, James B; Valentine, Sean R

    2006-12-01

    Previous work indicates that individuals' optimism is related to superior performance in adverse situations. This study examined correlations after flooding for measures of business recovery but found only weak support (very small common variance) for business owners' optimism scores and sales recovery. Using traditional measures of recovery, in this study was little empirical evidence that optimism would be of value in identifying businesses at risk after a natural disaster.

  15. Design, Performance and Optimization for Multimodal Radar Operation

    PubMed Central

    Bhat, Surendra S.; Narayanan, Ram M.; Rangaswamy, Muralidhar

    2012-01-01

    This paper describes the underlying methodology behind an adaptive multimodal radar sensor that is capable of progressively optimizing its range resolution depending upon the target scattering features. It consists of a test-bed that enables the generation of linear frequency modulated waveforms of various bandwidths. This paper discusses a theoretical approach to optimizing the bandwidth used by the multimodal radar. It also discusses the various experimental results obtained from measurement. The resolution predicted from theory agrees quite well with that obtained from experiments for different target arrangements.

  16. Optimizing Hydronic System Performance in Residential Applications

    SciTech Connect

    2013-10-01

    Even though new homes constructed with hydronic heat comprise only 3% of the market (US Census Bureau 2009), of the 115 million existing homes in the United States, almost 14 million of those homes (11%) are heated with steam or hot water systems according to 2009 US Census data. Therefore, improvements in hydronic system performance could result in significant energy savings in the US.

  17. Psychopharmacological Techniques for Optimizing Human Performance

    DTIC Science & Technology

    1983-03-22

    triazolam, flurazepam, and nitrazepam . Psychopharmacology, 1980, 68: 61-65. 12. Pegram, V., Hyde, P., and Linton, P. Chronic use of triazolam: the...Hindmarch, I. and Clyde, C. A. The effects of triazolam and nitrazepam on sleep quality, morning vigilance, and psychomotor performance. Arzneim

  18. Performance bounds on optimal watermark synchronizers

    NASA Astrophysics Data System (ADS)

    Licks, Vinicius; Ourique, Fabricio; Jordan, Ramiro

    2004-06-01

    The inability of existing countermeasures to consistently cope against localized geometric attacks has precluded the widespread acceptance of image watermarking for commercial applications. The efficiency of these attacks against the so-called spread spectrum methods resides in their ability to affect the synchronization between the watermark reference and the extracted watermark at the detector end. In systems based on quantization schemes, geometric attacks have the effect of moving the watermark vector away from its actual quantization centroid, thus causing the watermark decoder to output wrong message symbols. In this paper, our goal is to gain a better understanding of the challenges imposed by the watermark synchronization problem in the context of localized geometric attacks. For that matter, we propose a model for the watermark synchronization problem based on maximum-likelihood (ML) estimation techniques. In that way, we derive theoretically optimal watermark synchronizer structures for either blind or non-blind schemes and based on the Cramer-Rao inequality we set lower bounds on the variance of these attack parameter estimates as a means to assess the accuracy of such synchronizers.

  19. Optimal adaptive two-stage designs for early phase II clinical trials.

    PubMed

    Shan, Guogen; Wilding, Gregory E; Hutson, Alan D; Gerstenberger, Shawn

    2016-04-15

    Simon's optimal two-stage design has been widely used in early phase clinical trials for Oncology and AIDS studies with binary endpoints. With this approach, the second-stage sample size is fixed when the trial passes the first stage with sufficient activity. Adaptive designs, such as those due to Banerjee and Tsiatis (2006) and Englert and Kieser (2013), are flexible in the sense that the second-stage sample size depends on the response from the first stage, and these designs are often seen to reduce the expected sample size under the null hypothesis as compared with Simon's approach. An unappealing trait of the existing designs is that they are not associated with a second-stage sample size, which is a non-increasing function of the first-stage response rate. In this paper, an efficient intelligent process, the branch-and-bound algorithm, is used in extensively searching for the optimal adaptive design with the smallest expected sample size under the null, while the type I and II error rates are maintained and the aforementioned monotonicity characteristic is respected. The proposed optimal design is observed to have smaller expected sample sizes compared to Simon's optimal design, and the maximum total sample size of the proposed adaptive design is very close to that from Simon's method. The proposed optimal adaptive two-stage design is recommended for use in practice to improve the flexibility and efficiency of early phase therapeutic development.

  20. Fuzzy physical programming for Space Manoeuvre Vehicles trajectory optimization based on hp-adaptive pseudospectral method

    NASA Astrophysics Data System (ADS)

    Chai, Runqi; Savvaris, Al; Tsourdos, Antonios

    2016-06-01

    In this paper, a fuzzy physical programming (FPP) method has been introduced for solving multi-objective Space Manoeuvre Vehicles (SMV) skip trajectory optimization problem based on hp-adaptive pseudospectral methods. The dynamic model of SMV is elaborated and then, by employing hp-adaptive pseudospectral methods, the problem has been transformed to nonlinear programming (NLP) problem. According to the mission requirements, the solutions were calculated for each single-objective scenario. To get a compromised solution for each target, the fuzzy physical programming (FPP) model is proposed. The preference function is established with considering the fuzzy factor of the system such that a proper compromised trajectory can be acquired. In addition, the NSGA-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the FPP solution. Simulation results indicate that the proposed method is effective and feasible in terms of dealing with the multi-objective skip trajectory optimization for the SMV.

  1. Bayesian optimal response-adaptive design for binary responses using stopping rule.

    PubMed

    Komaki, Fumiyasu; Biswas, Atanu

    2016-05-02

    Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.

  2. Adaptive FEM with coarse initial mesh guarantees optimal convergence rates for compactly perturbed elliptic problems

    NASA Astrophysics Data System (ADS)

    Bespalov, Alex; Haberl, Alexander; Praetorius, Dirk

    2017-04-01

    We prove that for compactly perturbed elliptic problems, where the corresponding bilinear form satisfies a Garding inequality, adaptive mesh-refinement is capable of overcoming the preasymptotic behavior and eventually leads to convergence with optimal algebraic rates. As an important consequence of our analysis, one does not have to deal with the a-priori assumption that the underlying meshes are sufficiently fine. Hence, the overall conclusion of our results is that adaptivity has stabilizing effects and can overcome possibly pessimistic restrictions on the meshes. In particular, our analysis covers adaptive mesh-refinement for the finite element discretization of the Helmholtz equation from where our interest originated.

  3. Adaptive interventions may optimize outcomes in drug courts: a pilot study.

    PubMed

    Marlowe, Douglas B; Festinger, David S; Arabia, Patricia L; Dugosh, Karen L; Benasutti, Kathleen M; Croft, Jason R

    2009-10-01

    Adaptive interventions apply a priori decision rules for adjusting treatment services in response to participants' clinical presentation or performance in treatment. This pilot study (n = 30) experimentally examined an adaptive intervention in a misdemeanor drug court. The participants were primarily charged with possession of marijuana (73%) or possession of drug paraphernalia (23%). Results revealed that participants in the adaptive condition had higher graduation rates and required significantly less time to graduate from the program and achieve a final resolution of the case. It took an average of nearly 4 fewer months for participants in the adaptive intervention to resolve their cases compared with those participating in drug court as usual. Participants in the adaptive condition also reported equivalent satisfaction with the program and therapeutic alliances with their counselors. These data suggest that adaptive interventions may enhance the efficiency and effectiveness of drug courts and justify examining adaptive interventions in large-scale drug court studies.

  4. Adaptive Interventions May Optimize Outcomes in Drug Courts: A Pilot Study

    PubMed Central

    Marlowe, Douglas B.; Festinger, David S.; Arabia, Patricia L.; Dugosh, Karen L.; Benasutti, Kathleen M.; Croft, Jason R.

    2009-01-01

    Adaptive interventions apply a priori decision rules for adjusting treatment services in response to participants’ clinical presentation or performance in treatment. This pilot study (N = 30) experimentally examined an adaptive intervention in a misdemeanor drug court. The participants were primarily charged with possession of marijuana (73%) or possession of drug paraphernalia (23%). Results revealed that participants in the adaptive condition had relatively higher graduation rates and required significantly less time to graduate from the program and achieve a final resolution of the case. It took an average of nearly 4 fewer months for participants in the adaptive intervention to resolve their cases as compared to drug court as-usual. Participants in the adaptive condition also reported equivalent satisfaction with the program and therapeutic alliances with their counselors. These data suggest that adaptive interventions may enhance the efficiency and effectiveness of drug courts, and justify examining adaptive interventions in large-scale drug court studies. PMID:19785978

  5. On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2011-01-01

    This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.

  6. Local adaptation of reproductive performance during thermal stress.

    PubMed

    Porcelli, D; Gaston, K J; Butlin, R K; Snook, R R

    2017-02-01

    Considerable evidence exists for local adaptation of critical thermal limits in ectotherms following adult temperature stress, but fewer studies have tested for local adaptation of sublethal heat stress effects across life-history stages. In organisms with complex life cycles, such as holometabolous insects, heat stress during juvenile stages may severely impact gametogenesis, having downstream consequences on reproductive performance that may be mediated by local adaptation, although this is rarely studied. Here, we tested how exposure to either benign or heat stress temperature during juvenile and adult stages, either independently or combined, influences egg-to-adult viability, adult sperm motility and fertility in high- and low-latitude populations of Drosophila subobscura. We found both population- and temperature-specific effects on survival and sperm motility; juvenile heat stress decreased survival and subsequent sperm motility and each trait was lower in the northern population. We found an interaction between population and temperature on fertility following application of juvenile heat stress; although fertility was negatively impacted in both populations, the southern population was less affected. When the adult stage was also subject to heat stress, the southern population exhibited positive carry-over effects whereas the northern population's fertility remained low. Thus, the northern population is more susceptible to sublethal reproductive consequences following exposure to juvenile heat stress. This may be common in other organisms with complex life cycles and current models predicting population responses to climate change, which do not take into account the impact of juvenile heat stress on reproductive performance, may be too conservative.

  7. Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

    PubMed

    Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

    2006-04-01

    This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control

  8. An adaptive metamodel-based global optimization algorithm for black-box type problems

    NASA Astrophysics Data System (ADS)

    Jie, Haoxiang; Wu, Yizhong; Ding, Jianwan

    2015-11-01

    In this article, an adaptive metamodel-based global optimization (AMGO) algorithm is presented to solve unconstrained black-box problems. In the AMGO algorithm, a type of hybrid model composed of kriging and augmented radial basis function (RBF) is used as the surrogate model. The weight factors of hybrid model are adaptively selected in the optimization process. To balance the local and global search, a sub-optimization problem is constructed during each iteration to determine the new iterative points. As numerical experiments, six standard two-dimensional test functions are selected to show the distributions of iterative points. The AMGO algorithm is also tested on seven well-known benchmark optimization problems and contrasted with three representative metamodel-based optimization methods: efficient global optimization (EGO), GutmannRBF and hybrid and adaptive metamodel (HAM). The test results demonstrate the efficiency and robustness of the proposed method. The AMGO algorithm is finally applied to the structural design of the import and export chamber of a cycloid gear pump, achieving satisfactory results.

  9. System reliability, performance and trust in adaptable automation.

    PubMed

    Chavaillaz, Alain; Wastell, David; Sauer, Jürgen

    2016-01-01

    The present study examined the effects of reduced system reliability on operator performance and automation management in an adaptable automation environment. 39 operators were randomly assigned to one of three experimental groups: low (60%), medium (80%), and high (100%) reliability of automation support. The support system provided five incremental levels of automation which operators could freely select according to their needs. After 3 h of training on a simulated process control task (AutoCAMS) in which the automation worked infallibly, operator performance and automation management were measured during a 2.5-h testing session. Trust and workload were also assessed through questionnaires. Results showed that although reduced system reliability resulted in lower levels of trust towards automation, there were no corresponding differences in the operators' reliance on automation. While operators showed overall a noteworthy ability to cope with automation failure, there were, however, decrements in diagnostic speed and prospective memory with lower reliability.

  10. Optimal energy-splitting method for an open-loop liquid crystal adaptive optics system.

    PubMed

    Cao, Zhaoliang; Mu, Quanquan; Hu, Lifa; Liu, Yonggang; Peng, Zenghui; Yang, Qingyun; Meng, Haoran; Yao, Lishuang; Xuan, Li

    2012-08-13

    A waveband-splitting method is proposed for open-loop liquid crystal adaptive optics systems (LC AOSs). The proposed method extends the working waveband, splits energy flexibly, and improves detection capability. Simulated analysis is performed for a waveband in the range of 350 nm to 950 nm. The results show that the optimal energy split is 7:3 for the wavefront sensor (WFS) and for the imaging camera with the waveband split into 350 nm to 700 nm and 700 nm to 950 nm, respectively. A validation experiment is conducted by measuring the signal-to-noise ratio (SNR) of the WFS and the imaging camera. The results indicate that for the waveband-splitting method, the SNR of WFS is approximately equal to that of the imaging camera with a variation in the intensity. On the other hand, the SNR of the WFS is significantly different from that of the imaging camera for the polarized beam splitter energy splitting scheme. Therefore, the waveband-splitting method is more suitable for an open-loop LC AOS. An adaptive correction experiment is also performed on a 1.2-meter telescope. A star with a visual magnitude of 4.45 is observed and corrected and an angular resolution ability of 0.31″ is achieved. A double star with a combined visual magnitude of 4.3 is observed as well, and its two components are resolved after correction. The results indicate that the proposed method can significantly improve the detection capability of an open-loop LC AOS.

  11. 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.

  12. Leaf Area Adjustment As an Optimal Drought-Adaptation Strategy

    NASA Astrophysics Data System (ADS)

    Manzoni, S.; Beyer, F.; Thompson, S. E.; Vico, G.; Weih, M.

    2014-12-01

    Leaf phenology plays a major role in land-atmosphere mass and energy exchanges. Much work has focused on phenological responses to light and temperature, but less to leaf area changes during dry periods. Because the duration of droughts is expected to increase under future climates in seasonally-dry as well as mesic environments, it is crucial to (i) predict drought-related phenological changes and (ii) to develop physiologically-sound models of leaf area dynamics during dry periods. Several optimization criteria have been proposed to model leaf area adjustment as soil moisture decreases. Some theories are based on the plant carbon (C) balance, hypothesizing that leaf area will decline when instantaneous net photosynthetic rates become negative (equivalent to maximization of cumulative C gain). Other theories draw on hydraulic principles, suggesting that leaf area should adjust to either maintain a constant leaf water potential (isohydric behavior) or to avoid leaf water potentials with negative impacts on photosynthesis (i.e., minimization of water stress). Evergreen leaf phenology is considered as a control case. Merging these theories into a unified framework, we quantify the effect of phenological strategy and climate forcing on the net C gain over the entire growing season. By accounting for the C costs of leaf flushing and the gains stemming from leaf photosynthesis, this metric assesses the effectiveness of different phenological strategies, under different climatic scenarios. Evergreen species are favored only when the dry period is relatively short, as they can exploit most of the growing season, and only incur leaf maintenance costs during the short dry period. In contrast, deciduous species that lower maintenance costs by losing leaves are advantaged under drier climates. Moreover, among drought-deciduous species, isohydric behavior leads to lowest C gains. Losing leaves gradually so as to maintain a net C uptake equal to zero during the driest period in

  13. Optimal control of distributed parameter systems using adaptive critic neural networks

    NASA Astrophysics Data System (ADS)

    Padhi, Radhakant

    In this dissertation, two systematic optimal control synthesis techniques are presented for distributed parameter systems based on the adaptive critic neural networks. Following the philosophy of dynamic programming, this adaptive critic optimal control synthesis approach has many desirable features, viz. having a feedback form of the control, ability for on-line implementation, no need for approximating the nonlinear system dynamics, etc. More important, unlike the dynamic programming, it can accomplish these objectives without getting overwhelmed by the computational and storage requirements. First, an approximate dynamic programming based adaptive critic control synthesis formulation was carried out assuming an approximation of the system dynamics in a discrete form. A variety of example problems were solved using this proposed general approach. Next a different formulation is presented, which is capable of directly addressing the continuous form of system dynamics for control design. This was obtained following the methodology of Galerkin projection based weighted residual approximation using a set of orthogonal basis functions. The basis functions were designed by with the help of proper orthogonal decomposition, which leads to a very low-dimensional lumped parameter representation. The regulator problems of linear and nonlinear heat equations were revisited. Optimal controllers were synthesized first assuming a continuous controller and then a set of discrete controllers in the spatial domain. Another contribution of this study is the formulation of simplified adaptive critics for a large class of problems, which can be interpreted as a significant improvement of the existing adaptive critic technique.

  14. Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

    SciTech Connect

    Nie Xiaobo; Liang Jian; Yan Di

    2012-12-15

    Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h

  15. Optimization of reactor network design problem using Jumping Gene Adaptation of Differential Evolution

    NASA Astrophysics Data System (ADS)

    Gujarathi, Ashish M.; Purohit, S.; Srikanth, B.

    2015-06-01

    Detailed working principle of jumping gene adaptation of differential evolution (DE-JGa) is presented. The performance of the DE-JGa algorithm is compared with the performance of differential evolution (DE) and modified DE (MDE) by applying these algorithms on industrial problems. In this study Reactor network design (RND) problem is solved using DE, MDE, and DE-JGa algorithms: These industrial processes are highly nonlinear and complex with reference to optimal operating conditions with many equality and inequality constraints. Extensive computational comparisons have been made for all the chemical engineering problems considered. The results obtained in the present study show that DE-JGa algorithm outperforms the other algorithms (DE and MDE). Several comparisons are made among the algorithms with regard to the number of function evaluations (NFE)/CPU- time required to find the global optimum. The standard deviation and the variance values obtained using DE-JGa, DE and MDE algorithms also show that the DE-JGa algorithm gives consistent set of results for the majority of the test problems and the industrial real world problems.

  16. An optimized adaptive optics experimental setup for in vivo retinal imaging

    NASA Astrophysics Data System (ADS)

    Balderas-Mata, S. E.; Valdivieso González, L. G.; Ramírez Zavaleta, G.; López Olazagasti, E.; Tepichin Rodriguez, E.

    2012-10-01

    The use of Adaptive Optics (AO) in ophthalmologic instruments to image human retinas has been probed to improve the imaging lateral resolution, by correcting both static and dynamic aberrations inherent in human eyes. Typically, the configuration of the AO arm uses an infrared beam from a superluminescent diode (SLD), which is focused on the retina, acting as a point source. The back reflected light emerges through the eye optical system bringing with it the aberrations of the cornea. The aberrated wavefront is measured with a Shack - Hartmann wavefront sensor (SHWFS). However, the aberrations in the optical imaging system can reduced the performance of the wave front correction. The aim of this work is to present an optimized first stage AO experimental setup for in vivo retinal imaging. In our proposal, the imaging optical system has been designed in order to reduce spherical aberrations due to the lenses. The ANSI Standard is followed assuring the safety power levels. The performance of the system will be compared with a commercial aberrometer. This system will be used as the AO arm of a flood-illuminated fundus camera system for retinal imaging. We present preliminary experimental results showing the enhancement.

  17. A self adaptive hybrid enhanced artificial bee colony algorithm for continuous optimization problems.

    PubMed

    Shan, Hai; Yasuda, Toshiyuki; Ohkura, Kazuhiro

    2015-06-01

    The artificial bee colony (ABC) algorithm is one of popular swarm intelligence algorithms that inspired by the foraging behavior of honeybee colonies. To improve the convergence ability, search speed of finding the best solution and control the balance between exploration and exploitation using this approach, we propose a self adaptive hybrid enhanced ABC algorithm in this paper. To evaluate the performance of standard ABC, best-so-far ABC (BsfABC), incremental ABC (IABC), and the proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation (CEC) 2014 test suite. Our experimental results show the comparative performance of standard ABC, BsfABC, IABC, and the proposed ABC algorithms. According to the results, we conclude that the proposed ABC algorithm is competitive to those state-of-the-art modified ABC algorithms such as BsfABC and IABC algorithms based on the benchmark problems defined by CEC 2014 test suite with dimension sizes of 10, 30, and 50, respectively.

  18. Transient analysis of an adaptive system for optimization of design parameters

    NASA Technical Reports Server (NTRS)

    Bayard, D. S.

    1992-01-01

    Averaging methods are applied to analyzing and optimizing the transient response associated with the direct adaptive control of an oscillatory second-order minimum-phase system. The analytical design methods developed for a second-order plant can be applied with some approximation to a MIMO flexible structure having a single dominant mode.

  19. Optimal Stratification of Item Pools in a-Stratified Computerized Adaptive Testing. Research Report.

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    A method based on 0-1 linear programming (LP) is presented to stratify an item pool optimally for use in "alpha"-stratified adaptive testing. Because the 0-1 LP model belongs to the subclass of models with a network-flow structure, efficient solutions are possible. The method is applied to a previous item pool from the computerized…

  20. Career Adaptability, Hope, Optimism, and Life Satisfaction in Italian and Swiss Adolescents

    ERIC Educational Resources Information Center

    Santilli, Sara; Marcionetti, Jenny; Rochat, Shékina; Rossier, Jérôme; Nota, Laura

    2017-01-01

    The consequences of economic crisis are different from one European context to the other. Based on life design (LD) approach, the present study focused on two variables--career adaptability and a positive orientation toward future (hope and optimism)--relevant to coping with the current work context and their role in affecting life satisfaction. A…

  1. Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

    NASA Astrophysics Data System (ADS)

    Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

    2016-01-01

    An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

  2. Optimal 3D Viewing with Adaptive Stereo Displays for Advanced Telemanipulation

    NASA Technical Reports Server (NTRS)

    Lee, S.; Lakshmanan, S.; Ro, S.; Park, J.; Lee, C.

    1996-01-01

    A method of optimal 3D viewing based on adaptive displays of stereo images is presented for advanced telemanipulation. The method provides the viewer with the capability of accurately observing a virtual 3D object or local scene of his/her choice with minimum distortion.

  3. Optimal control of gene expression for fast proteome adaptation to environmental change.

    PubMed

    Pavlov, Michael Y; Ehrenberg, Måns

    2013-12-17

    Bacterial populations growing in a changing world must adjust their proteome composition in response to alterations in the environment. Rapid proteome responses to growth medium changes are expected to increase the average growth rate and fitness value of these populations. Little is known about the dynamics of proteome change, e.g., whether bacteria use optimal strategies of gene expression for rapid proteome adjustments and if there are lower bounds to the time of proteome adaptation in response to growth medium changes. To begin answering these types of questions, we modeled growing bacteria as stoichiometrically coupled networks of metabolic pathways. These are balanced during steady-state growth in a constant environment but are initially unbalanced after rapid medium shifts due to a shortage of enzymes required at higher concentrations in the new environment. We identified an optimal strategy for rapid proteome adjustment in the absence of protein degradation and found a lower bound to the time of proteome adaptation after medium shifts. This minimal time is determined by the ratio between the Kullback-Leibler distance from the pre- to the postshift proteome and the postshift steady-state growth rate. The dynamics of optimally controlled proteome adaptation has a simple analytical solution. We used detailed numerical modeling to demonstrate that realistic bacterial control systems can emulate this optimal strategy for rapid proteome adaptation. Our results may provide a conceptual link between the physiology and population genetics of growing bacteria.

  4. Optimal control of gene expression for fast proteome adaptation to environmental change

    PubMed Central

    Pavlov, Michael Y.; Ehrenberg, Måns

    2013-01-01

    Bacterial populations growing in a changing world must adjust their proteome composition in response to alterations in the environment. Rapid proteome responses to growth medium changes are expected to increase the average growth rate and fitness value of these populations. Little is known about the dynamics of proteome change, e.g., whether bacteria use optimal strategies of gene expression for rapid proteome adjustments and if there are lower bounds to the time of proteome adaptation in response to growth medium changes. To begin answering these types of questions, we modeled growing bacteria as stoichiometrically coupled networks of metabolic pathways. These are balanced during steady-state growth in a constant environment but are initially unbalanced after rapid medium shifts due to a shortage of enzymes required at higher concentrations in the new environment. We identified an optimal strategy for rapid proteome adjustment in the absence of protein degradation and found a lower bound to the time of proteome adaptation after medium shifts. This minimal time is determined by the ratio between the Kullback–Leibler distance from the pre- to the postshift proteome and the postshift steady-state growth rate. The dynamics of optimally controlled proteome adaptation has a simple analytical solution. We used detailed numerical modeling to demonstrate that realistic bacterial control systems can emulate this optimal strategy for rapid proteome adaptation. Our results may provide a conceptual link between the physiology and population genetics of growing bacteria. PMID:24297927

  5. Discrete-time entropy formulation of optimal and adaptive control problems

    NASA Technical Reports Server (NTRS)

    Tsai, Yweting A.; Casiello, Francisco A.; Loparo, Kenneth A.

    1992-01-01

    The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

  6. Architectural modifications for flexible supercapacitor performance optimization

    NASA Astrophysics Data System (ADS)

    Keskinen, Jari; Lehtimäki, Suvi; Dastpak, Arman; Tuukkanen, Sampo; Flyktman, Timo; Kraft, Thomas; Railanmaa, Anna; Lupo, Donald

    2016-09-01

    We have developed material and architectural alternatives for flexible supercapacitors and investigated their effect on practical performance. The substrate alternatives include paperboard as well as various polyethylene terephthalate (PET) films and laminates, with aqueous NaCl electrolyte used in all devices. In all the supercapacitors, activated carbon is used as the active layer and graphite ink as the current collector, with various aluminium or copper structures applied to enhance the current collectors' conductivity. The capacitance of the supercapacitors was between 0.05 F and 0.58 F and their equivalent series resistance (ESR) was from <1 Ω to 14 Ω, depending mainly on the current collector structure. Furthermore, leakage current and selfdischarge rates were defined and compared for the various architectures. The barrier properties of the supercapacitor encapsulation have a clear correlation with leakage current, as was clearly shown by the lower leakage in devices with an aluminium barrier layer. A cycle life test showed that after 40000 charge-discharge cycles the capacitance decreases by less than 10%.

  7. Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.

    PubMed

    Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong

    2015-04-01

    Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.

  8. Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails

    PubMed Central

    2012-01-01

    Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742

  9. Adaptation of CHO cells in serum-free conditions for erythropoietin production: Application of EVOP technique for process optimization.

    PubMed

    Jukić, Suzana; Bubenik, Dijana; Pavlović, Nediljko; Tušek, Ana Jurinjak; Srček, Višnja Gaurina

    2016-09-01

    Mammalian cell cultures are the preferred expression systems for the production of biopharmaceuticals requiring posttranslational processing. Usually, cell cultures are cultivated in medium supplemented with serum, which supports cell proliferation, viability, and productivity. However, due to scientific and regulatory concerns, serum-free conditions are required in recombinant protein production. Cell lines that are intended for commercial recombinant protein production have to adapt to serum- or protein-free conditions early in their development. This is a labor- and time-consuming process because of the specific cell requirements related to their adaptation in new microenvironment. In the present study, a Chinese hamster ovary (CHO) cell line producing glycosylated recombinant human erythropoietin (rhEPO) was adapted for growth and rhEPO production in serum- and protein-free conditions. The physiology, growth parameters, and morphology of the CHO cells and rhEPO biosynthesis and structure were closely monitored during the adaptation process to avoid unwanted selection of cell subpopulations. The results showed that the CHO cells were successfully adapted to suspension growth and rhEPO production in the protein-free conditions and that the structure of rhEPO remained nearly unchanged. In addition, during rhEPO production in the protein-free suspension conditions, the agitation rate seem to be significant for optimal process performance in contrast to the initial cell concentration, evaluated through evolutionary operation method.

  10. The Differentiation of Adaptive Behaviours: Evidence from High and Low Performers

    ERIC Educational Resources Information Center

    Kane, Harrison; Oakland, Thomas David

    2015-01-01

    Background: Professionals who use measures of adaptive behaviour when working with special populations may assume that adaptive behaviour is a consistent and linear construct at various ability levels and thus believe the construct of adaptive behaviour is the same for high and low performers. That is, highly adaptive people simply are assumed to…

  11. Performance of the Keck Observatory adaptive optics system

    SciTech Connect

    van Dam, M A; Mignant, D L; Macintosh, B A

    2004-01-19

    In this paper, the adaptive optics (AO) system at the W.M. Keck Observatory is characterized. The authors calculate the error budget of the Keck AO system operating in natural guide star mode with a near infrared imaging camera. By modeling the control loops and recording residual centroids, the measurement noise and band-width errors are obtained. The error budget is consistent with the images obtained. Results of sky performance tests are presented: the AO system is shown to deliver images with average Strehl ratios of up to 0.37 at 1.58 {micro}m using a bright guide star and 0.19 for a magnitude 12 star.

  12. Optimal Stellar Photometry for Multi-conjugate Adaptive Optics Systems Using Science-based Metrics

    NASA Astrophysics Data System (ADS)

    Turri, P.; McConnachie, A. W.; Stetson, P. B.; Fiorentino, G.; Andersen, D. R.; Bono, G.; Massari, D.; Véran, J.-P.

    2017-04-01

    We present a detailed discussion of how to obtain precise stellar photometry in crowded fields using images from multi-conjugate adaptive optics (MCAO) systems, with the intent of informing the scientific development of this key technology for the Extremely Large Telescopes. We use deep J and K s exposures of NGC 1851 taken with the Gemini Multi-Conjugate Adaptive Optics System (GeMS) on Gemini South to quantify the performance of the instrument and to develop an optimal strategy for stellar photometry using point-spread function (PSF)-fitting techniques. We judge the success of the various methods we employ by using science-based metrics, particularly the width of the main sequence turnoff region. We also compare the GeMS photometry with the exquisite HST data in the visible of the same target. We show that the PSF produced by GeMS possesses significant spatial and temporal variability that must be accounted for during the analysis. We show that the majority of the variation of the PSF occurs within the “control radius” of the MCAO system and that the best photometry is obtained when the PSF radius is chosen to closely match this spatial scale. We identify photometric calibration as a critical issue for next-generation MCAO systems such as those on the Thirty Meter Telescope and European Extremely Large Telescope. Our final CMDs reach K s ∼ 22—below the main sequence knee—making it one of the deepest for a globular cluster available from the ground. Theoretical isochrones are in remarkable agreement with the stellar locus in our data from below the main sequence knee to the upper red giant branch.

  13. Improved media performance in optimally coupled exchange spring layer media

    NASA Astrophysics Data System (ADS)

    Berger, A.; Supper, N.; Ikeda, Y.; Lengsfield, B.; Moser, A.; Fullerton, E. E.

    2008-09-01

    We have studied the recording performance of perpendicular exchange spring layer (ESL)-media for hard disk drive recording. In particular, we investigated the role of interlayer coupling by varying the thickness of a nonmagnetic coupling layer (CL). We demonstrate that not only the media writeability is improved upon optimizing the CL thickness, but also that substantial recording performance improvements can be achieved due to improved media noise properties. The potential of these media structures for high areal density recording is demonstrated by performing areal density measurements, which showed a substantial improvement for optimally coupled ESL-media.

  14. On-line re-optimization of prostate IMRT plan for adaptive radiation therapy: A feasibility study and implementation

    NASA Astrophysics Data System (ADS)

    Thongphiew, Danthai

    Prostate cancer is a disease that affected approximately 200,000 men in United States in 2006. Radiation therapy is a non invasive treatment option for this disease and is highly effective. The goal of radiation therapy is to deliver the prescription dose to the tumor (prostate) while sparing the surrounding healthy organs (e.g. bladder, rectum, and femoral heads). One limitation of the radiation therapy is organ position and shape variation from day to day. These variations could be as large as half inch. The conventional solution to this problem is to include some margins surrounding the target when plan the treatment. The development of image guided radiation therapy technique allows in-room correction which potentially eliminates the patient setup error however the uncertainty due to organ deformation still remains. Performing a plan re-optimization will take about half hour which is infeasible to perform an online correction. A technique of performing online re-optimization of intensity modulated radiation therapy is developed for adaptive radiation therapy of prostate cancer. The technique is capable of correction both organ positioning and shape changes within a few minutes. The proposed technique involves (1) 3D on-board imaging of daily anatomy, (2) registering the daily images with original planning CT images and mapping the original dose distribution to the daily anatomy, (3) real time re-optimization of the plan. Finally the leaf sequences are calculated for the treatment delivery. The feasibility of this online adaptive radiation therapy scheme was evaluated by clinical cases. The results demonstrate that it is feasible to perform online re-optimization of the original plan when large position or shape variation occurs.

  15. Application of an optimization method to high performance propeller designs

    NASA Technical Reports Server (NTRS)

    Li, K. C.; Stefko, G. L.

    1984-01-01

    The application of an optimization method to determine the propeller blade twist distribution which maximizes propeller efficiency is presented. The optimization employs a previously developed method which has been improved to include the effects of blade drag, camber and thickness. Before the optimization portion of the computer code is used, comparisons of calculated propeller efficiencies and power coefficients are made with experimental data for one NACA propeller at Mach numbers in the range of 0.24 to 0.50 and another NACA propeller at a Mach number of 0.71 to validate the propeller aerodynamic analysis portion of the computer code. Then comparisons of calculated propeller efficiencies for the optimized and the original propellers show the benefits of the optimization method in improving propeller performance. This method can be applied to the aerodynamic design of propellers having straight, swept, or nonplanar propeller blades.

  16. 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.

  17. Optimization and performance of Space Station Freedom solar cells

    NASA Technical Reports Server (NTRS)

    Khemthong, S.; Hansen, N.; Bower, M.

    1991-01-01

    High efficiency, large area and low cost solar cells are the drivers for Space Station solar array designs. The manufacturing throughput, process complexity, yield of the cells, and array manufacturing technique determine the economics of the solar array design. The cell efficiency optimization of large area (8 x 8 m), dielectric wrapthrough contact solar cells are described. The results of the optimization are reported and the solar cell performance of limited production runs is reported.

  18. A Self-Driven and Adaptive Adjusting Teaching Learning Method for Optimizing Optical Multicast Network Throughput

    NASA Astrophysics Data System (ADS)

    Liu, Huanlin; Xu, Yifan; Chen, Yong; Zhang, Mingjia

    2016-09-01

    With the development of one point to multiple point applications, network resources become scarcer and wavelength channels become more crowded in optical networks. To improve the bandwidth utilization, the multicast routing algorithm based on network coding can greatly increase the resource utilization, but it is most difficult to maximize the network throughput owing to ignoring the differences between the multicast receiving nodes. For making full use of the destination nodes' receives ability to maximize optical multicast's network throughput, a new optical multicast routing algorithm based on teaching-learning-based optimization (MR-iTLBO) is proposed in the paper. In order to increase the diversity of learning, a self-driven learning method is adopted in MR-iTLBO algorithm, and the mutation operator of genetic algorithm is introduced to prevent the algorithm into a local optimum. For increasing learner's learning efficiency, an adaptive learning factor is designed to adjust the learning process. Moreover, the reconfiguration scheme based on probability vector is devised to expand its global search capability in MR-iTLBO algorithm. The simulation results show that performance in terms of network throughput and convergence rate has been improved significantly with respect to the TLBO and the variant TLBO.

  19. Fitting of adaptive neuron model to electrophysiological recordings using particle swarm optimization algorithm

    NASA Astrophysics Data System (ADS)

    Shan, Bonan; Wang, Jiang; Zhang, Lvxia; Deng, Bin; Wei, Xile

    2017-02-01

    In order to fit neural model’s spiking features to electrophysiological recordings, in this paper, a fitting framework based on particle swarm optimization (PSO) algorithm is proposed to estimate the model parameters in an augmented multi-timescale adaptive threshold (AugMAT) model. PSO algorithm is an advanced evolutionary calculation method based on iteration. Selecting a reasonable criterion function will ensure the effectiveness of PSO algorithm. In this work, firing rate information is used as the main spiking feature and the estimation error of firing rate is selected as the criterion for fitting. A series of simulations are presented to verify the performance of the framework. The first step is model validation; an artificial training data is introduced to test the fitting procedure. Then we talk about the suitable PSO parameters, which exhibit adequate compromise between speediness and accuracy. Lastly, this framework is used to fit the electrophysiological recordings, after three adjustment steps, the features of experimental data are translated into realistic spiking neuron model.

  20. Multilevel control optimization using subsystem relative performance index sensitivity

    NASA Technical Reports Server (NTRS)

    Leininger, G. G.; Lehtinen, F. B.

    1974-01-01

    A method is presented for the design of optimal feedback controllers for large multivariable systems with subsystem sensitivity constraints. The weighted sum of subsystem and/or operational mode relative performance index sensitivities is defined as the overall performance index. The method is developed for linear systems with quadratic performance criteria and either full or partial state feedback. An example concerning the design of a stability augmentation system for a VTOL aircraft in the transition mode demonstrates the effectiveness of the design method.

  1. Compiler-Driven Performance Optimization and Tuning for Multicore Architectures

    DTIC Science & Technology

    2015-04-10

    Report: Compiler-Driven Performance Optimization and Tuning for Multicore Architectures The widespread emergence of multicore processors as the computing...applications have enjoyed the free-ride of performance improvement with each new processor generation. The reality today is that existing and new...applications must be changed to make them multi-threaded if they are to experience any performance benefits from newer generations of processors . An

  2. Proficient brain for optimal performance: the MAP model perspective

    PubMed Central

    di Fronso, Selenia; Filho, Edson; Conforto, Silvia; Schmid, Maurizio; Bortoli, Laura; Comani, Silvia; Robazza, Claudio

    2016-01-01

    Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances. Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the “neural efficiency hypothesis.” We also observed more ERD as related to optimal-controlled performance in conditions of “neural adaptability” and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques. PMID:27257557

  3. Optimization of Irreversible Cogeneration Systems under Alternative Performance Criteria

    NASA Astrophysics Data System (ADS)

    Atmaca, M.; Gumus, M.; Inan, A. T.; Yilmaz, T.

    2009-10-01

    In this study, an exergy optimization has been performed for a cogeneration plant consisting of an irreversible Carnot heat engine. In the analysis, different objective functions have been defined based on alternative performance criteria and the optimum values of the design parameters of a cogeneration cycle were determined for different criteria. In this context, the effects of irreversibilities on the exergetic performance are investigated, and the results are discussed.

  4. Adaptive Urban Stormwater Management Using a Two-stage Stochastic Optimization Model

    NASA Astrophysics Data System (ADS)

    Hung, F.; Hobbs, B. F.; McGarity, A. E.

    2014-12-01

    In many older cities, stormwater results in combined sewer overflows (CSOs) and consequent water quality impairments. Because of the expense of traditional approaches for controlling CSOs, cities are considering the use of green infrastructure (GI) to reduce runoff and pollutants. Examples of GI include tree trenches, rain gardens, green roofs, and rain barrels. However, the cost and effectiveness of GI are uncertain, especially at the watershed scale. We present a two-stage stochastic extension of the Stormwater Investment Strategy Evaluation (StormWISE) model (A. McGarity, JWRPM, 2012, 111-24) to explicitly model and optimize these uncertainties in an adaptive management framework. A two-stage model represents the immediate commitment of resources ("here & now") followed by later investment and adaptation decisions ("wait & see"). A case study is presented for Philadelphia, which intends to extensively deploy GI over the next two decades (PWD, "Green City, Clean Water - Implementation and Adaptive Management Plan," 2011). After first-stage decisions are made, the model updates the stochastic objective and constraints (learning). We model two types of "learning" about GI cost and performance. One assumes that learning occurs over time, is automatic, and does not depend on what has been done in stage one (basic model). The other considers learning resulting from active experimentation and learning-by-doing (advanced model). Both require expert probability elicitations, and learning from research and monitoring is modelled by Bayesian updating (as in S. Jacobi et al., JWRPM, 2013, 534-43). The model allocates limited financial resources to GI investments over time to achieve multiple objectives with a given reliability. Objectives include minimizing construction and O&M costs; achieving nutrient, sediment, and runoff volume targets; and community concerns, such as aesthetics, CO2 emissions, heat islands, and recreational values. CVaR (Conditional Value at Risk) and

  5. Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

    2016-01-01

    Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

  6. Scaling multiconjugate adaptive optics performance estimates to extremely large telescopes

    NASA Astrophysics Data System (ADS)

    Ellerbroek, Brent L.; Rigaut, Francois J.

    2000-07-01

    Multi-conjugate adaptive optics (MCAO) is a key technology for extremely large, ground-based telescopes (ELT's) because it enables near-uniform atmospheric turbulence compensation over fields-of-view considerably larger than can be corrected with more conventional AO systems. Quantitative performance evaluation using detailed analytical or simulation models is difficult, however, due to the very large number of deformable mirror (DM) actuators, wave front sensors (WFS) subapertures, and guide stars which might comprise an MCAO system for an ELT. This paper employs more restricted minimal variance estimation methods to evaluate the fundamental performance limits imposed by anisoplanatism alone upon MCAO performance for a range of sample cases. Each case is defined by a atmospheric turbulence profile, telescope aperture diameter, field-of-view, guide star constellation, and set of DM conjugate ranges. For a Kolmogorov turbulence spectrum with an infinite outer scale, MCAO performance for a whole range of aperture diameters and proportional fields-of-view can be computed at once using a scaling law analogous to the (D/dO)5/3 formula for the cone effect. For 30 meter telescopes, useful levels of performance are possible across a 1.0 - 2.0 arc minute square field-of-view using 5 laser guide stars (LGS's) and 3 DM's, and somewhat larger fields can be corrected using 9 guide stars and 4 mirrors. 3 or more tip/tilt natural guide stars (NGS's) are necessary to detect modes of tilt anisoplanatism which cannot be detected using LGS's, however. LGS MCAO performance is a quite weak function of aperture diameter for a fixed field-of-view, and it is tempting to scale these results to larger apertures. NGS MCAO performance is moderately superior to LGS MCAO if the NGS constellation is within the compensated field-of-view, but degrades rapidly as the guide stars move away from the field. The penalty relaxes slowly with increasing aperture diameter, but how to extrapolate this trend

  7. Laser pulse design using optimal control theory-based adaptive simulated annealing technique: vibrational transitions and photo-dissociation

    NASA Astrophysics Data System (ADS)

    Nath, Bikram; Mondal, Chandan Kumar

    2014-08-01

    We have designed and optimised a combined laser pulse using optimal control theory-based adaptive simulated annealing technique for selective vibrational excitations and photo-dissociation. Since proper choice of pulses for specific excitation and dissociation phenomena is very difficult, we have designed a linearly combined pulse for such processes and optimised the different parameters involved in those pulses so that we can get an efficient combined pulse. The technique makes us free from choosing any arbitrary type of pulses and makes a ground to check their suitability. We have also emphasised on how we can improve the performance of simulated annealing technique by introducing an adaptive step length of the different variables during the optimisation processes. We have also pointed out on how we can choose the initial temperature for the optimisation process by introducing heating/cooling step to reduce the annealing steps so that the method becomes cost effective.

  8. Performance Management and Optimization of Semiconductor Design Projects

    NASA Astrophysics Data System (ADS)

    Hinrichs, Neele; Olbrich, Markus; Barke, Erich

    2010-06-01

    The semiconductor industry is characterized by fast technological changes and small time-to-market windows. Improving productivity is the key factor to stand up to the competitors and thus successfully persist in the market. In this paper a Performance Management System for analyzing, optimizing and evaluating chip design projects is presented. A task graph representation is used to optimize the design process regarding time, cost and workload of resources. Key Performance Indicators are defined in the main areas cost, profit, resources, process and technical output to appraise the project.

  9. Adaptive feature selection using v-shaped binary particle swarm optimization

    PubMed Central

    Dong, Hongbin; Zhou, Xiurong

    2017-01-01

    Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers. PMID:28358850

  10. A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

    PubMed Central

    Wang, Zhihao; Yi, Jing

    2016-01-01

    For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

  11. A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters.

    PubMed

    Ren, Min; Liu, Peiyu; Wang, Zhihao; Yi, Jing

    2016-01-01

    For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule [Formula: see text] and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result.

  12. Orbit design and optimization based on global telecommunication performance metrics

    NASA Technical Reports Server (NTRS)

    Lee, Seungwon; Lee, Charles H.; Kerridge, Stuart; Cheung, Kar-Ming; Edwards, Charles D.

    2006-01-01

    The orbit selection of telecommunications orbiters is one of the critical design processes and should be guided by global telecom performance metrics and mission-specific constraints. In order to aid the orbit selection, we have coupled the Telecom Orbit Analysis and Simulation Tool (TOAST) with genetic optimization algorithms. As a demonstration, we have applied the developed tool to select an optimal orbit for general Mars telecommunications orbiters with the constraint of being a frozen orbit. While a typical optimization goal is to minimize tele-communications down time, several relevant performance metrics are examined: 1) area-weighted average gap time, 2) global maximum of local maximum gap time, 3) global maximum of local minimum gap time. Optimal solutions are found with each of the metrics. Common and different features among the optimal solutions as well as the advantage and disadvantage of each metric are presented. The optimal solutions are compared with several candidate orbits that were considered during the development of Mars Telecommunications Orbiter.

  13. Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids

    NASA Technical Reports Server (NTRS)

    Nielsen, Eric J.

    2006-01-01

    Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.

  14. Crop classification by forward neural network with adaptive chaotic particle swarm optimization.

    PubMed

    Zhang, Yudong; Wu, Lenan

    2011-01-01

    This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10(-7) s.

  15. Integrated optimal allocation model for complex adaptive system of water resources management (II): Case study

    NASA Astrophysics Data System (ADS)

    Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Liu, Dedi; Chen, Lu; Wang, Dong

    2015-12-01

    Climate change, rapid economic development and increase of the human population are considered as the major triggers of increasing challenges for water resources management. This proposed integrated optimal allocation model (IOAM) for complex adaptive system of water resources management is applied in Dongjiang River basin located in the Guangdong Province of China. The IOAM is calibrated and validated under baseline period 2010 year and future period 2011-2030 year, respectively. The simulation results indicate that the proposed model can make a trade-off between demand and supply for sustainable development of society, economy, ecology and environment and achieve adaptive management of water resources allocation. The optimal scheme derived by multi-objective evaluation is recommended for decision-makers in order to maximize the comprehensive benefits of water resources management.

  16. Crop Classification by Forward Neural Network with Adaptive Chaotic Particle Swarm Optimization

    PubMed Central

    Zhang, Yudong; Wu, Lenan

    2011-01-01

    This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10−7 s. PMID:22163872

  17. An adaptive controller for enhancing operator performance during teleoperation

    NASA Technical Reports Server (NTRS)

    Carignan, Craig R.; Tarrant, Janice M.; Mosier, Gary E.

    1989-01-01

    An adaptive controller is developed for adjusting robot arm parameters while manipulating payloads of unknown mass and inertia. The controller is tested experimentally in a master/slave configuration where the adaptive slave arm is commanded via human operator inputs from a master. Kinematically similar six-joint master and slave arms are used with the last three joints locked for simplification. After a brief initial adaptation period for the unloaded arm, the slave arm retrieves different size payloads and maneuvers them about the workspace. Comparisons are then drawn with similar tasks where the adaptation is turned off. Several simplifications of the controller dynamics are also addressed and experimentally verified.

  18. Development of Variable Camber Continuous Trailing Edge Flap for Performance Adaptive Aeroelastic Wing

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan; Kaul, Upender; Lebofsky, Sonia; Ting, Eric; Chaparro, Daniel; Urnes, James

    2015-01-01

    This paper summarizes the recent development of an adaptive aeroelastic wing shaping control technology called variable camber continuous trailing edge flap (VCCTEF). As wing flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. The initial VCCTEF concept was developed in 2010 by NASA under a NASA Innovation Fund study entitled "Elastically Shaped Future Air Vehicle Concept," which showed that highly flexible wing aerodynamic surfaces can be elastically shaped in-flight by active control of wing twist and bending deflection in order to optimize the spanwise lift distribution for drag reduction. A collaboration between NASA and Boeing Research & Technology was subsequently funded by NASA from 2012 to 2014 to further develop the VCCTEF concept. This paper summarizes some of the key research areas conducted by NASA during the collaboration with Boeing Research and Technology. These research areas include VCCTEF design concepts, aerodynamic analysis of VCCTEF camber shapes, aerodynamic optimization of lift distribution for drag minimization, wind tunnel test results for cruise and high-lift configurations, flutter analysis and suppression control of flexible wing aircraft, and multi-objective flight control for adaptive aeroelastic wing shaping control.

  19. Adaptable Metadata Rich IO Methods for Portable High Performance IO

    SciTech Connect

    Lofstead, J.; Zheng, Fang; Klasky, Scott A; Schwan, Karsten

    2009-01-01

    Since IO performance on HPC machines strongly depends on machine characteristics and configuration, it is important to carefully tune IO libraries and make good use of appropriate library APIs. For instance, on current petascale machines, independent IO tends to outperform collective IO, in part due to bottlenecks at the metadata server. The problem is exacerbated by scaling issues, since each IO library scales differently on each machine, and typically, operates efficiently to different levels of scaling on different machines. With scientific codes being run on a variety of HPC resources, efficient code execution requires us to address three important issues: (1) end users should be able to select the most efficient IO methods for their codes, with minimal effort in terms of code updates or alterations; (2) such performance-driven choices should not prevent data from being stored in the desired file formats, since those are crucial for later data analysis; and (3) it is important to have efficient ways of identifying and selecting certain data for analysis, to help end users cope with the flood of data produced by high end codes. This paper employs ADIOS, the ADaptable IO System, as an IO API to address (1)-(3) above. Concerning (1), ADIOS makes it possible to independently select the IO methods being used by each grouping of data in an application, so that end users can use those IO methods that exhibit best performance based on both IO patterns and the underlying hardware. In this paper, we also use this facility of ADIOS to experimentally evaluate on petascale machines alternative methods for high performance IO. Specific examples studied include methods that use strong file consistency vs. delayed parallel data consistency, as that provided by MPI-IO or POSIX IO. Concerning (2), to avoid linking IO methods to specific file formats and attain high IO performance, ADIOS introduces an efficient intermediate file format, termed BP, which can be converted, at small

  20. Perturbing engine performance measurements to determine optimal engine control settings

    DOEpatents

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

    2014-12-30

    Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initial value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.

  1. Beam width and transmitter power adaptive to tracking system performance for free-space optical communication.

    PubMed

    Arnon, S; Rotman, S; Kopeika, N S

    1997-08-20

    The basic free-space optical communication system includes at least two satellites. To communicate between them, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is to increase the satellite receiver beacon power. However, this solution requires increased power consumption and weight, both of which are disadvantageous in satellite development. Considering these facts, we derive a mathematical model of a communication system that adapts optimally the transmitter beam width and the transmitted power to the tracking system performance. Based on this model, we investigate the performance of a communication system with discrete element optical phased array transmitter telescope gain. An example for a practical communication system between a Low Earth Orbit Satellite and a Geostationary Earth Orbit Satellite is presented. From the results of this research it can be seen that a four-element adaptive transmitter telescope is sufficient to compensate for vibration amplitude doubling. The benefits of the proposed model are less required transmitter power and improved communication system performance.

  2. Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller.

    PubMed

    Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; Del Toro Matamoros, Raúl M

    2016-05-12

    The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value.

  3. Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller †

    PubMed Central

    Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; del Toro Matamoros, Raúl M.

    2016-01-01

    The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. PMID:27187397

  4. Improving the Hydrodynamic Performance of Diffuser Vanes via Shape Optimization

    NASA Technical Reports Server (NTRS)

    Goel, Tushar; Dorney, Daniel J.; Haftka, Raphael T.; Shyy, Wei

    2007-01-01

    The performance of a diffuser in a pump stage depends on its configuration and placement within the stage. The influence of vane shape on the hydrodynamic performance of a diffuser has been studied. The goal of this effort has been to improve the performance of a pump stage by optimizing the shape of the diffuser vanes. The shape of the vanes was defined using Bezier curves and circular arcs. Surrogate model based tools were used to identify regions of the vane that have a strong influence on its performance. Optimization of the vane shape, in the absence of manufacturing, and stress constraints, led to a nearly nine percent reduction in the total pressure losses compared to the baseline design by reducing the extent of the base separation.

  5. Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2013-01-01

    This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

  6. Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors

    SciTech Connect

    Datta, Kaushik; Kamil, Shoaib; Williams, Samuel; Oliker, Leonid; Shalf, John; Yelick, Katherine

    2007-06-01

    Stencil-based kernels constitute the core of many important scientific applications on blockstructured grids. Unfortunately, these codes achieve a low fraction of peak performance, due primarily to the disparity between processor and main memory speeds. In this paper, we explore the impact of trends in memory subsystems on a variety of stencil optimization techniques and develop performance models to analytically guide our optimizations. Our work targets cache reuse methodologies across single and multiple stencil sweeps, examining cache-aware algorithms as well as cache-oblivious techniques on the Intel Itanium2, AMD Opteron, and IBM Power5. Additionally, we consider stencil computations on the heterogeneous multicore design of the Cell processor, a machine with an explicitly managed memory hierarchy. Overall our work represents one of the most extensive analyses of stencil optimizations and performance modeling to date. Results demonstrate that recent trends in memory system organization have reduced the efficacy of traditional cache-blocking optimizations. We also show that a cache-aware implementation is significantly faster than a cache-oblivious approach, while the explicitly managed memory on Cell enables the highest overall efficiency: Cell attains 88% of algorithmic peak while the best competing cache-based processor achieves only 54% of algorithmic peak performance.

  7. Application of multi-objective controller to optimal tuning of PID gains for a hydraulic turbine regulating system using adaptive grid particle swam optimization.

    PubMed

    Chen, Zhihuan; Yuan, Yanbin; Yuan, Xiaohui; Huang, Yuehua; Li, Xianshan; Li, Wenwu

    2015-05-01

    A hydraulic turbine regulating system (HTRS) is one of the most important components of hydropower plant, which plays a key role in maintaining safety, stability and economical operation of hydro-electrical installations. At present, the conventional PID controller is widely applied in the HTRS system for its practicability and robustness, and the primary problem with respect to this control law is how to optimally tune the parameters, i.e. the determination of PID controller gains for satisfactory performance. In this paper, a kind of multi-objective evolutionary algorithms, named adaptive grid particle swarm optimization (AGPSO) is applied to solve the PID gains tuning problem of the HTRS system. This newly AGPSO optimized method, which differs from a traditional one-single objective optimization method, is designed to take care of settling time and overshoot level simultaneously, in which a set of non-inferior alternatives solutions (i.e. Pareto solution) is generated. Furthermore, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto set. An illustrative example associated with the best compromise solution for parameter tuning of the nonlinear HTRS system is introduced to verify the feasibility and the effectiveness of the proposed AGPSO-based optimization approach, as compared with two another prominent multi-objective algorithms, i.e. Non-dominated Sorting Genetic Algorithm II (NSGAII) and Strength Pareto Evolutionary Algorithm II (SPEAII), for the quality and diversity of obtained Pareto solutions set. Consequently, simulation results show that this AGPSO optimized approach outperforms than compared methods with higher efficiency and better quality no matter whether the HTRS system works under unload or load conditions.

  8. Performance optimization of a pneumatic wave energy conversion device

    NASA Astrophysics Data System (ADS)

    Surko, S. W.

    1982-08-01

    The purpose of this study was, for the first time, to optimize the performance of a pneumatic wave energy conversion device. The experiments of Jolly and Newmaster (1979) and Trop and Casey (1980) left a capture chamber and turbine for further investigation. To optimize the system performance the turbine had to be first analyzed so that its power performance curves could be determined. These curves were needed to help define the possible overall performance of the system, and for the impedance matching of the system necessary for performance optimization. With this knowledge, an appropriate generator was purchased and a generator-turbine linkage designed and built. The completed system was then analyzed in the 380 ft wave tank at the U.S. Naval Academy to establish its optimum performance. From the research it is clear that pneumatic wave energy conversion is a promising concept. With several hundred of these devices situated some 100 km off the coast of the Pacific Northwest each device would be producing from 50 to 200 kW which would be transferred back to shore.

  9. Hull-form optimization of KSUEZMAX to enhance resistance performance

    NASA Astrophysics Data System (ADS)

    Park, Jong-Heon; Choi, Jung-Eun; Chun, Ho-Hwan

    2015-01-01

    This paper deploys optimization techniques to obtain the optimum hull form of KSUEZMAX at the conditions of full-load draft and design speed. The processes have been carried out using a RaPID-HOP program. The bow and the stern hull-forms are optimized separately without altering neither, and the resulting versions of the two are then combined. Objective functions are the minimum values of wave-making and viscous pressure resistance coefficients for the bow and stern. Parametric modification functions for the bow hull-form variation are SAC shape, section shape (U-V type, DLWL type), bulb shape (bulb height and size); and those for the stern are SAC and section shape (U-V type, DLWL type). WAVIS version 1.3 code is used for the potential and the viscous-flow solver. Prior to the optimization, a parametric study has been conducted to observe the effects of design parameters on the objective functions. SQP has been applied for the optimization algorithm. The model tests have been conducted at a towing tank to evaluate the resistance performance of the optimized hull-form. It has been noted that the optimized hull-form brings 2.4% and 6.8% reduction in total and residual resistance coefficients compared to those of the original hull-form. The propulsive efficiency increases by 2.0% and the delivered power is reduced 3.7%, whereas the propeller rotating speed increases slightly by 0.41 rpm.

  10. Application of the theory of optimal experiments to adaptive electromagnetic-induction sensing of buried targets.

    PubMed

    Liao, Xuejun; Carin, Lawrence

    2004-08-01

    A mobile electromagnetic-induction (EMI) sensor is considered for detection and characterization of buried conducting and/or ferrous targets. The sensor may be placed on a robot and, here, we consider design of an optimal adaptive-search strategy. A frequency-dependent magnetic-dipole model is used to characterize the target at EMI frequencies. The goal of the search is accurate characterization of the dipole-model parameters, denoted bythe vector theta; the target position and orientation are a subset of theta. The sensor position and operating frequency are denoted by the parameter vector p and a measurement is represented by the pair (p, O), where O denotes the observed data. The parametersp are fixed for a given measurement, but, in the context of a sequence of measurements p may be changed adaptively. In a locally optimal sequence of measurements, we desire the optimal sensor parameters, P(N+1) for estimation of theta, based on the previous measurements (p(n), On)n=1,N. The search strategy is based on the theory of optimal experiments, as discussed in detail and demonstrated via several numerical examples.

  11. Error bounds of adaptive dynamic programming algorithms for solving undiscounted optimal control problems.

    PubMed

    Liu, Derong; Li, Hongliang; Wang, Ding

    2015-06-01

    In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.

  12. Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

    NASA Astrophysics Data System (ADS)

    Yang, Xiong; Liu, Derong; Wang, Ding

    2014-03-01

    In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.

  13. A Study on the Optimization Performance of Fireworks and Cuckoo Search Algorithms in Laser Machining Processes

    NASA Astrophysics Data System (ADS)

    Goswami, D.; Chakraborty, S.

    2014-11-01

    Laser machining is a promising non-contact process for effective machining of difficult-to-process advanced engineering materials. Increasing interest in the use of lasers for various machining operations can be attributed to its several unique advantages, like high productivity, non-contact processing, elimination of finishing operations, adaptability to automation, reduced processing cost, improved product quality, greater material utilization, minimum heat-affected zone and green manufacturing. To achieve the best desired machining performance and high quality characteristics of the machined components, it is extremely important to determine the optimal values of the laser machining process parameters. In this paper, fireworks algorithm and cuckoo search (CS) algorithm are applied for single as well as multi-response optimization of two laser machining processes. It is observed that although almost similar solutions are obtained for both these algorithms, CS algorithm outperforms fireworks algorithm with respect to average computation time, convergence rate and performance consistency.

  14. Empirical performance of the spectral independent morphological adaptive classifier

    NASA Astrophysics Data System (ADS)

    Montgomery, Joel B.; Montgomery, Christine T.; Sanderson, Richard B.; McCalmont, John F.

    2008-04-01

    Effective missile warning and countermeasures continue to be an unfulfilled goal for the Air Force including the wider military and civilian aerospace community. To make the necessary detection and jamming timeframes dictated by today's proliferated missiles and near-term upgraded threats, sensors with required sensitivity, field of regard, and spatial resolution are being pursued in conjunction with advanced processing techniques allowing for detection and discrimination beyond 10 km. The greatest driver of any missile warning system is detection and correct declaration, in which all targets need to be detected with a high confidence and with very few false alarms. Generally, imaging sensors are limited in their detection capability by the presence of heavy background clutter, sun glints, and inherent sensor noise. Many threat environments include false alarm sources like burning fuels, flares, exploding ordinance, and industrial emitters. Spectral discrimination has been shown to be one of the most effective methods of improving the performance of typical missile warning sensors, particularly for heavy clutter situations. Its utility has been demonstrated in the field and on-board multiple aircraft. Utilization of the background and clutter spectral content, coupled with additional spatial and temporal filtering techniques, have yielded robust adaptive real-time algorithms to increase signal-to-clutter ratios against point targets, and thereby to increase detection range. The algorithm outlined is the result of continued work with reported results against visible missile tactical data. The results are summarized and compared in terms of computational cost expected to be implemented on a real-time field-programmable gate array (FPGA) processor.

  15. 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.

  16. Performance of an Adaptive Matched Filter Using the Griffiths Algorithm

    DTIC Science & Technology

    1988-12-01

    Simon. Introduction to Adaptive Filters. New York: Macmillan Publishing Company, 1984. 11. Sklar , Bernard . Digital Communications Fundamentals and...York: Harper and Row, 1986. 8. Widrow, Bernard and Samuel D. Stearns. Adaptive Signal Processing. Englewood Cliffs, N.J.: Prentice-Hall, 1985. 9...Fourier Transforms. and Optics. New York: John Wiley and Sons, 1978. 15. Widrow, Bernard and others. "The Complex LMS Algorithm," Proceedings of the IEEE

  17. Dynamic Aberration Correction for Conformal Window of High-Speed Aircraft Using Optimized Model-Based Wavefront Sensorless Adaptive Optics.

    PubMed

    Dong, Bing; Li, Yan; Han, Xin-Li; Hu, Bin

    2016-09-02

    For high-speed aircraft, a conformal window is used to optimize the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of dynamic aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for dynamic aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To optimize the dynamic correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the dynamic aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during dynamic correction is 1.436 × 10(-5) in optimized correction and is 1.427 × 10(-5) in un-optimized correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method.

  18. Dynamic Aberration Correction for Conformal Window of High-Speed Aircraft Using Optimized Model-Based Wavefront Sensorless Adaptive Optics

    PubMed Central

    Dong, Bing; Li, Yan; Han, Xin-li; Hu, Bin

    2016-01-01

    For high-speed aircraft, a conformal window is used to optimize the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of dynamic aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for dynamic aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To optimize the dynamic correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the dynamic aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during dynamic correction is 1.436 × 10−5 in optimized correction and is 1.427 × 10−5 in un-optimized correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method. PMID:27598161

  19. Performance enhancement of a pump impeller using optimal design method

    NASA Astrophysics Data System (ADS)

    Jeon, Seok-Yun; Kim, Chul-Kyu; Lee, Sang-Moon; Yoon, Joon-Yong; Jang, Choon-Man

    2017-04-01

    This paper presents the performance evaluation of a regenerative pump to increase its efficiency using optimal design method. Two design parameters which define the shape of the pump impeller, are introduced and analyzed. Pump performance is evaluated by numerical simulation and design of experiments(DOE). To analyze three-dimensional flow field in the pump, general analysis code, CFX, is used in the present work. Shear stress turbulence model is employed to estimate the eddy viscosity. Experimental apparatus with an open-loop facility is set up for measuring the pump performance. Pump performance, efficiency and pressure, obtained from numerical simulation are validated by comparison with the results of experiments. Throughout the shape optimization of the pump impeller at the operating flow condition, the pump efficiency is successfully increased by 3 percent compared to the reference pump. It is noted that the pressure increase of the optimum pump is mainly caused by higher momentum force generated inside blade passage due to the optimal blade shape. Comparisons of pump internal flow on the reference and optimum pump are also investigated and discussed in detail.

  20. Field of view selection for optimal airborne imaging sensor performance

    NASA Astrophysics Data System (ADS)

    Goss, Tristan M.; Barnard, P. Werner; Fildis, Halidun; Erbudak, Mustafa; Senger, Tolga; Alpman, Mehmet E.

    2014-05-01

    The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor's sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system's performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.

  1. Strong stabilization servo controller with optimization of performance criteria.

    PubMed

    Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor

    2011-07-01

    Synthesis of a simple robust controller with a pole placement technique and a H(∞) metrics is the method used for control of a servo mechanism with BLDC and BDC electric motors. The method includes solving a polynomial equation on the basis of the chosen characteristic polynomial using the Manabe standard polynomial form and parametric solutions. Parametric solutions are introduced directly into the structure of the servo controller. On the basis of the chosen parametric solutions the robustness of a closed-loop system is assessed through uncertainty models and assessment of the norm ‖•‖(∞). The design procedure and the optimization are performed with a genetic algorithm differential evolution - DE. The DE optimization method determines a suboptimal solution throughout the optimization on the basis of a spectrally square polynomial and Šiljak's absolute stability test. The stability of the designed controller during the optimization is being checked with Lipatov's stability condition. Both utilized approaches: Šiljak's test and Lipatov's condition, check the robustness and stability characteristics on the basis of the polynomial's coefficients, and are very convenient for automated design of closed-loop control and for application in optimization algorithms such as DE.

  2. Hybrid adaptive optimal control of anaerobic fluidized bed bioreactor for the de-icing waste treatment.

    PubMed

    Seok, Jonghyuk

    2003-04-24

    Hybrid adaptive control strategy was developed and tested for the degradation of propylene glycol, a major component in de-icing waste, in an anaerobic fluidized bed bioreactor (AFBR). A linearized model with time-varying parameters was first employed to describe the dynamic behavior of the AFBR using a recursive off-line system identification method. A hybrid adaptive control strategy was then tested using a recursive off-line system identification routine followed by an on-line adaptive optimal control algorithm. The objective of the controller was to achieve the desired set point value of the propionate concentration (stand-alone control output variable) by manipulating the dilution rate (control input variable). To do so, the optimal control law was developed by minimizing a cost function with constraint equations. This novel idea was successfully applied to the underlying system for 200 h. The set point (700 mg HPrl(-1)) was achieved even in the case where the feed concentration suddenly increased by 50% (9000 mg HPrl(-1) to 13500 mg HPrl(-1)).

  3. Airbag Landing Impact Performance Optimization for the Orion Crew Module

    NASA Technical Reports Server (NTRS)

    Lee, Timothy J.; McKinney, John; Corliss, James M.

    2008-01-01

    This report will discuss the use of advanced simulation techniques to optimize the performance of the proposed Orion Crew Module airbag landing system design. The Boeing Company and the National Aeronautic and Space Administration s Langley Research Center collaborated in the analysis of the proposed airbag landing system for the next generation space shuttle replacement, the Orion spacecraft. Using LS-DYNA to simulate the Crew Module landing impacts, two main objectives were established and achieved: the investigation of potential methods of optimizing the airbag performance in order to reduce rebound on the anti-bottoming bags, lower overall landing loads, and increase overall Crew Module stability; and the determination of the Crew Module stability and load boundaries using the optimized airbag design, based on the potential Crew Module landing pitch angles and ground slopes in both the center of gravity forward and aft configurations. This paper describes the optimization and stability and load boundary studies and presents a summary of the results obtained and key lessons learned from this analysis.

  4. Challenges when performing economic optimization of waste treatment: A review

    SciTech Connect

    Juul, N.; Münster, M.; Ravn, H.; Söderman, M. Ljunggren

    2013-09-15

    Highlights: • Review of main optimization tools in the field of waste management. • Different optimization methods are applied. • Different fractions are analyzed. • There is focus on different parameters in different geographical regions. • More research is needed which encompasses both recycling and energy solutions. - Abstract: Strategic and operational decisions in waste management, in particular with respect to investments in new treatment facilities, are needed due to a number of factors, including continuously increasing amounts of waste, political demands for efficient utilization of waste resources, and the decommissioning of existing waste treatment facilities. Optimization models can assist in ensuring that these investment strategies are economically feasible. Various economic optimization models for waste treatment have been developed which focus on different parameters. Models focusing on transport are one example, but models focusing on energy production have also been developed, as well as models which take into account a plant’s economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi-criteria analysis have been developed. A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy-makers and model-developers involved in assessing the economic performance of waste treatment alternatives.

  5. Performance optimization of lateral displacement estimation with spatial angular compounding.

    PubMed

    He, Qiong; Tong, Ling; Huang, Lingyun; Liu, Jing; Chen, Yinran; Luo, Jianwen

    2017-01-01

    Elastography provides tissue mechanical information to differentiate normal and disease states. Nowadays, axial displacement and strain are usually estimated in clinical practice whereas lateral estimation is rarely used given that its accuracy is typically one order of magnitude worse than that of axial estimation. To improve the performance of lateral estimation, spatial angular compounding of multiple axial displacements along ultrasound beams transmitting in different steering angles was previously proposed. However, few studies have been conducted to evaluate the influence of key factors such as grating lobe noise (GLN), the number of steering angles (NSA) and maximum steering angle (MSA) in terms of performance optimization. The aim of this study was thus to investigate the effects of these factors through both computer simulations and phantom experiments. Only lateral rigid motion was considered in this study to separate its effects from those of axial and lateral strains on lateral displacement estimation. The performance as indicated by the root mean square error (RMSE) and standard deviation (SD) of the estimated lateral displacements validates the capability of spatial angular compounding in improving the performance of lateral estimation. It is necessary to filter the GLN for better estimation, and better performance is associated with a larger NSA and bigger MSA in both simulations and experiments, which is in agreement with the theoretical analysis. As indicated by the RMSE and SD, two steering angles with a larger steering angle are recommended. These results could provide insights into the performance optimization of lateral displacement estimation with spatial angular compounding.

  6. An auto-adaptive optimization approach for targeting nonpoint source pollution control practices

    PubMed Central

    Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

    2015-01-01

    To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs. PMID:26487474

  7. Simple model for predicting microchannel heat sink performance and optimization

    NASA Astrophysics Data System (ADS)

    Tsai, Tsung-Hsun; Chein, Reiyu

    2012-05-01

    A simple model was established to predict microchannel heat sink performance based on energy balance. Both hydrodynamically and thermally developed effects were included. Comparisons with the experimental data show that this model provides satisfactory thermal resistance prediction. The model is further extended to carry out geometric optimization on the microchannel heat sink. The results from the simple model are in good agreement as compared with those obtained from three-dimensional simulations.

  8. Integrated optimization of management cost of hierarchical mobile IPv6 and its performance simulation

    NASA Astrophysics Data System (ADS)

    Peng, Xue-hai; Zhang, Hong-ke; Zhang, Si-dong

    2004-04-01

    Mobile IPv6 was designed to enable an IPv6 terminal to continue communications seamlessly while changing its access to network. Decreasing communication and management cost is a key issue of the research of the Internet mobility management. Hierarchical Mobile IPv6 was proposed to reduce the number of management messages in backbone network. However, the resources consumptions inside a hierarchical domain are increased as expense according to our cost models. Based on the idea of integrated optimization, adaptive mobility management scheme (AMMS) is proposed in this paper, which decreases the total cost of delivering management messages and data payload on the viewpoint of entire network resources by selecting a suitable mobility management scheme adaptively for a mobile node. The results of simulation show that AMMS has better performance than unmixed Mobile IPv6 and Hierarchical Mobile IPv6.

  9. Error Estimation and h-Adaptivity for Optimal Finite Element Analysis

    NASA Technical Reports Server (NTRS)

    Cwik, Tom; Lou, John

    1997-01-01

    The objective of adaptive meshing and automatic error control in finite element analysis is to eliminate the need for the application engineer from re-meshing and re-running design simulations to verify numerical accuracy. The user should only need to enter the component geometry and a coarse finite element mesh. The software will then autonomously and adaptively refine this mesh where needed, reducing the error in the fields to a user prescribed value. The ideal end result of the simulation is a measurable quantity (e.g. scattered field, input impedance), calculated to a prescribed error, in less time and less machine memory than if the user applied typical uniform mesh refinement by hand. It would also allow for the simulation of larger objects since an optimal mesh is created.

  10. Development of a new adaptive ordinal approach to continuous-variable probabilistic optimization.

    SciTech Connect

    Romero, Vicente JosÔe; Chen, Chun-Hung (George Mason University, Fairfax, VA)

    2006-11-01

    A very general and robust approach to solving continuous-variable optimization problems involving uncertainty in the objective function is through the use of ordinal optimization. At each step in the optimization problem, improvement is based only on a relative ranking of the uncertainty effects on local design alternatives, rather than on precise quantification of the effects. One simply asks ''Is that alternative better or worse than this one?'' -not ''HOW MUCH better or worse is that alternative to this one?'' The answer to the latter question requires precise characterization of the uncertainty--with the corresponding sampling/integration expense for precise resolution. However, in this report we demonstrate correct decision-making in a continuous-variable probabilistic optimization problem despite extreme vagueness in the statistical characterization of the design options. We present a new adaptive ordinal method for probabilistic optimization in which the trade-off between computational expense and vagueness in the uncertainty characterization can be conveniently managed in various phases of the optimization problem to make cost-effective stepping decisions in the design space. Spatial correlation of uncertainty in the continuous-variable design space is exploited to dramatically increase method efficiency. Under many circumstances the method appears to have favorable robustness and cost-scaling properties relative to other probabilistic optimization methods, and uniquely has mechanisms for quantifying and controlling error likelihood in design-space stepping decisions. The method is asymptotically convergent to the true probabilistic optimum, so could be useful as a reference standard against which the efficiency and robustness of other methods can be compared--analogous to the role that Monte Carlo simulation plays in uncertainty propagation.

  11. Preliminary flight evaluation of an engine performance optimization algorithm

    NASA Technical Reports Server (NTRS)

    Lambert, H. H.; Gilyard, G. B.; Chisholm, J. D.; Kerr, L. J.

    1991-01-01

    A performance seeking control (PSC) algorithm has undergone initial flight test evaluation in subsonic operation of a PW 1128 engined F-15. This algorithm is designed to optimize the quasi-steady performance of an engine for three primary modes: (1) minimum fuel consumption; (2) minimum fan turbine inlet temperature (FTIT); and (3) maximum thrust. The flight test results have verified a thrust specific fuel consumption reduction of 1 pct., up to 100 R decreases in FTIT, and increases of as much as 12 pct. in maximum thrust. PSC technology promises to be of value in next generation tactical and transport aircraft.

  12. Fueling strategies to optimize performance: training high or training low?

    PubMed

    Burke, L M

    2010-10-01

    Availability of carbohydrate as a substrate for the muscle and central nervous system is critical for the performance of both intermittent high-intensity work and prolonged aerobic exercise. Therefore, strategies that promote carbohydrate availability, such as ingesting carbohydrate before, during and after exercise, are critical for the performance of many sports and a key component of current sports nutrition guidelines. Guidelines for daily carbohydrate intakes have evolved from the "one size fits all" recommendation for a high-carbohydrate diets to an individualized approach to fuel needs based on the athlete's body size and exercise program. More recently, it has been suggested that athletes should train with low carbohydrate stores but restore fuel availability for competition ("train low, compete high"), based on observations that the intracellular signaling pathways underpinning adaptations to training are enhanced when exercise is undertaken with low glycogen stores. The present literature is limited to studies of "twice a day" training (low glycogen for the second session) or withholding carbohydrate intake during training sessions. Despite increasing the muscle adaptive response and reducing the reliance on carbohydrate utilization during exercise, there is no clear evidence that these strategies enhance exercise performance. Further studies on dietary periodization strategies, especially those mimicking real-life athletic practices, are needed.

  13. A multi-layer robust adaptive fault tolerant control system for high performance aircraft

    NASA Astrophysics Data System (ADS)

    Huo, Ying

    Modern high-performance aircraft demand advanced fault-tolerant flight control strategies. Not only the control effector failures, but the aerodynamic type failures like wing-body damages often result in substantially deteriorate performance because of low available redundancy. As a result the remaining control actuators may yield substantially lower maneuvering capabilities which do not authorize the accomplishment of the air-craft's original specified mission. The problem is to solve the control reconfiguration on available control redundancies when the mission modification is urged to save the aircraft. The proposed robust adaptive fault-tolerant control (RAFTC) system consists of a multi-layer reconfigurable flight controller architecture. It contains three layers accounting for different types and levels of failures including sensor, actuator, and fuselage damages. In case of the nominal operation with possible minor failure(s) a standard adaptive controller stands to achieve the control allocation. This is referred to as the first layer, the controller layer. The performance adjustment is accounted for in the second layer, the reference layer, whose role is to adjust the reference model in the controller design with a degraded transit performance. The upmost mission adjust is in the third layer, the mission layer, when the original mission is not feasible with greatly restricted control capabilities. The modified mission is achieved through the optimization of the command signal which guarantees the boundedness of the closed-loop signals. The main distinguishing feature of this layer is the the mission decision property based on the current available resources. The contribution of the research is the multi-layer fault-tolerant architecture that can address the complete failure scenarios and their accommodations in realities. Moreover, the emphasis is on the mission design capabilities which may guarantee the stability of the aircraft with restricted post

  14. Performance Trades Study for Robust Airfoil Shape Optimization

    NASA Technical Reports Server (NTRS)

    Li, Wu; Padula, Sharon

    2003-01-01

    From time to time, existing aircraft need to be redesigned for new missions with modified operating conditions such as required lift or cruise speed. This research is motivated by the needs of conceptual and preliminary design teams for smooth airfoil shapes that are similar to the baseline design but have improved drag performance over a range of flight conditions. The proposed modified profile optimization method (MPOM) modifies a large number of design variables to search for nonintuitive performance improvements, while avoiding off-design performance degradation. Given a good initial design, the MPOM generates fairly smooth airfoils that are better than the baseline without making drastic shape changes. Moreover, the MPOM allows users to gain valuable information by exploring performance trades over various design conditions. Four simulation cases of airfoil optimization in transonic viscous ow are included to demonstrate the usefulness of the MPOM as a performance trades study tool. Simulation results are obtained by solving fully turbulent Navier-Stokes equations and the corresponding discrete adjoint equations using an unstructured grid computational fluid dynamics code FUN2D.

  15. Performance Study and Dynamic Optimization Design for Thread Pool Systems

    SciTech Connect

    Xu, Dongping

    2004-12-19

    Thread pools have been widely used by many multithreaded applications. However, the determination of the pool size according to the application behavior still remains problematic. To automate this process, in this thesis we have developed a set of performance metrics for quantitatively analyzing thread pool performance. For our experiments, we built a thread pool system which provides a general framework for thread pool research. Based on this simulation environment, we studied the performance impact brought by the thread pool on different multithreaded applications. Additionally, the correlations between internal characterizations of thread pools and their throughput were also examined. We then proposed and evaluated a heuristic algorithm to dynamically determine the optimal thread pool size. The simulation results show that this approach is effective in improving overall application performance.

  16. Performance Characterization of KAPAO, a Low-Cost Natural Guide Star Adaptive Optics Instrument

    NASA Astrophysics Data System (ADS)

    Long, Joseph; Choi, P. I.; Severson, S. A.; Littleton, E.; Badham, K.; Bolger, D.; Guerrero, C.; Ortega, F.; Wong, J.; Baranec, C.; Riddle, R. L.

    2014-01-01

    We present a software overview of KAPAO, an adaptive optics system designed for the Pomona College 1-meter telescope at Table Mountain Observatory. The instrument is currently in the commissioning phase and data presented here are from both in-lab and on-sky observations. In an effort to maximize on-sky performance, we have developed a suite of instrument-specific data analysis tools. This suite of tools aids in the alignment of the instrument's optics, and the optimization of on-sky performance. The analysis suite visualizes and extends the telemetry output by the Robo-AO control software. This includes visualization of deformable mirror and wavefront sensor telemetry and a Zernike decomposition of the residual wavefront error. We complement this with analysis tools for the science camera data. We model a synthetic PSF for the Table Mountain telescope to calibrate our Strehl measurements, and process image data cubes to track instrument performance over the course of an observation. By coupling WFS telemetry with science camera data we can use image sharpening techniques to account for non-common-path wavefront errors and improve image performance. Python packages for scientific computing, such as NumPy and Matplotlib, are employed to complement existing IDL code. A primary goal of this suite of software is to support the remote use of the system by a broad range of users that includes faculty and undergraduate students from the consortium of member campuses.

  17. Power and Performance Trade-offs for Space Time Adaptive Processing

    SciTech Connect

    Gawande, Nitin A.; Manzano Franco, Joseph B.; Tumeo, Antonino; Tallent, Nathan R.; Kerbyson, Darren J.; Hoisie, Adolfy

    2015-07-27

    Computational efficiency – performance relative to power or energy – is one of the most important concerns when designing RADAR processing systems. This paper analyzes power and performance trade-offs for a typical Space Time Adaptive Processing (STAP) application. We study STAP implementations for CUDA and OpenMP on two computationally efficient architectures, Intel Haswell Core I7-4770TE and NVIDIA Kayla with a GK208 GPU. We analyze the power and performance of STAP’s computationally intensive kernels across the two hardware testbeds. We also show the impact and trade-offs of GPU optimization techniques. We show that data parallelism can be exploited for efficient implementation on the Haswell CPU architecture. The GPU architecture is able to process large size data sets without increase in power requirement. The use of shared memory has a significant impact on the power requirement for the GPU. A balance between the use of shared memory and main memory access leads to an improved performance in a typical STAP application.

  18. Adaptable structural synthesis using advanced analysis and optimization coupled by a computer operating system

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, J.; Bhat, R. B.

    1979-01-01

    A finite element program is linked with a general purpose optimization program in a 'programing system' which includes user supplied codes that contain problem dependent formulations of the design variables, objective function and constraints. The result is a system adaptable to a wide spectrum of structural optimization problems. In a sample of numerical examples, the design variables are the cross-sectional dimensions and the parameters of overall shape geometry, constraints are applied to stresses, displacements, buckling and vibration characteristics, and structural mass is the objective function. Thin-walled, built-up structures and frameworks are included in the sample. Details of the system organization and characteristics of the component programs are given.

  19. [An adaptive ultrasound sound speed optimization based on image contrast analysis].

    PubMed

    Li, Xiaoying; Liu, Dongquan

    2011-12-01

    In order to get real time ultrasound images with clear structure and improved contrast, an adaptive ultrasound sound speed optimization method based on image contrast analysis was investigated. It firstly introduced the dynamic beamforming of ultrasound system, as well as the definition of assumed system's sound speed and the true sound speed propagated in tissues the degrade image quality due to their mismatch was also discussed. After given the pixel gray level value based ultrasound image contrast ratio, the basic idea to precisely estimate the true sound speed for real time system sound speed was proposed. Algorithms have been verified both in tissue-mimicking phantoms with known sound speeds and in vivo ultrasound images, compared with other existing method. The testing results showed that this new method not only produced accurate sound speed for ultrasound image optimization, but also finely met the critical computation requirement for real time applications.

  20. Optimization of Transient Heat Exchanger Performance for Improved Energy Efficiency

    NASA Astrophysics Data System (ADS)

    Bran Anleu, Gabriela; Kavehpour, Pirouz; Lavine, Adrienne; Wirz, Richard

    2014-11-01

    Heat exchangers are used in a multitude of applications within systems for energy generation, energy conversion, or energy storage. Many of these systems (e.g. solar power plants) function under transient conditions, but the design of the heat exchangers is typically optimized assuming steady state conditions. There is a potential for significant energy savings if the transient behavior of the heat exchanger is taken into account in designing the heat exchanger by optimizing its operating conditions in relation to the transient behavior of the overall system. The physics of the transient behavior of a heat exchanger needs to be understood to provide design parameters for transient heat exchangers to deliver energy savings. A numerical model was used to determine the optimized mass flow rates thermal properties for a thermal energy storage system. The transient behavior is strongly linked to the dimensionless parameters relating fluid properties, the mass flow rates, and the temperature of the fluids at the inlet of each stream. Smart metals, or advanced heat exchanger surface geometries and methods of construction will be used to meet the three goals mentioned before: 1) energy and cost reduction, 2) size reduction, and 3) optimal performance for all modes of operation.

  1. Partially supervised P300 speller adaptation for eventual stimulus timing optimization: target confidence is superior to error-related potential score as an uncertain label

    NASA Astrophysics Data System (ADS)

    Zeyl, Timothy; Yin, Erwei; Keightley, Michelle; Chau, Tom

    2016-04-01

    Objective. Error-related potentials (ErrPs) have the potential to guide classifier adaptation in BCI spellers, for addressing non-stationary performance as well as for online optimization of system parameters, by providing imperfect or partial labels. However, the usefulness of ErrP-based labels for BCI adaptation has not been established in comparison to other partially supervised methods. Our objective is to make this comparison by retraining a two-step P300 speller on a subset of confident online trials using naïve labels taken from speller output, where confidence is determined either by (i) ErrP scores, (ii) posterior target scores derived from the P300 potential, or (iii) a hybrid of these scores. We further wish to evaluate the ability of partially supervised adaptation and retraining methods to adjust to a new stimulus-onset asynchrony (SOA), a necessary step towards online SOA optimization. Approach. Eleven consenting able-bodied adults attended three online spelling sessions on separate days with feedback in which SOAs were set at 160 ms (sessions 1 and 2) and 80 ms (session 3). A post hoc offline analysis and a simulated online analysis were performed on sessions two and three to compare multiple adaptation methods. Area under the curve (AUC) and symbols spelled per minute (SPM) were the primary outcome measures. Main results. Retraining using supervised labels confirmed improvements of 0.9 percentage points (session 2, p < 0.01) and 1.9 percentage points (session 3, p < 0.05) in AUC using same-day training data over using data from a previous day, which supports classifier adaptation in general. Significance. Using posterior target score alone as a confidence measure resulted in the highest SPM of the partially supervised methods, indicating that ErrPs are not necessary to boost the performance of partially supervised adaptive classification. Partial supervision significantly improved SPM at a novel SOA, showing promise for eventual online SOA

  2. Threat of resource loss: The role of self-regulation in adaptive task performance.

    PubMed

    Niessen, Cornelia; Jimmieson, Nerina L

    2016-03-01

    Changes at work are often accompanied with the threat of, or actual, resource loss. Through an experiment, we investigated the detrimental effect of the threat of resource loss on adaptive task performance. Self-regulation (i.e., task focus and emotion control) was hypothesized to buffer the negative relationship between the threat of resource loss and adaptive task performance. Adaptation was conceptualized as relearning after a change in task execution rules. Threat of resource loss was manipulated for 100 participants undertaking an air traffic control task. Using discontinuous growth curve modeling, 2 kinds of adaptation--transition adaptation and reacquisition adaptation--were differentiated. The results showed that individuals who experienced the threat of resource loss had a stronger drop in performance (less transition adaptation) and a subsequent slower recovery (less reacquisition adaptation) compared with the control group who experienced no threat. Emotion control (but not task focus) moderated the relationship between the threat of resource loss and transition adaptation. In this respect, individuals who felt threatened but regulated their emotions performed better immediately after the task change (but not later on) compared with those individuals who felt threatened and did not regulate their emotions as well. However, later on, relearning (reacquisition adaptation) under the threat of resource loss was facilitated when individuals concentrated on the task at hand.

  3. A wavelet-optimized, very high order adaptive grid and order numerical method

    NASA Technical Reports Server (NTRS)

    Jameson, Leland

    1996-01-01

    Differencing operators of arbitrarily high order can be constructed by interpolating a polynomial through a set of data followed by differentiation of this polynomial and finally evaluation of the polynomial at the point where a derivative approximation is desired. Furthermore, the interpolating polynomial can be constructed from algebraic, trigonometric, or, perhaps exponential polynomials. This paper begins with a comparison of such differencing operator construction. Next, the issue of proper grids for high order polynomials is addressed. Finally, an adaptive numerical method is introduced which adapts the numerical grid and the order of the differencing operator depending on the data. The numerical grid adaptation is performed on a Chebyshev grid. That is, at each level of refinement the grid is a Chebvshev grid and this grid is refined locally based on wavelet analysis.

  4. A feature extraction method of the particle swarm optimization algorithm based on adaptive inertia weight and chaos optimization for Brillouin scattering spectra

    NASA Astrophysics Data System (ADS)

    Zhang, Yanjun; Zhao, Yu; Fu, Xinghu; Xu, Jinrui

    2016-10-01

    A novel particle swarm optimization algorithm based on adaptive inertia weight and chaos optimization is proposed for extracting the features of Brillouin scattering spectra. Firstly, the adaptive inertia weight parameter of the velocity is introduced to the basic particle swarm algorithm. Based on the current iteration number of particles and the adaptation value, the algorithm can change the weight coefficient and adjust the iteration speed of searching space for particles, so the local optimization ability can be enhanced. Secondly, the logical self-mapping chaotic search is carried out by using the chaos optimization in particle swarm optimization algorithm, which makes the particle swarm optimization algorithm jump out of local optimum. The novel algorithm is compared with finite element analysis-Levenberg Marquardt algorithm, particle swarm optimization-Levenberg Marquardt algorithm and particle swarm optimization algorithm by changing the linewidth, the signal-to-noise ratio and the linear weight ratio of Brillouin scattering spectra. Then the algorithm is applied to the feature extraction of Brillouin scattering spectra in different temperatures. The simulation analysis and experimental results show that this algorithm has a high fitting degree and small Brillouin frequency shift error for different linewidth, SNR and linear weight ratio. Therefore, this algorithm can be applied to the distributed optical fiber sensing system based on Brillouin optical time domain reflection, which can effectively improve the accuracy of Brillouin frequency shift extraction.

  5. Optimal adaptive control for quantum metrology with time-dependent Hamiltonians

    NASA Astrophysics Data System (ADS)

    Pang, Shengshi; Jordan, Andrew N.

    2017-03-01

    Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case.

  6. Optimal adaptive control for quantum metrology with time-dependent Hamiltonians.

    PubMed

    Pang, Shengshi; Jordan, Andrew N

    2017-03-09

    Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T(2) time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T(4) in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case.

  7. Optimization of wind farm performance using low-order models

    NASA Astrophysics Data System (ADS)

    Dabiri, John; Brownstein, Ian

    2015-11-01

    A low order model that captures the dominant flow behaviors in a vertical-axis wind turbine (VAWT) array is used to maximize the power output of wind farms utilizing VAWTs. The leaky Rankine body model (LRB) was shown by Araya et al. (JRSE 2014) to predict the ranking of individual turbine performances in an array to within measurement uncertainty as compared to field data collected from full-scale VAWTs. Further, this model is able to predict array performance with significantly less computational expense than higher fidelity numerical simulations of the flow, making it ideal for use in optimization of wind farm performance. This presentation will explore the ability of the LRB model to rank the relative power output of different wind turbine array configurations as well as the ranking of individual array performance over a variety of wind directions, using various complex configurations tested in the field and simpler configurations tested in a wind tunnel. Results will be presented in which the model is used to determine array fitness in an evolutionary algorithm seeking to find optimal array configurations given a number of turbines, area of available land, and site wind direction profile. Comparison with field measurements will be presented.

  8. A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning

    SciTech Connect

    Zarepisheh, Masoud; Li, Nan; Long, Troy; Romeijn, H. Edwin; Tian, Zhen; Jia, Xun; Jiang, Steve B.

    2014-06-15

    Purpose: To develop a novel algorithm that incorporates prior treatment knowledge into intensity modulated radiation therapy optimization to facilitate automatic treatment planning and adaptive radiotherapy (ART) replanning. Methods: The algorithm automatically creates a treatment plan guided by the DVH curves of a reference plan that contains information on the clinician-approved dose-volume trade-offs among different targets/organs and among different portions of a DVH curve for an organ. In ART, the reference plan is the initial plan for the same patient, while for automatic treatment planning the reference plan is selected from a library of clinically approved and delivered plans of previously treated patients with similar medical conditions and geometry. The proposed algorithm employs a voxel-based optimization model and navigates the large voxel-based Pareto surface. The voxel weights are iteratively adjusted to approach a plan that is similar to the reference plan in terms of the DVHs. If the reference plan is feasible but not Pareto optimal, the algorithm generates a Pareto optimal plan with the DVHs better than the reference ones. If the reference plan is too restricting for the new geometry, the algorithm generates a Pareto plan with DVHs close to the reference ones. In both cases, the new plans have similar DVH trade-offs as the reference plans. Results: The algorithm was tested using three patient cases and found to be able to automatically adjust the voxel-weighting factors in order to generate a Pareto plan with similar DVH trade-offs as the reference plan. The algorithm has also been implemented on a GPU for high efficiency. Conclusions: A novel prior-knowledge-based optimization algorithm has been developed that automatically adjust the voxel weights and generate a clinical optimal plan at high efficiency. It is found that the new algorithm can significantly improve the plan quality and planning efficiency in ART replanning and automatic treatment

  9. Multi-objective optimization of gear forging process based on adaptive surrogate meta-models

    NASA Astrophysics Data System (ADS)

    Meng, Fanjuan; Labergere, Carl; Lafon, Pascal; Daniel, Laurent

    2013-05-01

    In forging industry, net shape or near net shape forging of gears has been the subject of considerable research effort in the last few decades. So in this paper, a multi-objective optimization methodology of net shape gear forging process design has been discussed. The study is mainly done in four parts: building parametric CAD geometry model, simulating the forging process, fitting surrogate meta-models and optimizing the process by using an advanced algorithm. In order to maximally appropriate meta-models of the real response, an adaptive meta-model based design strategy has been applied. This is a continuous process: first, bui Id a preliminary version of the meta-models after the initial simulated calculations; second, improve the accuracy and update the meta-models by adding some new representative samplings. By using this iterative strategy, the number of the initial sample points for real numerical simulations is greatly decreased and the time for the forged gear design is significantly shortened. Finally, an optimal design for an industrial application of a 27-teeth gear forging process was introduced, which includes three optimization variables and two objective functions. A 3D FE nu merical simulation model is used to realize the process and an advanced thermo-elasto-visco-plastic constitutive equation is considered to represent the material behavior. The meta-model applied for this example is kriging and the optimization algorithm is NSGA-II. At last, a relatively better Pareto optimal front (POF) is gotten with gradually improving the obtained surrogate meta-models.

  10. Optimizing SFR transmutation performance through direct adjoining control theory

    NASA Astrophysics Data System (ADS)

    Davis, Jeffrey C.

    2007-12-01

    We have developed the CORTANA code to optimize the transmutation performance of sodium cooled fast reactors (SFRs). We obtain the necessary conditions for optimal fuel and burnable absorber loadings using Pontryagin's maximum principle with a direct adjoining approach to explicitly account for either a flat flux or a power peaking inequality constraint providing a set of coupled system, Euler-Lagrange (E-L), and optimality equations which are iteratively solved with the method of conjugate gradients until no further improvement in the objective function is achieved. To satisfy the inequality constraints throughout the operating cycle, we have implemented a backwards diffusion theory (BDT) to establish a relationship between fuel loading and the relative assembly power distribution during the cycle and systematically eliminate the constraint violations with each conjugate gradient iteration. The CORTANA SFR optimization code uses multi-group, three-dimensional neutron diffusion theory, with a microscopic depletion scheme. We solve the system equations in a quasi-static fashion forward in time from beginning-of-cycle (BOC) to end-of-cycle (EOC), while we solve the E-L equations backwards in time from EOC to BOC, reflecting the adjoint nature of the Lagrange multipliers. A two enrichment-zone SFR problem verifies our formulation, yielding a TRU enrichment distribution nearly identical to that of the reference SFR core in the Generation IV Roadmap. Using a full heavy metal recycling mode, we coupled our optimization methodology with the REBUS-3 equilibrium cycle methodology to optimize an SFR operating as a second tier transmuter. We model the system using a three-dimensional triangular-z finite differencing scheme with full core symmetry and a time-independent 33-group microscopic cross section library. Beginning from a uniform TRU distribution, our CORTANA improves the SFR performance by reducing the maximum relative assembly power from 1.7 to 1.25, minimizes

  11. USING AN ADAPTER TO PERFORM THE CHALFANT-STYLE CONTAINMENT VESSEL PERIODIC MAINTENANCE LEAK RATE TEST

    SciTech Connect

    Loftin, B.; Abramczyk, G.; Trapp, D.

    2011-06-03

    Recently the Packaging Technology and Pressurized Systems (PT&PS) organization at the Savannah River National Laboratory was asked to develop an adapter for performing the leak-rate test of a Chalfant-style containment vessel. The PT&PS organization collaborated with designers at the Department of Energy's Pantex Plant to develop the adapter currently in use for performing the leak-rate testing on the containment vessels. This paper will give the history of leak-rate testing of the Chalfant-style containment vessels, discuss the design concept for the adapter, give an overview of the design, and will present results of the testing done using the adapter.

  12. Performance of laser guide star adaptive optics at Lick Observatory

    SciTech Connect

    Olivier, S.S.; An, J.; Avicola, K.

    1995-07-19

    A sodium-layer laser guide star adaptive optics system has been developed at Lawrence Livermore National Laboratory (LLNL) for use on the 3-meter Shane telescope at Lick Observatory. The system is based on a 127-actuator continuous-surface deformable mirror, a Hartmann wavefront sensor equipped with a fast-framing low-noise CCD camera, and a pulsed solid-state-pumped dye laser tuned to the atomic sodium resonance line at 589 nm. The adaptive optics system has been tested on the Shane telescope using natural reference stars yielding up to a factor of 12 increase in image peak intensity and a factor of 6.5 reduction in image full width at half maximum (FWHM). The results are consistent with theoretical expectations. The laser guide star system has been installed and operated on the Shane telescope yielding a beam with 22 W average power at 589 nm. Based on experimental data, this laser should generate an 8th magnitude guide star at this site, and the integrated laser guide star adaptive optics system should produce images with Strehl ratios of 0.4 at 2.2 {mu}m in median seeing and 0.7 at 2.2 {mu}m in good seeing.

  13. Graphene-loaded tin oxide nanofibers: optimization and sensing performance

    NASA Astrophysics Data System (ADS)

    Abideen, Zain Ul; Park, Jae Young; Kim, Hyoun Woo; Kim, Sang Sub

    2017-01-01

    We investigated the gas sensing characteristics of graphene nanosheet (NS)-loaded SnO2 nanofibers (NFs) that were synthesized by a low-cost facile electrospinning process. The sensing performance was characterized as a function of the graphene content with various gases such as C6H6, C7H8, CO, CO2, and H2S. The loading of graphene NSs significantly improved the gas sensing performances of SnO2 NFs. The optimal amount of graphene NSs was found to be 0.5 wt%. We proposed a sensing mechanism for the enhanced sensing performance based on the chemical sensitization of graphene NSs and the charge transfer through the heterointerfaces between graphene NSs and SnO2 nanograins. The results show that graphene NS-loaded SnO2 NFs are a promising sensing material system that can detect hazardous gaseous species.

  14. LAMMPS strong scaling performance optimization on Blue Gene/Q

    SciTech Connect

    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 an 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.

  15. [Adaptive optimized technologies for ecological sanitation and their complex ecological benefits].

    PubMed

    Zhou, Chuan-Bin; Wang, Ru-Song; Yang, Wen-Rui; Jin, Jia-Sheng

    2008-02-01

    Aiming at the ecological characters of the cities in central and west China, several ecological sanitary (ecosan) technologies with different adaptability were integrated, and five adaptive optimized technologies were established. The environmental effects, resources recyclable potential, economic benefits, management difficulties, and public acceptance of each of the technologies were studied, with the possible complex eco-benefits of the technical improvement assessed. The results showed that decentralized ecosan technologies had the advantages of conserving water, recycling nutrients and saving cost, but also had the problems in management and public acceptance. Centralized ecosan technologies had the advantages in management and public acceptance, but were short in high cost and low recycling potential. If the sanitary system was improved through applying ecosan technologies, the greenhouse gases emission (CO2 equivalent) and water pollution (calculated as BOD5) could be reduced by 70% and 30%, respectively, while recycled nutrients (the sum of N, P, K) could be increased by 15 times. The optimized system could supply 3% of domestic energy, 10% of domestic water, and 15% of food demand, and the total cost could be reduced by 56% when the resource-recycling benefits were taken into account.

  16. Stochastic Optimal Regulation of Nonlinear Networked Control Systems by Using Event-Driven Adaptive Dynamic Programming.

    PubMed

    Sahoo, Avimanyu; Jagannathan, Sarangapani

    2017-02-01

    In this paper, an event-driven stochastic adaptive dynamic programming (ADP)-based technique is introduced for nonlinear systems with a communication network within its feedback loop. A near optimal control policy is designed using an actor-critic framework and ADP with event sampled state vector. First, the system dynamics are approximated by using a novel neural network (NN) identifier with event sampled state vector. The optimal control policy is generated via an actor NN by using the NN identifier and value function approximated by a critic NN through ADP. The stochastic NN identifier, actor, and critic NN weights are tuned at the event sampled instants leading to aperiodic weight tuning laws. Above all, an adaptive event sampling condition based on estimated NN weights is designed by using the Lyapunov technique to ensure ultimate boundedness of all the closed-loop signals along with the approximation accuracy. The net result is event-driven stochastic ADP technique that can significantly reduce the computation and network transmissions. Finally, the analytical design is substantiated with simulation results.

  17. Multidisciplinary Design Optimization of a Full Vehicle with High Performance Computing

    NASA Technical Reports Server (NTRS)

    Yang, R. J.; Gu, L.; Tho, C. H.; Sobieszczanski-Sobieski, Jaroslaw

    2001-01-01

    Multidisciplinary design optimization (MDO) of a full vehicle under the constraints of crashworthiness, NVH (Noise, Vibration and Harshness), durability, and other performance attributes is one of the imperative goals for automotive industry. However, it is often infeasible due to the lack of computational resources, robust simulation capabilities, and efficient optimization methodologies. This paper intends to move closer towards that goal by using parallel computers for the intensive computation and combining different approximations for dissimilar analyses in the MDO process. The MDO process presented in this paper is an extension of the previous work reported by Sobieski et al. In addition to the roof crush, two full vehicle crash modes are added: full frontal impact and 50% frontal offset crash. Instead of using an adaptive polynomial response surface method, this paper employs a DOE/RSM method for exploring the design space and constructing highly nonlinear crash functions. Two NMO strategies are used and results are compared. This paper demonstrates that with high performance computing, a conventionally intractable real world full vehicle multidisciplinary optimization problem considering all performance attributes with large number of design variables become feasible.

  18. Advances in Adaptive Control Methods

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2009-01-01

    This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

  19. Investigation on adaptive optics performance from propagation channel characterization with the small optical transponder

    NASA Astrophysics Data System (ADS)

    Petit, Cyril; Védrenne, Nicolas; Velluet, Marie Therese; Michau, Vincent; Artaud, Geraldine; Samain, Etienne; Toyoshima, Morio

    2016-11-01

    In order to address the high throughput requested for both downlink and uplink satellite to ground laser links, adaptive optics (AO) has become a key technology. While maturing, application of this technology for satellite to ground telecommunication, however, faces difficulties, such as higher bandwidth and optimal operation for a wide variety of atmospheric conditions (daytime and nighttime) with potentially low elevations that might severely affect wavefront sensing because of scintillation. To address these specificities, an accurate understanding of the origin of the perturbations is required, as well as operational validation of AO on real laser links. We report here on a low Earth orbiting (LEO) microsatellite to ground downlink with AO correction. We discuss propagation channel characterization based on Shack-Hartmann wavefront sensor (WFS) measurements. Fine modeling of the propagation channel is proposed based on multi-Gaussian model of turbulence profile. This model is then used to estimate the AO performance and validate the experimental results. While AO performance is limited by the experimental set-up, it proves to comply with expected performance and further interesting information on propagation channel is extracted. These results shall help dimensioning and operating AO systems for LEO to ground downlinks.

  20. An optimized DSP implementation of adaptive filtering and ICA for motion artifact reduction in ambulatory ECG monitoring.

    PubMed

    Berset, Torfinn; Geng, Di; Romero, Iñaki

    2012-01-01

    Noise from motion artifacts is currently one of the main challenges in the field of ambulatory ECG recording. To address this problem, we propose the use of two different approaches. First, an adaptive filter with electrode-skin impedance as a reference signal is described. Secondly, a multi-channel ECG algorithm based on Independent Component Analysis is introduced. Both algorithms have been designed and further optimized for real-time work embedded in a dedicated Digital Signal Processor. We show that both algorithms improve the performance of a beat detection algorithm when applied in high noise conditions. In addition, an efficient way of choosing this methods is suggested with the aim of reduce the overall total system power consumption.

  1. Adaptation to a fat-rich diet: effects on endurance performance in humans.

    PubMed

    Helge, J W

    2000-11-01

    The focus of this review is on studies where dietary fat content was manipulated to investigate the potential ergogenic effect of fat loading on endurance exercise performance. Adaptation to a fat-rich diet is influenced by several factors, of which the duration of the adaptation period, the exercise intensity of the performance test and the content of fat and carbohydrate in the experimental diet are the most important. Evidence is presented that short term adaptation, < 6 days, to a fat-rich diet is detrimental to exercise performance. When adaptation to a fat-rich diet was performed over longer periods, studies where performance was tested at moderate intensity, 60 to 80% of maximal oxygen uptake, demonstrate either no difference or an attenuated performance after consumption of a fat-rich compared with a carbohydrate-rich diet. When performance was measured at high intensity after a longer period of adaptation, it was at best maintained, but in most cases attenuated, compared with consuming a carbohydrate-rich diet. Furthermore, evidence is presented that adaptation to a fat-rich diet leads to an increased capacity of the fat oxidative system and an enhancement of the fat supply and subsequently the amount of fat oxidised during exercise. However, in most cases muscle glycogen storage is compromised, and although muscle glycogen breakdown is diminished to a certain extent, this is probably part of the explanation for the lack of performance enhancement after adaptation to a fat-rich diet.

  2. Parallel Performance Optimization of the Direct Simulation Monte Carlo Method

    NASA Astrophysics Data System (ADS)

    Gao, Da; Zhang, Chonglin; Schwartzentruber, Thomas

    2009-11-01

    Although the direct simulation Monte Carlo (DSMC) particle method is more computationally intensive compared to continuum methods, it is accurate for conditions ranging from continuum to free-molecular, accurate in highly non-equilibrium flow regions, and holds potential for incorporating advanced molecular-based models for gas-phase and gas-surface interactions. As available computer resources continue their rapid growth, the DSMC method is continually being applied to increasingly complex flow problems. Although processor clock speed continues to increase, a trend of increasing multi-core-per-node parallel architectures is emerging. To effectively utilize such current and future parallel computing systems, a combined shared/distributed memory parallel implementation (using both Open Multi-Processing (OpenMP) and Message Passing Interface (MPI)) of the DSMC method is under development. The parallel implementation of a new state-of-the-art 3D DSMC code employing an embedded 3-level Cartesian mesh will be outlined. The presentation will focus on performance optimization strategies for DSMC, which includes, but is not limited to, modified algorithm designs, practical code-tuning techniques, and parallel performance optimization. Specifically, key issues important to the DSMC shared memory (OpenMP) parallel performance are identified as (1) granularity (2) load balancing (3) locality and (4) synchronization. Challenges and solutions associated with these issues as they pertain to the DSMC method will be discussed.

  3. Face adaptation does not improve performance on search or discrimination tasks.

    PubMed

    Ng, Minna; Boynton, Geoffrey M; Fine, Ione

    2008-01-04

    The face adaptation effect, as described by M. A. Webster and O. H. MacLin (1999), is a robust perceptual shift in the appearance of faces after a brief adaptation period. For example, prolonged exposure to Asian faces causes a Eurasian face to appear distinctly Caucasian. This adaptation effect has been documented for general configural effects, as well as for the facial properties of gender, ethnicity, expression, and identity. We began by replicating the finding that adaptation to ethnicity, gender, and a combination of both features induces selective shifts in category appearance. We then investigated whether this adaptation has perceptual consequences beyond a shift in the perceived category boundary by measuring the effects of adaptation on RSVP, spatial search, and discrimination tasks. Adaptation had no discernable effect on performance for any of these tasks.

  4. Approaching direct optimization of as-built lens performance

    NASA Astrophysics Data System (ADS)

    McGuire, James P.; Kuper, Thomas G.

    2012-10-01

    We describe a method approaching direct optimization of the rms wavefront error of a lens including tolerances. By including the effect of tolerances in the error function, the designer can choose to improve the as-built performance with a fixed set of tolerances and/or reduce the cost of production lenses with looser tolerances. The method relies on the speed of differential tolerance analysis and has recently become practical due to the combination of continuing increases in computer hardware speed and multiple core processing We illustrate the method's use on a Cooke triplet, a double Gauss, and two plastic mobile phone camera lenses.

  5. Characterization, performance and optimization of PVDF as a piezoelectric film for advanced space mirror concepts.

    SciTech Connect

    Jones, Gary D.; Assink, Roger Alan; Dargaville, Tim Richard; Chaplya, Pavel Mikhail; Clough, Roger Lee; Elliott, Julie M.; Martin, Jeffrey W.; Mowery, Daniel Michael; Celina, Mathew Christopher

    2005-11-01

    Piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes as adaptive or smart materials. Dimensional adjustments of adaptive polymer films depend on controlled charge deposition. Predicting their long-term performance requires a detailed understanding of the piezoelectric material features, expected to suffer due to space environmental degradation. Hence, the degradation and performance of PVDF and its copolymers under various stress environments expected in low Earth orbit has been reviewed and investigated. Various experiments were conducted to expose these polymers to elevated temperature, vacuum UV, {gamma}-radiation and atomic oxygen. The resulting degradative processes were evaluated. The overall materials performance is governed by a combination of chemical and physical degradation processes. Molecular changes are primarily induced via radiative damage, and physical damage from temperature and atomic oxygen exposure is evident as depoling, loss of orientation and surface erosion. The effects of combined vacuum UV radiation and atomic oxygen resulted in expected surface erosion and pitting rates that determine the lifetime of thin films. Interestingly, the piezo responsiveness in the underlying bulk material remained largely unchanged. This study has delivered a comprehensive framework for material properties and degradation sensitivities with variations in individual polymer performances clearly apparent. The results provide guidance for material selection, qualification, optimization strategies, feedback for manufacturing and processing, or alternative materials. Further material qualification should be conducted via experiments under actual space conditions.

  6. Experimental studies of adaptive structures for precision performance

    NASA Technical Reports Server (NTRS)

    Chen, G.-S.; Lurie, B. J.; Wada, B. K.

    1989-01-01

    An experimental study was made of the adaptive structure concept. Experimental data were obtained for a three-longeron, thirteen-bay truss-type test structure. This test structure can be softly suspended as well as rigidly clamped at the central bay. The load-carrying active member consists of a stack of concentric piezoelectric wafers, an eddy current displacement sensor, and a strain gage force sensor. A bridge (or compound) feedback technique developed in communication engineering is applied to the problem of active damping augmentation in adaptive structures. Using collocated force and velocity feedback around the active member, a desired output mechanical impedance can be implemented to maximize energy absorption by the active members. In addition, large gains can be implemented to linearize the active member's nonlinear behavior. Good agreements with linear finite element analysis was found for both static and dynamic structural responses. An 11 percent damping in the first bending mode was demonstrated in the closed-loop damping experiment.

  7. Adaptive optimization of reference intensity for optical coherence imaging using galvanometric mirror tilting method

    NASA Astrophysics Data System (ADS)

    Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

    2015-09-01

    Integration time and reference intensity are important factors for achieving high signal-to-noise ratio (SNR) and sensitivity in optical coherence tomography (OCT). In this context, we present an adaptive optimization method of reference intensity for OCT setup. The reference intensity is automatically controlled by tilting a beam position using a Galvanometric scanning mirror system. Before sample scanning, the OCT system acquires two dimensional intensity map with normalized intensity and variables in color spaces using false-color mapping. Then, the system increases or decreases reference intensity following the map data for optimization with a given algorithm. In our experiments, the proposed method successfully corrected the reference intensity with maintaining spectral shape, enabled to change integration time without manual calibration of the reference intensity, and prevented image degradation due to over-saturation and insufficient reference intensity. Also, SNR and sensitivity could be improved by increasing integration time with automatic adjustment of the reference intensity. We believe that our findings can significantly aid in the optimization of SNR and sensitivity for optical coherence tomography systems.

  8. Adaptive multi-stage integrators for optimal energy conservation in molecular simulations

    NASA Astrophysics Data System (ADS)

    Fernández-Pendás, Mario; Akhmatskaya, Elena; Sanz-Serna, J. M.

    2016-12-01

    We introduce a new Adaptive Integration Approach (AIA) to be used in a wide range of molecular simulations. Given a simulation problem and a step size, the method automatically chooses the optimal scheme out of an available family of numerical integrators. Although we focus on two-stage splitting integrators, the idea may be used with more general families. In each instance, the system-specific integrating scheme identified by our approach is optimal in the sense that it provides the best conservation of energy for harmonic forces. The AIA method has been implemented in the BCAM-modified GROMACS software package. Numerical tests in molecular dynamics and hybrid Monte Carlo simulations of constrained and unconstrained physical systems show that the method successfully realizes the fail-safe strategy. In all experiments, and for each of the criteria employed, the AIA is at least as good as, and often significantly outperforms the standard Verlet scheme, as well as fixed parameter, optimized two-stage integrators. In particular, for the systems where harmonic forces play an important role, the sampling efficiency found in simulations using the AIA is up to 5 times better than the one achieved with other tested schemes.

  9. An Adaptive Intelligent Integrated Lighting Control Approach for High-Performance Office Buildings

    NASA Astrophysics Data System (ADS)

    Karizi, Nasim

    An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings. This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.'s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.

  10. Perform - A performance optimizing computer program for dynamic systems subject to transient loadings

    NASA Technical Reports Server (NTRS)

    Pilkey, W. D.; Wang, B. P.; Yoo, Y.; Clark, B.

    1973-01-01

    A description and applications of a computer capability for determining the ultimate optimal behavior of a dynamically loaded structural-mechanical system are presented. This capability provides characteristics of the theoretically best, or limiting, design concept according to response criteria dictated by design requirements. Equations of motion of the system in first or second order form include incompletely specified elements whose characteristics are determined in the optimization of one or more performance indices subject to the response criteria in the form of constraints. The system is subject to deterministic transient inputs, and the computer capability is designed to operate with a large linear programming on-the-shelf software package which performs the desired optimization. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of dynamics problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.

  11. Optimizing intramuscular adaptations to aerobic exercise: effects of carbohydrate restriction and protein supplementation on mitochondrial biogenesis.

    PubMed

    Margolis, Lee M; Pasiakos, Stefan M

    2013-11-01

    Mitochondrial biogenesis is a critical metabolic adaptation to aerobic exercise training that results in enhanced mitochondrial size, content, number, and activity. Recent evidence has shown that dietary manipulation can further enhance mitochondrial adaptations to aerobic exercise training, which may delay skeletal muscle fatigue and enhance exercise performance. Specifically, studies have demonstrated that combining carbohydrate restriction (endogenous and exogenous) with a single bout of aerobic exercise potentiates the beneficial effects of exercise on markers of mitochondrial biogenesis. Additionally, studies have demonstrated that high-quality protein supplementation enhances anabolic skeletal muscle intracellular signaling and mitochondrial protein synthesis following a single bout of aerobic exercise. Mitochondrial biogenesis is stimulated by complex intracellular signaling pathways that appear to be primarily regulated by 5'AMP-activated protein kinase and p38 mitogen-activated protein kinase mediated through proliferator-activated γ receptor co-activator 1 α activation, resulting in increased mitochondrial DNA expression and enhanced skeletal muscle oxidative capacity. However, the mechanisms by which concomitant carbohydrate restriction and dietary protein supplementation modulates mitochondrial adaptations to aerobic exercise training remains unclear. This review summarizes intracellular regulation of mitochondrial biogenesis and the effects of carbohydrate restriction and protein supplementation on mitochondrial adaptations to aerobic exercise.

  12. An optimal performance control scheme for a 3D crane

    NASA Astrophysics Data System (ADS)

    Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.

    2016-01-01

    This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.

  13. Motor planning flexibly optimizes performance under uncertainty about task goals

    PubMed Central

    Wong, Aaron L.; Haith, Adrian M.

    2017-01-01

    In an environment full of potential goals, how does the brain determine which movement to execute? Existing theories posit that the motor system prepares for all potential goals by generating several motor plans in parallel. One major line of evidence for such theories is that presenting two competing goals often results in a movement intermediate between them. These intermediate movements are thought to reflect an unintentional averaging of the competing plans. However, normative theories suggest instead that intermediate movements might actually be deliberate, generated because they improve task performance over a random guessing strategy. To test this hypothesis, we vary the benefit of making an intermediate movement by changing movement speed. We find that participants generate intermediate movements only at (slower) speeds where they measurably improve performance. Our findings support the normative view that the motor system selects only a single, flexible motor plan, optimized for uncertain goals. PMID:28256513

  14. Performance comparison of polynomial representations for optimizing optical freeform systems

    NASA Astrophysics Data System (ADS)

    Brömel, A.; Gross, H.; Ochse, D.; Lippmann, U.; Ma, C.; Zhong, Y.; Oleszko, M.

    2015-09-01

    Optical systems can benefit strongly from freeform surfaces, however the choice of the right representation isn`t an easy one. Classical representations like X-Y-polynomials, as well as Zernike-polynomials are often used for such systems, but should have some disadvantage regarding their orthogonality, resulting in worse convergence and reduced quality in final results compared to newer representations like the Q-polynomials by Forbes. Additionally the supported aperture is a circle, which can be a huge drawback in case of optical systems with rectangular aperture. In this case other representations like Chebyshev-or Legendre-polynomials come into focus. There are a larger number of possibilities; however the experience with these newer representations is rather limited. Therefore in this work the focus is on investigating the performance of four widely used representations in optimizing two ambitious systems with very different properties: Three-Mirror-Anastigmat and an anamorphic System. The chosen surface descriptions offer support for circular or rectangular aperture, as well as different grades of departure from rotational symmetry. The basic shapes are for example a conic or best-fit-sphere and the polynomial set is non-, spatial or slope-orthogonal. These surface representations were chosen to evaluate the impact of these aspects on the performance optimization of the two example systems. Freeform descriptions investigated here were XY-polynomials, Zernike in Fringe representation, Q-polynomials by Forbes, as well as 2-dimensional Chebyshev-polynomials. As a result recommendations for the right choice of freeform surface representations for practical issues in the optimization of optical systems can be given.

  15. Experiences performing conceptual design optimization of transport aircraft

    NASA Technical Reports Server (NTRS)

    Arbuckle, P. D.; Sliwa, S. M.

    1984-01-01

    Optimum Preliminary Design of Transports (OPDOT) is a computer program developed at NASA Langley Research Center for evaluating the impact of new technologies upon transport aircraft. For example, it provides the capability to look at configurations which have been resized to take advantage of active controls and provide and indication of economic sensitivity to its use. Although this tool returns a conceptual design configuration as its output, it does not have the accuracy, in absolute terms, to yield satisfactory point designs for immediate use by aircraft manufacturers. However, the relative accuracy of comparing OPDOT-generated configurations while varying technological assumptions has been demonstrated to be highly reliable. Hence, OPDOT is a useful tool for ascertaining the synergistic benefits of active controls, composite structures, improved engine efficiencies and other advanced technological developments. The approach used by OPDOT is a direct numerical optimization of an economic performance index. A set of independent design variables is iterated, given a set of design constants and data. The design variables include wing geometry, tail geometry, fuselage size, and engine size. This iteration continues until the optimum performance index is found which satisfies all the constraint functions. The analyst interacts with OPDOT by varying the input parameters to either the constraint functions or the design constants. Note that the optimization of aircraft geometry parameters is equivalent to finding the ideal aircraft size, but with more degrees of freedom than classical design procedures will allow.

  16. Optimization of oar blade design for improved performance in rowing.

    PubMed

    Caplan, Nicholas; Gardner, Trevor N

    2007-11-01

    The aim of the present study was to find a more optimal blade design for rowing performance than the Big Blade, which has been shown to be less than optimal for propulsion. As well as the Big Blade, a flat Big Blade, a flat rectangular blade, and a rectangular blade with the same curvature and projected area as the Big Blade were tested in a water flume to determine their fluid dynamic characteristics at the full range of angles at which the oar blade might present itself to the water. Similarities were observed between the flat Big Blade and rectangular blades. However, the curved rectangular blade generated significantly more lift in the angle range 0-90 degrees than the curved Big Blade, although it was similar between 90 and 180 degrees. This difference was attributed to the shape of the upper and lower edges of the blade and their influence on the fluid flow around the blade. Although the influence of oar blade design on boat speed was not investigated here, the significant increases in fluid force coefficients for the curved rectangular blade suggest that this new oar blade design could elicit a practically significant improvement in rowing performance.

  17. Carbon Material Optimized Biocathode for Improving Microbial Fuel Cell Performance

    PubMed Central

    Tursun, Hairti; Liu, Rui; Li, Jing; Abro, Rashid; Wang, Xiaohui; Gao, Yanmei; Li, Yuan

    2016-01-01

    To improve the performance of microbial fuel cells (MFCs), the biocathode electrode material of double-chamber was optimized. Alongside the basic carbon fiber brush, three carbon materials namely graphite granules, activated carbon granules (ACG) and activated carbon powder, were added to the cathode-chambers to improve power generation. The result shows that the addition of carbon materials increased the amount of available electroactive microbes on the electrode surface and thus promote oxygen reduction rate, which improved the generation performance of the MFCs. The Output current (external resistance = 1000 Ω) greatly increased after addition of the three carbon materials and maximum power densities in current stable phase increased by 47.4, 166.1, and 33.5%, respectively. Additionally, coulombic efficiencies of the MFC increased by 16.3, 64.3, and 20.1%, respectively. These results show that MFC when optimized with ACG show better power generation, higher chemical oxygen demands removal rate and coulombic efficiency. PMID:26858695

  18. Performance analysis and optimization of power plants with gas turbines

    NASA Astrophysics Data System (ADS)

    Besharati-Givi, Maryam

    The gas turbine is one of the most important applications for power generation. The purpose of this research is performance analysis and optimization of power plants by using different design systems at different operation conditions. In this research, accurate efficiency calculation and finding optimum values of efficiency for design of chiller inlet cooling and blade cooled gas turbine are investigated. This research shows how it is possible to find the optimum design for different operation conditions, like ambient temperature, relative humidity, turbine inlet temperature, and compressor pressure ratio. The simulated designs include the chiller, with varied COP and fogging cooling for a compressor. In addition, the overall thermal efficiency is improved by adding some design systems like reheat and regenerative heating. The other goal of this research focuses on the blade-cooled gas turbine for higher turbine inlet temperature, and consequently, higher efficiency. New film cooling equations, along with changing film cooling effectiveness for optimum cooling air requirement at the first-stage blades, and an internal and trailing edge cooling for the second stage, are innovated for optimal efficiency calculation. This research sets the groundwork for using the optimum value of efficiency calculation, while using inlet cooling and blade cooling designs. In the final step, the designed systems in the gas cycles are combined with a steam cycle for performance improvement.

  19. Multiband RF pulses with improved performance via convex optimization.

    PubMed

    Shang, Hong; Larson, Peder E Z; Kerr, Adam; Reed, Galen; Sukumar, Subramaniam; Elkhaled, Adam; Gordon, Jeremy W; Ohliger, Michael A; Pauly, John M; Lustig, Michael; Vigneron, Daniel B

    2016-01-01

    Selective RF pulses are commonly designed with the desired profile as a low pass filter frequency response. However, for many MRI and NMR applications, the spectrum is sparse with signals existing at a few discrete resonant frequencies. By specifying a multiband profile and releasing the constraint on "don't-care" regions, the RF pulse performance can be improved to enable a shorter duration, sharper transition, or lower peak B1 amplitude. In this project, a framework for designing multiband RF pulses with improved performance was developed based on the Shinnar-Le Roux (SLR) algorithm and convex optimization. It can create several types of RF pulses with multiband magnitude profiles, arbitrary phase profiles and generalized flip angles. The advantage of this framework with a convex optimization approach is the flexible trade-off of different pulse characteristics. Designs for specialized selective RF pulses for balanced SSFP hyperpolarized (HP) (13)C MRI, a dualband saturation RF pulse for (1)H MR spectroscopy, and a pre-saturation pulse for HP (13)C study were developed and tested.

  20. A Study on the Self-Adaption Incentive Performance Salary

    NASA Astrophysics Data System (ADS)

    Zhang, Chuanming; Wang, Yang

    In project managing, the performance salary management mode is often used to motivate project managers and other similar staff to improve performance or reduce the cost. But the engineering activities who own a lot of internal and external uncertain factors can not be known by the principle. It is difficult for to develop a suitable incentive target to project managers etch. This paper thinks that the manager self master the maximum of information on engineering activities. So this paper sets up an incentive model: the project managers themselves report performance objectives; owner gives the managers reward or punishment combined with their reported performance and actual performance. The model to ensure that the project manager is only accurate self reported its results to get the maximum profit. At the same time, it cans incentive managers to improve performance or reduce the cost. This paper focuses on setting up the model, analyzing the model parameters. And cite an example analyze them.

  1. A multilevel examination of the relationships among training outcomes, mediating regulatory processes, and adaptive performance.

    PubMed

    Chen, Gilad; Thomas, Brian; Wallace, J Craig

    2005-09-01

    This study examined whether cognitive, affective-motivational, and behavioral training outcomes relate to posttraining regulatory processes and adaptive performance similarly at the individual and team levels of analysis. Longitudinal data were collected from 156 individuals composing 78 teams who were trained on and then performed a simulated flight task. Results showed that posttraining regulation processes related similarly to adaptive performance across levels. Also, regulation processes fully mediated the influences of self- and collective efficacy beliefs on individual and team adaptive performance. Finally, knowledge and skill more strongly and directly related to adaptive performance at the individual than the team level of analysis. Implications to theory and practice, limitations, and future directions are discussed.

  2. Adaptation.

    PubMed

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  3. Examining the Relationship between Learning Organization Characteristics and Change Adaptation, Innovation, and Organizational Performance

    ERIC Educational Resources Information Center

    Kontoghiorghes, Constantine; Awbre, Susan M.; Feurig, Pamela L.

    2005-01-01

    The main purpose of this exploratory study was to examine the relationship between certain learning organization characteristics and change adaptation, innovation, and bottom-line organizational performance. The following learning organization characteristics were found to be the strongest predictors of rapid change adaptation, quick product or…

  4. Performance and control of optimized shear discharges in JET

    NASA Astrophysics Data System (ADS)

    Bécoulet, A.; Eriksson, L.-G.; Baranov, Yu. F.; Borba, D. N.; Challis, C. D.; Conway, G. D.; Fuchs, V.; Gormezano, C.; Gowers, C. W.; Hawkes, N. C.; Hender, T. C.; Huysmans, G. T. A.; Joffrin, E.; Litaudon, X.; Lomas, P. J.; Maas, A.; Mayoral, M. L.; Parail, V. V.; Rimini, F. G.; Rochard, F.; Sarazin, Y.; Sips, A. C. C.; Söldner, F. X.; Zastrow, K.-D.; Zwingman, W. P.

    2000-06-01

    High performance discharges are routinely obtained on JET with low or reversed magnetic shear (s = (r/q)dq/dr), and the potential for steady state operation of such discharges is under investigation. With the use of the proper heating and fuelling, these `optimized shear' (OS) discharges exhibit an internal transport barrier (ITB), resulting in a strong peaking of the pressure profile, and thus in high fusion performance. These regimes have been extensively studied during the last (DD and DT) JET campaigns in order to promote this type of scenario as the basis for `advanced tokamak' operation. A review is given of the highest performance achieved on JET OS discharges during the last experimental campaigns, in both DD (up to 5.6 × 1016neutrons/s) and DT operation (fusion power up to 8.2 MW, ni0Ti0τE up to 1021 m-3 keV s). The role of the plasma edge is pointed out, as the power required to trigger an ITB is often higher than the H mode power threshold, leading to double barrier regimes. The presence of an H mode pedestal both modifies the ITB and induces edge bootstrap and ELM activity, which should be controlled to prolong such discharges. The operational procedure of optimization is then discussed, addressing the problems of ITB formation (power threshold, timing of the main heating phase, i.e. optimization of the target q profile, influence of the heating scheme, electron versus ion ITBs), ITB evolution (expansion of the ITB footpoint, H mode formation) and ITB termination (disruptive and/or `soft' MHD limits). Finally, the crucial problem of the route to steady state for such OS discharges is addressed, both in terms of ITB sustainment and control within the stability domain and in terms of edge pedestal control by means of impurity injection. The impurity behaviour is found, and examples of high performance discharges sustained for several energy confinement times are given (βN = 1.95, H89 = 2.3, Pfusioneq~10 MW, QDTeq~0.4 sustained for ~3 s). Extrapolation

  5. Neural network-based optimal adaptive output feedback control of a helicopter UAV.

    PubMed

    Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

    2013-07-01

    Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

  6. Adapting sensory data for multiple robots performing spill cleanup

    SciTech Connect

    Storjohann, K.; Saltzen, E.

    1990-09-01

    This paper describes a possible method of converting a single performing robot algorithm into a multiple performing robot algorithm without the need to modify previously written codes. The algorithm to be converted involves spill detection and clean up by the HERMIES-III mobile robot. In order to achieve the goal of multiple performing robots with this algorithm, two steps are taken. First, the task is formally divided into two sub-tasks, spill detection and spill clean-up, the former of which is allocated to the added performing robot, HERMIES-IIB. Second, a inverse perspective mapping, is applied to the data acquired by the new performing robot (HERMIES-IIB), allowing the data to be processed by the previously written algorithm without re-writing the code. 6 refs., 4 figs.

  7. Optimal reconstruction for closed-loop ground-layer adaptive optics with elongated spots.

    PubMed

    Béchet, Clémentine; Tallon, Michel; Tallon-Bosc, Isabelle; Thiébaut, Éric; Le Louarn, Miska; Clare, Richard M

    2010-11-01

    The design of the laser-guide-star-based adaptive optics (AO) systems for the Extremely Large Telescopes requires careful study of the issue of elongated spots produced on Shack-Hartmann wavefront sensors. The importance of a correct modeling of the nonuniformity and correlations of the noise induced by this elongation has already been demonstrated for wavefront reconstruction. We report here on the first (to our knowledge) end-to-end simulations of closed-loop ground-layer AO with laser guide stars with such an improved noise model. The results are compared with the level of performance predicted by a classical noise model for the reconstruction. The performance is studied in terms of ensquared energy and confirms that, thanks to the improved noise model, central or side launching of the lasers does not affect the performance with respect to the laser guide stars' flux. These two launching schemes also perform similarly whatever the atmospheric turbulence strength.

  8. Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

    NASA Technical Reports Server (NTRS)

    Litt, Jonathan S.

    2004-01-01

    The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control

  9. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park

    USGS Publications Warehouse

    Martin, Julien; Fackler, Paul L.; Nichols, James D.; Runge, Michael C.; McIntyre, Carol L.; Lubow, Bruce L.; McCluskie, Maggie C.; Schmutz, Joel A.

    2011-01-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles

  10. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park.

    PubMed

    Martin, Julien; Fackler, Paul L; Nichols, James D; Runge, Michael C; McIntyre, Carol L; Lubow, Bruce L; McCluskie, Maggie C; Schmutz, Joel A

    2011-04-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.

  11. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs.

    PubMed

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

    2013-12-21

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

  12. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs

    NASA Astrophysics Data System (ADS)

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Jiang Graves, Yan; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

    2013-12-01

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

  13. Adaptive λ estimation in Lagrangian rate-distortion optimization for video coding

    NASA Astrophysics Data System (ADS)

    Chen, Lulin; Garbacea, Ilie

    2006-01-01

    In this paper, adaptive Lagrangian multiplier λ estimation in Larangian R-D optimization for video coding is presented that is based on the ρ-domain linear rate model and distortion model. It yields that λ is a function of rate, distortion and coding input statistics and can be written as λ(R, D, σ2) = β(ln(σ2/D) + δ)D/R + k 0, with β, δ and k 0 as coding constants, σ2 is variance of prediction error input. λ(R, D, σ2) describes its ubiquitous relationship with coding statistics and coding input in hybrid video coding such as H.263, MPEG-2/4 and H.264/AVC. The lambda evaluation is de-coupled with quantization parameters. The proposed lambda estimation enables a fine encoder design and encoder control.

  14. Adapting to aging losses: do resources facilitate strategies of selection, compensation, and optimization in everyday functioning?

    PubMed

    Lang, Frieder R; Rieckmann, Nina; Baltes, Margret M

    2002-11-01

    Previous cross-sectional research has shown that older people who are rich in sensorimotor-cognitive and social-personality resources are better functioning in everyday life and exhibit fewer negative age differences than resource-poor adults. Longitudinal data from the Berlin Aging Study was used to examine these findings across a 4-year time interval and to compare cross-sectional indicators of adaptive everyday functioning among survivors and nonsurvivors. Apart from their higher survival rate, resource-rich older people (a) invest more social time with their family members, (b) reduce the diversity of activities within the most salient leisure domain, (c) sleep more often and longer during daytime, and (d) increase the variability of time investments across activities after 4 years. Overall, findings suggest a greater use of selection, compensation, and optimization strategies in everyday functioning among resource-rich older adults as compared with resource-poor older adults.

  15. Adaptive optimal quantization for 3D mesh representation in the spherical coordinate system

    NASA Astrophysics Data System (ADS)

    Ahn, Jeong-Hwan; Ho, Yo-Sung

    1998-12-01

    In recent days, applications using 3D models are increasing. Since the 3D model contains a huge amount of information, compression of the 3D model data is necessary for efficient storage or transmission. In this paper, we propose an adaptive encoding scheme to compress the geometry information of the 3D model. Using the Levinson-Durbin algorithm, the encoder first predicts vertex positions along a vertex spanning tree. After each prediction error is normalized, the prediction error vector of each vertex point is represented in the spherical coordinate system (r,(theta) ,(phi) ). Each r is then quantizes by an optimal uniform quantizer. A pair of each ((theta) ,(phi) ) is also successively encoded by partitioning the surface of the sphere according to the quantized value of r. The proposed scheme demonstrates improved coding efficiency by exploiting the statistical properties of r and ((theta) ,(phi) ).

  16. Exercise and Training to Optimize Functional Motor Performance in Stroke: Driving Neural Reorganization?

    PubMed Central

    Shepherd, Roberta B.

    2001-01-01

    Neurorehabilitation is increasingly taking account of scientific findings. Research areas directing stroke rehabilitation are neurophysiology; adaptability to use and activity; biomechanics; skill learning; and exercise science (task, context specificity). Understanding impairments and adaptations enables a reappraisal of interventions—for example,changes in motor control resulting from impairments (decreased descending inputs, reduced motor unit synchronization), secondary soft tissue changes (muscle length and stiffness changes) are adaptations to lesion and disuse. Changes in interventions include increasing emphasis on active exercise and task-specific training, active and passive methods of preserving muscle extensibility. Training has the potential to drive brain reorganization and to optimize functional performance. Research drives the development of training programs, and therapists are relying less on one-to-one, hands-on service delivery, making use of circuit training and group exercise and of technological advances (interactive computerized systems, treadmills) which increase time spent in active practice, Emphasis is on skill training, stressing cognitive engagement and practice, aiming to increase strength, control, skill, endurance, fitness, and social readjustment. Rehabilitation services remain slow to make the changes necessary to upgrade environments, attitudes, and rehabilitation methodologies to those shown to be more scientifically rational and for which there is evidence of effectiveness. PMID:11530883

  17. Importance of eccentric actions in performance adaptations to resistance training

    NASA Technical Reports Server (NTRS)

    Dudley, Gary A.; Miller, Bruce J.; Buchanan, Paul; Tesch, Per A.

    1991-01-01

    The importance of eccentric (ecc) muscle actions in resistance training for the maintenance of muscle strength and mass in hypogravity was investigated in experiments in which human subjects, divided into three groups, were asked to perform four-five sets of 6 to 12 repetitions (rep) per set of three leg press and leg extension exercises, 2 days each weeks for 19 weeks. One group, labeled 'con', performed each rep with only concentric (con) actions, while group con/ecc with performed each rep with only ecc actions; the third group, con/con, performed twice as many sets with only con actions. Control subjects did not train. It was found that resistance training wih both con and ecc actions induced greater increases in muscle strength than did training with only con actions.

  18. Monte Carlo modelling of multiconjugate adaptive optics performance on the European Extremely Large Telescope

    NASA Astrophysics Data System (ADS)

    Basden, A. G.

    2015-11-01

    The performance of a wide-field adaptive optics system depends on input design parameters. Here we investigate the performance of a multiconjugate adaptive optics system design for the European Extremely Large Telescope, using an end-to-end Monte Carlo adaptive optics simulation tool, DASP (Durham adaptive optics simulation platform). We consider parameters such as the number of laser guide stars, sodium layer depth, wavefront sensor pixel scale, number of deformable mirrors (DMs), mirror conjugation and actuator pitch. We provide potential areas where costs savings can be made, and investigate trade-offs between performance and cost. We conclude that a six-laser guide star system using three DMs seems to be a sweet spot for performance and cost compromise.

  19. Anticipatory Control of Motion-to-Force Transitions With the Fingertips Adapts Optimally to Task Difficulty

    PubMed Central

    Cianchetti, Flor A.

    2010-01-01

    Moving our fingertips toward objects to produce well-directed forces immediately upon contact is fundamental to dexterous manipulation. This apparently simple motion-to-force transition in fact involves a time-critical, predictive switch in control strategy. Given that dexterous manipulation must accommodate multiple mechanical conditions, we investigated whether and how this transition adapts to task difficulty. Eight adults (19–39 yr) produced ramps of isometric vertical fingertip force against a rigid surface immediately following a tapping motion. By changing target surface friction and size, we defined an easier (sandpaper, 11 mm diam) versus a more difficult (polished steel, 5 mm diam) task. As in prior work, we assembled fine-wire electromyograms from all seven muscles of the index finger into a seven-dimensional vector defining the full muscle coordination pattern—and quantified its temporal evolution as its alignment with a reference coordination pattern vector for steady-state force production. As predicted by numerical optimizations to neuromuscular delays, our empirical and sigmoidal nonlinear regression analyses show that the coordination pattern transitions begin sooner for the more difficult tasks than for the easier tasks (∼120 ms, P < 0.02, and ∼115 ms, P < 0.015, respectively) and that the coordination pattern transition in alignment is well represented by a sigmoidal trend (R^2 > 0.7 in most cases). Importantly, the force vector following contact had smaller directional error (P < 0.02) for the more difficult task even though the transition in coordination pattern was less stereotypical and uniform than for the easier task. These adaptations of transition strategy to task difficulty are compatible with an optimization to counteract neuromuscular delays and noise to enable this fundamental element of dexterous manipulation. PMID:19889857

  20. Anticipatory control of motion-to-force transitions with the fingertips adapts optimally to task difficulty.

    PubMed

    Cianchetti, Flor A; Valero-Cuevas, Francisco J

    2010-01-01

    Moving our fingertips toward objects to produce well-directed forces immediately upon contact is fundamental to dexterous manipulation. This apparently simple motion-to-force transition in fact involves a time-critical, predictive switch in control strategy. Given that dexterous manipulation must accommodate multiple mechanical conditions, we investigated whether and how this transition adapts to task difficulty. Eight adults (19-39 yr) produced ramps of isometric vertical fingertip force against a rigid surface immediately following a tapping motion. By changing target surface friction and size, we defined an easier (sandpaper, 11 mm diam) versus a more difficult (polished steel, 5 mm diam) task. As in prior work, we assembled fine-wire electromyograms from all seven muscles of the index finger into a seven-dimensional vector defining the full muscle coordination pattern-and quantified its temporal evolution as its alignment with a reference coordination pattern vector for steady-state force production. As predicted by numerical optimizations to neuromuscular delays, our empirical and sigmoidal nonlinear regression analyses show that the coordination pattern transitions begin sooner for the more difficult tasks than for the easier tasks ( approximately 120 ms, P < 0.02, and approximately 115 ms, P < 0.015, respectively) and that the coordination pattern transition in alignment is well represented by a sigmoidal trend (R;2 > 0.7 in most cases). Importantly, the force vector following contact had smaller directional error (P < 0.02) for the more difficult task even though the transition in coordination pattern was less stereotypical and uniform than for the easier task. These adaptations of transition strategy to task difficulty are compatible with an optimization to counteract neuromuscular delays and noise to enable this fundamental element of dexterous manipulation.

  1. Real-time optimal adaptation for planetary geometry and texture: 4-8 tile hierarchies.

    PubMed

    Hwa, Lok M; Duchaineau, Mark A; Joy, Kenneth I

    2005-01-01

    The real-time display of huge geometry and imagery databases involves view-dependent approximations, typically through the use of precomputed hierarchies that are selectively refined at runtime. A classic motivating problem is terrain visualization in which planetary databases involving billions of elevation and color values are displayed on PC graphics hardware at high frame rates. This paper introduces a new diamond data structure for the basic selective-refinement processing, which is a streamlined method of representing the well-known hierarchies of right triangles that have enjoyed much success in real-time, view-dependent terrain display. Regular-grid tiles are proposed as the payload data per diamond for both geometry and texture. The use of 4-8 grid refinement and coarsening schemes allows level-of-detail transitions that are twice as gradual as traditional quadtree-based hierarchies, as well as very high-quality low-pass filtering compared to subsampling-based hierarchies. An out-of-core storage organization is introduced based on Sierpinski indices per diamond, along with a tile preprocessing framework based on fine-to-coarse, same-level, and coarse-to-fine gathering operations. To attain optimal frame-to-frame coherence and processing-order priorities, dual split and merge queues are developed similar to the Realtime Optimally Adapting Meshes (ROAM) Algorithm, as well as an adaptation of the ROAM frustum culling technique. Example applications of lake-detection and procedural terrain generation demonstrate the flexibility of the tile processing framework.

  2. Optimizing small wind turbine performance in battery charging applications

    SciTech Connect

    Drouilhet, S; Muljadi, E; Holz, R; Gevorgian, V

    1995-05-01

    Many small wind turbine generators (10 kW or less) consist of a variable speed rotor driving a permanent magnet synchronous generator (alternator). One application of such wind turbines is battery charging, in which the generator is connected through a rectifier to a battery bank. The wind turbine electrical interface is essentially the same whether the turbine is part of a remote power supply for telecommunications, a standalone residential power system, or a hybrid village power system, in short, any system in which the wind generator output is rectified and fed into a DC bus. Field experience with such applications has shown that both the peak power output and the total energy capture of the wind turbine often fall short of expectations based on rotor size and generator rating. In this paper, the authors present a simple analytical model of the typical wind generator battery charging system that allows one to calculate actual power curves if the generator and rotor properties are known. The model clearly illustrates how the load characteristics affect the generator output. In the second part of this paper, the authors present four approaches to maximizing energy capture from wind turbines in battery charging applications. The first of these is to determine the optimal battery bank voltage for a given WTG. The second consists of adding capacitors in series with the generator. The third approach is to place an optimizing DC/DC voltage converter between the rectifier and the battery bank. The fourth is a combination of the series capacitors and the optimizing voltage controller. They also discuss both the limitations and the potential performance gain associated with each of the four configurations.

  3. Economic performance of irrigation capacity development to adapt to climate in the American Southwest

    NASA Astrophysics Data System (ADS)

    Ward, Frank A.; Crawford, Terry L.

    2016-09-01

    Growing demands for food security to feed increasing populations worldwide have intensified the search for improved performance of irrigation, the world's largest water user. These challenges are raised in the face of climate variability and from growing environmental demands. Adaptation measures in irrigated agriculture include fallowing land, shifting cropping patterns, increased groundwater pumping, reservoir storage capacity expansion, and increased production of risk-averse crops. Water users in the Gila Basin headwaters of the U.S. Lower Colorado Basin have faced a long history of high water supply fluctuations producing low-valued defensive cropping patterns. To date, little research grade analysis has investigated economically viable measures for irrigation development to adjust to variable climate. This gap has made it hard to inform water resource policy decisions on workable measures to adapt to climate in the world's dry rural areas. This paper's contribution is to illustrate, formulate, develop, and apply a new methodology to examine the economic performance from irrigation capacity improvements in the Gila Basin of the American Southwest. An integrated empirical optimization model using mathematical programming is developed to forecast cropping patterns and farm income under two scenarios (1) status quo without added storage capacity and (2) with added storage capacity in which existing barriers to development of higher valued crops are dissolved. We find that storage capacity development can lead to a higher valued portfolio of irrigation production systems as well as more sustained and higher valued farm livelihoods. Results show that compared to scenario (1), scenario (2) increases regional farm income by 30%, in which some sub regions secure income gains exceeding 900% compared to base levels. Additional storage is most economically productive when institutional and technical constraints facing irrigated agriculture are dissolved. Along with

  4. Aircraft design for mission performance using nonlinear multiobjective optimization methods

    NASA Technical Reports Server (NTRS)

    Dovi, Augustine R.; Wrenn, Gregory A.

    1990-01-01

    A new technique which converts a constrained optimization problem to an unconstrained one where conflicting figures of merit may be simultaneously considered was combined with a complex mission analysis system. The method is compared with existing single and multiobjective optimization methods. A primary benefit from this new method for multiobjective optimization is the elimination of separate optimizations for each objective, which is required by some optimization methods. A typical wide body transport aircraft is used for the comparative studies.

  5. Optimization of an adaptive nonlinear filter for the analysis of nystagmus.

    PubMed

    Engelken, E J; Stevens, K W; Enderle, J D

    1991-01-01

    An adaptive nonlinear digital filter has been designed for the analysis of an eye-movement signal called nystagmus. Nystagmus is a bi-phasic signal consisting of a sequence of tracking eye movements called "slow-phase" interspersed with brief, high-velocity refixation movements called "fast-phase." The objective of the analysis is to separate the nystagmus signal into its fast- and slow-phase components. Specifically, the goal is to produce an evenly sampled estimate of slow-phase velocity (SPV) and an estimate of the peak fast-phase velocity. Classically this has been done using pattern recognition methods that exploit the fact that the fast-phase is a relatively short duration, high-velocity movement compared to the slow-phase. Unfortunately, these velocity and duration differences do not reliably separate the slow- and fast-phases under all conditions, especially when the signal is noisy. We have designed and built an adaptive nonlinear digital filter that easily outperforms the more complex pattern recognition algorithms. This new filter, called an Adaptive Asymmetrically Trimmed-Mean (AATM) filter, works under the assumption that, on the average, the eyes spend more time in slow-phase than in fast-phase. Thus, in any given data segment, most of the data samples are slow-phase samples. By analyzing the amplitude distribution of the data samples in the segment we can determine which of these samples are slow-phase. We used computer generated nystagmus signals contaminated with 3 levels of noise to evaluate the filter. The filter parameters were then optimized using Monte Carlo procedures producing an extremely robust analysis method.

  6. SAXO: the extreme adaptive optics system of SPHERE (I) system overview and global laboratory performance

    NASA Astrophysics Data System (ADS)

    Sauvage, Jean-Francois; Fusco, Thierry; Petit, Cyril; Costille, Anne; Mouillet, David; Beuzit, Jean-Luc; Dohlen, Kjetil; Kasper, Markus; Suarez, Marcos; Soenke, Christian; Baruffolo, Andrea; Salasnich, Bernardo; Rochat, Sylvain; Fedrigo, Enrico; Baudoz, Pierre; Hugot, Emmanuel; Sevin, Arnaud; Perret, Denis; Wildi, Francois; Downing, Mark; Feautrier, Philippe; Puget, Pascal; Vigan, Arthur; O'Neal, Jared; Girard, Julien; Mawet, Dimitri; Schmid, Hans Martin; Roelfsema, Ronald

    2016-04-01

    The direct imaging of exoplanet is a leading field of today's astronomy. The photons coming from the planet carry precious information on the chemical composition of its atmosphere. The second-generation instrument, Spectro-Polarimetric High contrast Exoplanet Research (SPHERE), dedicated to detection, photometry and spectral characterization of Jovian-like planets, is now in operation on the European very large telescope. This instrument relies on an extreme adaptive optics (XAO) system to compensate for atmospheric turbulence as well as for internal errors with an unprecedented accuracy. We demonstrate the high level of performance reached by the SPHERE XAO system (SAXO) during the assembly integration and test (AIT) period. In order to fully characterize the instrument quality, two AIT periods have been mandatory. In the first phase at Observatoire de Paris, the performance of SAXO itself was assessed. In the second phase at IPAG Grenoble Observatory, the operation of SAXO in interaction with the overall instrument has been optimized. In addition to the first two phases, a final check has been performed after the reintegration of the instrument at Paranal Observatory, in the New Integration Hall before integration at the telescope focus. The final performance aimed by the SPHERE instrument with the help of SAXO is among the highest Strehl ratio pretended for an operational instrument (90% in H band, 43% in V band in a realistic turbulence r0, and wind speed condition), a limit R magnitude for loop closure at 15, and a robustness to high wind speeds. The full-width at half-maximum reached by the instrument is 40 mas for infrared in H band and unprecedented 18.5 mas in V band.

  7. Optimizing the separation performance of a gas centrifuge

    NASA Astrophysics Data System (ADS)

    Wood, H. G.

    1997-11-01

    Gas centrifuges were originally developed for the enrichment of U^235 from naturally occurring uranium for the purpose of providing fuel for nuclear power reactors and material for nuclear weapons. This required the separation of a binary mixture composed of U^235 and U^238. Since the end of the cold war, a surplus of enriched uranium exists on the world market, but many centrifuge plants exist in numerous countries. These circumstances together with the growing demand for stable isotopes for chemical and physical research and in medical science has led to the exploration of alternate applications of gas centrifuge technology. In order to acieve these multi-component separations, existing centrifuges must be modified or new centrifuges must be designed. In either case, it is important to have models of the internal flow fields to predict the separation performance and algorithms to seek the optimal operating conditions of the centrifuges. Here, we use the Onsager pancake model of the internal flow field, and we present an optimization strategy which exploits a similarity parameter in the pancake model. Numerical examples will be presented.

  8. Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing electro chemical machining process

    NASA Astrophysics Data System (ADS)

    Teimouri, Reza; Sohrabpoor, Hamed

    2013-12-01

    Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

  9. Parallel performance optimizations on unstructured mesh-based simulations

    DOE PAGES

    Sarje, Abhinav; Song, Sukhyun; Jacobsen, Douglas; ...

    2015-06-01

    This paper addresses two key parallelization challenges the unstructured mesh-based ocean modeling code, MPAS-Ocean, which uses a mesh based on Voronoi tessellations: (1) load imbalance across processes, and (2) unstructured data access patterns, that inhibit intra- and inter-node performance. Our work analyzes the load imbalance due to naive partitioning of the mesh, and develops methods to generate mesh partitioning with better load balance and reduced communication. Furthermore, we present methods that minimize both inter- and intranode data movement and maximize data reuse. Our techniques include predictive ordering of data elements for higher cache efficiency, as well as communication reduction approaches.more » We present detailed performance data when running on thousands of cores using the Cray XC30 supercomputer and show that our optimization strategies can exceed the original performance by over 2×. Additionally, many of these solutions can be broadly applied to a wide variety of unstructured grid-based computations.« less

  10. Calibration Modeling Methodology to Optimize Performance for Low Range Applications

    NASA Technical Reports Server (NTRS)

    McCollum, Raymond A.; Commo, Sean A.; Parker, Peter A.

    2010-01-01

    Calibration is a vital process in characterizing the performance of an instrument in an application environment and seeks to obtain acceptable accuracy over the entire design range. Often, project requirements specify a maximum total measurement uncertainty, expressed as a percent of full-scale. However in some applications, we seek to obtain enhanced performance at the low range, therefore expressing the accuracy as a percent of reading should be considered as a modeling strategy. For example, it is common to desire to use a force balance in multiple facilities or regimes, often well below its designed full-scale capacity. This paper presents a general statistical methodology for optimizing calibration mathematical models based on a percent of reading accuracy requirement, which has broad application in all types of transducer applications where low range performance is required. A case study illustrates the proposed methodology for the Mars Entry Atmospheric Data System that employs seven strain-gage based pressure transducers mounted on the heatshield of the Mars Science Laboratory mission.

  11. Performance optimized, small structurally integrated ion thruster system

    NASA Technical Reports Server (NTRS)

    Hyman, J., Jr.

    1973-01-01

    A 5-cm structurally integrated ion thruster has been developed for attitude control and stationkeeping of synchronous satellites. As optimized with a conventional ion extraction system, the system demonstrates a thrust T = 0.47 mlb at a beam voltage of 1600 V, total mass efficiency of 76%, and electrical efficiency of 56%. Under the subject contract effort, no significant performance change was noted for operation with two dimensional electrostatic thrust-vectoring grids. Structural integrity with the vectoring grids was demonstrated for shock (+ or - 30 G), sinusoidal (9 G), and random (19.9 G rms) accelerations. System envelope is 31.2 cm long by 13.4 cm flange bolt circle, with a mass of 9.0 Kg, including 6.8 Kg mercury propellant.

  12. Medical Device Risk Management For Performance Assurance Optimization and Prioritization.

    PubMed

    Gaamangwe, Tidimogo; Babbar, Vishvek; Krivoy, Agustina; Moore, Michael; Kresta, Petr

    2015-01-01

    Performance assurance (PA) is an integral component of clinical engineering medical device risk management. For that reason, the clinical engineering (CE) community has made concerted efforts to define appropriate risk factors and develop quantitative risk models for efficient data processing and improved PA program operational decision making. However, a common framework that relates the various processes of a quantitative risk system does not exist. This article provides a perspective that focuses on medical device quality and risk-based elements of the PA program, which include device inclusion/exclusion, schedule optimization, and inspection prioritization. A PA risk management framework is provided, and previous quantitative models that have contributed to the advancement of PA risk management are examined. A general model for quantitative risk systems is proposed, and further perspective on possible future directions in the area of PA technology is also provided.

  13. Optimizing FGS2R2 Performance with the AMA

    NASA Astrophysics Data System (ADS)

    Nelan, Edmund

    2009-07-01

    Ths proposal satisfies SMOV4 AD OTA/FGSS-054. S-curves with PUPIL and F583W will be obtained at selected locations within the FGS2R2 FOV during SMOV4. These data will be will be used to adjust the AMA so as to align the HST pupil onto the interferometer's Koesters prisms. The final AMA position will be set to produce an acceptable set of S-curves across the FGS2R2 FOV. The AMA will be adjusted using CCL/instructions from the ground. It is intended that this proposal executes during the SMOV4 BEA and will require several {on the order of 4} iterations to achieve optimal interferometric performance.

  14. Optimizing timing performance of silicon photomultiplier-based scintillation detectors

    PubMed Central

    Yeom, Jung Yeol; Vinke, Ruud

    2013-01-01

    Precise timing resolution is crucial for applications requiring photon time-of-flight (ToF) information such as ToF positron emission tomography (PET). Silicon photomultipliers (SiPM) for PET, with their high output capacitance, are known to require custom preamplifiers to optimize timing performance. In this paper, we describe simple alternative front-end electronics based on a commercial low-noise RF preamplifier and methods that have been implemented to achieve excellent timing resolution. Two radiation detectors with L(Y)SO scintillators coupled to Hamamatsu SiPMs (MPPC S10362–33-050C) and front-end electronics based on an RF amplifier (MAR-3SM+), typically used for wireless applications that require minimal additional circuitry, have been fabricated. These detectors were used to detect annihilation photons from a Ge-68 source and the output signals were subsequently digitized by a high speed oscilloscope for offline processing. A coincident resolving time (CRT) of 147 ± 3 ps FWHM and 186 ± 3 ps FWHM with 3 × 3 × 5 mm3 and with 3 × 3 × 20 mm3 LYSO crystal elements were measured, respectively. With smaller 2 × 2 × 3 mm3 LSO crystals, a CRT of 125 ± 2 ps FWHM was achieved with slight improvement to 121 ± 3 ps at a lower temperature (15°C). Finally, with the 20 mm length crystals, a degradation of timing resolution was observed for annihilation photon interactions that occur close to the photosensor compared to shallow depth-of-interaction (DOI). We conclude that commercial RF amplifiers optimized for noise, besides their ease of use, can produce excellent timing resolution comparable to best reported values acquired with custom readout electronics. On the other hand, as timing performance degrades with increasing photon DOI, a head-on detector configuration will produce better CRT than a side-irradiated setup for longer crystals. PMID:23369872

  15. Optimal configuration of redundant inertial sensors for navigation and FDI performance.

    PubMed

    Shim, Duk-Sun; Yang, Cheol-Kwan

    2010-01-01

    This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method.

  16. Optimal Configuration of Redundant Inertial Sensors for Navigation and FDI Performance

    PubMed Central

    Shim, Duk-Sun; Yang, Cheol-Kwan

    2010-01-01

    This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method. PMID:22163563

  17. Enabling the extended compact genetic algorithm for real-parameter optimization by using adaptive discretization.

    PubMed

    Chen, Ying-ping; Chen, Chao-Hong

    2010-01-01

    An adaptive discretization method, called split-on-demand (SoD), enables estimation of distribution algorithms (EDAs) for discrete variables to solve continuous optimization problems. SoD randomly splits a continuous interval if the number of search points within the interval exceeds a threshold, which is decreased at every iteration. After the split operation, the nonempty intervals are assigned integer codes, and the search points are discretized accordingly. As an example of using SoD with EDAs, the integration of SoD and the extended compact genetic algorithm (ECGA) is presented and numerically examined. In this integration, we adopt a local search mechanism as an optional component of our back end optimization engine. As a result, the proposed framework can be considered as a memetic algorithm, and SoD can potentially be applied to other memetic algorithms. The numerical experiments consist of two parts: (1) a set of benchmark functions on which ECGA with SoD and ECGA with two well-known discretization methods: the fixed-height histogram (FHH) and the fixed-width histogram (FWH) are compared; (2) a real-world application, the economic dispatch problem, on which ECGA with SoD is compared to other methods. The experimental results indicate that SoD is a better discretization method to work with ECGA. Moreover, ECGA with SoD works quite well on the economic dispatch problem and delivers solutions better than the best known results obtained by other methods in existence.

  18. Inference for Optimal Dynamic Treatment Regimes using an Adaptive m-out-of-n Bootstrap Scheme

    PubMed Central

    Chakraborty, Bibhas; Laber, Eric B.; Zhao, Yingqi

    2013-01-01

    Summary A dynamic treatment regime consists of a set of decision rules that dictate how to individualize treatment to patients based on available treatment and covariate history. A common method for estimating an optimal dynamic treatment regime from data is Q-learning which involves nonsmooth operations of the data. This nonsmoothness causes standard asymptotic approaches for inference like the bootstrap or Taylor series arguments to breakdown if applied without correction. Here, we consider the m-out-of-n bootstrap for constructing confidence intervals for the parameters indexing the optimal dynamic regime. We propose an adaptive choice of m and show that it produces asymptotically correct confidence sets under fixed alternatives. Furthermore, the proposed method has the advantage of being conceptually and computationally much more simple than competing methods possessing this same theoretical property. We provide an extensive simulation study to compare the proposed method with currently available inference procedures. The results suggest that the proposed method delivers nominal coverage while being less conservative than alternatives. The proposed methods are implemented in the qLearn R-package and have been made available on the Comprehensive R-Archive Network (http://cran.r-project.org/). Analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study is used as an illustrative example. PMID:23845276

  19. Adaptive design optimization: a mutual information-based approach to model discrimination in cognitive science.

    PubMed

    Cavagnaro, Daniel R; Myung, Jay I; Pitt, Mark A; Kujala, Janne V

    2010-04-01

    Discriminating among competing statistical models is a pressing issue for many experimentalists in the field of cognitive science. Resolving this issue begins with designing maximally informative experiments. To this end, the problem to be solved in adaptive design optimization is identifying experimental designs under which one can infer the underlying model in the fewest possible steps. When the models under consideration are nonlinear, as is often the case in cognitive science, this problem can be impossible to solve analytically without simplifying assumptions. However, as we show in this letter, a full solution can be found numerically with the help of a Bayesian computational trick derived from the statistics literature, which recasts the problem as a probability density simulation in which the optimal design is the mode of the density. We use a utility function based on mutual information and give three intuitive interpretations of the utility function in terms of Bayesian posterior estimates. As a proof of concept, we offer a simple example application to an experiment on memory retention.

  20. Adaptive track scheduling to optimize concurrency and vectorization in GeantV

    DOE PAGES

    Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; ...

    2015-05-22

    The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The modelmore » has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. Lastly, this work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.« less

  1. Adaptive track scheduling to optimize concurrency and vectorization in GeantV

    SciTech Connect

    Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; Brun, R.; Canal, P.; Carminati, F.; Licht, J. C. De Fine; Duhem, L.; Elvira, V. D.; Gheata, A.; Jun, S. Y.; Lima, G.; Novak, M.; Sehgal, R.; Shadura, O.; Wenzel, S.

    2015-05-22

    The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. Lastly, this work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.

  2. Development of an adaptive hp-version finite element method for computational optimal control

    NASA Technical Reports Server (NTRS)

    Hodges, Dewey H.; Warner, Michael S.

    1994-01-01

    In this research effort, the usefulness of hp-version finite elements and adaptive solution-refinement techniques in generating numerical solutions to optimal control problems has been investigated. Under NAG-939, a general FORTRAN code was developed which approximated solutions to optimal control problems with control constraints and state constraints. Within that methodology, to get high-order accuracy in solutions, the finite element mesh would have to be refined repeatedly through bisection of the entire mesh in a given phase. In the current research effort, the order of the shape functions in each element has been made a variable, giving more flexibility in error reduction and smoothing. Similarly, individual elements can each be subdivided into many pieces, depending on the local error indicator, while other parts of the mesh remain coarsely discretized. The problem remains to reduce and smooth the error while still keeping computational effort reasonable enough to calculate time histories in a short enough time for on-board applications.

  3. Adaptive track scheduling to optimize concurrency and vectorization in GeantV

    NASA Astrophysics Data System (ADS)

    Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; Brun, R.; Canal, P.; Carminati, F.; De Fine Licht, J. C.; Duhem, L.; Elvira, V. D.; Gheata, A.; Jun, S. Y.; Lima, G.; Novak, M.; Sehgal, R.; Shadura, O.; Wenzel, S.

    2015-05-01

    The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. This work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.

  4. Teachers Adapt Their Instruction According to Students' Academic Performance

    ERIC Educational Resources Information Center

    Nurmi, Jari-Erik; Viljaranta, Jaana; Tolvanen, Asko; Aunola, Kaisa

    2012-01-01

    This study examined the extent to which a student's academic performance in first grade contributes to the active instruction given by a teacher to a particular student. To investigate this, 105 first graders were tested in mathematics and reading in the fall and spring of their first school year. At the same time points, their teachers filled in…

  5. The Adapted Dance Process: Planning, Partnering, and Performing

    ERIC Educational Resources Information Center

    Block, Betty A.; Johnson, Peggy V.

    2011-01-01

    This article contains specific planning, partnering, and performing techniques for fully integrating dancers with special needs into a dance pedagogy program. Each aspect is discussed within the context of the domains of learning. Fundamental partnering strategies are related to each domain as part of the integration process. The authors recommend…

  6. Tuning of patient-specific deformable models using an adaptive evolutionary optimization strategy.

    PubMed

    Vidal, Franck P; Villard, Pierre-Frédéric; Lutton, Evelyne

    2012-10-01

    We present and analyze the behavior of an evolutionary algorithm designed to estimate the parameters of a complex organ behavior model. The model is adaptable to account for patient's specificities. The aim is to finely tune the model to be accurately adapted to various real patient datasets. It can then be embedded, for example, in high fidelity simulations of the human physiology. We present here an application focused on respiration modeling. The algorithm is automatic and adaptive. A compound fitness function has been designed to take into account for various quantities that have to be minimized. The algorithm efficiency is experimentally analyzed on several real test cases: 1) three patient datasets have been acquired with the "breath hold" protocol, and 2) two datasets corresponds to 4-D CT scans. Its performance is compared with two traditional methods (downhill simplex and conjugate gradient descent): a random search and a basic real-valued genetic algorithm. The results show that our evolutionary scheme provides more significantly stable and accurate results.

  7. Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment.

    PubMed

    Kraatz, Miriam; Sears, Lindsay E; Coberley, Carter R; Pope, James E

    2016-08-01

    Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284-290).

  8. Dynamically optimized Wang-Landau sampling with adaptive trial moves and modification factors.

    PubMed

    Koh, Yang Wei; Lee, Hwee Kuan; Okabe, Yutaka

    2013-11-01

    The density of states of continuous models is known to span many orders of magnitudes at different energies due to the small volume of phase space near the ground state. Consequently, the traditional Wang-Landau sampling which uses the same trial move for all energies faces difficulties sampling the low-entropic states. We developed an adaptive variant of the Wang-Landau algorithm that very effectively samples the density of states of continuous models across the entire energy range. By extending the acceptance ratio method of Bouzida, Kumar, and Swendsen such that the step size of the trial move and acceptance rate are adapted in an energy-dependent fashion, the random walker efficiently adapts its sampling according to the local phase space structure. The Wang-Landau modification factor is also made energy dependent in accordance with the step size, enhancing the accumulation of the density of states. Numerical simulations show that our proposed method performs much better than the traditional Wang-Landau sampling.

  9. Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment

    PubMed Central

    Kraatz, Miriam; Coberley, Carter R.; Pope, James E.

    2016-01-01

    Abstract Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284–290) PMID:26674396

  10. A Phase I/II adaptive design to determine the optimal treatment regimen from a set of combination immunotherapies in high-risk melanoma.

    PubMed

    Wages, Nolan A; Slingluff, Craig L; Petroni, Gina R

    2015-03-01

    In oncology, vaccine-based immunotherapy often investigates regimens that demonstrate minimal toxicity overall and higher doses may not correlate with greater immune response. Rather than determining the maximum tolerated dose, the goal of the study becomes locating the optimal biological dose, which is defined as a safe dose demonstrating the greatest immunogenicity, based on some predefined measure of immune response. Incorporation of adjuvants, new or optimized peptide vaccines, and combining vaccines with immune modulators may enhance immune response, with the aim of improving clinical response. Innovative dose escalation strategies are needed to establish the safety and immunogenicity of new immunologic combinations. We describe the implementation of an adaptive design for identifying the optimal treatment strategy in a multi-site, FDA-approved, phase I/II trial of a novel vaccination approach using long-peptides plus TLR agonists for resected stage IIB-IV melanoma. Operating characteristics of the design are demonstrated under various possible true scenarios via simulation studies. Overall performance indicates that the design is a practical Phase I/II adaptive method for use with combined immunotherapy agents. The simulation results demonstrate the method's ability to effectively recommend optimal regimens in a high percentage of trials with manageable sample sizes. The numerical results presented in this work include the type of simulation information that aid review boards in understanding design performance, such as average sample size and frequency of early trial termination, which we hope will augment early-phase trial design in cancer immunotherapy.

  11. Estimated performance of an adaptive trailing-edge device aimed at reducing fuel consumption on a medium-size aircraft

    NASA Astrophysics Data System (ADS)

    Diodati, Gianluca; Concilio, Antonio; Ricci, Sergio; De Gaspari, Alessandro; Huvelin, Fabien; Dumont, Antoine; Godard, Jean-Luc

    2013-03-01

    This paper deals with the estimation of the performance of a medium-size aircraft (3-hour flight range) equipped with an adaptive trailing edge device (ATED) that runs span-wise from the wing root in the flap zone and extends chord-wise for a limited percentage of the MAC. Computations are calculated referring to the full wing and do not refer to the complete aircraft configuration. Aerodynamic computations, taking into account ideal shapes, have been performed by using both Euler and Navier- Stokes method in order to extract the wing polars for the reference and the optimal wing, implementing an ATED, deflected upwards and downwards. A comparison of the achieved results is discussed. Considering the shape domain, a suitable interpolation procedure has been set up to obtain the wing polar envelop of the adaptive wing, intended as the set of "best" values, picked by each different polar. At the end, the performances of the complete reference and adaptive wing are computed and compared for a symmetric, centered, leveled and steady cruise flight for a medium size aircraft. A significant fuel burn reduction estimate or, alternatively, an increased range capability is demonstrated, with margins of further improvements. The research leading to these results has gratefully received funding from the European Union Seventh Framework Programme (FP7/2007- 2013) under Grant Agreement n° 284562.

  12. Co-Adaptive Aiding and Automation Enhance Operator Performance

    DTIC Science & Technology

    2013-03-01

    Wilson for providing insightful comments on the design and analysis, and Dr. Joel Warm for many comments that have improved this manuscript. Lastly...weapon type was not counted as success. Participants could use the mouse to designate waypoints and direct RPAs away from pre-planned routes but were...lower on Day 3 than that observed with no aiding even though there was no significant difference in performance. The present work was not designed

  13. Modeling Reduced Human Performance as a Complex Adaptive System

    DTIC Science & Technology

    2003-09-01

    impacts human performance in general. It has a degrading effect (Belenky 1994) that can, in certain circumstances, be counteracted with noise ( Loeb 1986...going into design details that have just been described. D. RHPM AND FERBER’S FORMULA Jacques Ferber describes the major elements of a multi...Vocabulary, and its Relation to Organizations." Emergence 1(1): 110-127. Loeb , M. (1986). Noise and Human Efficiency. Chichester, UK, John Wiley

  14. Threshold Region Performance Prediction for Adaptive Matched Field Processing Localization

    DTIC Science & Technology

    2007-11-02

    significant non-local estimation errors at low signal-to-noise ratios ( SNRs )-errors not modeled by traditional localization measures such as the Cramer...as a function of SNR , for apertures and environments of interest. Particular attention will be given to the "threshold SNR " (below which localization...performance degrades rapidly due to global estimation errors) and to the minimum SNR required to achieve acceptable range/depth localization. Initial

  15. The Astronaut-Athlete: Optimizing Human Performance in Space.

    PubMed

    Hackney, Kyle J; Scott, Jessica M; Hanson, Andrea M; English, Kirk L; Downs, Meghan E; Ploutz-Snyder, Lori L

    2015-12-01

    It is well known that long-duration spaceflight results in deconditioning of neuromuscular and cardiovascular systems, leading to a decline in physical fitness. On reloading in gravitational environments, reduced fitness (e.g., aerobic capacity, muscular strength, and endurance) could impair human performance, mission success, and crew safety. The level of fitness necessary for the performance of routine and off-nominal terrestrial mission tasks remains an unanswered and pressing question for scientists and flight physicians. To mitigate fitness loss during spaceflight, resistance and aerobic exercise are the most effective countermeasure available to astronauts. Currently, 2.5 h·d, 6-7 d·wk is allotted in crew schedules for exercise to be performed on highly specialized hardware on the International Space Station (ISS). Exercise hardware provides up to 273 kg of loading capability for resistance exercise, treadmill speeds between 0.44 and 5.5 m·s, and cycle workloads from 0 and 350 W. Compared to ISS missions, future missions beyond low earth orbit will likely be accomplished with less vehicle volume and power allocated for exercise hardware. Concomitant factors, such as diet and age, will also affect the physiologic responses to exercise training (e.g., anabolic resistance) in the space environment. Research into the potential optimization of exercise countermeasures through use of dietary supplementation, and pharmaceuticals may assist in reducing physiological deconditioning during long-duration spaceflight and have the potential to enhance performance of occupationally related astronaut tasks (e.g., extravehicular activity, habitat construction, equipment repairs, planetary exploration, and emergency response).

  16. Cyclone performance and optimization: First quarterly progress report

    SciTech Connect

    Leith, D.

    1987-12-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is impoortant because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. The project is on or ahead of schedule. During this time, the laboratory scale equipment necessary for this project has been constructed and used to make measurements of the gas flow pattern within cyclones. Tangential gas velocities for a matrix of eleven different cuclones and operating conditions have been measured. For each different test condition tangential velocities over a wide range of axial and radial positions have been measured. In addition, the literature search that began while the proposal for this work was written has been continued. The computer and printer necessary for modeling the experimental results have been ordered and received. 1 fig.

  17. Performance Optimization of the Gasdynamic Mirror Propulsion System

    NASA Technical Reports Server (NTRS)

    Emrich, William J., Jr.; Kammash, Terry

    1999-01-01

    Nuclear fusion appears to be a most promising concept for producing extremely high specific impulse rocket engines. Engines such as these would effectively open up the solar system to human exploration and would virtually eliminate launch window restrictions. A preliminary vehicle sizing and mission study was performed based on the conceptual design of a Gasdynamic Mirror (GDM) fusion propulsion system. This study indicated that the potential specific impulse for this engine is approximately 142,000 sec. with about 22,100 N of thrust using a deuterium-tritium fuel cycle. The engine weight inclusive of the power conversion system was optimized around an allowable engine mass of 1500 Mg assuming advanced superconducting magnets and a Field Reversed Configuration (FRC) end plug at the mirrors. The vehicle habitat, lander, and structural weights are based on a NASA Mars mission study which assumes the use of nuclear thermal propulsion' Several manned missions to various planets were analyzed to determine fuel requirements and launch windows. For all fusion propulsion cases studied, the fuel weight remained a minor component of the total system weight regardless of when the missions commenced. In other words, the use of fusion propulsion virtually eliminates all mission window constraints and effectively allows unlimited manned exploration of the entire solar system. It also mitigates the need to have a large space infrastructure which would be required to support the transfer of massive amounts of fuel and supplies to lower a performing spacecraft.

  18. Global optimization strategies for high-performance controls

    SciTech Connect

    Hartman, T.B.

    1995-12-31

    The current trend of extending digital heating, ventilating, and air-conditioning (HVAC) and lighting controls to terminal devices has had an enormous impact on the role of global strategies for energy and comfort optimization. In some respects optimization algorithms are becoming simpler because more complete information about conditions throughout the building is now available to the control system. However, the task of analyzing this information often adds a new layer of complexity to the process of developing these algorithms. Also, the extension of direct digital control (DDC) to terminal devices offers new energy and comfort control optimization opportunities that require additional global optimization algorithms. This paper discusses the changing role of global optimization strategies as the integration of DDC systems is extended to terminal equipment. The discussion offers suggestions about how the development of more powerful global optimization strategies needs to be considered in the design of the mechanical equipment. Specifically, four areas of global optimization are discussed: optimization of variable-air-volume (VAV) airflow, optimization of lighting level via dimming ballasts, optimization of space temperature setpoint, and optimization of chiller and boiler operation. In each of these categories, a control philosophy employing global optimization is discussed, sample control algorithms are provided, and a discussion of the implication of these new control opportunities on the design of the mechanical components is included.

  19. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    SciTech Connect

    Mohan Kelkar

    2002-09-30

    The main objectives of the proposed study are as follows: (1) To understand and evaluate an unusual primary oil production mechanism which results in decreasing (retrograde) oil cut (ROC) behavior as reservoir pressure declines. (2) To improve calculations of initial oil in place so as to determine the economic feasibility of completing and producing a well. (3) To optimize the location of new wells based on understanding of geological and petrophysical properties heterogeneities. (4) To evaluate various secondary recovery techniques for oil reservoirs producing from fractured formations. (5) To enhance the productivity of producing wells by using new completion techniques. These objectives are important for optimizing field performance from West Carney Field located in Lincoln County, Oklahoma. The field, which was discovered in 1980, produces from Hunton Formation in a shallow-shelf carbonate reservoir. The early development in the field was sporadic. Many of the initial wells were abandoned due to high water production and constraints in surface facilities for disposing excess produced water. The field development began in earnest in 1995 by Altex Resources. They had recognized that production from this field was only possible if large volumes of water can be disposed. Being able to dispose large amounts of water, Altex aggressively drilled several producers. With few exceptions, all these wells exhibited similar characteristics. The initial production indicated trace amount of oil and gas with mostly water as dominant phase. As the reservoir was depleted, the oil cut eventually improved, making the overall production feasible. The decreasing oil cut (ROC) behavior has not been well understood. However, the field has been subjected to intense drilling activity because of prior success of Altex Resources. In this work, we will investigate the primary production mechanism by conducting several core flood experiments. After collecting cores from representative

  20. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  1. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    SciTech Connect

    Mohan Kelkar

    2003-01-01

    The main objectives of the proposed study are as follows: (1) To understand and evaluate an unusual primary oil production mechanism which results in decreasing (retrograde) oil cut (ROC) behavior as reservoir pressure declines. (2) To improve calculations of initial oil in place so as to determine the economic feasibility of completing and producing a well. (3) To optimize the location of new wells based on understanding of geological and petrophysical properties heterogeneities. (4) To evaluate various secondary recovery techniques for oil reservoirs producing from fractured formations. (5) To enhance the productivity of producing wells by using new completion techniques. These objectives are important for optimizing field performance from West Carney Field located in Lincoln County, Oklahoma. The field, which was discovered in 1980, produces from Hunton Formation in a shallow-shelf carbonate reservoir. The early development in the field was sporadic. Many of the initial wells were abandoned due to high water production and constraints in surface facilities for disposing excess produced water. The field development began in earnest in 1995 by Altex Resources. They had recognized that production from this field was only possible if large volumes of water can be disposed. Being able to dispose large amounts of water, Altex aggressively drilled several producers. With few exceptions, all these wells exhibited similar characteristics. The initial production indicated trace amount of oil and gas with mostly water as dominant phase. As the reservoir was depleted, the oil cut eventually improved, making the overall production feasible. The decreasing oil cut (ROC) behavior has not been well understood. However, the field has been subjected to intense drilling activity because of prior success of Altex Resources. In this work, we will investigate the primary production mechanism by conducting several core flood experiments. After collecting cores from representative

  2. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    SciTech Connect

    Mohan Kelkar

    2001-10-01

    The main objectives of the proposed study are as follows: (1) To understand and evaluate an unusual primary oil production mechanism which results in decreasing (retrograde) oil cut (ROC) behavior as reservoir pressure declines. (2) To develop better, produced water, disposal techniques so as to minimize lifting costs, surface separation costs and water disposal costs. (3) To improve calculations of initial oil in place so as to determine the economic feasibility of completing and producing a well. (4) To optimize the location of new wells based on understanding of geological and petrophysical properties heterogeneities. (5) To evaluate various secondary recovery techniques for oil reservoirs producing from fractured formations. (6) To enhance the productivity of producing wells by using new completion techniques. These objectives are important for optimizing field performance from West Carney Field located in Lincoln County, Oklahoma. The field, which was discovered in 1980, produces from Hunton Formation in a shallow-shelf carbonate reservoir. The early development in the field was sporadic. Many of the initial wells were abandoned due to high water production and constraints in surface facilities for disposing excess produced water. The field development began in earnest in 1995 by Altex Resources. They had recognized that production from this field was only possible if large volumes of water can be disposed. Being able to dispose large amounts of water, Altex aggressively drilled several producers. With few exceptions, all these wells exhibited similar characteristics. The initial production indicated trace amount of oil and gas with mostly water as dominant phase. As the reservoir was depleted, the oil cut eventually improved, making the overall production feasible. The decreasing oil cut (ROC) behavior has not been well understood. However, the field has been subjected to intense drilling activity because of prior success of Altex Resources. In this work, we

  3. Performing aggressive code optimization with an ability to rollback changes made by the aggressive optimizations

    DOEpatents

    Gschwind, Michael K

    2013-07-23

    Mechanisms for aggressively optimizing computer code are provided. With these mechanisms, a compiler determines an optimization to apply to a portion of source code and determines if the optimization as applied to the portion of source code will result in unsafe optimized code that introduces a new source of exceptions being generated by the optimized code. In response to a determination that the optimization is an unsafe optimization, the compiler generates an aggressively compiled code version, in which the unsafe optimization is applied, and a conservatively compiled code version in which the unsafe optimization is not applied. The compiler stores both versions and provides them for execution. Mechanisms are provided for switching between these versions during execution in the event of a failure of the aggressively compiled code version. Moreover, predictive mechanisms are provided for predicting whether such a failure is likely.

  4. A optimized context-based adaptive binary arithmetic coding algorithm in progressive H.264 encoder

    NASA Astrophysics Data System (ADS)

    Xiao, Guang; Shi, Xu-li; An, Ping; Zhang, Zhao-yang; Gao, Ge; Teng, Guo-wei

    2006-05-01

    Context-based Adaptive Binary Arithmetic Coding (CABAC) is a new entropy coding method presented in H.264/AVC that is highly efficient in video coding. In the method, the probability of current symbol is estimated by using the wisely designed context model, which is adaptive and can approach to the statistic characteristic. Then an arithmetic coding mechanism largely reduces the redundancy in inter-symbol. Compared with UVLC method in the prior standard, CABAC is complicated but efficiently reduce the bit rate. Based on thorough analysis of coding and decoding methods of CABAC, This paper proposed two methods, sub-table method and stream-reuse methods, to improve the encoding efficiency implemented in H.264 JM code. In JM, the CABAC function produces bits one by one of every syntactic element. Multiplication operating times after times in the CABAC function lead to it inefficient.The proposed algorithm creates tables beforehand and then produce every bits of syntactic element. In JM, intra-prediction and inter-prediction mode selection algorithm with different criterion is based on RDO(rate distortion optimization) model. One of the parameter of the RDO model is bit rate that is produced by CABAC operator. After intra-prediction or inter-prediction mode selection, the CABAC stream is discard and is recalculated to output stream. The proposed Stream-reuse algorithm puts the stream in memory that is created in mode selection algorithm and reuses it in encoding function. Experiment results show that our proposed algorithm can averagely speed up 17 to 78 MSEL higher speed for QCIF and CIF sequences individually compared with the original algorithm of JM at the cost of only a little memory space. The CABAC was realized in our progressive h.264 encoder.

  5. Improving transient performance of adaptive control architectures using frequency-limited system error dynamics

    NASA Astrophysics Data System (ADS)

    Yucelen, Tansel; De La Torre, Gerardo; Johnson, Eric N.

    2014-11-01

    Although adaptive control theory offers mathematical tools to achieve system performance without excessive reliance on dynamical system models, its applications to safety-critical systems can be limited due to poor transient performance and robustness. In this paper, we develop an adaptive control architecture to achieve stabilisation and command following of uncertain dynamical systems with improved transient performance. Our framework consists of a new reference system and an adaptive controller. The proposed reference system captures a desired closed-loop dynamical system behaviour modified by a mismatch term representing the high-frequency content between the uncertain dynamical system and this reference system, i.e., the system error. In particular, this mismatch term allows the frequency content of the system error dynamics to be limited, which is used to drive the adaptive controller. It is shown that this key feature of our framework yields fast adaptation without incurring high-frequency oscillations in the transient performance. We further show the effects of design parameters on the system performance, analyse closeness of the uncertain dynamical system to the unmodified (ideal) reference system, discuss robustness of the proposed approach with respect to time-varying uncertainties and disturbances, and make connections to gradient minimisation and classical control theory. A numerical example is provided to demonstrate the efficacy of the proposed architecture.

  6. Performance optimization for doubly fed wind power generation systems

    SciTech Connect

    Bhowmik, S.; Spee, R.; Enslin, J.H.R.

    1999-08-01

    Significant variation of the resource kinetic energy, in the form of wind speed, results in substantially reduced energy capture in a fixed-speed wind turbine. In order to increase the wind energy capture in the turbine, variable-speed generation (VSG) strategies have been proposed and implemented. However, that requires an expensive ac/ac power converter, which increases the capital investment significantly. Consequently, doubly fed systems have been proposed to reduce the size of the power converter and, thereby, the associated cost. Additionally, in doubly fed systems, as a fixed operating point (power and speed), power flow can be regulated between the two winding systems on the machine. This feature can by utilized to essentially minimize losses in the machine associated with the given operating point or achieve other desired performance enhancements. In this paper, a brushless doubly fed machine (BDFM) is utilized to develop a VSG wind power generator. The VSG controller employs a wind-speed-estimation-based maximum power point tracker and a heuristic-model-based maximum efficiency point tracker to optimize the power output of the system. The controller has been verified for efficacy on a 1.5-kW laboratory VSG wind generator. The strategy is applicable to all doubly fed configurations, including conventional wound-rotor induction machines, Scherbius cascades, BDFM's and doubly fed reluctance machines.

  7. Materials Testing and Performance Optimization for the SAMURAI-TPC

    NASA Astrophysics Data System (ADS)

    Long, K. D.; Lynch, W. G.; Barney, J.; Chajecki, Z.; Estee, J.; Shane, R.; Tangwanchareon, S.; Tsang, M. B.; Yurkon, J.

    2012-10-01

    The SAMURAI time-projection chamber (TPC) will be used to make measurements of pion spectra from heavy ion collisions at RIBF in Japan. Such research provides an opportunity to study supra-saturation density neutron-rich matter in the laboratory, and is critical to understanding the structure of neutron stars. It will provide a complete, 3D picture of the ionization deposited in a gas volume, from which particle types and momenta can be determined. The gas-containment volume is composed of surfaces of aluminum and plastic, as well as halogen-free printed circuit board. During multiplication of the ionized electrons at the anode wire plane of the TPC, UV photons are produced. These cause unwanted discharges when they interact with oxidized aluminum surfaces, which have low work functions. This problem can be addressed by application of a suitable conductive paint or epoxy. Paints were investigated to insure they did not contain any materials capable of inhibiting the performance of the detector gas. These investigations were cross-checked by tests carried out using an existing BRAHMS-TPC. Details on these tests and the materials chosen will be shown. The design and optimization of the gating grid, used to limit data collection to triggered events, will also be discussed.

  8. Development of a real-time transport performance optimization methodology

    NASA Technical Reports Server (NTRS)

    Gilyard, Glenn

    1996-01-01

    The practical application of real-time performance optimization is addressed (using a wide-body transport simulation) based on real-time measurements and calculation of incremental drag from forced response maneuvers. Various controller combinations can be envisioned although this study used symmetric outboard aileron and stabilizer. The approach is based on navigation instrumentation and other measurements found on state-of-the-art transports. This information is used to calculate winds and angle of attack. Thrust is estimated from a representative engine model as a function of measured variables. The lift and drag equations are then used to calculate lift and drag coefficients. An expression for drag coefficient, which is a function of parasite drag, induced drag, and aileron drag, is solved from forced excitation response data. Estimates of the parasite drag, curvature of the aileron drag variation, and minimum drag aileron position are produced. Minimum drag is then obtained by repositioning the symmetric aileron. Simulation results are also presented which evaluate the affects of measurement bias and resolution.

  9. Performance benefits of adaptive, multimicrophone, interference-canceling systems in everyday environments

    NASA Astrophysics Data System (ADS)

    Desloge, Joseph G.; Zimmer, Martin J.; Zurek, Patrick M.

    2004-05-01

    Adaptive multimicrophone systems are currently used for a variety of noise-cancellation applications (such as hearing aids) to preserve signals arriving from a particular (target) direction while canceling other (jammer) signals in the environment. Although the performance of these systems is known to degrade with increasing reverberation, there are few measurements of adaptive performance in everyday reverberant environments. In this study, adaptive performance was compared to that of a simple, nonadaptive cardioid microphone to determine a measure of adaptive benefit. Both systems used recordings (at an Fs of 22050 Hz) from the same two omnidirectional microphones, which were separated by 1 cm. Four classes of environment were considered: outdoors, household, parking garage, and public establishment. Sources were either environmental noises (e.g., household appliances, restaurant noise) or a controlled noise source. In all situations, no target was present (i.e., all signals were jammers) to obtain maximal jammer cancellation. Adaptive processing was based upon the Griffiths-Jim generalized sidelobe canceller using filter lengths up to 400 points. Average intelligibility-weighted adaptive benefit levels at a source distance of 1 m were, at most, 1.5 dB for public establishments, 2 dB for household rooms and the parking garage, and 3 dB outdoors. [Work supported by NIOSH.

  10. The emergence of performance trade-offs during local adaptation: insights from experimental evolution.

    PubMed

    Bono, Lisa M; Smith, Leno B; Pfennig, David W; Burch, Christina L

    2016-12-28

    Environmental heterogeneity is considered a general explanation for phenotypic diversification, particularly when heterogeneity causes populations to diverge via local adaptation. Performance trade-offs, such as those stemming from antagonistic pleiotropy, are thought to contribute to the maintenance of diversity in this scenario. Specifically, alleles that promote adaptation in one environment are expected to promote maladaptation in alternative environments. Contrary to this expectation, however, alleles that underlie locally adaptive traits often fail to exhibit fitness costs in alternative environments. Here, we attempt to explain this paradox by reviewing the results of experimental evolution studies, including a new one of our own, that examined the evolution of trade-offs during adaptation to homogeneous versus heterogeneous environments. We propose that when pleiotropic effects vary, whether or not trade-offs emerge among diverging populations will depend critically on ecology. For example, adaptation to a locally homogeneous environment is more likely to occur by alleles that are antagonistically pleiotropic than adaptation to a locally heterogeneous environment, simply because selection is blind to costs associated with environments that are not experienced locally. Our literature review confirmed the resulting prediction that performance trade-offs were more likely to evolve during selection in homogeneous than heterogeneous environments. The nature of the environmental heterogeneity (spatial versus temporal) and the length of the experiment also contributed in predictable ways to the likelihood that performance trade-offs evolved.

  11. Fast simulated annealing and adaptive Monte Carlo sampling based parameter optimization for dense optical-flow deformable image registration of 4DCT lung anatomy

    NASA Astrophysics Data System (ADS)

    Dou, Tai H.; Min, Yugang; Neylon, John; Thomas, David; Kupelian, Patrick; Santhanam, Anand P.

    2016-03-01

    Deformable image registration (DIR) is an important step in radiotherapy treatment planning. An optimal input registration parameter set is critical to achieve the best registration performance with the specific algorithm. Methods In this paper, we investigated a parameter optimization strategy for Optical-flow based DIR of the 4DCT lung anatomy. A novel fast simulated annealing with adaptive Monte Carlo sampling algorithm (FSA-AMC) was investigated for solving the complex non-convex parameter optimization problem. The metric for registration error for a given parameter set was computed using landmark-based mean target registration error (mTRE) between a given volumetric image pair. To reduce the computational time in the parameter optimization process, a GPU based 3D dense optical-flow algorithm was employed for registering the lung volumes. Numerical analyses on the parameter optimization for the DIR were performed using 4DCT datasets generated with breathing motion models and open-source 4DCT datasets. Results showed that the proposed method efficiently estimated the optimum parameters for optical-flow and closely matched the best registration parameters obtained using an exhaustive parameter search method.

  12. Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization.

    PubMed

    Niu, Liyong; Zhang, Di

    2015-01-01

    Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly.

  13. Optimal rejection of multiplicative noise via adaptive shrinkage of undecimated wavelet coefficients

    NASA Astrophysics Data System (ADS)

    Alparone, Luciano; Anghele, Nicola; Argenti, Fabrizio

    2001-12-01

    In this paper speckle reduction is approached as a Wiener-like filtering performed in the wavelet domain by means of an adaptive shrinkage of the detail coefficients of an undecimated decomposition. The amplitude of each coefficient is divided by the variance ratio of the noisy coefficient to the noise-free one. All the above quantities are analytically calculated from the speckled image, the speckle variance, and the wavelet filters. On the test image Lenna corrupted by synthetic speckle, the proposed method outperforms Kuan's LLMMSE filtering by almost 3 dB SNR. Experiments carried out on true and synthetic speckled images demonstrate that the visual quality of the results is excellent in terms of both background smoothing and preservation of edge sharpness and textures. The absence of decimation in the wavelet decomposition avoids the typical ringing impairments produced by critically-subsampled wavelet-based denoising.

  14. Novel L1 neural network adaptive control architecture with guaranteed transient performance.

    PubMed

    Cao, Chengyu; Hovakimyan, Naira

    2007-07-01

    In this paper, we present a novel neural network (NN) adaptive control architecture with guaranteed transient performance. With this new architecture, both input and output signals of an uncertain nonlinear system follow a desired linear system during the transient phase, in addition to stable tracking. This new architecture uses a low-pass filter in the feedback loop, which consequently enables to enforce the desired transient performance by increasing the adaptation gain. For the guaranteed transient performance of both input and output signals of the uncertain nonlinear system, the L1 gain of a cascaded system, comprised of the low-pass filter and the closed-loop desired reference model, is required to be less than the inverse of the Lipschitz constant of the unknown nonlinearities in the system. The tools from this paper can be used to develop a theoretically justified verification and validation framework for NN adaptive controllers. Simulation results illustrate the theoretical findings.

  15. Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions

    PubMed Central

    Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

    2011-01-01

    Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots. PMID:21980274

  16. Stochastic optimization framework (SOF) for computer-optimized design, engineering, and performance of multi-dimensional systems and processes

    NASA Astrophysics Data System (ADS)

    Fink, Wolfgang

    2008-04-01

    Many systems and processes, both natural and artificial, may be described by parameter-driven mathematical and physical models. We introduce a generally applicable Stochastic Optimization Framework (SOF) that can be interfaced to or wrapped around such models to optimize model outcomes by effectively "inverting" them. The Visual and Autonomous Exploration Systems Research Laboratory (http://autonomy.caltech.edu edu) at the California Institute of Technology (Caltech) has long-term experience in the optimization of multi-dimensional systems and processes. Several examples of successful application of a SOF are reviewed and presented, including biochemistry, robotics, device performance, mission design, parameter retrieval, and fractal landscape optimization. Applications of a SOF are manifold, such as in science, engineering, industry, defense & security, and reconnaissance/exploration. Keywords: Multi-parameter optimization, design/performance optimization, gradient-based steepest-descent methods, local minima, global minimum, degeneracy, overlap parameter distribution, fitness function, stochastic optimization framework, Simulated Annealing, Genetic Algorithms, Evolutionary Algorithms, Genetic Programming, Evolutionary Computation, multi-objective optimization, Pareto-optimal front, trade studies )

  17. Impact of In-Service Training and Staff Development on Workers' Job Performance and Optimal Productivity in Public Secondary Schools in Osun State, Nigeria

    ERIC Educational Resources Information Center

    Fejoh, Johnson; Faniran, Victoria Loveth

    2016-01-01

    This study investigated the impact of in-service training and staff development on workers' job performance and optimal productivity in public secondary schools in Osun State, Nigeria. The study used the ex-post-facto research design. Three research questions and three hypotheses were generated and tested using questionnaire items adapted from…

  18. Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

    PubMed Central

    Lee, Chaewoo

    2014-01-01

    The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862

  19. Integer-linear-programing optimization in scalable video multicast with adaptive modulation and coding in wireless networks.

    PubMed

    Lee, Dongyul; Lee, Chaewoo

    2014-01-01

    The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

  20. Performance bounds on micro-Doppler estimation and adaptive waveform design using OFDM signals

    NASA Astrophysics Data System (ADS)

    Sen, Satyabrata; Barhen, Jacob; Glover, Charles W.

    2014-05-01

    We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Craḿer-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.

  1. Performance Bounds on Micro-Doppler Estimation and Adaptive Waveform Design Using OFDM Signals

    SciTech Connect

    Sen, Satyabrata; Barhen, Jacob; Glover, Charles Wayne

    2014-01-01

    We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Cram er-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.

  2. Performance Enhancing Diets and the PRISE Protocol to Optimize Athletic Performance

    PubMed Central

    Arciero, Paul J.; Ward, Emery

    2015-01-01

    The training regimens of modern-day athletes have evolved from the sole emphasis on a single fitness component (e.g., endurance athlete or resistance/strength athlete) to an integrative, multimode approach encompassing all four of the major fitness components: resistance (R), interval sprints (I), stretching (S), and endurance (E) training. Athletes rarely, if ever, focus their training on only one mode of exercise but instead routinely engage in a multimode training program. In addition, timed-daily protein (P) intake has become a hallmark for all athletes. Recent studies, including from our laboratory, have validated the effectiveness of this multimode paradigm (RISE) and protein-feeding regimen, which we have collectively termed PRISE. Unfortunately, sports nutrition recommendations and guidelines have lagged behind the PRISE integrative nutrition and training model and therefore limit an athletes' ability to succeed. Thus, it is the purpose of this review to provide a clearly defined roadmap linking specific performance enhancing diets (PEDs) with each PRISE component to facilitate optimal nourishment and ultimately optimal athletic performance. PMID:25949823

  3. Performance Enhancing Diets and the PRISE Protocol to Optimize Athletic Performance.

    PubMed

    Arciero, Paul J; Miller, Vincent J; Ward, Emery

    2015-01-01

    The training regimens of modern-day athletes have evolved from the sole emphasis on a single fitness component (e.g., endurance athlete or resistance/strength athlete) to an integrative, multimode approach encompassing all four of the major fitness components: resistance (R), interval sprints (I), stretching (S), and endurance (E) training. Athletes rarely, if ever, focus their training on only one mode of exercise but instead routinely engage in a multimode training program. In addition, timed-daily protein (P) intake has become a hallmark for all athletes. Recent studies, including from our laboratory, have validated the effectiveness of this multimode paradigm (RISE) and protein-feeding regimen, which we have collectively termed PRISE. Unfortunately, sports nutrition recommendations and guidelines have lagged behind the PRISE integrative nutrition and training model and therefore limit an athletes' ability to succeed. Thus, it is the purpose of this review to provide a clearly defined roadmap linking specific performance enhancing diets (PEDs) with each PRISE component to facilitate optimal nourishment and ultimately optimal athletic performance.

  4. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

    PubMed Central

    Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R.; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

    2016-01-01

    A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

  5. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.

    PubMed

    Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

    2016-09-09

    A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm.

  6. SWAT system performance predictions. Project report. [SWAT (Short-Wavelength Adaptive Techniques)

    SciTech Connect

    Parenti, R.R.; Sasiela, R.J.

    1993-03-10

    In the next phase of Lincoln Laboratory's SWAT (Short-Wavelength Adaptive Techniques) program, the performance of a 241-actuator adaptive-optics system will be measured using a variety of synthetic-beacon geometries. As an aid in this experimental investigation, a detailed set of theoretical predictions has also been assembled. The computational tools that have been applied in this study include a numerical approach in which Monte-Carlo ray-trace simulations of accumulated phase error are developed, and an analytical analysis of the expected system behavior. This report describes the basis of these two computational techniques and compares their estimates of overall system performance. Although their regions of applicability tend to be complementary rather than redundant, good agreement is usually obtained when both sets of results can be derived for the same engagement scenario.... Adaptive optics, Phase conjugation, Atmospheric turbulence Synthetic beacon, Laser guide star.

  7. Optimizing Partial Credit Algorithms to Predict Student Performance

    ERIC Educational Resources Information Center

    Ostrow, Korinn; Donnelly, Chistopher; Heffernan, Neil

    2015-01-01

    As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…

  8. Adaptation of a Fast Optimal Interpolation Algorithm to the Mapping of Oceangraphic Data

    NASA Technical Reports Server (NTRS)

    Menemenlis, Dimitris; Fieguth, Paul; Wunsch, Carl; Willsky, Alan

    1997-01-01

    A fast, recently developed, multiscale optimal interpolation algorithm has been adapted to the mapping of hydrographic and other oceanographic data. This algorithm produces solution and error estimates which are consistent with those obtained from exact least squares methods, but at a small fraction of the computational cost. Problems whose solution would be completely impractical using exact least squares, that is, problems with tens or hundreds of thousands of measurements and estimation grid points, can easily be solved on a small workstation using the multiscale algorithm. In contrast to methods previously proposed for solving large least squares problems, our approach provides estimation error statistics while permitting long-range correlations, using all measurements, and permitting arbitrary measurement locations. The multiscale algorithm itself, published elsewhere, is not the focus of this paper. However, the algorithm requires statistical models having a very particular multiscale structure; it is the development of a class of multiscale statistical models, appropriate for oceanographic mapping problems, with which we concern ourselves in this paper. The approach is illustrated by mapping temperature in the northeastern Pacific. The number of hydrographic stations is kept deliberately small to show that multiscale and exact least squares results are comparable. A portion of the data were not used in the analysis; these data serve to test the multiscale estimates. A major advantage of the present approach is the ability to repeat the estimation procedure a large number of times for sensitivity studies, parameter estimation, and model testing. We have made available by anonymous Ftp a set of MATLAB-callable routines which implement the multiscale algorithm and the statistical models developed in this paper.

  9. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    NASA Astrophysics Data System (ADS)

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E.; Lo, Yeh-Chi

    2016-04-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as  -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  10. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    PubMed Central

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

    2017-01-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as −0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients. PMID:27008349

  11. A zonal computational procedure adapted to the optimization of two-dimensional thrust augmentor inlets

    NASA Technical Reports Server (NTRS)

    Lund, T. S.; Tavella, D. A.; Roberts, L.

    1985-01-01

    A viscous-inviscid interaction methodology based on a zonal description of the flowfield is developed as a mean of predicting the performance of two-dimensional thrust augmenting ejectors. An inviscid zone comprising the irrotational flow about the device is patched together with a viscous zone containing the turbulent mixing flow. The inviscid region is computed by a higher order panel method, while an integral method is used for the description of the viscous part. A non-linear, constrained optimization study is undertaken for the design of the inlet region. In this study, the viscous-inviscid analysis is complemented with a boundary layer calculation to account for flow separation from the walls of the inlet region. The thrust-based Reynolds number as well as the free stream velocity are shown to be important parameters in the design of a thrust augmentor inlet.

  12. Performance investigation of multigrid optimization for DNS-based optimal control problems

    NASA Astrophysics Data System (ADS)

    Nita, Cornelia; Vandewalle, Stefan; Meyers, Johan

    2016-11-01

    Optimal control theory in Direct Numerical Simulation (DNS) or Large-Eddy Simulation (LES) of turbulent flow involves large computational cost and memory overhead for the optimization of the controls. In this context, the minimization of the cost functional is typically achieved by employing gradient-based iterative methods such as quasi-Newton, truncated Newton or non-linear conjugate gradient. In the current work, we investigate the multigrid optimization strategy (MGOpt) in order to speed up the convergence of the damped L-BFGS algorithm for DNS-based optimal control problems. The method consists in a hierarchy of optimization problems defined on different representation levels aiming to reduce the computational resources associated with the cost functional improvement on the finest level. We examine the MGOpt efficiency for the optimization of an internal volume force distribution with the goal of reducing the turbulent kinetic energy or increasing the energy extraction in a turbulent wall-bounded flow; problems that are respectively related to drag reduction in boundary layers, or energy extraction in large wind farms. Results indicate that in some cases the multigrid optimization method requires up to a factor two less DNS and adjoint DNS than single-grid damped L-BFGS. The authors acknowledge support from OPTEC (OPTimization in Engineering Center of Excellence, KU Leuven, Grant No PFV/10/002).

  13. Self Adapted Testing as Formative Assessment: Effects of Feedback and Scoring on Engagement and Performance

    ERIC Educational Resources Information Center

    Arieli-Attali, Meirav

    2016-01-01

    This dissertation investigated the feasibility of self-adapted testing (SAT) as a formative assessment tool with the focus on learning. Under two different orientation goals--to excel on a test (performance goal) or to learn from the test (learning goal)--I examined the effect of different scoring rules provided as interactive feedback, on test…

  14. Restricted and Adaptive Masculine Gender Performance in White Gay College Men

    ERIC Educational Resources Information Center

    Anderson-Martinez, Richard; Vianden, Jörg

    2014-01-01

    This article presents the results of a qualitative exploration of the performance of masculine gender identities in six gay male students enrolled at a master's comprehensive public institution in the Midwest. This article builds on the work of Laker and Davis (2011) and Rankin (2005). The findings indicate participants adapted their gender…

  15. Adaptive Effects on Locomotion Performance Following Exposure to a Rotating Virtual Environment

    NASA Technical Reports Server (NTRS)

    Mulavara, A. P.; Richards, J. T.; Marshburn, A. M.; Bucello, R.; Bloomberg, J. J.

    2003-01-01

    adaptive generalization. The purpose of this study was to determine if adaptive modification in locomotor performance could be achieved by viewing simulated self-motion in a passive-immersive virtual ' environment over a prolonged period during treadmill locomotion.

  16. Optimized performance for neutron interrogation to detect SNM

    SciTech Connect

    Slaughter, D R; Asztalos, S J; Biltoft, P J; Church, J A; Descalle, M; Hall, J M; Luu, T C; Manatt, D R; Mauger, G J; Norman, E B; Petersen, D C; Pruet, J A; Prussin, S G

    2007-02-14

    A program of simulations and validating experiments was utilized to evaluate a concept for neutron interrogation of commercial cargo containers that would reliably detect special nuclear material (SNM). The goals were to develop an interrogation system capable of detecting a 5 kg solid sphere of high-enriched uranium (HEU) even when deeply embedded in commercial cargo. Performance goals included a minimum detection probability, P{sub d} {ge} 95%, a maximum occurrence of false positive indications, P{sub fA} {le} 0.001, and maximum scan duration of t {le} 1 min. The conditions necessary to meet these goals were demonstrated in experimental measurements even when the SNM is deeply buried in any commercial cargo, and are projected to be met successfully in the most challenging cases of steel or hydrocarbons at areal density {rho}L {le} 150 g/cm{sup 2}. Optimal performance was obtained with a collimated ({Delta}{Theta} = {+-} 15{sup o}) neutron beam at energy E{sub n} = 7 MeV produced by the D(d,n) reaction with the deuteron energy E{sub d} = 4 MeV. Two fission product signatures are utilized to uniquely identify SNM, including delayed neutrons detected in a large array of polyethylene moderated 3He proportional counters and high energy {beta}-delayed fission product {gamma}-radiation detected in a large array of 61 x 61 x 25 cm{sup 3} plastic scintillators. The latter detectors are nearly blind to normal terrestrial background radiation by setting an energy threshold on the detection at E{sub min} {ge} 3 MeV. Detection goals were attained with a low beam current (I{sub d} = 15-65 {micro}A) source up to {rho}L = 75 g/cm{sup 2} utilizing long irradiations, T = 30 sec, and long counting times, t = 30-100 sec. Projecting to a higher beam current, I{sub d} {ge} 600 {micro}A and larger detector array the detection and false alarm goals would be attained even with intervening cargo overburden as large as {rho}L {le} 150 g/cm{sup 2}. The latter cargo thickness corresponds to

  17. Optimizing Airborne Networking Performance with Cross-Layer Design Approach

    DTIC Science & Technology

    2009-06-01

    b. ABSTRACT U c. THIS PAGE U 19b. TELEPHONE NUMBER (Include area code ) N/A Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std...the link layer must adapt to the changes, by increasing the transmit power or using a better coding scheme. This would temporarily solve the problem...transport of compressed video. Video standards, such as MPEG [2] and H.263 [3], use motion- compensated predictive (MCP) coding to reduce the temporal

  18. A new multiobjective performance criterion used in PID tuning optimization algorithms

    PubMed Central

    Sahib, Mouayad A.; Ahmed, Bestoun S.

    2015-01-01

    In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions. PMID:26843978

  19. A new multiobjective performance criterion used in PID tuning optimization algorithms.

    PubMed

    Sahib, Mouayad A; Ahmed, Bestoun S

    2016-01-01

    In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions.

  20. EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

    PubMed

    Ahirwal, M K; Kumar, Anil; Singh, G K

    2013-01-01

    This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

  1. Recent performance of the normal incident x-ray telescope with adaptive optics

    NASA Astrophysics Data System (ADS)

    Kitamoto, S.; Ishii, R.; Nukamori, S.; Imai, K.; Mochida, A.; Sato, S.; Ohgi, Y.; Yoshida, Y.; Hoshino, A.

    2016-09-01

    We report recent results of the performance measurement of our X-ray telescope with adaptive optics. The telescope is designed to use the 13.5nm EUV with the Mo/Si multilayers, making a normal incident optics. The primary mirror is 80mm in its diameter and the focal length of 2m. The deformable mirror is controlled by measuring a wave-front of an optical laser. Effects of a difference between the light paths from the reference and from an object are examined. The angular resolution is measured with optical light and we confirm almost diffraction limited resolution as well as its appropriate function as adaptive optics.

  2. Advancing adaptive optics technology: Laboratory turbulence simulation and optimization of laser guide stars

    NASA Astrophysics Data System (ADS)

    Rampy, Rachel A.

    Since Galileo's first telescope some 400 years ago, astronomers have been building ever-larger instruments. Yet only within the last two decades has it become possible to realize the potential angular resolutions of large ground-based telescopes, by using adaptive optics (AO) technology to counter the blurring effects of Earth's atmosphere. And only within the past decade have the development of laser guide stars (LGS) extended AO capabilities to observe science targets nearly anywhere in the sky. Improving turbulence simulation strategies and LGS are the two main topics of my research. In the first part of this thesis, I report on the development of a technique for manufacturing phase plates for simulating atmospheric turbulence in the laboratory. The process involves strategic application of clear acrylic paint onto a transparent substrate. Results of interferometric characterization of the plates are described and compared to Kolmogorov statistics. The range of r0 (Fried's parameter) achieved thus far is 0.2--1.2 mm at 650 nm measurement wavelength, with a Kolmogorov power law. These plates proved valuable at the Laboratory for Adaptive Optics at University of California, Santa Cruz, where they have been used in the Multi-Conjugate Adaptive Optics testbed, during integration and testing of the Gemini Planet Imager, and as part of the calibration system of the on-sky AO testbed named ViLLaGEs (Visible Light Laser Guidestar Experiments). I present a comparison of measurements taken by ViLLaGEs of the power spectrum of a plate and the real sky turbulence. The plate is demonstrated to follow Kolmogorov theory well, while the sky power spectrum does so in a third of the data. This method of fabricating phase plates has been established as an effective and low-cost means of creating simulated turbulence. Due to the demand for such devices, they are now being distributed to other members of the AO community. The second topic of this thesis pertains to understanding and

  3. Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

    NASA Astrophysics Data System (ADS)

    Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.

    2011-04-01

    Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.

  4. Design and adaptation of ocean observing systems at coastal scales, the role of data assimilation in the optimization of measures.

    NASA Astrophysics Data System (ADS)

    Brandini, Carlo; Taddei, Stefano; Fattorini, Maria; Doronzo, Bartolomeo; Lapucci, Chiara; Ortolani, Alberto; Poulain, Pierre Marie

    2015-04-01

    The design and the implementation of observation systems, in the current view, are not limited to the capability to observe some phenomena of particular interest in a given sea area, but must ensure maximum benefits to the analysis/prediction systems that are based on numerical models. The design of these experimental systems takes great advantage from the use of synthetic data, whose characteristics are as close as possible to the observed data (e.g. in-situ), in terms of spatial and temporal variability, particularly when the power spectrum of the observed signal is close to that reproduced by a numerical model. This method, usually referred to as OSSE (Observing System Simulation Experiment), is a preferred way to test numerical data for assimilation into models as if they were real data, with the advantage of defining different datasets for data assimilation at almost no cost. This applies both to the design of fixed networks (such as buoys or coastal radars), and to the improvement of the performance of mobile platforms, such as autonomous marine vehicles, floats or mobile radars, through the optimization of parameters for vehicle guidance, coverage, trajectories or localization of sampling points, according to the adaptive observation concept. In this work we present the results of some experimental activities recently undertaken in the coastal area between the Ligurian and Northern Tyrrhenian seas, that have shown a great vulnerability in recent years, due to a number of marine accidents and environmental issues. In this cross-border area an observation and forecasting system is being installed as part of the SICOMAR project (PO maritime Italy-France), in order to provide real time data at high spatial and time resolution, and to design interoperable, expandable and flexible observing platforms, that can be quickly adapted to the needs of local problems (e.g. accidents at sea). The starting SICOMAR network includes HF coastal radars, FerryBoxes onboard ships

  5. Improved performance of the laser guide star adaptive optics system at Lick Observatory

    SciTech Connect

    An, J R; Avicola, K; Bauman, B J; Brase, J M; Campbell, E W; Carrano, C; Cooke, J B; Freeze, G J; Friedman, H W; Max, C E; Gates, E L; Gavel, D T; Kanz, V K; Kuklo, T C; Macintosh, B A; Newman, M J; Olivier, S S; Pierce, E L; Waltjen, K E; Watson, A

    1999-07-20

    Results of experiments with the laser guide star adaptive optics system on the 3-meter Shane telescope at Lick Observatory have demonstrated a factor of 4 performance improvement over previous results. Stellar images recorded at a wavelength of 2 {micro}m were corrected to over 40% of the theoretical diffraction-limited peak intensity. For the previous two years, this sodium-layer laser guide star system has corrected stellar images at this wavelength to {approx}10% of the theoretical peak intensity limit. After a campaign to improve the beam quality of the laser system, and to improve calibration accuracy and stability of the adaptive optics system using new techniques for phase retrieval and phase-shifting diffraction interferometry, the system performance has been substantially increased. The next step will be to use the Lick system for astronomical science observations, and to demonstrate this level of performance with the new system being installed on the 10-meter Keck II telescope.

  6. Improved performance of the laser guide star adaptive optics system at Lick Observatory

    NASA Astrophysics Data System (ADS)

    Olivier, Scot S.; Gavel, Donald T.; Friedman, Herbert W.; Max, Claire E.; An, Jong R.; Avicola, Kenneth; Bauman, Brian J.; Brase, James M.; Campbell, Eugene W.; Carrano, Carmen J.; Cooke, Jeffrey B.; Freeze, Gary J.; Gates, Elinor L.; Kanz, Vernon K.; Kuklo, Thomas C.; Macintosh, Bruce A.; Newman, Michael J.; Pierce, Edward L.; Waltjen, Kenneth E.; Watson, James A.

    1999-09-01

    Results of experiments with the laser guide star adaptive optics system on the 3-meter Shane telescope at Lick Observatory have demonstrated a factor of 4 performance improvement over previous results. Stellar images recorded at a wavelength of 2 micrometers were corrected to over 40 percent of the theoretical diffraction-limited peak intensity. For the previous two years, this sodium-layer laser guide star system has corrected stellar images at this wavelength to approximately 10 percent of the theoretical peak intensity limit. After a campaign to improve the beam quality of the laser system, and to improve calibration accuracy and stability of the adaptive optics system using new techniques for phase retrieval and phase-shifting diffraction interferometry, the system performance has been substantially increased. The next step will be to use the Lick system for astronomical science observations, and to demonstrate this level of performance with the new system being installed on the 10-meter Keck II telescope.

  7. Performance of a MEMS-base Adaptive Optics Optical Coherency Tomography System

    SciTech Connect

    Evans, J; Zadwadzki, R J; Jones, S; Olivier, S; Opkpodu, S; Werner, J S

    2008-01-16

    We have demonstrated that a microelectrical mechanical systems (MEMS) deformable mirror can be flattened to < 1 nm RMS within controllable spatial frequencies over a 9.2-mm aperture making it a viable option for high-contrast adaptive optics systems (also known as Extreme Adaptive Optics). The Extreme Adaptive Optics Testbed at UC Santa Cruz is being used to investigate and develop technologies for high-contrast imaging, especially wavefront control. A phase shifting diffraction interferometer (PSDI) measures wavefront errors with sub-nm precision and accuracy for metrology and wavefront control. Consistent flattening, required testing and characterization of the individual actuator response, including the effects of dead and low-response actuators. Stability and repeatability of the MEMS devices was also tested. An error budget for MEMS closed loop performance will summarize MEMS characterization.

  8. Extreme Adaptive Optics Testbed: Performance and Characterization of a 1024 Deformable Mirror

    SciTech Connect

    Evans, J W; Morzinski, K; Severson, S; Poyneer, L; Macintosh, B; Dillon, D; REza, L; Gavel, D; Palmer, D

    2005-10-30

    We have demonstrated that a microelectrical mechanical systems (MEMS) deformable mirror can be flattened to < 1 nm RMS within controllable spatial frequencies over a 9.2-mm aperture making it a viable option for high-contrast adaptive optics systems (also known as Extreme Adaptive Optics). The Extreme Adaptive Optics Testbed at UC Santa Cruz is being used to investigate and develop technologies for high-contrast imaging, especially wavefront control. A phase shifting diffraction interferometer (PSDI) measures wavefront errors with sub-nm precision and accuracy for metrology and wavefront control. Consistent flattening, required testing and characterization of the individual actuator response, including the effects of dead and low-response actuators. Stability and repeatability of the MEMS devices was also tested. An error budget for MEMS closed loop performance will summarize MEMS characterization.

  9. Updating a finite element model to the real experimental setup by thermographic measurements and adaptive regression optimization

    NASA Astrophysics Data System (ADS)

    Peeters, J.; Arroud, G.; Ribbens, B.; Dirckx, J. J. J.; Steenackers, G.

    2015-12-01

    In non-destructive evaluation the use of finite element models to evaluate structural behavior and experimental setup optimization can complement with the inspector's experience. A new adaptive response surface methodology, especially adapted for thermal problems, is used to update the experimental setup parameters in a finite element model to the state of the test sample measured by pulsed thermography. Poly Vinyl Chloride (PVC) test samples are used to examine the results for thermal insulator models. A comparison of the achieved results is made by changing the target values from experimental pulsed thermography data to a fixed validation model. Several optimizers are compared and discussed with the focus on speed and accuracy. A time efficiency increase of over 20 and an accuracy of over 99.5% are achieved by the choice of the correct parameter sets and optimizer. Proper parameter set selection criteria are defined and the influence of the choice of the optimization algorithm and parameter set on the accuracy and convergence time are investigated.

  10. Adaptive nearly optimal control for a class of continuous-time nonaffine nonlinear systems with inequality constraints.

    PubMed

    Fan, Quan-Yong; Yang, Guang-Hong

    2017-01-01

    The state inequality constraints have been hardly considered in the literature on solving the nonlinear optimal control problem based the adaptive dynamic programming (ADP) method. In this paper, an actor-critic (AC) algorithm is developed to solve the optimal control problem with a discounted cost function for a class of state-constrained nonaffine nonlinear systems. To overcome the difficulties resulting from the inequality constraints and the nonaffine nonlinearities of the controlled systems, a novel transformation technique with redesigned slack functions and a pre-compensator method are introduced to convert the constrained optimal control problem into an unconstrained one for affine nonlinear systems. Then, based on the policy iteration (PI) algorithm, an online AC scheme is proposed to learn the nearly optimal control policy for the obtained affine nonlinear dynamics. Using the information of the nonlinear model, novel adaptive update laws are designed to guarantee the convergence of the neural network (NN) weights and the stability of the affine nonlinear dynamics without the requirement for the probing signal. Finally, the effectiveness of the proposed method is validated by simulation studies.

  11. A texture-based rolling bearing fault diagnosis scheme using adaptive optimal kernel time frequency representation and uniform local binary patterns

    NASA Astrophysics Data System (ADS)

    Chen, Haizhou; Wang, Jiaxu; Li, Junyang; Tang, Baoping

    2017-03-01

    This paper presents a new scheme for rolling bearing fault diagnosis using texture features extracted from the time-frequency representations (TFRs) of the signal. To derive the proposed texture features, firstly adaptive optimal kernel time frequency representation (AOK-TFR) is applied to extract TFRs of the signal which essentially describe the energy distribution characteristics of the signal over time and frequency domain. Since the AOK-TFR uses the signal-dependent radially Gaussian kernel that adapts over time, it can exactly track the minor variations in the signal and provide an excellent time-frequency concentration in noisy environment. Simulation experiments are furthermore performed in comparison with common time-frequency analysis methods under different noisy conditions. Secondly, the uniform local binary pattern (uLBP), which is a computationally simple and noise-resistant texture analysis method, is used to calculate the histograms from the TFRs to characterize rolling bearing fault information. Finally, the obtained histogram feature vectors are input into the multi-SVM classifier for pattern recognition. We validate the effectiveness of the proposed scheme by several experiments, and comparative results demonstrate that the new fault diagnosis technique performs better than most state-of-the-art techniques, and yet we find that the proposed algorithm possess the adaptivity and noise resistance qualities that could be very useful in real industrial applications.

  12. Mixed-Integer Nonconvex Quadratic Optimization Relaxations and Performance Analysis

    DTIC Science & Technology

    2016-10-11

    portfolio deleveraging with market impact,” (Jingnan Chen, Liming Feng, Jiming Peng, Yinyu Ye), Operations Research, 62(1) (2014) 195-206. In this...Stanley 2012 Prize for Excellence in Financial Markets , First runner-up. “Space tensor conic programming,” (L Qi and Y Ye), Computational Optimization...portfolio deleveraging with market impact," (J. Chen, L. Feng, J. Peng, Y. Ye), Operations Research, 62(1) (2014) 195-206. "Simultaneous Beam Sampling

  13. Optimizing Hammermill Performance Through Screen Selection and Hammer Design

    SciTech Connect

    Neal A. Yancey; Tyler L. Westover; Christopher T. Wright

    2013-01-01

    Background: Mechanical preprocessing, which includes particle size reduction and mechanical separation, is one of the primary operations in the feedstock supply system for a lignocellulosic biorefinery. It is the means by which raw biomass from the field or forest is mechanically transformed into an on-spec feedstock with characteristics better suited for the fuel conversion process. Results: This work provides a general overview of the objectives and methodologies of mechanical preprocessing and then presents experimental results illustrating (1) improved size reduction via optimization of hammer mill configuration, (2) improved size reduction via pneumatic-assisted hammer milling, and (3) improved control of particle size and particle size distribution through proper selection of grinder process parameters. Conclusion: Optimal grinder configuration for maximal process throughput and efficiency is strongly dependent on feedstock type and properties, such moisture content. Tests conducted using a HG200 hammer grinder indicate that increasing the tip speed, optimizing hammer geometry, and adding pneumatic assist can increase grinder throughput as much as 400%.

  14. Spatial Cognitive Performance During Adaptation to Conflicting Tilt-Translation Stimuli as a Sensorimotor Spaceflight Analog

    NASA Technical Reports Server (NTRS)

    Kayanickupuram, A. J.; Ramos, K. A.; Cordova, M. L.; Wood, S. J.

    2009-01-01

    The need to resolve new patterns of sensory feedback in altered gravitoinertial environments requires cognitive processes to develop appropriate reference frames for spatial orientation awareness. The purpose of this study was to examine deficits in spatial cognitive performance during adaptation to conflicting tilt-translation stimuli. Fourteen subjects were tilted within a lighted enclosure that simultaneously translated at one of 3 frequencies. Tilt and translation motion was synchronized to maintain the resultant gravitoinertial force aligned with the longitudinal body axis, resulting in a mismatch analogous to spaceflight in which the canals and vision signal tilt while the otoliths do not. Changes in performance on different spatial cognitive tasks were compared 1) without motion, 2) with tilt motion alone (pitch at 0.15, 0.3 and 0.6 Hz or roll at 0.3 Hz), and 3) with conflicting tilt-translation motion. The adaptation paradigm was continued for up to 30 min or until the onset of nausea. The order of the adaptation conditions were counter-balanced across 4 different test sessions. There was a significant effect of stimulus frequency on both motion sickness and spatial cognitive performance. Only 3 of 14 were able to complete the full 30 min protocol at 0.15 Hz, while 7 of 14 completed 0.3 Hz and 13 of 14 completed 0.6 Hz. There were no changes in simple visual-spatial cognitive tests, e.g., mental rotation or match-to-sample. There were significant deficits during 0.15 Hz adaptation in both accuracy and reaction time during a spatial reference task in which subjects are asked to identify a match of a 3D reoriented cube assemblage. Our results are consistent with antidotal reports of cognitive impairment that are common during sensorimotor adaptation with G-transitions. We conclude that these cognitive deficits stem from the ambiguity of spatial reference frames for central processing of inertial motion cues.

  15. Binocular self-calibration performed via adaptive genetic algorithm based on laser line imaging

    NASA Astrophysics Data System (ADS)

    Apolinar Muñoz Rodríguez, J.; Mejía Alanís, Francisco Carlos

    2016-07-01

    An accurate technique to perform binocular self-calibration by means of an adaptive genetic algorithm based on a laser line is presented. In this calibration, the genetic algorithm computes the vision parameters through simulated binary crossover (SBX). To carry it out, the genetic algorithm constructs an objective function from the binocular geometry of the laser line projection. Then, the SBX minimizes the objective function via chromosomes recombination. In this algorithm, the adaptive procedure determines the search space via line position to obtain the minimum convergence. Thus, the chromosomes of vision parameters provide the minimization. The approach of the proposed adaptive genetic algorithm is to calibrate and recalibrate the binocular setup without references and physical measurements. This procedure leads to improve the traditional genetic algorithms, which calibrate the vision parameters by means of references and an unknown search space. It is because the proposed adaptive algorithm avoids errors produced by the missing of references. Additionally, the three-dimensional vision is carried out based on the laser line position and vision parameters. The contribution of the proposed algorithm is corroborated by an evaluation of accuracy of binocular calibration, which is performed via traditional genetic algorithms.

  16. An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

    NASA Astrophysics Data System (ADS)

    Haghnevis, Moeed

    The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

  17. A modular and adaptive mass spectrometry-based platform for support of bioprocess development toward optimal host cell protein clearance.

    PubMed

    Walker, Donald E; Yang, Feng; Carver, Joseph; Joe, Koman; Michels, David A; Yu, X Christopher

    2017-03-27

    A modular and adaptive mass spectrometry (MS)-based platform was developed to provide fast, robust and sensitive host cell protein (HCP) analytics to support process development. This platform relies on one-dimensional ultra-high performance liquid chromatography (1D UHPLC) combined with several different MS data acquisition strategies to meet the needs of purification process development. The workflow was designed to allow HCP composition and quantitation for up to 20 samples per day, a throughput considered essential for real time bioprocess development support. With data-dependent acquisition (DDA), the 1D UHPLC-MS/MS method had excellent speed and demonstrated robustness in detecting unknown HCPs at ≥ 50 ng/mg (ppm) level. Combining 1D UHPLC with sequential window acquisition of all theoretical spectra (SWATH) MS enabled simultaneous detection and quantitation of all HCPs in single-digit ng/mg range within 1 hour, demonstrating for the first time the benefit of SWATH MS as a technique for HCP analysis. As another alternative, a targeted MS approach can be used to track the clearance of specific known HCP under various process conditions. This study highlights the importance of designing a robust LC-MS/MS workflow that not only allows HCP discovery, but also affords greatly improved process knowledge and capability in HCP removal. As an orthogonal and complementary detection approach to traditional HCP analysis by enzyme-linked immunosorbent assay, the reported LC-MS/MS workflow supports the development of bioprocesses with optimal HCP clearance and the production of safe and high quality therapeutic biopharmaceuticals.

  18. Low probability of intercept-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems

    NASA Astrophysics Data System (ADS)

    Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

    2016-12-01

    In this paper, we investigate the problem of low probability of intercept (LPI)-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems, where the radar system optimizes the transmitted waveform such that the interference caused to the cellular communication systems is strictly controlled. Assuming that the precise knowledge of the target spectra, the power spectral densities (PSDs) of signal-dependent clutters, the propagation losses of corresponding channels and the communication signals is known by the radar, three different LPI based criteria for radar waveform optimization are proposed to minimize the total transmitted power of the radar system by optimizing the multicarrier radar waveform with a predefined signal-to-interference-plus-noise ratio (SINR) constraint and a minimum required capacity for the cellular communication systems. These criteria differ in the way the communication signals scattered off the target are considered in the radar waveform design: (1) as useful energy, (2) as interference or (3) ignored altogether. The resulting problems are solved analytically and their solutions represent the optimum power allocation for each subcarrier in the multicarrier radar waveform. We show with numerical results that the LPI performance of the radar system can be significantly improved by exploiting the scattered echoes off the target due to cellular communication signals received at the radar receiver.

  19. Low probability of intercept-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems.

    PubMed

    Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

    2016-01-01

    In this paper, we investigate the problem of low probability of intercept (LPI)-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems, where the radar system optimizes the transmitted waveform such that the interference caused to the cellular communication systems is strictly controlled. Assuming that the precise knowledge of the target spectra, the power spectral densities (PSDs) of signal-dependent clutters, the propagation losses of corresponding channels and the communication signals is known by the radar, three different LPI based criteria for radar waveform optimization are proposed to minimize the total transmitted power of the radar system by optimizing the multicarrier radar waveform with a predefined signal-to-interference-plus-noise ratio (SINR) constraint and a minimum required capacity for the cellular communication systems. These criteria differ in the way the communication signals scattered off the target are considered in the radar waveform design: (1) as useful energy, (2) as interference or (3) ignored altogether. The resulting problems are solved analytically and their solutions represent the optimum power allocation for each subcarrier in the multicarrier radar waveform. We show with numerical results that the LPI performance of the radar system can be significantly improved by exploiting the scattered echoes off the target due to cellular communication signals received at the radar receiver.

  20. Performance of an adaptive phase estimator for coherent free-space optical communications over Gamma-Gamma turbulence

    NASA Astrophysics Data System (ADS)

    Li, Yiming; Gao, Chao; Liang, Haodong; Miao, Maoke; Li, Xiaofeng

    2017-04-01

    This paper investigates an adaptive phase estimator for coherent free-space optical (FSO) communication systems. Closed-form solutions for variance of phase errors are derived when the optical beam is subjected to Gamma-Gamma distributed turbulence. The adaptive phase estimator has improved upon the phase error performance in comparison to conventional phase estimators. We also demonstrate notable improvement in BER performance when applying our adaptive phase estimator to coherent FSO communication systems.