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Sample records for predictive control method

  1. A method to predict circulation control noise

    NASA Astrophysics Data System (ADS)

    Reger, Robert W.

    Underwater vehicles suffer from reduced maneuverability with conventional lifting append-\\ ages due to the low velocity of operation. Circulation control offers a method to increase maneuverability independent of vehicle speed. However, with circulation control comes additional noise sources, which are not well understood. To better understand these noise sources, a modal-based prediction method is developed, potentially offering a quantitative connection between flow structures and far-field noise. This method involves estimation of the velocity field, surface pressure field, and far-field noise, using only non-time-resolved velocity fields and time-resolved probe measurements. Proper orthogonal decomposition, linear stochastic estimation and Kalman smoothing are employed to estimate time-resolved velocity fields. Poisson's equation is used to calculate time-resolved pressure fields from velocity. Curle's analogy is then used to propagate the surface pressure forces to the far field. This method is developed on a direct numerical simulation of a two-dimensional cylinder at a low Reynolds number (150). Since each of the fields to be estimated are also known from the simulation, a means of obtaining the error from using the methodology is provided. The velocity estimation and the simulated velocity match well when the simulated additive measurement noise is low. The pressure field suffers due to a small domain size; however, the surface pressures estimates fare much better. The far-field estimation contains similar frequency content with reduced magnitudes, attributed to the exclusion of the viscous forces in Curle's analogy. In the absence of added noise, the estimation procedure performs quite nicely for this model problem. The method is tested experimentally on a 650,000 chord-Reynolds-number flow over a 2-D, 20% thick, elliptic circulation control airfoil. Slot jet momentum coefficients of 0 and 0.10 are investigated. Particle image velocimetry, unsteady

  2. Application of linear gauss pseudospectral method in model predictive control

    NASA Astrophysics Data System (ADS)

    Yang, Liang; Zhou, Hao; Chen, Wanchun

    2014-03-01

    This paper presents a model predictive control(MPC) method aimed at solving the nonlinear optimal control problem with hard terminal constraints and quadratic performance index. The method combines the philosophies of the nonlinear approximation model predictive control, linear quadrature optimal control and Gauss Pseudospectral method. The current control is obtained by successively solving linear algebraic equations transferred from the original problem via linearization and the Gauss Pseudospectral method. It is not only of high computational efficiency since it does not need to solve nonlinear programming problem, but also of high accuracy though there are a few discrete points. Therefore, this method is suitable for on-board applications. A design of terminal impact with a specified direction is carried out to evaluate the performance of this method. Augmented PN guidance law in the three-dimensional coordinate system is applied to produce the initial guess. And various cases for target with straight-line movements are employed to demonstrate the applicability in different impact angles. Moreover, performance of the proposed method is also assessed by comparison with other guidance laws. Simulation results indicate that this method is not only of high computational efficiency and accuracy, but also applicable in the framework of guidance design.

  3. Comparison of Predictive Control Methods for High Consumption Industrial Furnace

    PubMed Central

    2013-01-01

    We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn. PMID:24319354

  4. Comparison of predictive control methods for high consumption industrial furnace.

    PubMed

    Stojanovski, Goran; Stankovski, Mile

    2013-01-01

    We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn.

  5. Prediction by neural network methods compared for energy control problems

    SciTech Connect

    Surkan, A.J.; Skurikhin, A.N.

    1996-10-01

    Daily recordings of energy consumption are sequenced to construct a time series that is used to test the accuracy of a variety of neural networks in making one- and two-day demand predictions. Five neural network methods were applied to the same data for a problem of predicting daily energy usage. These included four which were gradient-based, namely, back propagation (BACKPROP), quick-propagation (QUICKPROP), cascade correlation (CASCOR), memory neuron network (MNN), and a correlation-based method called ALOPEX. The observed time series is the only information source used for making predictions. Other supplementary parallel series of independent data can produce improvements. It was demonstrated that these neural network learning algorithms can train networks to predict consistently, one-day-ahead, over one year of set-aside test patterns and reduce the average error to below 19%. Reported is a comparison of applicability of neural networks by programmed simulations of the widely used gradient-based algorithms along with newer algorithms MNN and ALOPEX. The diverse capabilities of these various networks give insights which are a useful basis for selecting further studies.

  6. Two-Step Design Method of Engine Control System Based on Generalized Predictive Control

    NASA Astrophysics Data System (ADS)

    Hashimoto, Seiji; Okuda, Hiroyuki; Okada, Yasushi; Adachi, Shuichi; Niwa, Shinji; Kajitani, Mitsunobu

    Conservation of the environment has become critical to the automotive industry. Recently, requirements for on-board diagnostic and engine control systems have been strictly enforced. In the present paper, in order to meet the requirements for a low-emissions vehicle, a novel construction method of the air-fuel ratio (A/F) control system is proposed. The construction method of the system is divided into two steps. The first step is to design the A/F control system for the engine based on an open loop design. The second step is to design the A/F control system for the catalyst system. The design method is based on the generalized predictive control in order to satisfy the robustness to open loop control as well as model uncertainty. The effectiveness of the proposed A/F control system is verified through experiments using full-scale products.

  7. Study on model current predictive control method of PV grid- connected inverters systems with voltage sag

    NASA Astrophysics Data System (ADS)

    Jin, N.; Yang, F.; Shang, S. Y.; Tao, T.; Liu, J. S.

    2016-08-01

    According to the limitations of the LVRT technology of traditional photovoltaic inverter existed, this paper proposes a low voltage ride through (LVRT) control method based on model current predictive control (MCPC). This method can effectively improve the photovoltaic inverter output characteristics and response speed. The MCPC method of photovoltaic grid-connected inverter designed, the sum of the absolute value of the predictive current and the given current error is adopted as the cost function with the model predictive control method. According to the MCPC, the optimal space voltage vector is selected. Photovoltaic inverter has achieved automatically switches of priority active or reactive power control of two control modes according to the different operating states, which effectively improve the inverter capability of LVRT. The simulation and experimental results proves that the proposed method is correct and effective.

  8. Model predictive control system and method for integrated gasification combined cycle power generation

    SciTech Connect

    Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

    2013-04-09

    Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

  9. Validation of engineering methods for predicting hypersonic vehicle controls forces and moments

    NASA Technical Reports Server (NTRS)

    Maughmer, M.; Straussfogel, D.; Long, L.; Ozoroski, L.

    1991-01-01

    This work examines the ability of the aerodynamic analysis methods contained in an industry standard conceptual design code, the Aerodynamic Preliminary Analysis System (APAS II), to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds. Predicted control forces and moments generated by various control effectors are compared with previously published wind-tunnel and flight-test data for three vehicles: the North American X-15, a hypersonic research airplane concept, and the Space Shuttle Orbiter. Qualitative summaries of the results are given for each force and moment coefficient and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage.

  10. Prediction of forces and moments for flight vehicle control effectors. Part 1: Validation of methods for predicting hypersonic vehicle controls forces and moments

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.; Ozoroski, L.; Ozoroski, T.; Straussfogel, D.

    1990-01-01

    Many types of hypersonic aircraft configurations are currently being studied for feasibility of future development. Since the control of the hypersonic configurations throughout the speed range has a major impact on acceptable designs, it must be considered in the conceptual design stage. The ability of the aerodynamic analysis methods contained in an industry standard conceptual design system, APAS II, to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds is considered. Predicted control forces and moments generated by various control effectors are compared with previously published wind tunnel and flight test data for three configurations: the North American X-15, the Space Shuttle Orbiter, and a hypersonic research airplane concept. Qualitative summaries of the results are given for each longitudinal force and moment and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage. Results for most lateral/directional control derivatives are acceptable for conceptual design purposes; however, predictions at supersonic Mach numbers for the change in yawing moment due to aileron deflection and the change in rolling moment due to rudder deflection are found to be unacceptable. Including shielding effects in the analysis is shown to have little effect on lift and pitching moment predictions while improving drag predictions.

  11. High-order distortion control using a computational prediction method for device overlay

    NASA Astrophysics Data System (ADS)

    Kang, Young-Seog; Affentauschegg, Cedric; Mulkens, Jan; Kim, Jang-Sun; Shin, Ju-Hee; Kim, Young-Ha; Nam, Young-Sun; Choi, Young-Sin; Ha, Hunhwan; Lee, Dong-Han; Lee, Jae-il; Rizvi, Umar; Geh, Bernd; van der Heijden, Rob; Baselmans, Jan; Kwon, Oh-Sung

    2016-04-01

    As a result of the continuously shrinking features of the integrated circuit, the overlay budget requirements have become very demanding. Historically, overlay has been performed using metrology targets for process control, and most overlay enhancements were achieved by hardware improvements. However, this is no longer sufficient, and we need to consider additional solutions for overlay improvements in process variation using computational methods. In this paper, we present the limitations of third-order intrafield distortion corrections based on standard overlay metrology and propose an improved method which includes a prediction of the device overlay and corrects the lens aberration fingerprint based on this prediction. For a DRAM use case, we present a computational approach that calculates the overlay of the device pattern using lens aberrations as an additional input, next to the target-based overlay measurement result. Supporting experimental data are presented that demonstrate a significant reduction of the intrafield overlay fingerprint.

  12. A Prediction Method of TV Camera Image for Space Manual-control Rendezvous and Docking

    NASA Astrophysics Data System (ADS)

    Zhen, Huang; Qing, Yang; Wenrui, Wu

    Space manual-control rendezvous and docking (RVD) is a key technology for accomplishing the RVD mission in manned space engineering, especially when automatic control system is out of work. The pilot on chase spacecraft manipulates the hand-stick by the image of target spacecraft captured by TV camera. From the TV image, the relative position and attitude of chase and target spacecrafts can be shown. Therefore, the size, the position, the brightness and the shadow of the target on TV camera are key to guarantee the success of manual-control RVD. A method of predicting the on-orbit TV camera image at different relative positions and light conditions during the process of RVD is discussed. Firstly, the basic principle of capturing the image of cross drone on target spacecraft by TV camera is analyzed theoretically, based which the strategy of manual-control RVD is discussed in detail. Secondly, the relationship between the displayed size or position and the real relative distance of chase and target spacecrafts is presented, the brightness and reflection by the target spacecraft at different light conditions are decribed, the shadow on cross drone caused by the chase or target spacecraft is analyzed. Thirdly, a prediction method of on-orbit TV camera images at certain orbit and light condition is provided, and the characteristics of TV camera image during the RVD is analyzed. Finally, the size, the position, the brightness and the shadow of target spacecraft on TV camera image at typical orbit is simulated. The result, by comparing the simulated images with the real images captured by the TV camera on Shenzhou manned spaceship , shows that the prediction method is reasonable

  13. Stable predictive control horizons

    NASA Astrophysics Data System (ADS)

    Estrada, Raúl; Favela, Antonio; Raimondi, Angelo; Nevado, Antonio; Requena, Ricardo; Beltrán-Carbajal, Francisco

    2012-04-01

    The stability theory of predictive and adaptive predictive control for processes of linear and stable nature is based on the hypothesis of a physically realisable driving desired trajectory (DDT). The formal theoretical verification of this hypothesis is trivial for processes with a stable inverse, but it is not for processes with an unstable inverse. The extended strategy of predictive control was developed with the purpose of overcoming methodologically this stability problem and it has delivered excellent performance and stability in its industrial applications given a suitable choice of the prediction horizon. From a theoretical point of view, the existence of a prediction horizon capable of ensuring stability for processes with an unstable inverse was proven in the literature. However, no analytical solution has been found for the determination of the prediction horizon values which guarantee stability, in spite of the theoretical and practical interest of this matter. This article presents a new method able to determine the set of prediction horizon values which ensure stability under the extended predictive control strategy formulation and a particular performance criterion for the design of the DDT generically used in many industrial applications. The practical application of this method is illustrated by means of simulation examples.

  14. A swarm intelligence-based tuning method for the Sliding Mode Generalized Predictive Control.

    PubMed

    Oliveira, J B; Boaventura-Cunha, J; Moura Oliveira, P B; Freire, H

    2014-09-01

    This work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy.

  15. Real-time optical path control method that utilizes multiple support vector machines for traffic prediction

    NASA Astrophysics Data System (ADS)

    Kawase, Hiroshi; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi

    2016-02-01

    An effective solution to the continuous Internet traffic expansion is to offload traffic to lower layers such as the L2 or L1 optical layers. One possible approach is to introduce dynamic optical path operations such as adaptive establishment/tear down according to traffic variation. Path operations cannot be done instantaneously; hence, traffic prediction is essential. Conventional prediction techniques need optimal parameter values to be determined in advance by averaging long-term variations from the past. However, this does not allow adaptation to the ever-changing short-term variations expected to be common in future networks. In this paper, we propose a real-time optical path control method based on a machinelearning technique involving support vector machines (SVMs). A SVM learns the most recent traffic characteristics, and so enables better adaptation to temporal traffic variations than conventional techniques. The difficulty lies in determining how to minimize the time gap between optical path operation and buffer management at the originating points of those paths. The gap makes the required learning data set enormous and the learning process costly. To resolve the problem, we propose the adoption of multiple SVMs running in parallel, trained with non-overlapping subsets of the original data set. The maximum value of the outputs of these SVMs will be the estimated number of necessary paths. Numerical experiments prove that our proposed method outperforms a conventional prediction method, the autoregressive moving average method with optimal parameter values determined by Akaike's information criterion, and reduces the packet-loss ratio by up to 98%.

  16. To predict sufentanil requirement for postoperative pain control using a real-time method

    PubMed Central

    Zhang, Yuhao; Duan, Guangyou; Guo, Shanna; Ying, Ying; Huang, Penghao; Zhang, Mi; Li, Ningbo; Zhang, Xianwei

    2016-01-01

    Abstract Preoperative identification of individual sensitivity to opioid analgesics could improve the quality of postoperative analgesia. We explored the feasibility and utility of a real-time assessment of sufentanil sensitivity in predicting postoperative analgesic requirement. Our primary study included 111 patients who underwent measurements of pressure and quantitative pricking pain thresholds before and 5 minutes after sufentanil infusion. Pain intensity was assessed during the first 24-hour postsurgery, and patients who reported inadequate levels of analgesia were excluded from the study. The sufentanil requirement for patient-controlled analgesia was recorded, and a subsequent exploratory study of 20 patients facilitated the interpretation of the primary study results. In the primary study, experimental pain thresholds increased (P < 0.001) 5 minutes after sufentanil infusion, and the percent change in pricking pain threshold was positively associated with sufentanil requirement at 12 and 24 hours after surgery (β = 0.318, P = 0.001; and β = 0.335, P = 0.001). A receiver-operating characteristic curve analysis showed that patients with a change in pricking pain threshold >188% were >50% likely to require more sufentanil for postoperative pain control. In the exploratory study, experimental pain thresholds significantly decreased after the operation (P < 0.001), and we observed a positive correlation (P < 0.001) between the percent change in pricking pain threshold before and after surgery. Preoperative detection of individual sensitivity to sufentanil via the above described real-time method was effective in predicting postoperative sufentanil requirement. Thus, percent change in pricking pain threshold might be a feasible predictive marker of postoperative analgesia requirement. PMID:27336880

  17. On identified predictive control

    NASA Technical Reports Server (NTRS)

    Bialasiewicz, Jan T.

    1993-01-01

    Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

  18. Controlling Bimetallic Nanostructures by the Microemulsion Method with Subnanometer Resolution Using a Prediction Model.

    PubMed

    Buceta, David; Tojo, Concha; Vukmirovic, Miomir B; Deepak, Francis Leonard; López-Quintela, M Arturo

    2015-07-14

    We present a theoretical model to predict the atomic structure of Au/Pt nanoparticles synthesized in microemulsions. Excellent concordance with the experimental results shows that the structure of the nanoparticles can be controlled at subnanometer resolution simply by changing the reactant concentration. The results of this study not only offer a better understanding of the complex mechanisms governing reactions in microemulsions, but open up a simple new way to synthesize bimetallic nanoparticles with ad hoc controlled nanostructures.

  19. Controlling bimetallic nanostructures by the microemulsion method with subnanometer resolution using a prediction model

    DOE PAGESBeta

    Buceta, David; Tojo, Concha; Vukmirovic, Miomir B.; Deepak, F. Leonard; Lopez-Quintela, M. Arturo

    2015-06-02

    In this study, we present a theoretical model to predict the atomic structure of Au/Pt nanoparticles synthesized in microemulsions. Excellent concordance with the experimental results shows that the structure of the nanoparticles can be controlled at sub-nanometer resolution simply by changing the reactants concentration. The results of this study not only offer a better understanding of the complex mechanisms governing reactions in microemulsions, but open up a simple new way to synthesize bimetallic nanoparticles with ad-hoc controlled nanostructures.

  20. Improved nonlinear prediction method

    NASA Astrophysics Data System (ADS)

    Adenan, Nur Hamiza; Md Noorani, Mohd Salmi

    2014-06-01

    The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.

  1. Adjoint Method and Predictive Control for 1-D Flow in NASA Ames 11-Foot Transonic Wind Tunnel

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan; Ardema, Mark

    2006-01-01

    This paper describes a modeling method and a new optimal control approach to investigate a Mach number control problem for the NASA Ames 11-Foot Transonic Wind Tunnel. The flow in the wind tunnel is modeled by the 1-D unsteady Euler equations whose boundary conditions prescribe a controlling action by a compressor. The boundary control inputs to the compressor are in turn controlled by a drive motor system and an inlet guide vane system whose dynamics are modeled by ordinary differential equations. The resulting Euler equations are thus coupled to the ordinary differential equations via the boundary conditions. Optimality conditions are established by an adjoint method and are used to develop a model predictive linear-quadratic optimal control for regulating the Mach number due to a test model disturbance during a continuous pitch

  2. Multi-objective optimal design of online PID controllers using model predictive control based on the group method of data handling-type neural networks

    NASA Astrophysics Data System (ADS)

    Majdabadi-Farahani, V.; Hanif, M.; Gholaminezhad, I.; Jamali, A.; Nariman-Zadeh, N.

    2014-10-01

    In this paper, model predictive control (MPC) is used for optimal selection of proportional-integral-derivative (PID) controller gains. In conventional tuning methods a history of response error of the system under control in the passed time is measured and used to adjust PID parameters in order to improve the performance of the system in proceeding time. But MPC obviates this characteristic of classic PID. In fact MPC tries to tune the controller by predicting the system's behaviour some time steps ahead. In this way, PID parameters are adjusted before any real error occurs in the system's response. For this purpose, polynomial meta-models based on the evolved group method of data handling neural networks are obtained to simply simulate the time response of the dynamic system. Moreover, a non-dominated sorting genetic algorithm has been used in a multi-objective Pareto optimisation to select the parameters of the MPC which are prediction horizon, control horizon and relation of weight of Δ u and error, to minimise simultaneously two objective functions that are control effort and integral time absolute error of the system response. The results mentioned at the end obviously declare that the proposed method surpasses conventional tuning methods for PID controllers, and Pareto optimal selection of predictive parameters also improves the performance of the introduced method.

  3. Deadbeat Predictive Controllers

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Phan, Minh

    1997-01-01

    Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.

  4. Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

    PubMed

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2014-05-01

    This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. PMID:24559835

  5. Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

    PubMed

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2014-05-01

    This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach.

  6. Predictive spark timing method

    SciTech Connect

    Tang, D.L.; Chang, M.F.; Sultan, M.C.

    1990-01-09

    This patent describes a method of determining spark time in a spark timing system of an internal combustion engine having a plurality of cylinders and a spark period for each cylinder in which a spark occurs. It comprises: generating at least one crankshaft position reference pulse for each spark firing event, the reference pulse nearest the next spark being set to occur within a same cylinder event as the next spark; measuring at least two reference periods between recent reference pulses; calculating the spark timing synchronously with crankshaft position by performing the calculation upon receipt of the reference pulse nearest the next spark; predicting the engine speed for the next spark period from at least two reference periods including the most recent reference period; and based on the predicted speed, calculating a spark time measured from the the reference pulse nearest the next spark.

  7. Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

    NASA Astrophysics Data System (ADS)

    Na, Xiaoxiang; Cole, David J.

    2013-02-01

    This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy.

  8. Motor degradation prediction methods

    SciTech Connect

    Arnold, J.R.; Kelly, J.F.; Delzingaro, M.J.

    1996-12-01

    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor`s duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures.

  9. Progress in analytical methods to predict and control azimuthal combustion instability modes in annular chambers

    NASA Astrophysics Data System (ADS)

    Bauerheim, M.; Nicoud, F.; Poinsot, T.

    2016-02-01

    Longitudinal low-frequency thermoacoustic unstable modes in combustion chambers have been intensively studied experimentally, numerically, and theoretically, leading to significant progress in both understanding and controlling these acoustic modes. However, modern annular gas turbines may also exhibit azimuthal modes, which are much less studied and feature specific mode structures and dynamic behaviors, leading to more complex situations. Moreover, dealing with 10-20 burners mounted in the same chamber limits the use of high fidelity simulations or annular experiments to investigate these modes because of their complexity and costs. Consequently, for such circumferential acoustic modes, theoretical tools have been developed to uncover underlying phenomena controlling their stability, nature, and dynamics. This review presents recent progress in this field. First, Galerkin and network models are described with their pros and cons in both the temporal and frequency framework. Then, key features of such acoustic modes are unveiled, focusing on their specificities such as symmetry breaking, non-linear modal coupling, forcing by turbulence. Finally, recent works on uncertainty quantifications, guided by theoretical studies and applied to annular combustors, are presented. The objective is to provide a global view of theoretical research on azimuthal modes to highlight their complexities and potential.

  10. Data-Based Predictive Control with Multirate Prediction Step

    NASA Technical Reports Server (NTRS)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  11. Near-field noise prediction for aircraft in cruising flight: Methods manual. [laminar flow control noise effects analysis

    NASA Technical Reports Server (NTRS)

    Tibbetts, J. G.

    1979-01-01

    Methods for predicting noise at any point on an aircraft while the aircraft is in a cruise flight regime are presented. Developed for use in laminar flow control (LFC) noise effects analyses, they can be used in any case where aircraft generated noise needs to be evaluated at a location on an aircraft while under high altitude, high speed conditions. For each noise source applicable to the LFC problem, a noise computational procedure is given in algorithm format, suitable for computerization. Three categories of noise sources are covered: (1) propulsion system, (2) airframe, and (3) LFC suction system. In addition, procedures are given for noise modifications due to source soundproofing and the shielding effects of the aircraft structure wherever needed. Sample cases, for each of the individual noise source procedures, are provided to familiarize the user with typical input and computed data.

  12. Predictive Control of Speededness in Adaptive Testing

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    2009-01-01

    An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

  13. Prediction method abstracts

    SciTech Connect

    1994-12-31

    This conference was held December 4--8, 1994 in Asilomar, California. The purpose of this meeting was to provide a forum for exchange of state-of-the-art information concerning the prediction of protein structure. Attention if focused on the following: comparative modeling; sequence to fold assignment; and ab initio folding.

  14. 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.

  15. Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

    NASA Technical Reports Server (NTRS)

    Kelkar, Atul G.

    2000-01-01

    The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

  16. A Course in... Model Predictive Control.

    ERIC Educational Resources Information Center

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  17. Inhibitory Control Predicts Grammatical Ability.

    PubMed

    Ibbotson, Paul; Kearvell-White, Jennifer

    2015-01-01

    We present evidence that individual variation in grammatical ability can be predicted by individual variation in inhibitory control. We tested 81 5-year-olds using two classic tests from linguistics and psychology (Past Tense and the Stroop). Inhibitory control was a better predicator of grammatical ability than either vocabulary or age. Our explanation is that giving the correct response in both tests requires using a common cognitive capacity to inhibit unwanted competition. The implications are that understanding the developmental trajectory of language acquisition can benefit from integrating the developmental trajectory of non-linguistic faculties, such as executive control.

  18. Inhibitory Control Predicts Grammatical Ability

    PubMed Central

    Ibbotson, Paul; Kearvell-White, Jennifer

    2015-01-01

    We present evidence that individual variation in grammatical ability can be predicted by individual variation in inhibitory control. We tested 81 5-year-olds using two classic tests from linguistics and psychology (Past Tense and the Stroop). Inhibitory control was a better predicator of grammatical ability than either vocabulary or age. Our explanation is that giving the correct response in both tests requires using a common cognitive capacity to inhibit unwanted competition. The implications are that understanding the developmental trajectory of language acquisition can benefit from integrating the developmental trajectory of non-linguistic faculties, such as executive control. PMID:26659926

  19. Predictive control and estimation - State space approach

    NASA Technical Reports Server (NTRS)

    Gawronski, W.

    1991-01-01

    A modified output prediction procedure and a new controller design based on the predictive control law are presented. A new predictive estimator enhances system performance. The predictive controller was designed and applied to the tracking control of the NASA/JPL 70-m antenna. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

  20. Windamper method of galloping control. Pt. II. Prediction of dynamic galloping. Final report. [Ice buildup on windward side

    SciTech Connect

    Richardson, A.S. Jr.

    1983-10-15

    This has been a technical review and extension of the Windamper methodology for controlling galloping (ice buildup on windward side). The new material consists of three main parts. First, there is the review and analysis of single conductor by coupled two-degree-of-freedom analysis. Second, there is the extension of that method to the bundled conductor. Third, there is the report of the new Windamper aerodynamic data (Appendix). The analytical work supports the general hypothesis and theory of Den Hartog. The Windamper appears to act to stabilize conductors which would otherwise become unstable when lift slope is negative. When lift slope is positive, a flutter type of gallop may be identified, owing to lee-side location of the damper c.g. In single conductors, the realization of the flutter gallop requires very large positive lift slope, and the torsion component dominates the motion which also would limit gallop amplitude. In bundled conductors, the realization of the flutter gallop requires only small positive lift slope because of the proximity of the two natural frequencies to each other. Very little torsion is present in the bundle motion, and the Windamper aerodynamic drag produces a net flow of energy to damp the motion.

  1. Fast predictive control of networked energy systems

    NASA Astrophysics Data System (ADS)

    Chuang, Frank Fu-Han

    forecasts. We show that the exact control policies can be found efficiently for certain types of robust predictive control problems. The second half of the thesis deals with improving computation speed and memory usage through model reduction and exploitation of symmetries in the predictive control problem. We present a model reduction technique tailored for networked systems which preserves sparsity and thus greatly improves computation speed. We also show how to apply symmetry methods for efficient computation of explicit model predictive controllers to systems which are not perfectly symmetric.

  2. Broadband Noise Control Using Predictive Techniques

    NASA Technical Reports Server (NTRS)

    Eure, Kenneth W.; Juang, Jer-Nan

    1997-01-01

    Predictive controllers have found applications in a wide range of industrial processes. Two types of such controllers are generalized predictive control and deadbeat control. Recently, deadbeat control has been augmented to include an extended horizon. This modification, named deadbeat predictive control, retains the advantage of guaranteed stability and offers a novel way of control weighting. This paper presents an application of both predictive control techniques to vibration suppression of plate modes. Several system identification routines are presented. Both algorithms are outlined and shown to be useful in the suppression of plate vibrations. Experimental results are given and the algorithms are shown to be applicable to non- minimal phase systems.

  3. Novel hyperspectral prediction method and apparatus

    NASA Astrophysics Data System (ADS)

    Kemeny, Gabor J.; Crothers, Natalie A.; Groth, Gard A.; Speck, Kathy A.; Marbach, Ralf

    2009-05-01

    Both the power and the challenge of hyperspectral technologies is the very large amount of data produced by spectral cameras. While off-line methodologies allow the collection of gigabytes of data, extended data analysis sessions are required to convert the data into useful information. In contrast, real-time monitoring, such as on-line process control, requires that compression of spectral data and analysis occur at a sustained full camera data rate. Efficient, high-speed practical methods for calibration and prediction are therefore sought to optimize the value of hyperspectral imaging. A novel method of matched filtering known as science based multivariate calibration (SBC) was developed for hyperspectral calibration. Classical (MLR) and inverse (PLS, PCR) methods are combined by spectroscopically measuring the spectral "signal" and by statistically estimating the spectral "noise." The accuracy of the inverse model is thus combined with the easy interpretability of the classical model. The SBC method is optimized for hyperspectral data in the Hyper-CalTM software used for the present work. The prediction algorithms can then be downloaded into a dedicated FPGA based High-Speed Prediction EngineTM module. Spectral pretreatments and calibration coefficients are stored on interchangeable SD memory cards, and predicted compositions are produced on a USB interface at real-time camera output rates. Applications include minerals, pharmaceuticals, food processing and remote sensing.

  4. Predicting Loss-of-Control Boundaries Toward a Piloting Aid

    NASA Technical Reports Server (NTRS)

    Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

  5. Control system design method

    DOEpatents

    Wilson, David G.; Robinett, III, Rush D.

    2012-02-21

    A control system design method and concomitant control system comprising representing a physical apparatus to be controlled as a Hamiltonian system, determining elements of the Hamiltonian system representation which are power generators, power dissipators, and power storage devices, analyzing stability and performance of the Hamiltonian system based on the results of the determining step and determining necessary and sufficient conditions for stability of the Hamiltonian system, creating a stable control system based on the results of the analyzing step, and employing the resulting control system to control the physical apparatus.

  6. Dual drug load and release behavior on ion-exchange fiber: influencing factors and prediction method for precise control of the loading amount.

    PubMed

    Yuan, Jing; Gao, Yanan; Liu, Tiaotiao; Wang, Xinyu; Liu, Hongzhuo; Li, Sanming

    2015-01-01

    Ion-exchange fiber undergoes a stoichiometric exchange reaction and has large exchange capability, which makes it a promising candidate as a multiple drug carrier. Because combinatorial effects can act synergistically, additively or antagonistically depending on the ratio of the agents being combined, the objective of this study was to learn the dual drug loading of ion-exchange fiber and develop a mathematical method for precisely control of the loading amount. Atenolol and Gatifloxacin, with different loading behaviors into strong cationic ion-exchange fiber ZB-1, were used to build a representative of dual loading. Not suitable pH value of drug solutions could make simultaneous loading fail, while the change of drug solution volume hardly affected the equilibrium. Ion-exchange groups occupied by the drug which owned lower affinity to fiber could be grabbed by the higher affinity drug, indicating the existence of competition between drugs. Thermodynamic model was introduced to guide the loading prediction and a favorable relevance had been shown between determined and predicted data. The release behaviors of each drug from dual drug-fiber complex were similar to those from single drug-fiber complexes.

  7. Assessment and evaluation of noise controls on roof bolting equipment and a method for predicting sound pressure levels in underground coal mining

    NASA Astrophysics Data System (ADS)

    Matetic, Rudy J.

    Over-exposure to noise remains a widespread and serious health hazard in the U.S. mining industries despite 25 years of regulation. Every day, 80% of the nation's miners go to work in an environment where the time weighted average (TWA) noise level exceeds 85 dBA and more than 25% of the miners are exposed to a TWA noise level that exceeds 90 dBA, the permissible exposure limit (PEL). Additionally, MSHA coal noise sample data collected from 2000 to 2002 show that 65% of the equipment whose operators exceeded 100% noise dosage comprise only seven different types of machines; auger miners, bulldozers, continuous miners, front end loaders, roof bolters, shuttle cars (electric), and trucks. In addition, the MSHA data indicate that the roof bolter is third among all the equipment and second among equipment in underground coal whose operators exceed 100% dosage. A research program was implemented to: (1) determine, characterize and to measure sound power levels radiated by a roof bolting machine during differing drilling configurations (thrust, rotational speed, penetration rate, etc.) and utilizing differing types of drilling methods in high compressive strength rock media (>20,000 psi). The research approach characterized the sound power level results from laboratory testing and provided the mining industry with empirical data relative to utilizing differing noise control technologies (drilling configurations and types of drilling methods) in reducing sound power level emissions on a roof bolting machine; (2) distinguish and correlate the empirical data into one, statistically valid, equation, in which, provided the mining industry with a tool to predict overall sound power levels of a roof bolting machine given any type of drilling configuration and drilling method utilized in industry; (3) provided the mining industry with several approaches to predict or determine sound pressure levels in an underground coal mine utilizing laboratory test results from a roof bolting

  8. Optimization approaches to nonlinear model predictive control

    SciTech Connect

    Biegler, L.T. . Dept. of Chemical Engineering); Rawlings, J.B. . Dept. of Chemical Engineering)

    1991-01-01

    With the development of sophisticated methods for nonlinear programming and powerful computer hardware, it now becomes useful and efficient to formulate and solve nonlinear process control problems through on-line optimization methods. This paper explores and reviews control techniques based on repeated solution of nonlinear programming (NLP) problems. Here several advantages present themselves. These include minimization of readily quantifiable objectives, coordinated and accurate handling of process nonlinearities and interactions, and systematic ways of dealing with process constraints. We motivate this NLP-based approach with small nonlinear examples and present a basic algorithm for optimization-based process control. As can be seen this approach is a straightforward extension of popular model-predictive controllers (MPCs) that are used for linear systems. The statement of the basic algorithm raises a number of questions regarding stability and robustness of the method, efficiency of the control calculations, incorporation of feedback into the controller and reliable ways of handling process constraints. Each of these will be treated through analysis and/or modification of the basic algorithm. To highlight and support this discussion, several examples are presented and key results are examined and further developed. 74 refs., 11 figs.

  9. Predictive sensor method and apparatus

    NASA Technical Reports Server (NTRS)

    Cambridge, Vivien J.; Koger, Thomas L.

    1993-01-01

    A microprocessor and electronics package employing predictive methodology was developed to accelerate the response time of slowly responding hydrogen sensors. The system developed improved sensor response time from approximately 90 seconds to 8.5 seconds. The microprocessor works in real-time providing accurate hydrogen concentration corrected for fluctuations in sensor output resulting from changes in atmospheric pressure and temperature. Following the successful development of the hydrogen sensor system, the system and predictive methodology was adapted to a commercial medical thermometer probe. Results of the experiment indicate that, with some customization of hardware and software, response time improvements are possible for medical thermometers as well as other slowly responding sensors.

  10. Controlling and Predicting Unpredictable Behavior.

    PubMed

    de Souza Barba, Lourenço

    2015-05-01

    Behaving predictably can be advantageous in some situations, but unpredictability can also be advantageous in some competitive situations like sports, games, and war. Can, however, unpredictable behavior be conditioned? If a contingency of reinforcement based upon the predictability of behavior generates unpredictable responding, is it possible to conclude that predictability is itself a reinforceable dimension of behavior? In this paper, I address these questions by examining the concept and measures of predictability and the procedures generally used to increase unpredictable responding. I discuss the hypothesis that contingencies based on response frequency shape the generalized operant "to vary" and an alternative hypothesis that such contingencies generate unpredictable responding by balancing the strength of each alternative response over time. I discuss the findings that support the balance hypothesis as well as its limitations. I conclude that the two alternative hypotheses may be complementary in explaining unpredictable responding. PMID:27606162

  11. Predicting survival in heart failure case and control subjects by use of fully automated methods for deriving nonlinear and conventional indices of heart rate dynamics

    NASA Technical Reports Server (NTRS)

    Ho, K. K.; Moody, G. B.; Peng, C. K.; Mietus, J. E.; Larson, M. G.; Levy, D.; Goldberger, A. L.

    1997-01-01

    BACKGROUND: Despite much recent interest in quantification of heart rate variability (HRV), the prognostic value of conventional measures of HRV and of newer indices based on nonlinear dynamics is not universally accepted. METHODS AND RESULTS: We have designed algorithms for analyzing ambulatory ECG recordings and measuring HRV without human intervention, using robust methods for obtaining time-domain measures (mean and SD of heart rate), frequency-domain measures (power in the bands of 0.001 to 0.01 Hz [VLF], 0.01 to 0.15 Hz [LF], and 0.15 to 0.5 Hz [HF] and total spectral power [TP] over all three of these bands), and measures based on nonlinear dynamics (approximate entropy [ApEn], a measure of complexity, and detrended fluctuation analysis [DFA], a measure of long-term correlations). The study population consisted of chronic congestive heart failure (CHF) case patients and sex- and age-matched control subjects in the Framingham Heart Study. After exclusion of technically inadequate studies and those with atrial fibrillation, we used these algorithms to study HRV in 2-hour ambulatory ECG recordings of 69 participants (mean age, 71.7+/-8.1 years). By use of separate Cox proportional-hazards models, the conventional measures SD (P<.01), LF (P<.01), VLF (P<.05), and TP (P<.01) and the nonlinear measure DFA (P<.05) were predictors of survival over a mean follow-up period of 1.9 years; other measures, including ApEn (P>.3), were not. In multivariable models, DFA was of borderline predictive significance (P=.06) after adjustment for the diagnosis of CHF and SD. CONCLUSIONS: These results demonstrate that HRV analysis of ambulatory ECG recordings based on fully automated methods can have prognostic value in a population-based study and that nonlinear HRV indices may contribute prognostic value to complement traditional HRV measures.

  12. Protein Residue Contacts and Prediction Methods

    PubMed Central

    Adhikari, Badri

    2016-01-01

    In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch. In this chapter, we briefly discuss many elements of protein residue–residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. PMID:27115648

  13. Method of controlling injector

    SciTech Connect

    Ito, S.; Minoura, M.

    1989-01-17

    This patent describes a method of controlling a fuel injector intermittently injecting liquid fuel to an engine comprising the steps of supplying a pulse signal to an actuator for reciprocating a valve body, varying the stroke of the valve body by a voltage signal applied to a stroke limiting member; changing the width of the pulse signal to thereby control the open time of the injector, and varying the voltage applied to the stroke limiting member to thereby control the stroke of the valve body.

  14. Protein structure prediction using hybrid AI methods

    SciTech Connect

    Guan, X.; Mural, R.J.; Uberbacher, E.C.

    1993-11-01

    This paper describes a new approach for predicting protein structures based on Artificial Intelligence methods and genetic algorithms. We combine nearest neighbor searching algorithms, neural networks, heuristic rules and genetic algorithms to form an integrated system to predict protein structures from their primary amino acid sequences. First we describe our methods and how they are integrated, and then apply our methods to several protein sequences. The results are very close to the real structures obtained by crystallography. Parallel genetic algorithms are also implemented.

  15. A Robustly Stabilizing Model Predictive Control Algorithm

    NASA Technical Reports Server (NTRS)

    Ackmece, A. Behcet; Carson, John M., III

    2007-01-01

    A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

  16. THE PREDICTIVE POWER OF OHL'S PRECURSOR METHOD

    SciTech Connect

    Du, Z. L.; Wang, H. N.; Li, R.

    2009-12-15

    Using linear regression techniques and correlation analysis, the predictive power of Ohl's method is shown to satisfy one of the following relationships. Either a successful prediction of cycle amplitude can be obtained if the correlation between the minimum aa geomagnetic index in the declining phase of a solar cycle and the sunspot maximum of the succeeding cycle becomes stronger, or the prediction error exceeds the expected prediction error if the correlation becomes weaker. The correlation coefficient has a declining secular variation, which leads to a weakening trend in predictive power, as well as a 44 year periodicity that may explain why the prediction method did not work well for solar cycle 23. As this finding only emerged twice in the {approx}100 year period studied, this 44 year periodicity may occur with a degree of uncertainty and may therefore need to be checked in the future. Two quantities, namely a prediction parameter and the prediction index, are proposed to analyze predictive power. Using the above properties, the success probability of a prediction result can be analyzed in advance.

  17. Prediction, Control and the Challenge to Complexity

    ERIC Educational Resources Information Center

    Radford, Mike

    2008-01-01

    The dominant discourse in research, management and teaching is one that may loosely be characterised as that of prediction and control. The objective of research is to identify causal correlations within policy, management, teaching strategies and educational outcomes that are sufficiently robust as to be able to predict outcomes and make…

  18. Automatic transmission control method

    SciTech Connect

    Hasegawa, H.; Ishiguro, T.

    1989-07-04

    This patent describes a method of controlling an automatic transmission of an automotive vehicle. The transmission has a gear train which includes a brake for establishing a first lowest speed of the transmission, the brake acting directly on a ring gear which meshes with a pinion, the pinion meshing with a sun gear in a planetary gear train, the ring gear connected with an output member, the sun gear being engageable and disengageable with an input member of the transmission by means of a clutch. The method comprises the steps of: detecting that a shift position of the automatic transmission has been shifted to a neutral range; thereafter introducing hydraulic pressure to the brake if present vehicle velocity is below a predetermined value, whereby the brake is engaged to establish the first lowest speed; and exhausting hydraulic pressure from the brake if present vehicle velocity is higher than a predetermined value, whereby the brake is disengaged.

  19. Method of turbocharger control

    SciTech Connect

    Lyon, K.M.

    1990-10-09

    This patent describes a method of turbocharger control in a vehicle having an engine and a turbocharger for increasing the density of at least the air entering a cylinder of the engine. The turbocharger has at least a compressor and a turbine coupled by a shaft and a nozzle to increase the angular momentum of the flow of gas to the turbine. The nozzle has a housing and movable vanes to vary the angle and velocity that the exhaust gas hits the wheel of the turbine, and actuator for moving the vanes, a can separated by a diaphragm and having an A side and B side for actuating the actuator, solenoid-actuated valves for controlling the pressure in the A and B sides of the can, an electronic control unit (ECU) having memory for storing data and predetermined values and for actuating and de-actuating the solenoid-actuated valves, a plurality of inputs to the ECU for providing input data indicative of engine temperature, engine speed, vehicle speed, intake manifold pressure, throttle angle, engine knock and charge air temperature.

  20. Hierarchical Ensemble Methods for Protein Function Prediction

    PubMed Central

    2014-01-01

    Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

  1. Robust predictive cruise control for commercial vehicles

    NASA Astrophysics Data System (ADS)

    Junell, Jaime; Tumer, Kagan

    2013-10-01

    In this paper we explore learning-based predictive cruise control and the impact of this technology on increasing fuel efficiency for commercial trucks. Traditional cruise control is wasteful when maintaining a constant velocity over rolling hills. Predictive cruise control (PCC) is able to look ahead at future road conditions and solve for a cost-effective course of action. Model- based controllers have been implemented in this field but cannot accommodate many complexities of a dynamic environment which includes changing road and vehicle conditions. In this work, we focus on incorporating a learner into an already successful model- based predictive cruise controller in order to improve its performance. We explore back propagating neural networks to predict future errors then take actions to prevent said errors from occurring. The results show that this approach improves the model based PCC by up to 60% under certain conditions. In addition, we explore the benefits of classifier ensembles to further improve the gains due to intelligent cruise control.

  2. Cephalometric methods of prediction in orthognathic surgery.

    PubMed

    Kolokitha, Olga-Elpis; Topouzelis, Nikolaos

    2011-09-01

    Over the past decade the growing number of adult patients seeking for orthodontic treatment made orthognathic surgery popular. Surgical and orthodontic techniques have developed to the point where combined orthodontic and surgical treatment is now feasible to manage dentofacial deformity problems very satisfactorily. The prediction of orthognathic treatment outcome is an important part of orthognathic planning and the process of patient' inform consent. The predicted results must be presented to the patients prior to treatment in order to assess the treatment's feasibility, optimize case management and increase patient understanding and acceptance of the recommended treatment. Cephalometrics is a routine part of the diagnosis and treatment planning process and also allows the clinician to evaluate changes following orthognathic surgery. Traditionally cephalometry has been employed manually; nowadays computerized cephalometric systems are very popular. Cephalometric prediction in orthognathic surgery can be done manually or by computers, using several currently available software programs, alone or in combination with video images. Both manual and computerized cephalometric prediction methods are two-dimensional and cannot fully describe three-dimensional phenomena. Today, three-dimensional prediction methods are available, such as three-dimensional computerized tomography (3DCT), 3D magnetic resonance imaging (3DMRI) and surface scan/cone-beam CT. The aim of this article is to present and discuss the different methods of cephalometric prediction of the orthognathic surgery outcome.

  3. Effectiveness of computational methods in haplotype prediction.

    PubMed

    Xu, Chun-Fang; Lewis, Karen; Cantone, Kathryn L; Khan, Parveen; Donnelly, Christine; White, Nicola; Crocker, Nikki; Boyd, Pete R; Zaykin, Dmitri V; Purvis, Ian J

    2002-02-01

    Haplotype analysis has been used for narrowing down the location of disease-susceptibility genes and for investigating many population processes. Computational algorithms have been developed to estimate haplotype frequencies and to predict haplotype phases from genotype data for unrelated individuals. However, the accuracy of such computational methods needs to be evaluated before their applications can be advocated. We have experimentally determined the haplotypes at two loci, the N-acetyltransferase 2 gene ( NAT2, 850 bp, n=81) and a 140-kb region on chromosome X ( n=77), each consisting of five single nucleotide polymorphisms (SNPs). We empirically evaluated and compared the accuracy of the subtraction method, the expectation-maximization (EM) method, and the PHASE method in haplotype frequency estimation and in haplotype phase prediction. Where there was near complete linkage disequilibrium (LD) between SNPs (the NAT2 gene), all three methods provided effective and accurate estimates for haplotype frequencies and individual haplotype phases. For a genomic region in which marked LD was not maintained (the chromosome X locus), the computational methods were adequate in estimating overall haplotype frequencies. However, none of the methods was accurate in predicting individual haplotype phases. The EM and the PHASE methods provided better estimates for overall haplotype frequencies than the subtraction method for both genomic regions.

  4. Launch ascent guidance by discrete multi-model predictive control

    NASA Astrophysics Data System (ADS)

    Vachon, Alexandre; Desbiens, André; Gagnon, Eric; Bérard, Caroline

    2014-02-01

    This paper studies the application of discrete multi-model predictive control as a trajectory tracking guidance law for a space launcher. Two different algorithms are developed, each one based on a different representation of launcher translation dynamics. These representations are based on an interpolation of the linear approximation of nonlinear pseudo-five degrees of freedom equations of translation around an elliptical Earth. The interpolation gives a linear-time-varying representation and a linear-fractional representation. They are used as the predictive model of multi-model predictive controllers. The controlled variables are the orbital parameters, and constraints on a terminal region for the minimal accepted precision are also included. Use of orbital parameters as the controlled variables allows for a partial definition of the trajectory. Constraints can also be included in multi-model predictive control to reduce the number of unknowns of the problem by defining input shaping constraints. The guidance algorithms are tested in nominal conditions and off-nominal conditions with uncertainties on the thrust. The results are compared to those of a similar formulation with a nonlinear model predictive controller and to a guidance method based on the resolution of a simplified version of the two-point boundary value problem. In nominal conditions, the model predictive controllers are more precise and produce a more optimal trajectory but are longer to compute than the two-point boundary solution. Moreover, in presence of uncertainties, developed algorithms exhibit poor robustness properties. The multi-model predictive control algorithms do not reach the desired orbit while the nonlinear model predictive control algorithm still converges but produces larger maneuvers than the other method.

  5. Fuzzy Predictive Control Strategy in the Application of the Industrial Furnace Temperature Control

    NASA Astrophysics Data System (ADS)

    Dai, Luping; Chen, Xingliang; Chen, Liu; Liu, Xia

    Ceramic kiln with large heat capacity, big lag and nonlinear characteristic, this paper proposes a combining fuzzy control and predictive control of the control algorithm, to enhance the tracking and anti-interference ability of the algorithm. The simulation results show, this method compared with the control of PID has the high steady precision and dynamic characteristic.

  6. Neural predictive control for active buffet alleviation

    NASA Astrophysics Data System (ADS)

    Pado, Lawrence E.; Lichtenwalner, Peter F.; Liguore, Salvatore L.; Drouin, Donald

    1998-06-01

    The adaptive neural control of aeroelastic response (ANCAR) and the affordable loads and dynamics independent research and development (IRAD) programs at the Boeing Company jointly examined using neural network based active control technology for alleviating undesirable vibration and aeroelastic response in a scale model aircraft vertical tail. The potential benefits of adaptive control includes reducing aeroelastic response associated with buffet and atmospheric turbulence, increasing flutter margins, and reducing response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and thus loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Wind tunnel tests were undertaken on a rigid 15% scale aircraft in Boeing's mini-speed wind tunnel, which is used for testing at very low air speeds up to 80 mph. The model included a dynamically scaled flexible fail consisting of an aluminum spar with balsa wood cross sections with a hydraulically powered rudder. Neural predictive control was used to actuate the vertical tail rudder in response to strain gauge feedback to alleviate buffeting effects. First mode RMS strain reduction of 50% was achieved. The neural predictive control system was developed and implemented by the Boeing Company to provide an intelligent, adaptive control architecture for smart structures applications with automated synthesis, self-optimization, real-time adaptation, nonlinear control, and fault tolerance capabilities. It is designed to solve complex control problems though a process of automated synthesis, eliminating costly control design and surpassing it in many instances by accounting for real world non-linearities.

  7. Hybrid robust predictive optimization method of power system dispatch

    DOEpatents

    Chandra, Ramu Sharat; Liu, Yan; Bose, Sumit; de Bedout, Juan Manuel

    2011-08-02

    A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

  8. Model predictive torque control with an extended prediction horizon for electrical drive systems

    NASA Astrophysics Data System (ADS)

    Wang, Fengxiang; Zhang, Zhenbin; Kennel, Ralph; Rodríguez, José

    2015-07-01

    This paper presents a model predictive torque control method for electrical drive systems. A two-step prediction horizon is achieved by considering the reduction of the torque ripples. The electromagnetic torque and the stator flux error between predicted values and the references, and an over-current protection are considered in the cost function design. The best voltage vector is selected by minimising the value of the cost function, which aims to achieve a low torque ripple in two intervals. The study is carried out experimentally. The results show that the proposed method achieves good performance in both steady and transient states.

  9. Composite predictive flight control for airbreathing hypersonic vehicles

    NASA Astrophysics Data System (ADS)

    Yang, Jun; Zhao, Zhenhua; Li, Shihua; Zheng, Wei Xing

    2014-09-01

    The robust optimised tracking control problem for a generic airbreathing hypersonic vehicle (AHV) subject to nonvanishing mismatched disturbances/uncertainties is investigated in this paper. A baseline nonlinear model predictive control (MPC) method is firstly introduced for optimised tracking control of the nominal dynamics. A nonlinear-disturbance-observer-based control law is then developed for robustness enhancement in the presence of both external disturbances and uncertainties. Compared with the existing robust tracking control methods for AHVs, the proposed composite nonlinear MPC method obtains not only promising robustness and disturbance rejection performance but also optimised nominal tracking control performance. The merits of the proposed method are validated by implementing simulation studies on the AHV system.

  10. Adaptive method for electron bunch profile prediction

    SciTech Connect

    Scheinker, Alexander; Gessner, Spencer

    2015-10-01

    We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial control system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.

  11. Neural network learning of optimal Kalman prediction and control.

    PubMed

    Linsker, Ralph

    2008-11-01

    Although there are many neural network (NN) algorithms for prediction and for control, and although methods for optimal estimation (including filtering and prediction) and for optimal control in linear systems were provided by Kalman in 1960 (with nonlinear extensions since then), there has been, to my knowledge, no NN algorithm that learns either Kalman prediction or Kalman control (apart from the special case of stationary control). Here we show how optimal Kalman prediction and control (KPC), as well as system identification, can be learned and executed by a recurrent neural network composed of linear-response nodes, using as input only a stream of noisy measurement data. The requirements of KPC appear to impose significant constraints on the allowed NN circuitry and signal flows. The NN architecture implied by these constraints bears certain resemblances to the local-circuit architecture of mammalian cerebral cortex. We discuss these resemblances, as well as caveats that limit our current ability to draw inferences for biological function. It has been suggested that the local cortical circuit (LCC) architecture may perform core functions (as yet unknown) that underlie sensory, motor, and other cortical processing. It is reasonable to conjecture that such functions may include prediction, the estimation or inference of missing or noisy sensory data, and the goal-driven generation of control signals. The resemblances found between the KPC NN architecture and that of the LCC are consistent with this conjecture.

  12. Wind farms production: Control and prediction

    NASA Astrophysics Data System (ADS)

    El-Fouly, Tarek Hussein Mostafa

    Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect

  13. A novel trajectory prediction control for proximate time-optimal digital control DC—DC converters

    NASA Astrophysics Data System (ADS)

    Qing, Wang; Ning, Chen; Shen, Xu; Weifeng, Sun; Longxing, Shi

    2014-09-01

    The purpose of this paper is to present a novel trajectory prediction method for proximate time-optimal digital control DC—DC converters. The control method provides pre-estimations of the duty ratio in the next several switching cycles, so as to compensate the computational time delay of the control loop and increase the control loop bandwidth, thereby improving the response speed. The experiment results show that the fastest transient response time of the digital DC—DC with the proposed prediction is about 8 μs when the load current changes from 0.6 to 0.1 A.

  14. Real-time Adaptive Control Using Neural Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  15. Voltage control in pulsed system by predict-ahead control

    DOEpatents

    Payne, Anthony N.; Watson, James A.; Sampayan, Stephen E.

    1994-01-01

    A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load.

  16. Voltage control in pulsed system by predict-ahead control

    DOEpatents

    Payne, A.N.; Watson, J.A.; Sampayan, S.E.

    1994-09-13

    A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load. 4 figs.

  17. Airframe Noise Prediction Using the Sngr Method

    NASA Astrophysics Data System (ADS)

    Chen, Rongqian; Wu, Yizhao; Xia, Jian

    In this paper, the Stochastic Noise Generation and Radiation method (SNGR) is used to predict airframe noise. The SNGR method combines a stochastic model with Computational Fluid Dynamics (CFD), and it can give acceptable noise results while the computation cost is relatively low. In the method, the time-averaged mean flow field is firstly obtained by solving Reynolds Averaged Navier-Stokes equations (RANS), and a stochastic velocity is generated based on the obtained information. Then the turbulent field is used to generate the source for the Acoustic Perturbation Equations (APEs) that simulate the noise propagation. For numerical methods, timeaveraged RANS equations are solved by finite volume method, and the turbulent model is K - ɛ model; APEs are solved by finite difference method, and the numerical scheme is the Dispersion-Relation-Preserving (DRP) scheme, with explicit optimized 5-stage Rung-Kutta scheme time step. In order to test the APE solver, propagation of a Gaussian pulse in a uniform mean flow is firstly simulated and compared with the analytical solution. Then, using the method, the trailing edge noise of NACA0012 airfoil is calculated. The results are compared with reference data, and good agreements are demonstrated.

  18. Method for controlling brazing

    DOEpatents

    Hosking, F. Michael; Hall, Aaron C.; Givler, Richard C.; Walker, Charles A.

    2006-08-01

    A method for making a braze joint across a discontinuity in a work piece using alternating current. A filler metal is pre-placed at a location sufficiently close to the discontinuity such that, when an alternating current is applied across a work piece to heat the work piece and melt the filler metal, the filler metal is drawn into the discontinuity. The alternating current is maintained for a set residence time, generally less than 10 seconds and more particularly less than 3 seconds. The alternating current is then altered, generally by reducing the current and/or voltage such that the filler metal can solidify to form a braze joint of desired quality and thickness.

  19. Computational predictive methods for fracture and fatigue

    NASA Astrophysics Data System (ADS)

    Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.

    1994-09-01

    The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.

  20. Computational predictive methods for fracture and fatigue

    NASA Technical Reports Server (NTRS)

    Cordes, J.; Chang, A. T.; Nelson, N.; Kim, Y.

    1994-01-01

    The damage-tolerant design philosophy as used by aircraft industries enables aircraft components and aircraft structures to operate safely with minor damage, small cracks, and flaws. Maintenance and inspection procedures insure that damages developed during service remain below design values. When damage is found, repairs or design modifications are implemented and flight is resumed. Design and redesign guidelines, such as military specifications MIL-A-83444, have successfully reduced the incidence of damage and cracks. However, fatigue cracks continue to appear in aircraft well before the design life has expired. The F16 airplane, for instance, developed small cracks in the engine mount, wing support, bulk heads, the fuselage upper skin, the fuel shelf joints, and along the upper wings. Some cracks were found after 600 hours of the 8000 hour design service life and design modifications were required. Tests on the F16 plane showed that the design loading conditions were close to the predicted loading conditions. Improvements to analytic methods for predicting fatigue crack growth adjacent to holes, when multiple damage sites are present, and in corrosive environments would result in more cost-effective designs, fewer repairs, and fewer redesigns. The overall objective of the research described in this paper is to develop, verify, and extend the computational efficiency of analysis procedures necessary for damage tolerant design. This paper describes an elastic/plastic fracture method and an associated fatigue analysis method for damage tolerant design. Both methods are unique in that material parameters such as fracture toughness, R-curve data, and fatigue constants are not required. The methods are implemented with a general-purpose finite element package. Several proof-of-concept examples are given. With further development, the methods could be extended for analysis of multi-site damage, creep-fatigue, and corrosion fatigue problems.

  1. Current methods for predicting human food effect.

    PubMed

    Lentz, Kimberley A

    2008-06-01

    Food can impact the pharmacokinetics of a drug product through several mechanisms, including but not limited to, enhancement in drug solubility, changes in GI physiology, or direct interaction with the drug. Significant food effects complicate development of new drugs, especially when clinical plans require control and/or monitoring of food intake in relation to dosing. The prediction of whether a drug or drug product will show a human food effect is challenging. In vitro models which consider physical-chemical properties can classify the potential for a compound to demonstrate a positive, negative or no food effect, and may be appropriate for screening compounds at early stages of drug discovery. When comparing various formulations, dissolution tests in biorelevant media can serve as a predictor of human drug performance under fasted and fed conditions. Few in vivo models exist which predict the magnitude of change in pharmacokinetic parameters in humans when dosing in the presence of food, with the dog appearing to be the most studied species for this purpose. Control of gastric pH, as well as the amount and composition of the fed state in dogs are critical parameters to improving the predictability of the dog overall as a food effect model. No single universal model is applicable for all drugs at all stages of drug development. One or more models may be required depending whether the goal is to assess potential for a food effect, determine the magnitude of change in pharmacokinetic parameters in the fed/fasted state, or whether formulation efforts have the ability to mitigate an observed food effect.

  2. Method of controlling gene expression

    DOEpatents

    Peters, Norman K.; Frost, John W.; Long, Sharon R.

    1991-12-03

    A method of controlling expression of a DNA segment under the control of a nod gene promoter which comprises administering to a host containing a nod gene promoter an amount sufficient to control expression of the DNA segment of a compound of the formula: ##STR1## in which each R is independently H or OH, is described.

  3. Optimal Control of Distributed Energy Resources using Model Predictive Control

    SciTech Connect

    Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen

    2012-07-22

    In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.

  4. Systems and methods for predicting materials properties

    DOEpatents

    Ceder, Gerbrand; Fischer, Chris; Tibbetts, Kevin; Morgan, Dane; Curtarolo, Stefano

    2007-11-06

    Systems and methods for predicting features of materials of interest. Reference data are analyzed to deduce relationships between the input data sets and output data sets. Reference data includes measured values and/or computed values. The deduced relationships can be specified as equations, correspondences, and/or algorithmic processes that produce appropriate output data when suitable input data is used. In some instances, the output data set is a subset of the input data set, and computational results may be refined by optionally iterating the computational procedure. To deduce features of a new material of interest, a computed or measured input property of the material is provided to an equation, correspondence, or algorithmic procedure previously deduced, and an output is obtained. In some instances, the output is iteratively refined. In some instances, new features deduced for the material of interest are added to a database of input and output data for known materials.

  5. A nozzle internal performance prediction method

    NASA Technical Reports Server (NTRS)

    Carlson, John R.

    1992-01-01

    A prediction method was written and incorporated into a three-dimensional Navier-Stokes code (PAB3D) for the calculation of nozzle internal performance. The following quantities are calculated: (1) discharge coefficient; (2) normal, side, and axial thrust ratios; (3) rolling, pitching, and yawing moments; and (4) effective pitch and yaw vector angles. Four different case studies are presented to confirm the applicability of the methodology. Internal and, in most situations, external flow-field regions are required to be modeled. The computed nozzle discharge coefficient matches both the level and the trend of the experimental data within quoted experimental data accuracy (0.5 percent). Moment and force ratios are generally within 1 to 2 percent of the absolute level of experimental data, with the trends of data matched accurately.

  6. The predictive protective control of the heat exchanger

    NASA Astrophysics Data System (ADS)

    Nevriva, Pavel; Filipova, Blanka; Vilimec, Ladislav

    2016-06-01

    The paper deals with the predictive control applied to flexible cogeneration energy system FES. FES was designed and developed by the VITKOVICE POWER ENGINEERING joint-stock company and represents a new solution of decentralized cogeneration energy sources. In FES, the heating medium is flue gas generated by combustion of a solid fuel. The heated medium is power gas, which is a gas mixture of air and water steam. Power gas is superheated in the main heat exchanger and led to gas turbines. To protect the main heat exchanger against damage by overheating, the novel predictive protective control based on the mathematical model of exchanger was developed. The paper describes the principle, the design and the simulation of the predictive protective method applied to main heat exchanger of FES.

  7. Mode Decomposition Methods for Soil Moisture Prediction

    NASA Astrophysics Data System (ADS)

    Jana, R. B.; Efendiev, Y. R.; Mohanty, B.

    2014-12-01

    Lack of reliable, well-distributed, long-term datasets for model validation is a bottle-neck for most exercises in soil moisture analysis and prediction. Understanding what factors drive soil hydrological processes at different scales and their variability is very critical to further our ability to model the various components of the hydrologic cycle more accurately. For this, a comprehensive dataset with measurements across scales is very necessary. Intensive fine-resolution sampling of soil moisture over extended periods of time is financially and logistically prohibitive. Installation of a few long term monitoring stations is also expensive, and needs to be situated at critical locations. The concept of Time Stable Locations has been in use for some time now to find locations that reflect the mean values for the soil moisture across the watershed under all wetness conditions. However, the soil moisture variability across the watershed is lost when measuring at only time stable locations. We present here a study using techniques such as Dynamic Mode Decomposition (DMD) and Discrete Empirical Interpolation Method (DEIM) that extends the concept of time stable locations to arrive at locations that provide not simply the average soil moisture values for the watershed, but also those that can help re-capture the dynamics across all locations in the watershed. As with the time stability, the initial analysis is dependent on an intensive sampling history. The DMD/DEIM method is an application of model reduction techniques for non-linearly related measurements. Using this technique, we are able to determine the number of sampling points that would be required for a given accuracy of prediction across the watershed, and the location of those points. Locations with higher energetics in the basis domain are chosen first. We present case studies across watersheds in the US and India. The technique can be applied to other hydro-climates easily.

  8. Aircraft digital control design methods

    NASA Technical Reports Server (NTRS)

    Powell, J. D.; Parsons, E.; Tashker, M. G.

    1976-01-01

    Variations in design methods for aircraft digital flight control are evaluated and compared. The methods fall into two categories; those where the design is done in the continuous domain (or s plane) and those where the design is done in the discrete domain (or z plane). Design method fidelity is evaluated by examining closed loop root movement and the frequency response of the discretely controlled continuous aircraft. It was found that all methods provided acceptable performance for sample rates greater than 10 cps except the uncompensated s plane design method which was acceptable above 20 cps. A design procedure based on optimal control methods was proposed that provided the best fidelity at very slow sample rates and required no design iterations for changing sample rates.

  9. Comparison of Predictive Modeling Methods of Aircraft Landing Speed

    NASA Technical Reports Server (NTRS)

    Diallo, Ousmane H.

    2012-01-01

    Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

  10. Predictive onboard flow control for packet switching satellites

    NASA Technical Reports Server (NTRS)

    Bobinsky, Eric A.

    1992-01-01

    We outline two alternate approaches to predicting the onset of congestion in a packet switching satellite, and argue that predictive, rather than reactive, flow control is necessary for the efficient operation of such a system. The first method discussed is based on standard, statistical techniques which are used to periodically calculate a probability of near-term congestion based on arrival rate statistics. If this probability exceeds a present threshold, the satellite would transmit a rate-reduction signal to all active ground stations. The second method discussed would utilize a neural network to periodically predict the occurrence of buffer overflow based on input data which would include, in addition to arrival rates, the distributions of packet lengths, source addresses, and destination addresses.

  11. Predictive onboard flow control in packet switching satellites

    NASA Technical Reports Server (NTRS)

    Bobinsky, E. A.

    1992-01-01

    We outline two alternate approaches to predicting the onset of congestion in a packet switching satellite, and argue that predictive, rather than reactive, flow control is necessary for the efficient operation of such a system. The first method discussed is based on standard, statistical techniques which are used to periodically calculate a probability of near-term congestion based on arrival rate statistics. If this probability exceeds a present threshold, the satellite would transmit a rate-reduction signal to all active ground stations. The second method discussed would utilize a neural network to periodically predict the occurrence of buffer overflow based on input data which would include, in addition to arrival rates, the distributions of packet lengths, source addresses, and destination addresses.

  12. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  13. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  14. Methods of Predicting Solid Waste Characteristics.

    ERIC Educational Resources Information Center

    Boyd, Gail B.; Hawkins, Myron B.

    The project summarized by this report involved a preliminary design of a model for estimating and predicting the quantity and composition of solid waste and a determination of its feasibility. The novelty of the prediction model is that it estimates and predicts on the basis of knowledge of materials and quantities before they become a part of the…

  15. Cascade generalized predictive control strategy for boiler drum level.

    PubMed

    Xu, Min; Li, Shaoyuan; Cai, Wenjian

    2005-07-01

    This paper proposes a cascade model predictive control scheme for boiler drum level control. By employing generalized predictive control structures for both inner and outer loops, measured and unmeasured disturbances can be effectively rejected, and drum level at constant load is maintained. In addition, nonminimum phase characteristic and system constraints in both loops can be handled effectively by generalized predictive control algorithms. Simulation results are provided to show that cascade generalized predictive control results in better performance than that of well tuned cascade proportional integral differential controllers. The algorithm has also been implemented to control a 75-MW boiler plant, and the results show an improvement over conventional control schemes.

  16. Development of fireside performance indices, Task 7.33, Development of methods to predict agglomeration and deposition in FBCS, Task 7.36, Enhanced air toxics control, Task 7.45

    SciTech Connect

    Zygarlicke, C.J.; Mann, M.D.; Laudal, D.L.; Miller, S.J.

    1994-01-01

    The Energy & Environmental Research Center (EERC) has been developing advanced indices that rank coals according to their fouling and slagging propensity in utility boilers. The indices are based on sophisticated analytical techniques for identifying and quantifying coal inorganics and are useful in predicting the effects of proposed operational changes on ash deposition in coal-fired boilers. These indices are intended to provide an economical way to reduce the amount of full-scale testing needed to determine the best means of minimizing ash-related problems. The successful design and operation of the fluidized-bed combustor requires the ability to control and mitigate ash-related problems. The major ash-related problems in FBC are agglomeration of bed material, ash deposition on heat-transfer surfaces, ash deposition on refractory and uncooled surfaces, corrosion, and erosion. The focus of the Development of Methods to Predict Agglomeration and Deposition in FBCs is on the agglomeration and deposition problems in atmospheric bubbling and circulating beds. The 1990 Clean Air Act Amendments require study of air toxic emissions from coal combustion systems. Since most of the toxic metals present in coal will be in particulate form, a high level of fine-particle control appears to be the best approach to achieving a high level of air toxics control. However, over 50% of mercury and a portion of selenium emissions are in vapor form and are not typically collected in particulate control devices. Therefore, the goal of this project is to develop methods that capture the vapor-phase metals while simultaneously achieving ultrahigh collection efficiency of particulate air toxics.

  17. Flutter prediction for a wing with active aileron control

    NASA Technical Reports Server (NTRS)

    Penning, K.; Sandlin, D. R.

    1983-01-01

    A method for predicting the vibrational stability of an aircraft with an analog active aileron flutter suppression system (FSS) is expained. Active aileron refers to the use of an active control system connected to the aileron to damp vibrations. Wing vibrations are sensed by accelerometers and the information is used to deflect the aileron. Aerodynamic force caused by the aileron deflection oppose wing vibrations and effectively add additional damping to the system.

  18. Security control methods for CEDR

    SciTech Connect

    Rotem, D.

    1990-09-01

    The purpose of this document is to summarize the findings of recent studies on the security problem in statistical databases and examine their applicability to the specific needs of CEDR. The document is organized as follows: In Section 2 we describe some general control methods which are available on most commercial database software. In Section 3 we provide a classification of statistical security methods. In Section 4 we analyze the type of users of CEDR and the security control methods which may be applied to each type. In Section 5 we summarize the findings of this study and recommend possible solutions.

  19. Predictive controller and estimator for NASA Deep Space Network antennas

    NASA Technical Reports Server (NTRS)

    Gawronski, W.

    1992-01-01

    A new design procedure is presented for a predictive controller that significantly improves antenna tracking performance. The predictive controller uses future values of the stored output command to generate the control signal. For antennas tracking stars or spacecraft, these values are known in advance, hence the predictive control scheme is easily implemented in this case. The predictive controller is designed for tracking control of the the NASA/JPL 70-m antenna. On-axis tracking is considered, where the output is taken on the encoder, or tachometer. Simulation results show a significant improvement in performance over the LQ controller.

  20. Prediction Methods in Solar Sunspots Cycles

    PubMed Central

    Ng, Kim Kwee

    2016-01-01

    An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle. PMID:26868269

  1. Prediction Methods in Solar Sunspots Cycles

    NASA Astrophysics Data System (ADS)

    Ng, Kim Kwee

    2016-02-01

    An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle.

  2. Predictive and Neural Predictive Control of Uncertain Systems

    NASA Technical Reports Server (NTRS)

    Kelkar, Atul G.

    2000-01-01

    Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

  3. Precise flight-path control using a predictive algorithm

    NASA Technical Reports Server (NTRS)

    Hess, R. A.; Jung, Y. C.

    1991-01-01

    Generalized predictive control describes an algorithm for the control of dynamic systems in which a control input is generated that minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. A design technique is discussed for applying the single-input/single-output generalized predictive control algorithm to a problem of longitudinal/vertical terrain-following flight of a rotorcraft. By using the generalized predictive control technique to provide inputs to a classically designed stability and control augmentation system, it is demonstrated that a robust flight-path control system can be created that exhibits excellent tracking performance.

  4. Predict octane numbers using a generalized interaction method

    SciTech Connect

    Twu, C.H.; Coon, J.E.

    1996-02-01

    An interaction-based correlation using a new approach can be used to predict research and motor octane numbers of gasoline blends. An ultimately detailed analysis of the gasoline cut is not necessary. This correlation can describe blending behavior over the entire composition range of gasoline cuts. The component-oriented interaction approach is general and will accurately predict, without performing additional blending studies, blending behavior for new gasoline cuts. The proposed correlation fits the data quite closely for blends of many gasoline cuts. The regression gives realistic values for binary interaction parameters between components. A unique set of binary interaction parameters was found for the equation for predicting octane number of any gasoline blend. The binary interaction parameters between components contained in gasoline cuts have been converted to binary interaction parameters between gasoline cuts through a general equation to simplify the calculations. Because of the proposed method`s accuracy, optimum allocation of components among gasoline grades can be obtained and predicted values can be used for quality control of the octane number of marketed gasolines.

  5. Predictive IP controller for robust position control of linear servo system.

    PubMed

    Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi

    2016-07-01

    Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme.

  6. Earthquake prediction: Simple methods for complex phenomena

    NASA Astrophysics Data System (ADS)

    Luen, Bradley

    2010-09-01

    Earthquake predictions are often either based on stochastic models, or tested using stochastic models. Tests of predictions often tacitly assume predictions do not depend on past seismicity, which is false. We construct a naive predictor that, following each large earthquake, predicts another large earthquake will occur nearby soon. Because this "automatic alarm" strategy exploits clustering, it succeeds beyond "chance" according to a test that holds the predictions _xed. Some researchers try to remove clustering from earthquake catalogs and model the remaining events. There have been claims that the declustered catalogs are Poisson on the basis of statistical tests we show to be weak. Better tests show that declustered catalogs are not Poisson. In fact, there is evidence that events in declustered catalogs do not have exchangeable times given the locations, a necessary condition for the Poisson. If seismicity followed a stochastic process, an optimal predictor would turn on an alarm when the conditional intensity is high. The Epidemic-Type Aftershock (ETAS) model is a popular point process model that includes clustering. It has many parameters, but is still a simpli_cation of seismicity. Estimating the model is di_cult, and estimated parameters often give a non-stationary model. Even if the model is ETAS, temporal predictions based on the ETAS conditional intensity are not much better than those of magnitude-dependent automatic (MDA) alarms, a much simpler strategy with only one parameter instead of _ve. For a catalog of Southern Californian seismicity, ETAS predictions again o_er only slight improvement over MDA alarms

  7. Potential Method of Predicting Coronal Mass Ejection

    NASA Astrophysics Data System (ADS)

    Imholt, Timothy; Roberts, J. A.; Scott, J. B.; University Of North Texas Team

    2000-10-01

    Coronal Mass Ejections (CME) may be described as a blast of gas and highly charged solar mass fragments ejected into space. These ejections, when directed toward Earth, have many different effects on terrestrial systems ranging from the Aurora Borealis to changes in wireless communications. The importance of an early prediction of these solar events cannot be overlooked. There are several models currently accepted and utilized to predict these events, however, with earlier prediction of both the event and the location on the sun where the event occur allows us to have earlier warnings as to when they will effect man-made systems. A better prediction could perhaps be achieved by utilizing low angular resolution radio telescope arrays to catalog data from the sun at different radio frequencies on a regular basis. Once this data is cataloged a better predictor for these CME's could be found. We propose a model that allows a prediction to be made that appears to be longer than 24 hours.

  8. Potential Method of Predicting Coronal Mass Ejection

    NASA Astrophysics Data System (ADS)

    Imholt, Timothy

    2001-10-01

    Coronal Mass Ejections (CME) may be described as a blast of gas and highly charged solar mass fragments ejected into space. These ejections, when directed toward Earth, have many different effects on terrestrial systems ranging from the Aurora Borealis to changes in wireless communication. The early prediction of these solar events cannot be overlooked. There are several models currently accepted and utilized to predict these events, however, with earlier prediction of both the event and the location on the sun where the event occurs allows us to have earlier warnings as to when they will affect man-made systems. A better prediction could perhaps be achieved by utilizing low angular resolution radio telescope arrays to catalog data from the sun at different radio frequencies on a regular basis. Once this data is cataloged a better predictor for these CME’s could be found. We propose a model that allows a prediction to be made that appears to be longer than 24 hours.

  9. Predictions for rapid methods and automation in food microbiology.

    PubMed

    Fung, Daniel Y C

    2002-01-01

    A discussion is presented on the present status of rapid methods and automation in microbiology. Predictions are also presented for development in the following areas: viable cell counts; real-time monitoring of hygiene; polymerase chain reaction, ribotyping, and genetic tests in food laboratories; automated enzyme-linked immunosorbent assay and immunotests; rapid dipstick technology; biosensors for Hazard Analysis Critical Control Point programs; instant detection of target pathogens by computer-generated matrix; effective separation and concentration for rapid identification of target cells; microbiological alert systems in food packages; and rapid alert kits for detecting pathogens at home.

  10. Multiplexed model predictive control for active vehicle suspensions

    NASA Astrophysics Data System (ADS)

    Hu, Yinlong; Chen, Michael Z. Q.; Hou, Zhongsheng

    2015-02-01

    Multiplexed model predictive control (MMPC) is a recently proposed efficient model predictive control (MPC) algorithm, which can effectively reduce the computational burden of the online optimisation in MPC implementation by updating the control inputs in an asynchronous manner. This paper investigates the application of MMPC in active vehicle suspension design. An MMPC controller integrated with soft constraints and a Kalman filter is proposed based on a full-car model. Ride comfort, roadholding and suspension deflection are considered in this paper, where ride comfort and roadholding are formulated as a quadratic cost function in terms of sprung mass accelerations and tyre deflections, while suspension deflection performance is formulated as a hard constraint. The saturation of the actuator force is also considered and formulated as a hard constraint as well. Numerical simulation is performed with respect to different choices of weighting factors, vehicle speeds and control horizons. The results show that the overall performance of ride comfort and roadholding can be improved significantly by employing MMPC and the average time taken by MMPC to solve the individual quadratic programming problem is considerably smaller than that of the conventional MPC, which effectively demonstrate the effectiveness of the proposed method.

  11. Predicting Suicide: Issues, Methods and Constraints.

    ERIC Educational Resources Information Center

    Lettieri, Dan J.

    With the proliferation of suicide prevention centers in the United States, the task of rapidly and effectively assessing an individual caller's suicide potential has become an important research problem. However, the social science researcher is often confronted with an ethical problem when the results of his predictive equations can be used to…

  12. Model predictive control for a class of systems with isolated nonlinearity.

    PubMed

    Tao, Jili; Zhu, Yong; Fan, Qinru

    2014-07-01

    The paper is concerned with an overall convergent nonlinear model predictive control design for a kind of nonlinear mechatronic drive systems. The proposed nonlinear model predictive control results in the improvement of regulatory capacity for reference tracking and load disturbance rejection. The design of the nonlinear model predictive controller consists of two steps: the first step is to design a linear model predictive controller based on the linear part of the system at each sample instant, then an overall convergent nonlinear part is added to the linear model predictive controller to combine a nonlinear controller using error driven. The structure of the proposed controller is similar to that of classical PI optimal regulator but it also bears a set-point feed forward control loop, thus tracking ability and disturbance rejection are improved. The proposed method is compared with the results from recent literature, where control performance under both model match and mismatch cases are enlightened. PMID:24755053

  13. Method for controlling powertrain pumps

    DOEpatents

    Sime, Karl Andrew; Spohn, Brian L; Demirovic, Besim; Martini, Ryan D; Miller, Jean Marie

    2013-10-22

    A method of controlling a pump supplying a fluid to a transmission includes sensing a requested power and an excess power for a powertrain. The requested power substantially meets the needs of the powertrain, while the excess power is not part of the requested power. The method includes sensing a triggering condition in response to the ability to convert the excess power into heat in the transmission, and determining that an operating temperature of the transmission is below a maximum. The method also includes determining a calibrated baseline and a dissipation command for the pump. The calibrated baseline command is configured to supply the fluid based upon the requested power, and the dissipation command is configured to supply additional fluid and consume the excess power with the pump. The method operates the pump at a combined command, which is equal to the calibrated baseline command plus the dissipation command.

  14. Predicting Hepatic Steatosis in Living Liver Donors via Noninvasive Methods.

    PubMed

    Kim, Jong Man; Ha, Sang Yun; Joh, Jae-Won; Sinn, Dong Hyun; Jeong, Woo Kyung; Choi, Gyu-Seong; Gwak, Geum Youn; Kwon, Choon Hyuck David; Kim, Young Kon; Paik, Yong Han; Lee, Joon Hyeok; Lee, Won Jae; Lee, Suk-Koo; Park, Cheol Keun

    2016-02-01

    Hepatic steatosis assessment is of paramount importance for living liver donor selection because significant hepatic steatosis can affect the postoperative outcome of recipients and the safety of the donor. The validity of various noninvasive imaging methods to assess hepatic steatosis remains controversial. The purpose of our study is to investigate the association between noninvasive imaging methods and pathology to detect steatosis in living liver donors and to propose a prediction model for hepatic steatosis. Liver stiffness measurements (LSMs) and controlled attenuation parameter values in vibration controlled transient elastography, ultrasonography, computed tomography (CT), and magnetic resonance imaging were used as pretransplant screening methods to evaluate living liver donors between 2012 and 2014. Only 1 pathologist assessed tissue sample for hepatic steatosis. The median age of the 79 living donors (53 men and 26 women) was 32 years (16-68 years). The CT liver-spleen attenuation (L-S) difference and the controlled attenuation parameter values were well correlated with the level of hepatic steatosis on liver pathology. Multivariate analysis showed that liver stiffness measurement (LSM) (β = 0.903; 95% CI, 0.105-1.702; P = 0.027) and the CT L to S attenuation difference (β = -3.322; 95% CI, -0.502 to -0.142; P = 0.001) were closely associated with hepatic steatosis. We generated the following equation to predict total hepatic steatosis: Hepatic steatosis = 0.903 × LSM - 0.322 × CT L to S attenuation difference (AUC = 86.6% and P = 0.001). The values predicted by the equation correlated well with the presence of hepatic steatosis (r = 0.509 and P < 0.001). The combination of nonenhanced CT L to S attenuation difference and transient elastography using vibration controlled transient elastography provides sufficient information to predict hepatic steatosis in living liver donor candidates. PMID:26886612

  15. Predicting Hepatic Steatosis in Living Liver Donors via Noninvasive Methods

    PubMed Central

    Kim, Jong Man; Ha, Sang Yun; Joh, Jae-Won; Sinn, Dong Hyun; Jeong, Woo Kyung; Choi, Gyu-Seong; Gwak, Geum Youn; Kwon, Choon Hyuck David; Kim, Young Kon; Paik, Yong Han; Lee, Joon Hyeok; Lee, Won Jae; Lee, Suk-Koo; Park, Cheol Keun

    2016-01-01

    Abstract Hepatic steatosis assessment is of paramount importance for living liver donor selection because significant hepatic steatosis can affect the postoperative outcome of recipients and the safety of the donor. The validity of various noninvasive imaging methods to assess hepatic steatosis remains controversial. The purpose of our study is to investigate the association between noninvasive imaging methods and pathology to detect steatosis in living liver donors and to propose a prediction model for hepatic steatosis. Liver stiffness measurements (LSMs) and controlled attenuation parameter values in vibration controlled transient elastography, ultrasonography, computed tomography (CT), and magnetic resonance imaging were used as pretransplant screening methods to evaluate living liver donors between 2012 and 2014. Only 1 pathologist assessed tissue sample for hepatic steatosis. The median age of the 79 living donors (53 men and 26 women) was 32 years (16–68 years). The CT liver–spleen attenuation (L–S) difference and the controlled attenuation parameter values were well correlated with the level of hepatic steatosis on liver pathology. Multivariate analysis showed that liver stiffness measurement (LSM) (β = 0.903; 95% CI, 0.105–1.702; P = 0.027) and the CT L to S attenuation difference (β = −3.322; 95% CI, −0.502 to −0.142; P = 0.001) were closely associated with hepatic steatosis. We generated the following equation to predict total hepatic steatosis: Hepatic steatosis = 0.903 × LSM – 0.322 × CT L to S attenuation difference (AUC = 86.6% and P = 0.001). The values predicted by the equation correlated well with the presence of hepatic steatosis (r = 0.509 and P < 0.001). The combination of nonenhanced CT L to S attenuation difference and transient elastography using vibration controlled transient elastography provides sufficient information to predict hepatic steatosis in living liver donor

  16. Predictive powertrain control using powertrain history and GPS data

    SciTech Connect

    Weslati, Feisel; Krupadanam, Ashish A

    2015-03-03

    A method and powertrain apparatus that predicts a route of travel for a vehicle and uses historical powertrain loads and speeds for the predicted route of travel to optimize at least one powertrain operation for the vehicle.

  17. Recent methods for predicting quality of whole meat.

    PubMed

    Monin, G

    1998-01-01

    The world of meat faces a permanent need for new methods of meat quality evaluation. Researchers want improved techniques to deepen their understanding of meat features. Expectations of consumers for meat quality grow constantly, which induces the necessity of quality control at the levels of slaughtering, meat cutting, and distribution. This article is focused on techniques intended to predict technological and sensory qualities from measurements carried out on fresh intact meat. pH has been measured for a long time, but its on-line determination still progresses through automation. In the laboratory, NMR provides new insights on WHC mechanisms. Image processing has considerably improved the assessment of meat appearance. Developments of techniques for prediction of toughness are in progress, either directly, through ultrasonic analysis or NIR reflectance, or indirectly, through determination of connective tissue content by fluorescence probes. Control of authenticity benefits from the last developments of molecular biology and analytical chemistry. However, implementation of methods for meat quality evaluation has been very limited in the industry. The reasons for that situation are analyzed. Among the techniques recently described, the most promising for large-scale meat quality evaluation are considered to be ultrasonic analysis, image processing and NIR spectroscopy.

  18. Control method for prosthetic devices

    NASA Technical Reports Server (NTRS)

    Bozeman, Richard J., Jr. (Inventor)

    1995-01-01

    A control system and method for prosthetic devices is provided. The control system comprises a transducer for receiving movement from a body part for generating a sensing signal associated with that movement. The sensing signal is processed by a linearizer for linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part. The linearized sensing signal is normalized to be a function of the entire range of body part movement from the no-shrug position of the moveable body part. The normalized signal is divided into a plurality of discrete command signals. The discrete command signals are used by typical converter devices which are in operational association with the prosthetic device. The converter device uses the discrete command signals for driving the moveable portions of the prosthetic device and its sub-prosthesis. The method for controlling a prosthetic device associated with the present invention comprises the steps of receiving the movement from the body part, generating a sensing signal in association with the movement of the body part, linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part, normalizing the linear signal to be a function of the entire range of the body part movement, dividing the normalized signal into a plurality of discrete command signals, and implementing the plurality of discrete command signals for driving the respective moveable prosthesis device and its sub-prosthesis.

  19. Study on noise prediction model and control schemes for substation.

    PubMed

    Chen, Chuanmin; Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods. PMID:24672356

  20. Study on noise prediction model and control schemes for substation.

    PubMed

    Chen, Chuanmin; Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods.

  1. Novel method for controlled oxidation

    SciTech Connect

    Benjamin, B.M.; Raaen, V.F.

    1981-01-01

    The purpose of this paper is to describe a novel method for the oxidative degradation of coal or other organic material. The procedure is potentially useful for structure determination. As originally conceived, this method was intended for use with aqueous potassium permanganate as oxidant, but it is equally applicable with other oxidizing agents. Sodium hyprochlorite can be substituted for KMnO/sub 4/ except that controlling the pH and monitoring the end pilot become more difficult. Results with potassium permanganate only are described here but sodium hypochlorite was tried. An advantageous feature of the method is the simultaneous removal of soluble products from further contact with oxidizing agent as the oxidizing agent attacks the substrate. In principle, the experimental approach resembles that of column chromatography. Any oxidative degradation of a natural product for structure determination is of little use if carried out too far; for example, to the smallest, most oxidation-resistant materials such as carbon dioxide, acetic acid, and benzoic acid. Potassium permanganate oxidations of reactive species such as coal and kerogen are particularly difficult to control. Partially oxidized fragments which go into solution can be attacked more effectively than the solid starting phase, a situation which results in loss of structural information. Another difficulty is that phenolic materials can undergo coupling reactions thus generating larger molecules and giving misleading results due to a larger number of substituents. The procedure used is described.

  2. Predictability Influences Stopping and Response Control

    ERIC Educational Resources Information Center

    Morein-Zamir, Sharon; Chua, Romeo; Franks, Ian; Nagelkerke, Paul; Kingstone, Alan

    2007-01-01

    Using a continuous tracking task, the authors examined whether stopping is resistant to expectancies as well as whether it is a representative measure of response control. Participants controlled the speed of a moving marker by continuously adjusting their response force. Participants stopped their ongoing tracking in response to auditory signals…

  3. Gaussian mixture models as flux prediction method for central receivers

    NASA Astrophysics Data System (ADS)

    Grobler, Annemarie; Gauché, Paul; Smit, Willie

    2016-05-01

    Flux prediction methods are crucial to the design and operation of central receiver systems. Current methods such as the circular and elliptical (bivariate) Gaussian prediction methods are often used in field layout design and aiming strategies. For experimental or small central receiver systems, the flux profile of a single heliostat often deviates significantly from the circular and elliptical Gaussian models. Therefore a novel method of flux prediction was developed by incorporating the fitting of Gaussian mixture models onto flux profiles produced by flux measurement or ray tracing. A method was also developed to predict the Gaussian mixture model parameters of a single heliostat for a given time using image processing. Recording the predicted parameters in a database ensures that more accurate predictions are made in a shorter time frame.

  4. Axiomatic methods, dopamine and reward prediction error.

    PubMed

    Caplin, Andrew; Dean, Mark

    2008-04-01

    The phasic firing rate of midbrain dopamine neurons has been shown to respond both to the receipt of rewarding stimuli, and the degree to which such stimuli are anticipated by the recipient. This has led to the hypothesis that these neurons encode reward prediction error (RPE)-the difference between how rewarding an event is, and how rewarding it was expected to be. However, the RPE model is one of a number of competing explanations for dopamine activity that have proved hard to disentangle, mainly because they are couched in terms of latent, or unobservable, variables. This article describes techniques for dealing with latent variables common in economics and decision theory, and reviews work that uses these techniques to provide simple, non-parametric tests of the RPE hypothesis, allowing clear differentiation between competing explanations.

  5. A survey of the broadband shock associated noise prediction methods

    NASA Technical Reports Server (NTRS)

    Kim, Chan M.; Krejsa, Eugene A.; Khavaran, Abbas

    1992-01-01

    Several different prediction methods to estimate the broadband shock associated noise of a supersonic jet are introduced and compared with experimental data at various test conditions. The nozzle geometries considered for comparison include a convergent and a convergent-divergent nozzle, both axisymmetric. Capabilities and limitations of prediction methods in incorporating the two nozzle geometries, flight effect, and temperature effect are discussed. Predicted noise field shows the best agreement for a convergent nozzle geometry under static conditions. Predicted results for nozzles in flight show larger discrepancies from data and more dependable flight data are required for further comparison. Qualitative effects of jet temperature, as observed in experiment, are reproduced in predicted results.

  6. Methanol tailgas combustor control method

    DOEpatents

    Hart-Predmore, David J.; Pettit, William H.

    2002-01-01

    A method for controlling the power and temperature and fuel source of a combustor in a fuel cell apparatus to supply heat to a fuel processor where the combustor has dual fuel inlet streams including a first fuel stream, and a second fuel stream of anode effluent from the fuel cell and reformate from the fuel processor. In all operating modes, an enthalpy balance is determined by regulating the amount of the first and/or second fuel streams and the quantity of the first air flow stream to support fuel processor power requirements.

  7. Multiplexed Predictive Control of a Large Commercial Turbofan Engine

    NASA Technical Reports Server (NTRS)

    Richter, hanz; Singaraju, Anil; Litt, Jonathan S.

    2008-01-01

    Model predictive control is a strategy well-suited to handle the highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. However, it has thus far been infeasible to implement model predictive control in engine control applications, because of the combination of model complexity and the time allotted for the control update calculation. In this paper, a multiplexed implementation is proposed that dramatically reduces the computational burden of the quadratic programming optimization that must be solved online as part of the model-predictive-control algorithm. Actuator updates are calculated sequentially and cyclically in a multiplexed implementation, as opposed to the simultaneous optimization taking place in conventional model predictive control. Theoretical aspects are discussed based on a nominal model, and actual computational savings are demonstrated using a realistic commercial engine model.

  8. Method for Predicting Which Customers' Time Deposit Balances Will Increase

    NASA Astrophysics Data System (ADS)

    Ono, Toshiyuki; Yoshikawa, Hiroshi; Morita, Masahiro; Komoda, Norihisa

    This paper proposes a method of predicting which customers' account balances will increase by using data mining to effectively and efficiently promote sales. Prediction by mining all the data in a business is difficult because of much time required to collect, process, and calculate it. The selection of which features are used for prediction is a critical issue. We propose a method of selecting features to improve the accuracy of prediction within practical time limits. It consists of three parts: (1) converting collected features into financial behavior features that reflect customer actions, (2) extracting features affecting increases in account balances from these collected and financial behavior features, and (3) predicting customers whose account balances will increase based on the extracted features. We found the accuracy of prediction in an experiment with our method to be higher than with other conventional methods.

  9. Stabilizing model predictive control for constrained nonlinear distributed delay systems.

    PubMed

    Mahboobi Esfanjani, R; Nikravesh, S K Y

    2011-04-01

    In this paper, a model predictive control scheme with guaranteed closed-loop asymptotic stability is proposed for a class of constrained nonlinear time-delay systems with discrete and distributed delays. A suitable terminal cost functional and also an appropriate terminal region are utilized to achieve asymptotic stability. To determine the terminal cost, a locally asymptotically stabilizing controller is designed and an appropriate Lyapunov-Krasoskii functional of the locally stabilized system is employed as the terminal cost. Furthermore, an invariant set for locally stabilized system which is established by using the Razumikhin Theorem is used as the terminal region. Simple conditions are derived to obtain terminal cost and terminal region in terms of Bilinear Matrix Inequalities. The method is illustrated by a numerical example.

  10. Prospects for earthquake prediction and control

    USGS Publications Warehouse

    Healy, J.H.; Lee, W.H.K.; Pakiser, L.C.; Raleigh, C.B.; Wood, M.D.

    1972-01-01

    The San Andreas fault is viewed, according to the concepts of seafloor spreading and plate tectonics, as a transform fault that separates the Pacific and North American plates and along which relative movements of 2 to 6 cm/year have been taking place. The resulting strain can be released by creep, by earthquakes of moderate size, or (as near San Francisco and Los Angeles) by great earthquakes. Microearthquakes, as mapped by a dense seismograph network in central California, generally coincide with zones of the San Andreas fault system that are creeping. Microearthquakes are few and scattered in zones where elastic energy is being stored. Changes in the rate of strain, as recorded by tiltmeter arrays, have been observed before several earthquakes of about magnitude 4. Changes in fluid pressure may control timing of seismic activity and make it possible to control natural earthquakes by controlling variations in fluid pressure in fault zones. An experiment in earthquake control is underway at the Rangely oil field in Colorado, where the rates of fluid injection and withdrawal in experimental wells are being controlled. ?? 1972.

  11. Statistical energy analysis response prediction methods for structural systems

    NASA Technical Reports Server (NTRS)

    Davis, R. F.

    1979-01-01

    The results of an effort to document methods for accomplishing response predictions for commonly encountered aerospace structural configurations is presented. Application of these methods to specified aerospace structure to provide sample analyses is included. An applications manual, with the structural analyses appended as example problems is given. Comparisons of the response predictions with measured data are provided for three of the example problems.

  12. A Versatile Nonlinear Method for Predictive Modeling

    NASA Technical Reports Server (NTRS)

    Liou, Meng-Sing; Yao, Weigang

    2015-01-01

    As computational fluid dynamics techniques and tools become widely accepted for realworld practice today, it is intriguing to ask: what areas can it be utilized to its potential in the future. Some promising areas include design optimization and exploration of fluid dynamics phenomena (the concept of numerical wind tunnel), in which both have the common feature where some parameters are varied repeatedly and the computation can be costly. We are especially interested in the need for an accurate and efficient approach for handling these applications: (1) capturing complex nonlinear dynamics inherent in a system under consideration and (2) versatility (robustness) to encompass a range of parametric variations. In our previous paper, we proposed to use first-order Taylor expansion collected at numerous sampling points along a trajectory and assembled together via nonlinear weighting functions. The validity and performance of this approach was demonstrated for a number of problems with a vastly different input functions. In this study, we are especially interested in enhancing the method's accuracy; we extend it to include the second-orer Taylor expansion, which however requires a complicated evaluation of Hessian matrices for a system of equations, like in fluid dynamics. We propose a method to avoid these Hessian matrices, while maintaining the accuracy. Results based on the method are presented to confirm its validity.

  13. Tuning the Model Predictive Control of a Crude Distillation Unit.

    PubMed

    Yamashita, André Shigueo; Zanin, Antonio Carlos; Odloak, Darci

    2016-01-01

    Tuning the parameters of the Model Predictive Control (MPC) of an industrial Crude Distillation Unit (CDU) is considered here. A realistic scenario is depicted where the inputs of the CDU system have optimizing targets, which are provided by the Real Time Optimization layer of the control structure. It is considered the nominal case, in which both the CDU model and the MPC model are the same. The process outputs are controlled inside zones instead of at fixed set points. Then, the tuning procedure has to define the weights that penalize the output error with respect to the control zone, the weights that penalize the deviation of the inputs from their targets, as well as the weights that penalize the input moves. A tuning approach based on multi-objective optimization is proposed and applied to the MPC of the CDU system. The performance of the controller tuned with the proposed approach is compared through simulation with the results of an existing approach also based on multi-objective optimization. The simulation results are similar, but the proposed approach has a computational load significantly lower than the existing method. The tuning effort is also much lower than in the conventional practical approaches that are usually based on ad-hoc procedures.

  14. Methods for predicting wax precipitation and deposition

    SciTech Connect

    Weingarten, J.S.; Euchner, J.A.

    1988-02-01

    Removal of wax from wells and flowlines can account for significant additional operating costs. To evaluate these potential costs, the operating conditions that allow waxes to precipitate in the wellbore must be identified, and deposition rates must be estimated to determine the costs associated with removal of wax deposits. Presented in this paper are laboratory and analytic methods that can be used to estimate both the critical operating conditions and the deposition rates. The laboratory tests and analysis presented may be used to characterize any type of oil.

  15. Methods for predicting wax precipitation and deposition

    SciTech Connect

    Weingarten, J.S.; Euchner, J.A.

    1986-01-01

    Removal of wax from wells and flowlines can account for significant additional operating costs. To evaluate these potential costs, two things must be known. First, the operating conditions which allow waxes to precipitate in the wellbore must be identified. Second, deposition rates must be estimated to determine the costs associated with removal of wax deposits. Presented in this paper are laboratory and analytical methods which can be used to estimate both the critical operating conditions and the deposition rates. The laboratory tests and analysis presented may be used to characterize any type of oil.

  16. Computational methods in sequence and structure prediction

    NASA Astrophysics Data System (ADS)

    Lang, Caiyi

    This dissertation is organized into two parts. In the first part, we will discuss three computational methods for cis-regulatory element recognition in three different gene regulatory networks as the following: (a) Using a comprehensive "Phylogenetic Footprinting Comparison" method, we will investigate the promoter sequence structures of three enzymes (PAL, CHS and DFR) that catalyze sequential steps in the pathway from phenylalanine to anthocyanins in plants. Our result shows there exists a putative cis-regulatory element "AC(C/G)TAC(C)" in the upstream of these enzyme genes. We propose this cis-regulatory element to be responsible for the genetic regulation of these three enzymes and this element, might also be the binding site for MYB class transcription factor PAP1. (b) We will investigate the role of the Arabidopsis gene glutamate receptor 1.1 (AtGLR1.1) in C and N metabolism by utilizing the microarray data we obtained from AtGLR1.1 deficient lines (antiAtGLR1.1). We focus our investigation on the putatively co-regulated transcript profile of 876 genes we have collected in antiAtGLR1.1 lines. By (a) scanning the occurrence of several groups of known abscisic acid (ABA) related cisregulatory elements in the upstream regions of 876 Arabidopsis genes; and (b) exhaustive scanning of all possible 6-10 bps motif occurrence in the upstream regions of the same set of genes, we are able to make a quantative estimation on the enrichment level of each of the cis-regulatory element candidates. We finally conclude that one specific cis-regulatory element group, called "ABRE" elements, are statistically highly enriched within the 876-gene group as compared to their occurrence within the genome. (c) We will introduce a new general purpose algorithm, called "fuzzy REDUCE1", which we have developed recently for automated cis-regulatory element identification. In the second part, we will discuss our newly devised protein design framework. With this framework we have developed

  17. Predictive process control for sub-0.2-um lithography

    NASA Astrophysics Data System (ADS)

    Zavecz, Terrence E.; Blanquies, Rene M.

    2000-06-01

    An advanced control system providing modeling and predictive data simulation for pass-fail criteria of overlay production control has been used in 0.18 micrometer Design Rule production facilities for over a year. During this period overlay was measured on both product wafers and during periodic process qualification tests. The resulting raw data is modeled using exposure tool specific and layer-focused models. Modeled results, measured process statistics and tool signatures are combined in a real-time simulation to calculate the true overlay distribution over the entire wafer and lot. All results and raw data are automatically gathered and stored in a database for on-going analysis. In this manner, tool, product technology and process performance data are gathered for every overlay process-step. The data provides valuable insights into not only tool stability but also the process- step characteristic errors that contribute to the overlay spectrum of distortions. Data gathered in this manner is very stable and can be used to predict a feed-forward correction for all correctable coefficients. The technique must take into consideration algorithm modeled coefficient variations resulting from: (1) Reticle pattern-to-alignment mark design errors. (2) Process film variations. (3) Tool-to-tool static matching. (4) Tool-to-tool dynamic matching errors which are match-residual, process or time induced. This extensive database has resulted in a method of conducting Predictive Process Control (PPC) for overlay lithography within an advanced semiconductor line. Using PPC the wafer production facility experiences: (1) Improved Yield: Lots are always exposed with optimum setup. Optimized setups reduce rework levels and therefore wafer handling. (2) Capacity Improvement: Elimination of rework tacitly improves capacity in the facility. WIP is also simplified because lots do not have to wait for a dedicated exposure tool to become available. (3) Dynamic MatchingTM: Matching of

  18. Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

    NASA Technical Reports Server (NTRS)

    McMillan, Michelle L.; Mackie, Scott A.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James L.

    2011-01-01

    Fail-safe, hybrid, flow control (HFC) is a promising technology for meeting high-speed cruise efficiency, low-noise signature, and reduced fuel-burn goals for future, Hybrid-Wing-Body (HWB) aircraft with embedded engines. This report details the development of HFC technology that enables improved inlet performance in HWB vehicles with highly integrated inlets and embedded engines without adversely affecting vehicle performance. In addition, new test techniques for evaluating Boundary-Layer-Ingesting (BLI)-inlet flow-control technologies developed and demonstrated through this program are documented, including the ability to generate a BLI-like inlet-entrance flow in a direct-connect, wind-tunnel facility, as well as, the use of D-optimal, statistically designed experiments to optimize test efficiency and enable interpretation of results. Validated improvements in numerical analysis tools and methods accomplished through this program are also documented, including Reynolds-Averaged Navier-Stokes CFD simulations of steady-state flow physics for baseline, BLI-inlet diffuser flow, as well as, that created by flow-control devices. Finally, numerical methods were employed in a ground-breaking attempt to directly simulate dynamic distortion. The advances in inlet technologies and prediction tools will help to meet and exceed "N+2" project goals for future HWB aircraft.

  19. Observer-based tracking controller design for networked predictive control systems with uncertain Markov delays

    NASA Astrophysics Data System (ADS)

    Zhang, Hui; Shi, Yang; Wang, Junmin

    2013-10-01

    This paper is concerned with a tracking controller design problem for discrete-time networked predictive control systems. The control law used here is a combined state-feedback control and integral control. Since not all the states are available in practice, a local Luenberger observer is utilised to estimate the state vector. The measured output and estimated state vector are packed together and transmitted to the tracking controller via a communication channel with a limited capacity. Meanwhile, the control signal is also transmitted through a communication network.Network-induced delays on both links are considered for the signal transmission and modelled by Markov chains. Moreover, it is assumed that the elements in Markov transition matrices are subject to uncertainties. In order to fully compensate for network-induced delays, the controller generates a sequence of control signals which are dependent on each possible delay in the feedforward channel. By taking the augmentation twice, we obtain delay-free stochastic closed-loop systems and the controlled output is chosen as the tracking error. Sufficient conditions are provided for the energy-to-peak performance of the closed-loop systems. The feedback gains of the controller can be derived by solving a minimisation problem. Two examples are illustrated to demonstrate the effectiveness of the proposed design method.

  20. Preliminary thoughts on helicopter cabin noise prediction methods

    NASA Astrophysics Data System (ADS)

    Pollard, J. S.

    The problems of predicting helicopter cabin noise are discussed with particular reference to the Lynx helicopter. Available methods such as modal analysis adopted for propeller noise prediction do not cope with the higher frequency discrete tone content of helicopter gear noise, with the airborne and structureborne noise contributions. Statistical energy analysis methods may be the answer but until these are developed, one has to rely on classical noise transmission analysis and transfer function methods.

  1. Preview Scheduled Model Predictive Control For Horizontal Axis Wind Turbines

    NASA Astrophysics Data System (ADS)

    Laks, Jason H.

    This research investigates the use of model predictive control (MPC) in application to wind turbine operation from start-up to cut-out. The studies conducted are focused on the design of an MPC controller for a 650˜KW, three-bladed horizontal axis turbine that is in operation at the National Renewable Energy Laboratory's National Wind Technology Center outside of Golden, Colorado. This turbine is at the small end of utility scale turbines, but it provides advanced instrumentation and control capabilities, and there is a good probability that the approach developed in simulation for this thesis, will be field tested on the actual turbine. A contribution of this thesis is a method to combine the use of preview measurements with MPC while also providing regulation of turbine speed and cyclic blade loading. A common MPC technique provides integral-like control to achieve offset-free operation. At the same time in wind turbine applications, multiple studies have developed "feed-forward" controls based on applying a gain to an estimate of the wind speed changes obtained from an observer incorporating a disturbance model. These approaches are based on a technique that can be referred to as disturbance accommodating control (DAC). In this thesis, it is shown that offset-free tracking MPC is equivalent to a DAC approach when the disturbance gain is computed to satisfy a regulator equation. Although the MPC literature has recognized that this approach provides "structurally stable" disturbance rejection and tracking, this step is not typically divorced from the MPC computations repeated each sample hit. The DAC formulation is conceptually simpler, and essentially uncouples regulation considerations from MPC related issues. This thesis provides a self contained proof that the DAC formulation (an observer-controller and appropriate disturbance gain) provides structurally stable regulation.

  2. Experimental validation of boundary element methods for noise prediction

    NASA Technical Reports Server (NTRS)

    Seybert, A. F.; Oswald, Fred B.

    1992-01-01

    Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

  3. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    NASA Technical Reports Server (NTRS)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  4. Pilots Rate Augmented Generalized Predictive Control for Reconfiguration

    NASA Technical Reports Server (NTRS)

    Soloway, Don; Haley, Pam

    2004-01-01

    The objective of this paper is to report the results from the research being conducted in reconfigurable fight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft's control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive Control scheme and a Neural Network based Dynamic Inverse controller. This paper highlights the Predictive Control scheme where a simple augmentation to reduce zero steady-state error led to the neural network predictor model becoming redundant for the task. Instead of using a neural network predictor model, a nominal single point linear model was used and then augmented with an error corrector. This paper shows that the Generalized Predictive Controller and the Dynamic Inverse Neural Network controller perform equally well at reconfiguration, but with less rate requirements from the actuators. Also presented are the pilot ratings for each controller for various failure scenarios and two samples of the required control actuation during reconfiguration. Finally, the paper concludes by stepping through the Generalized Predictive Control's reconfiguration process for an elevator failure.

  5. Algorithm for predictive control implementation on fiber optic transmission lines

    NASA Astrophysics Data System (ADS)

    Andreev, Vladimir A.; Burdin, Vladimir A.; Voronkov, Andrey A.

    2014-04-01

    This paper presents the algorithm for predictive control implementation on fiber-optic transmission lines. In order to improve the maintenance of fiber optic communication lines, the algorithm prediction uptime optic communication cables have been worked out. It considers the results of scheduled preventive maintenance and database of various works on the track cable line during maintenance.

  6. Multiple-step terminal control with parameter identification and prediction during flight vehicle descent

    NASA Astrophysics Data System (ADS)

    Sirazetdinov, T. K.; Kiselev, V. I.

    A method is presented for multiple-step terminal control at a section of the glide path of a flight vehcile in the dense layers of the atmosphere. In accordance with the method, the parameters are identified and predicted at each step of the control process. Results of a computer simulation of the motion of a flight vehicle are presented.

  7. Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

    NASA Technical Reports Server (NTRS)

    Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

    2010-01-01

    Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

  8. What Predicts Use of Learning-Centered, Interactive Engagement Methods?

    ERIC Educational Resources Information Center

    Madson, Laura; Trafimow, David; Gray, Tara; Gutowitz, Michael

    2014-01-01

    What makes some faculty members more likely to use interactive engagement methods than others? We use the theory of reasoned action to predict faculty members' use of interactive engagement methods. Results indicate that faculty members' beliefs about the personal positive consequences of using these methods (e.g., "Using…

  9. Integrated control system and method

    SciTech Connect

    Wang, Paul Sai Keat; Baldwin, Darryl; Kim, Myoungjin

    2013-10-29

    An integrated control system for use with an engine connected to a generator providing electrical power to a switchgear is disclosed. The engine receives gas produced by a gasifier. The control system includes an electronic controller associated with the gasifier, engine, generator, and switchgear. A gas flow sensor monitors a gas flow from the gasifier to the engine through an engine gas control valve and provides a gas flow signal to the electronic controller. A gas oversupply sensor monitors a gas oversupply from the gasifier and provides an oversupply signal indicative of gas not provided to the engine. A power output sensor monitors a power output of the switchgear and provide a power output signal. The electronic controller changes gas production of the gasifier and the power output rating of the switchgear based on the gas flow signal, the oversupply signal, and the power output signal.

  10. In vitro method for prediction of plaque reduction by dentifrice.

    PubMed

    Tepper, Bruce; Howard, Brian; Schnell, Daniel; Mills, Lisa; Xu, Jian

    2015-11-01

    An in vitro Particle Based Biofilm (PBB) model was developed to enable high throughput screening tests to predict clinical plaque reduction. Multi-species oral biofilms were cultured from pooled stimulated human saliva on continuously-colliding hydroxyapatite particles. After three days PBBs were saline washed prior to use in screening tests. Testing involved dosing PBBs for 1min followed by neutralization of test materials and rinsing. PBBs were then assayed for intact biofilm activity measured as ATP. The ranking of commercial dentifrices from most to least reduction of intact biofilm activity was Crest ProHealth Clinical Gum Protection, Crest ProHealth, Colgate Total and Crest Cavity Protection. We demonstrated five advantages of the PBB model: 1) the ATP metric had a linear response over ≥1000-fold dynamic range, 2) potential interference with the ATP assay by treatments was easily eliminated by rinsing PBBs with saline, 3) discriminating power was statistically excellent between all treatment comparisons with the negative controls, 4) screening test results were reproducible across four tests, and 5) the screening test produced the same rank order for dentifrices as clinical studies that measured plaque reduction. In addition, 454 pyrosequencing of the PBBs indicated an oral microbial consortium was present. The most prevalent genera were Neisseria, Rothia, Streptococcus, Porphyromonas, Prevotella, Actinomyces, Fusobacterium, Veillonella and Haemophilus. We conclude these in vitro methods offer an efficient, effective and relevant screening tool for reduction of intact biofilm activity by dentifrices. Moreover, dentifrice rankings by the in vitro test method are expected to predict clinical results for plaque reduction. PMID:26151407

  11. Method and device for predicting wavelength dependent radiation influences in thermal systems

    DOEpatents

    Kee, Robert J.; Ting, Aili

    1996-01-01

    A method and apparatus for predicting the spectral (wavelength-dependent) radiation transport in thermal systems including interaction by the radiation with partially transmitting medium. The predicted model of the thermal system is used to design and control the thermal system. The predictions are well suited to be implemented in design and control of rapid thermal processing (RTP) reactors. The method involves generating a spectral thermal radiation transport model of an RTP reactor. The method also involves specifying a desired wafer time dependent temperature profile. The method further involves calculating an inverse of the generated model using the desired wafer time dependent temperature to determine heating element parameters required to produce the desired profile. The method also involves controlling the heating elements of the RTP reactor in accordance with the heating element parameters to heat the wafer in accordance with the desired profile.

  12. A method to objectively optimize coral bleaching prediction techniques

    NASA Astrophysics Data System (ADS)

    van Hooidonk, R. J.; Huber, M.

    2007-12-01

    Thermally induced coral bleaching is a global threat to coral reef health. Methodologies, e.g. the Degree Heating Week technique, have been developed to predict bleaching induced by thermal stress by utilizing remotely sensed sea surface temperature (SST) observations. These techniques can be used as a management tool for Marine Protected Areas (MPA). Predictions are valuable to decision makers and stakeholders on weekly to monthly time scales and can be employed to build public awareness and support for mitigation. The bleaching problem is only expected to worsen because global warming poses a major threat to coral reef health. Indeed, predictive bleaching methods combined with climate model output have been used to forecast the global demise of coral reef ecosystems within coming decades due to climate change. Accuracy of these predictive techniques has not been quantitatively characterized despite the critical role they play. Assessments have typically been limited, qualitative or anecdotal, or more frequently they are simply unpublished. Quantitative accuracy assessment, using well established methods and skill scores often used in meteorology and medical sciences, will enable objective optimization of existing predictive techniques. To accomplish this, we will use existing remotely sensed data sets of sea surface temperature (AVHRR and TMI), and predictive values from techniques such as the Degree Heating Week method. We will compare these predictive values with observations of coral reef health and calculate applicable skill scores (Peirce Skill Score, Hit Rate and False Alarm Rate). We will (a) quantitatively evaluate the accuracy of existing coral reef bleaching predictive methods against state-of- the-art reef health databases, and (b) present a technique that will objectively optimize the predictive method for any given location. We will illustrate this optimization technique for reefs located in Puerto Rico and the US Virgin Islands.

  13. Towards feasible and effective predictive wavefront control for adaptive optics

    SciTech Connect

    Poyneer, L A; Veran, J

    2008-06-04

    We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.

  14. Integration simulation method concerning speed control of ultrasonic motor

    NASA Astrophysics Data System (ADS)

    Miyauchi, R.; Yue, B.; Matsunaga, N.; Ishizuka, S.

    2016-09-01

    In this paper, the configuration of control system of the ultrasonic motor (USM) from finite element method (FEM) model by applying the nonlinear model order reduction (MOR) is proposed. First, the USM and the FEM model is introduced. Second, FEM model order reduction method is described. Third, the result of comparing the computing time and accuracy of the FEM model and reduced order model is shown. Finaly, nominal model for control is derived by system identification from reduced order model. Nonlinear model predictive control (NMPC) is applied to the nominal model, and speed is controlled. the controller effect is comfirmed by applying the proposed reduced order model.

  15. Modified-Fibonacci-Dual-Lucas method for earthquake prediction

    NASA Astrophysics Data System (ADS)

    Boucouvalas, A. C.; Gkasios, M.; Tselikas, N. T.; Drakatos, G.

    2015-06-01

    The FDL method makes use of Fibonacci, Dual and Lucas numbers and has shown considerable success in predicting earthquake events locally as well as globally. Predicting the location of the epicenter of an earthquake is one difficult challenge the other being the timing and magnitude. One technique for predicting the onset of earthquakes is the use of cycles, and the discovery of periodicity. Part of this category is the reported FDL method. The basis of the reported FDL method is the creation of FDL future dates based on the onset date of significant earthquakes. The assumption being that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series The connection between past earthquakes and future earthquakes based on FDL numbers has also been reported with sample earthquakes since 1900. Using clustering methods it has been shown that significant earthquakes (<6.5R) can be predicted with very good accuracy window (+-1 day). In this contribution we present an improvement modification to the FDL method, the MFDL method, which performs better than the FDL. We use the FDL numbers to develop possible earthquakes dates but with the important difference that the starting seed date is a trigger planetary aspect prior to the earthquake. Typical planetary aspects are Moon conjunct Sun, Moon opposite Sun, Moon conjunct or opposite North or South Modes. In order to test improvement of the method we used all +8R earthquakes recorded since 1900, (86 earthquakes from USGS data). We have developed the FDL numbers for each of those seeds, and examined the earthquake hit rates (for a window of 3, i.e. +-1 day of target date) and for <6.5R. The successes are counted for each one of the 86 earthquake seeds and we compare the MFDL method with the FDL method. In every case we find improvement when the starting seed date is on the planetary trigger date prior to the earthquake. We observe no improvement only when a planetary trigger coincided with

  16. Predictive neuro-fuzzy controller for multilink robot manipulator

    NASA Astrophysics Data System (ADS)

    Kaymaz, Emre; Mitra, Sunanda

    1995-10-01

    A generalized controller based on fuzzy clustering and fuzzy generalized predictive control has been developed for nonlinear systems including multilink robot manipulators. The proposed controller is particularly useful when the dynamics of the nonlinear system to be controlled are difficult to yield exact solutions and the system specification can be obtained in terms of crisp input-output pairs. It inherits the advantages of both fuzzy logic and predictive control. The identification of the nonlinear mapping of the system to be controlled is realized by a three- layer feed-forward neural network model employing the input-output data obtained from the system. The speed of convergence of the neural network is improved by the introduction of a fuzzy logic controlled backpropagation learning algorithm. The neural network model is then used as a simulation tool to generate the input-output data for developing the predictive fuzzy logic controller for the chosen nonlinear system. The use of fuzzy clustering facilitates automatic generation of membership relations of the input-output data. Unlike the linguistic fuzzy logic controller which requires approximate knowledge of the shape and the numbers of the membership functions in the input and output universes of the discourse, this integrated neuro-fuzzy approach allows one to find the fuzzy relations and the membership functions more accurately. Furthermore, it is not necessary to tune the controller. For a two-link robot manipulator, the performance of this predictive fuzzy controller is shown to be superior to that of a conventional controller employing an ARMA model of the system in terms of accuracy and consumption of energy.

  17. Prediction methods of spudcan penetration for jack-up units

    NASA Astrophysics Data System (ADS)

    Zhang, Ai-xia; Duan, Meng-lan; Li, Hai-ming; Zhao, Jun; Wang, Jian-jun

    2012-12-01

    Jack-up units are extensively playing a successful role in drilling engineering around the world, and their safety and efficiency take more and more attraction in both research and engineering practice. An accurate prediction of the spudcan penetration depth is quite instrumental in deciding on whether a jack-up unit is feasible to operate at the site. The prediction of a too large penetration depth may lead to the hesitation or even rejection of a site due to potential difficulties in the subsequent extraction process; the same is true of a too small depth prediction due to the problem of possible instability during operation. However, a deviation between predictive results and final field data usually exists, especially when a strong-over-soft soil is included in the strata. The ultimate decision sometimes to a great extent depends on the practical experience, not the predictive results given by the guideline. It is somewhat risky, but no choice. Therefore, a feasible predictive method for the spudcan penetration depth, especially in strata with strong-over-soft soil profile, is urgently needed by the jack-up industry. In view of this, a comprehensive investigation on methods of predicting spudcan penetration is executed. For types of different soil profiles, predictive methods for spudcan penetration depth are proposed, and the corresponding experiment is also conducted to validate these methods. In addition, to further verify the feasibility of the proposed methods, a practical engineering case encountered in the South China Sea is also presented, and the corresponding numerical and experimental results are also presented and discussed.

  18. The trajectory prediction of spacecraft by grey method

    NASA Astrophysics Data System (ADS)

    Wang, Qiyue; Zhang, Zili; Wang, Zhongyu; Wang, Yanqing; Zhou, Weihu

    2016-08-01

    The real-time and high-precision trajectory prediction of a moving object is a core technology in the field of aerospace engineering. The real-time monitoring and tracking technology are also significant guarantees of aerospace equipment. A dynamic trajectory prediction method called grey dynamic filter (GDF) which combines the dynamic measurement theory and grey system theory is proposed. GDF can use coordinates of the current period to extrapolate coordinates of the following period. At meantime, GDF can also keep the instantaneity of measured coordinates by the metabolism model. In this paper the optimal model length of GDF is firstly selected to improve the prediction accuracy. Then the simulation for uniformly accelerated motion and variably accelerated motion is conducted. The simulation results indicate that the mean composite position error of GDF prediction is one-fifth to that of Kalman filter (KF). By using a spacecraft landing experiment, the prediction accuracy of GDF is compared with the KF method and the primitive grey method (GM). The results show that the motion trajectory of spacecraft predicted by GDF is much closer to actual trajectory than the other two methods. The mean composite position error calculated by GDF is one-eighth to KF and one-fifth to GM respectively.

  19. Multi-objective optimization for model predictive control.

    PubMed

    Wojsznis, Willy; Mehta, Ashish; Wojsznis, Peter; Thiele, Dirk; Blevins, Terry

    2007-06-01

    This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC. PMID:17382946

  20. Improving active space telescope wavefront control using predictive thermal modeling

    NASA Astrophysics Data System (ADS)

    Gersh-Range, Jessica; Perrin, Marshall D.

    2015-01-01

    Active control algorithms for space telescopes are less mature than those for large ground telescopes due to differences in the wavefront control problems. Active wavefront control for space telescopes at L2, such as the James Webb Space Telescope (JWST), requires weighing control costs against the benefits of correcting wavefront perturbations that are a predictable byproduct of the observing schedule, which is known and determined in advance. To improve the control algorithms for these telescopes, we have developed a model that calculates the temperature and wavefront evolution during a hypothetical mission, assuming the dominant wavefront perturbations are due to changes in the spacecraft attitude with respect to the sun. Using this model, we show that the wavefront can be controlled passively by introducing scheduling constraints that limit the allowable attitudes for an observation based on the observation duration and the mean telescope temperature. We also describe the implementation of a predictive controller designed to prevent the wavefront error (WFE) from exceeding a desired threshold. This controller outperforms simpler algorithms even with substantial model error, achieving a lower WFE without requiring significantly more corrections. Consequently, predictive wavefront control based on known spacecraft attitude plans is a promising approach for JWST and other future active space observatories.

  1. Predicting sediment yield from alternative surface mining methods

    SciTech Connect

    Warner, R.C.; Wells, L.G.; Barfield, B.J.; Moore, I.D.; Wilson, B.N.

    1982-12-01

    The focus of this research was to compare the predicted sediment yield and hydrologic impact of three alternative surface mining methods used in the Central and Southern Appalachian coal regions. The mining methods investigated were: 1) mountaintop removal, 2) post-1977 block-cut haul-back contour mining, and 3) pre-1977 contour mining. Sediment and hydrologic impacts were predicted through use of the SEDIMOT model. For the mine plans analyzed the post-1977 block-cut haul-back mining method produced significantly lower sediment and peak storm response.

  2. COMSAC: Computational Methods for Stability and Control. Part 1

    NASA Technical Reports Server (NTRS)

    Fremaux, C. Michael (Compiler); Hall, Robert M. (Compiler)

    2004-01-01

    Work on stability and control included the following reports:Introductory Remarks; Introduction to Computational Methods for Stability and Control (COMSAC); Stability & Control Challenges for COMSAC: a NASA Langley Perspective; Emerging CFD Capabilities and Outlook A NASA Langley Perspective; The Role for Computational Fluid Dynamics for Stability and Control:Is it Time?; Northrop Grumman Perspective on COMSAC; Boeing Integrated Defense Systems Perspective on COMSAC; Computational Methods in Stability and Control:WPAFB Perspective; Perspective: Raytheon Aircraft Company; A Greybeard's View of the State of Aerodynamic Prediction; Computational Methods for Stability and Control: A Perspective; Boeing TacAir Stability and Control Issues for Computational Fluid Dynamics; NAVAIR S&C Issues for CFD; An S&C Perspective on CFD; Issues, Challenges & Payoffs: A Boeing User s Perspective on CFD for S&C; and Stability and Control in Computational Simulations for Conceptual and Preliminary Design: the Past, Today, and Future?

  3. Method For Model-Reference Adaptive Control

    NASA Technical Reports Server (NTRS)

    Seraji, Homayoun

    1990-01-01

    Relatively simple method of model-reference adaptive control (MRAC) developed from two prior classes of MRAC techniques: signal-synthesis method and parameter-adaption method. Incorporated into unified theory, which yields more general adaptation scheme.

  4. Computational Methods for Failure Analysis and Life Prediction

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K. (Compiler); Harris, Charles E. (Compiler); Housner, Jerrold M. (Compiler); Hopkins, Dale A. (Compiler)

    1993-01-01

    This conference publication contains the presentations and discussions from the joint UVA/NASA Workshop on Computational Methods for Failure Analysis and Life Prediction held at NASA Langley Research Center 14-15 Oct. 1992. The presentations focused on damage failure and life predictions of polymer-matrix composite structures. They covered some of the research activities at NASA Langley, NASA Lewis, Southwest Research Institute, industry, and universities. Both airframes and propulsion systems were considered.

  5. Prediction and control of limit cycling motions in boosting rockets

    NASA Astrophysics Data System (ADS)

    Newman, Brett

    An investigation concerning the prediction and control of observed limit cycling behavior in a boosting rocket is considered. The suspected source of the nonlinear behavior is the presence of Coulomb friction in the nozzle pivot mechanism. A classical sinusoidal describing function analysis is used to accurately recreate and predict the observed oscillatory characteristic. In so doing, insight is offered into the limit cycling mechanism and confidence is gained in the closed-loop system design. Nonlinear simulation results are further used to support and verify the results obtained from describing function theory. Insight into the limit cycling behavior is, in turn, used to adjust control system parameters in order to passively control the oscillatory tendencies. Tradeoffs with the guidance and control system stability/performance are also noted. Finally, active control of the limit cycling behavior, using a novel feedback algorithm to adjust the inherent nozzle sticking-unsticking characteristics, is considered.

  6. Optimized continuous pharmaceutical manufacturing via model-predictive control.

    PubMed

    Rehrl, Jakob; Kruisz, Julia; Sacher, Stephan; Khinast, Johannes; Horn, Martin

    2016-08-20

    This paper demonstrates the application of model-predictive control to a feeding blending unit used in continuous pharmaceutical manufacturing. The goal of this contribution is, on the one hand, to highlight the advantages of the proposed concept compared to conventional PI-controllers, and, on the other hand, to present a step-by-step guide for controller synthesis. The derivation of the required mathematical plant model is given in detail and all the steps required to develop a model-predictive controller are shown. Compared to conventional concepts, the proposed approach allows to conveniently consider constraints (e.g. mass hold-up in the blender) and offers a straightforward, easy to tune controller setup. The concept is implemented in a simulation environment. In order to realize it on a real system, additional aspects (e.g., state estimation, measurement equipment) will have to be investigated. PMID:27317987

  7. Optimized continuous pharmaceutical manufacturing via model-predictive control.

    PubMed

    Rehrl, Jakob; Kruisz, Julia; Sacher, Stephan; Khinast, Johannes; Horn, Martin

    2016-08-20

    This paper demonstrates the application of model-predictive control to a feeding blending unit used in continuous pharmaceutical manufacturing. The goal of this contribution is, on the one hand, to highlight the advantages of the proposed concept compared to conventional PI-controllers, and, on the other hand, to present a step-by-step guide for controller synthesis. The derivation of the required mathematical plant model is given in detail and all the steps required to develop a model-predictive controller are shown. Compared to conventional concepts, the proposed approach allows to conveniently consider constraints (e.g. mass hold-up in the blender) and offers a straightforward, easy to tune controller setup. The concept is implemented in a simulation environment. In order to realize it on a real system, additional aspects (e.g., state estimation, measurement equipment) will have to be investigated.

  8. Accuracy of Four Tooth Size Prediction Methods on Malay Population

    PubMed Central

    Mahmoud, Belal Khaled; Abu Asab, Saifeddin Hamed I.; Taib, Haslina

    2012-01-01

    Objective. To examine the accuracy of Moyers 50%, Tanaka and Johnston, Ling and Wong and Jaroontham and Godfrey methods in predicting the mesio-distal crown width of the permanent canines and premolars (C + P1 + P2) in Malay population. Materials and Methods. The study models of 240 Malay children (120 males and 120 females) aged 14 to 18 years, all free of any signs of dental pathology or anomalies, were measured using a digital caliper accurate to 0.01 mm. The predicted widths (C + P1 + P2) in both arches derived from the tested prediction equations were compared with the actual measured widths. Results. Moyers and Tanaka and Johnston methods showed significant difference between the actual and predicted widths of (C + P1 + P2) for both sexes. Ling and Wong method also showed statistically significant difference for males, however, there was no significant difference for females. Jaroontham and Godfrey method showed statistical significant difference for females, but the male values did not show any significant difference. Conclusion. For male Malay, the method proposed by Jaroontham and Godfrey for male Thai proved to be highly accurate. For female Malay, the method proposed by Ling and Wong for southern Chinese females proved to be highly accurate. PMID:23209918

  9. A simple method of predicting S-wave velocity

    USGS Publications Warehouse

    Lee, M.W.

    2006-01-01

    Prediction of shear-wave velocity plays an important role in seismic modeling, amplitude analysis with offset, and other exploration applications. This paper presents a method for predicting S-wave velocity from the P-wave velocity on the basis of the moduli of dry rock. Elastic velocities of water-saturated sediments at low frequencies can be predicted from the moduli of dry rock by using Gassmann's equation; hence, if the moduli of dry rock can be estimated from P-wave velocities, then S-wave velocities easily can be predicted from the moduli. Dry rock bulk modulus can be related to the shear modulus through a compaction constant. The numerical results indicate that the predicted S-wave velocities for consolidated and unconsolidated sediments agree well with measured velocities if differential pressure is greater than approximately 5 MPa. An advantage of this method is that there are no adjustable parameters to be chosen, such as the pore-aspect ratios required in some other methods. The predicted S-wave velocity depends only on the measured P-wave velocity and porosity. ?? 2006 Society of Exploration Geophysicists.

  10. Prediction Models are Basis for Rational Air Quality Control

    ERIC Educational Resources Information Center

    Daniels, Anders; Bach, Wilfrid

    1973-01-01

    An air quality control scheme employing meteorological diffusion, time averaging and frequency, and cost-benefit models is discussed. The methods outlined provide a constant feedback system for air quality control. Flow charts and maps are included. (BL)

  11. Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays.

    PubMed

    Tang, Xiaoming; Qu, Hongchun; Wang, Ping; Zhao, Meng

    2015-03-01

    This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S-A) and controller to actuator (C-A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method.

  12. Method for crystal growth control

    DOEpatents

    Yates, Douglas A.; Hatch, Arthur E.; Goldsmith, Jeff M.

    1981-01-01

    The growth of a crystalline body of a selected material is controlled so that the body has a selected cross-sectional shape. The apparatus is of the type which includes the structure normally employed in known capillary die devices as well as means for observing at least the portion of the surfaces of the growing crystalline body and the meniscus (of melt material from which the body is being pulled) including the solid/liquid/vapor junction in a direction substantially perpendicular to the meniscus surface formed at the junction when the growth of the crystalline body is under steady state conditions. The cross-sectional size of the growing crystalline body can be controlled by determining which points exhibit a sharp change in the amount of reflected radiation of a preselected wavelength and controlling the speed at which the body is being pulled or the temperature of the growth pool of melt so as to maintain those points exhibiting a sharp change at a preselected spatial position relative to a predetermined reference position. The improvement comprises reference object means positioned near the solid/liquid/vapor junction and capable of being observed by the means for observing so as to define said reference position so that the problems associated with convection current jitter are overcome.

  13. Evaluation of Methods to Predict Reactivity of Gold Nanoparticles

    SciTech Connect

    Allison, Thomas C.; Tong, Yu ye J.

    2011-06-20

    Several methods have appeared in the literature for predicting reactivity on metallic surfaces and on the surface of metallic nanoparticles. All of these methods have some relationship to the concept of frontier molecular orbital theory. The d-band theory of Hammer and Nørskov is perhaps the most widely used predictor of reactivity on metallic surfaces, and it has been successfully applied in many cases. Use of the Fukui function and the condensed Fukui function is well established in organic chemistry, but has not been so widely applied in predicting the reactivity of metallic nanoclusters. In this article, we will evaluate the usefulness of the condensed Fukui function in predicting the reactivity of a family of cubo-octahedral gold nanoparticles and make comparison with the d-band method.

  14. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  15. Predicting Spacecraft Trajectories by the WeavEncke Method

    NASA Technical Reports Server (NTRS)

    Weaver, Jonathan K.; Adamo, Daniel R.

    2011-01-01

    A combination of methods is proposed of predicting spacecraft trajectories that possibly include multiple maneuvers and/or perturbing accelerations, with greater speed, accuracy, and repeatability than were heretofore achievable. The combination is denoted the WeavEncke method because it is based on unpublished studies by Jonathan Weaver of the orbit-prediction formulation of the noted astronomer Johann Franz Encke. Weaver evaluated a number of alternatives that arise within that formulation, arriving at an orbit-predicting algorithm optimized for complex trajectory operations. In the WeavEncke method, Encke's method of prediction of perturbed orbits is enhanced by application of modern numerical methods. Among these methods are efficient Kepler s-equation time-of-flight solutions and self-starting numerical integration with time as the independent variable. Self-starting numerical integration satisfies the requirements for accuracy, reproducibility, and efficiency (and, hence, speed). Self-starting numerical integration also supports fully analytic regulation of integration step sizes, thereby further increasing speed while maintaining accuracy.

  16. Self-Control Assessments and Implications for Predicting Adolescent Offending.

    PubMed

    Fine, Adam; Steinberg, Laurence; Frick, Paul J; Cauffman, Elizabeth

    2016-04-01

    Although low self-control is consistently related to adolescent offending, it is unknown whether self-report measures or laboratory behavior tasks yield better predictive utility, or if a combination yields incremental predictive power. This is particularly important because developmental theory indicates that self-control is related to adolescent offending and, consequently, risk assessments rely on self-control measures. The present study (a) examines relationships between self-reported self-control on the Weinberger Adjustment Inventory with Go/No-Go response inhibition, and (b) compares the predictive utility of both assessment strategies for short- and long-term adolescent reoffending. It uses longitudinal data from the Crossroads Study of male, first-time adolescent offenders ages 13-17 (N = 930; 46 % Hispanic/Latino, 37 % Black/African-American, 15 % non-Hispanic White, 2 % other race). The results of the study indicate that the measures are largely unrelated, and that the self-report measure is a better indicator of both short- and long-term reoffending. The laboratory task measure does not add value to what is already predicted by the self-report measure. Implications for assessing self-control during adolescence and consequences of assessment strategy are discussed. PMID:26792266

  17. Predicted torque equilibrium attitude utilization for Space Station attitude control

    NASA Technical Reports Server (NTRS)

    Kumar, Renjith R.; Heck, Michael L.; Robertson, Brent P.

    1990-01-01

    An approximate knowledge of the torque equilibrium attitude (TEA) is shown to improve the performance of a control moment gyroscope (CMG) momentum management/attitude control law for Space Station Freedom. The linearized equations of motion are used in conjunction with a state transformation to obtain a control law which uses full state feedback and the predicted TEA to minimize both attitude excursions and CMG peak and secular momentum. The TEA can be computationally determined either by observing the steady state attitude of a 'controlled' spacecraft using arbitrary initial attitude, or by simulating a fixed attitude spacecraft flying in desired orbit subject to realistic environmental disturbance models.

  18. An analytical method to predict efficiency of aircraft gearboxes

    NASA Technical Reports Server (NTRS)

    Anderson, N. E.; Loewenthal, S. H.; Black, J. D.

    1984-01-01

    A spur gear efficiency prediction method previously developed by the authors was extended to include power loss of planetary gearsets. A friction coefficient model was developed for MIL-L-7808 oil based on disc machine data. This combined with the recent capability of predicting losses in spur gears of nonstandard proportions allows the calculation of power loss for complete aircraft gearboxes that utilize spur gears. The method was applied to the T56/501 turboprop gearbox and compared with measured test data. Bearing losses were calculated with large scale computer programs. Breakdowns of the gearbox losses point out areas for possible improvement.

  19. A correction method suitable for dynamical seasonal prediction

    NASA Astrophysics Data System (ADS)

    Chen, H.; Lin, Z. H.

    2006-05-01

    Based on the hindcast results of summer rainfall anomalies over China for the period 1981-2000 by the Dynamical Climate Prediction System (IAP-DCP) developed by the Institute of Atmospheric Physics, a correction method that can account for the dependence of model's systematic biases on SST anomalies is proposed. It is shown that this correction method can improve the hindcast skill of the IAP-DCP for summer rainfall anomalies over China, especially in western China and southeast China, which may imply its potential application to real-time seasonal prediction.

  20. Preface to the Focus Issue: Chaos Detection Methods and Predictability

    SciTech Connect

    Gottwald, Georg A.; Skokos, Charalampos

    2014-06-01

    This Focus Issue presents a collection of papers originating from the workshop Methods of Chaos Detection and Predictability: Theory and Applications held at the Max Planck Institute for the Physics of Complex Systems in Dresden, June 17–21, 2013. The main aim of this interdisciplinary workshop was to review comprehensively the theory and numerical implementation of the existing methods of chaos detection and predictability, as well as to report recent applications of these techniques to different scientific fields. The collection of twelve papers in this Focus Issue represents the wide range of applications, spanning mathematics, physics, astronomy, particle accelerator physics, meteorology and medical research. This Preface surveys the papers of this Issue.

  1. Development of aerodynamic prediction methods for irregular planform wings

    NASA Technical Reports Server (NTRS)

    Benepe, D. B., Sr.

    1983-01-01

    A set of empirical methods was developed to predict low-speed lift, drag and pitching-moment variations with angle of attack for a class of low aspect ratio irregular planform wings suitable for application to advanced aerospace vehicles. The data base, an extensive series of wind-tunnel tests accomplished by the Langley Research Center of the National Aeronautics and Space Administration, is summarized. The approaches used to analyze the wind tunnel data, the evaluation of previously existing methods, data correlation efforts, and the development of the selected methods are presented and discussed. A summary of the methods is also presented to document the equations, computational charts and design guides which have been programmed for digital computer solution. Comparisons of predictions and test data are presented which show that the new methods provide a significant improvement in capability for evaluating the landing characteristics of advanced aerospace vehicles during the preliminary design phase of the configuration development cycle.

  2. Neural Generalized Predictive Control: A Newton-Raphson Implementation

    NASA Technical Reports Server (NTRS)

    Soloway, Donald; Haley, Pamela J.

    1997-01-01

    An efficient implementation of Generalized Predictive Control using a multi-layer feedforward neural network as the plant's nonlinear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. The main cost of the Newton-Raphson algorithm is in the calculation of the Hessian, but even with this overhead the low iteration numbers make Newton-Raphson faster than other techniques and a viable algorithm for real-time control. This paper presents a detailed derivation of the Neural Generalized Predictive Control algorithm with Newton-Raphson as the minimization algorithm. Simulation results show convergence to a good solution within two iterations and timing data show that real-time control is possible. Comments about the algorithm's implementation are also included.

  3. Stabilisation of difference equations with noisy prediction-based control

    NASA Astrophysics Data System (ADS)

    Braverman, E.; Kelly, C.; Rodkina, A.

    2016-07-01

    We consider the influence of stochastic perturbations on stability of a unique positive equilibrium of a difference equation subject to prediction-based control. These perturbations may be multiplicative We begin by relaxing the control parameter in the deterministic equation, and deriving a range of values for the parameter over which all solutions eventually enter an invariant interval. Then, by allowing the variation to be stochastic, we derive sufficient conditions (less restrictive than known ones for the unperturbed equation) under which the positive equilibrium will be globally a.s. asymptotically stable: i.e. the presence of noise improves the known effectiveness of prediction-based control. Finally, we show that systemic noise has a "blurring" effect on the positive equilibrium, which can be made arbitrarily small by controlling the noise intensity. Numerical examples illustrate our results.

  4. Analysis of CASP8 targets, predictions and assessment methods

    PubMed Central

    Shi, ShuoYong; Pei, Jimin; Sadreyev, Ruslan I.; Kinch, Lisa N.; Majumdar, Indraneel; Tong, Jing; Cheng, Hua; Kim, Bong-Hyun; Grishin, Nick V.

    2009-01-01

    Results of the recent Critical Assessment of Techniques for Protein Structure Prediction, CASP8, present several valuable sources of information. First, CASP targets comprise a realistic sample of currently solved protein structures and exemplify the corresponding challenges for predictors. Second, the plethora of predictions by all possible methods provides an unusually rich material for evolutionary analysis of target proteins. Third, CASP results show the current state of the field and highlight specific problems in both predicting and assessing. Finally, these data can serve as grounds to develop and analyze methods for assessing prediction quality. Here we present results of our analysis in these areas. Our objective is not to duplicate CASP assessment, but to use our unique experience as former CASP5 assessors and CASP8 predictors to (i) offer more insights into CASP targets and predictions based on expert analysis, including invaluable analysis prior to target structure release; and (ii) develop an assessment methodology tailored towards current challenges in the field. Specifically, we discuss preparing target structures for assessment, parsing protein domains, balancing evaluations based on domains and on whole chains, dividing targets into categories and developing new evaluation scores. We also present evolutionary analysis of the most interesting and challenging targets. Database URL: Our results are available as a comprehensive database of targets and predictions at http://prodata.swmed.edu/CASP8. PMID:20157476

  5. Analysis of CASP8 targets, predictions and assessment methods.

    PubMed

    Shi, Shuoyong; Pei, Jimin; Sadreyev, Ruslan I; Kinch, Lisa N; Majumdar, Indraneel; Tong, Jing; Cheng, Hua; Kim, Bong-Hyun; Grishin, Nick V

    2009-01-01

    Results of the recent Critical Assessment of Techniques for Protein Structure Prediction, CASP8, present several valuable sources of information. First, CASP targets comprise a realistic sample of currently solved protein structures and exemplify the corresponding challenges for predictors. Second, the plethora of predictions by all possible methods provides an unusually rich material for evolutionary analysis of target proteins. Third, CASP results show the current state of the field and highlight specific problems in both predicting and assessing. Finally, these data can serve as grounds to develop and analyze methods for assessing prediction quality. Here we present results of our analysis in these areas. Our objective is not to duplicate CASP assessment, but to use our unique experience as former CASP5 assessors and CASP8 predictors to (i) offer more insights into CASP targets and predictions based on expert analysis, including invaluable analysis prior to target structure release; and (ii) develop an assessment methodology tailored towards current challenges in the field. Specifically, we discuss preparing target structures for assessment, parsing protein domains, balancing evaluations based on domains and on whole chains, dividing targets into categories and developing new evaluation scores. We also present evolutionary analysis of the most interesting and challenging targets.Database URL: Our results are available as a comprehensive database of targets and predictions at http://prodata.swmed.edu/CASP8. PMID:20157476

  6. Toxicologic methods: controlled human exposures.

    PubMed Central

    Utell, M J; Frampton, M W

    2000-01-01

    The assessment of risk from exposure to environmental air pollutants is complex, and involves the disciplines of epidemiology, animal toxicology, and human inhalation studies. Controlled, quantitative studies of exposed humans help determine health-related effects that result from breathing the atmosphere. The major unique feature of the clinical study is the ability to select, control, and quantify pollutant exposures of subjects of known clinical status, and determine their effects under ideal experimental conditions. The choice of outcomes to be assessed in human clinical studies can be guided by both scientific and practical considerations, but the diversity of human responses and responsiveness must be considered. Subjects considered to be among the most susceptible include those with asthma, chronic obstructive lung disease, and cardiovascular disease. New experimental approaches include exposures to concentrated ambient air particles, diesel engine exhaust, combustion products from smoking machines, and experimental model particles. Future investigations of the health effects of air pollution will benefit from collaborative efforts among the disciplines of epidemiology, animal toxicology, and human clinical studies. PMID:10931779

  7. Neural network based automatic limit prediction and avoidance system and method

    NASA Technical Reports Server (NTRS)

    Calise, Anthony J. (Inventor); Prasad, Jonnalagadda V. R. (Inventor); Horn, Joseph F. (Inventor)

    2001-01-01

    A method for performance envelope boundary cueing for a vehicle control system comprises the steps of formulating a prediction system for a neural network and training the neural network to predict values of limited parameters as a function of current control positions and current vehicle operating conditions. The method further comprises the steps of applying the neural network to the control system of the vehicle, where the vehicle has capability for measuring current control positions and current vehicle operating conditions. The neural network generates a map of current control positions and vehicle operating conditions versus the limited parameters in a pre-determined vehicle operating condition. The method estimates critical control deflections from the current control positions required to drive the vehicle to a performance envelope boundary. Finally, the method comprises the steps of communicating the critical control deflection to the vehicle control system; and driving the vehicle control system to provide a tactile cue to an operator of the vehicle as the control positions approach the critical control deflections.

  8. Development of Improved Surface Integral Methods for Jet Aeroacoustic Predictions

    NASA Technical Reports Server (NTRS)

    Pilon, Anthony R.; Lyrintzis, Anastasios S.

    1997-01-01

    The accurate prediction of aerodynamically generated noise has become an important goal over the past decade. Aeroacoustics must now be an integral part of the aircraft design process. The direct calculation of aerodynamically generated noise with CFD-like algorithms is plausible. However, large computer time and memory requirements often make these predictions impractical. It is therefore necessary to separate the aeroacoustics problem into two parts, one in which aerodynamic sound sources are determined, and another in which the propagating sound is calculated. This idea is applied in acoustic analogy methods. However, in the acoustic analogy, the determination of far-field sound requires the solution of a volume integral. This volume integration again leads to impractical computer requirements. An alternative to the volume integrations can be found in the Kirchhoff method. In this method, Green's theorem for the linear wave equation is used to determine sound propagation based on quantities on a surface surrounding the source region. The change from volume to surface integrals represents a tremendous savings in the computer resources required for an accurate prediction. This work is concerned with the development of enhancements of the Kirchhoff method for use in a wide variety of aeroacoustics problems. This enhanced method, the modified Kirchhoff method, is shown to be a Green's function solution of Lighthill's equation. It is also shown rigorously to be identical to the methods of Ffowcs Williams and Hawkings. This allows for development of versatile computer codes which can easily alternate between the different Kirchhoff and Ffowcs Williams-Hawkings formulations, using the most appropriate method for the problem at hand. The modified Kirchhoff method is developed primarily for use in jet aeroacoustics predictions. Applications of the method are shown for two dimensional and three dimensional jet flows. Additionally, the enhancements are generalized so that

  9. Increased Fidelity in Prediction Methods For Landing Gear Noise

    NASA Technical Reports Server (NTRS)

    Lopes, Leonard V.; Brentner, Kenneth S.; Morris, Philip J.; Lockhard, David P.

    2006-01-01

    An aeroacoustic prediction scheme has been developed for landing gear noise. The method is designed to handle the complex landing gear geometry of current and future aircraft. The gear is represented by a collection of subassemblies and simple components that are modeled using acoustic elements. These acoustic elements are generic, but generate noise representative of the physical components on a landing gear. The method sums the noise radiation from each component of the undercarriage in isolation accounting for interference with adjacent components through an estimate of the local upstream and downstream flows and turbulence intensities. The acoustic calculations are made in the code LGMAP, which computes the sound pressure levels at various observer locations. The method can calculate the noise from the undercarriage in isolation or installed on an aircraft for both main and nose landing gear. Comparisons with wind tunnel and flight data are used to initially calibrate the method, then it may be used to predict the noise of any landing gear. In this paper, noise predictions are compared with wind tunnel data for model landing gears of various scales and levels of fidelity, as well as with flight data on fullscale undercarriages. The present agreement between the calculations and measurements suggests the method has promise for future application in the prediction of airframe noise.

  10. Automaticity and cognitive control in the learned predictiveness effect.

    PubMed

    Shone, Lauren T; Harris, Irina M; Livesey, Evan J

    2015-01-01

    In novel contexts, learning is biased toward cues previously experienced as predictive compared with cues previously experienced as nonpredictive. This is known as learned predictiveness. A recent finding has shown that instructions issued about the causal status of cues influences the expression of learned predictiveness, suggesting that controlled, volitional processes play a role in this effect. Three experiments are reported further investigating the effects of instructional manipulations on learned predictiveness. Experiment 1 confirms the influence of inferential processes, extending previous work to suggest that instructions affect associative memory as well as causal reasoning. Experiments 2 and 3 used a procedure designed to tease apart inferential and automatic contributions to the bias by presenting instructed causes that were previously predictive and previously nonpredictive. The results demonstrate that the prior predictiveness of cues influences subsequent learning over and above the effect of explicit instruction. However, it appears that the relationship between explicit instruction and predictive history is interactive rather than additive. Potential explanations for this interactivity are discussed.

  11. Power control system and method

    DOEpatents

    Steigerwald, Robert Louis [Burnt Hills, NY; Anderson, Todd Alan [Niskayuna, NY

    2008-02-19

    A power system includes an energy harvesting device, a battery coupled to the energy harvesting device, and a circuit coupled to the energy harvesting device and the battery. The circuit is adapted to deliver power to a load by providing power generated by the energy harvesting device to the load without delivering excess power to the battery and to supplement the power generated by the energy harvesting device with power from the battery if the power generated by the energy harvesting device is insufficient to fully power the load. A method of operating the power system is also provided.

  12. Power control system and method

    DOEpatents

    Steigerwald, Robert Louis; Anderson, Todd Alan

    2006-11-07

    A power system includes an energy harvesting device, a battery coupled to the energy harvesting device, and a circuit coupled to the energy harvesting device and the battery. The circuit is adapted to deliver power to a load by providing power generated by the energy harvesting device to the load without delivering excess power to the battery and to supplement the power generated by the energy harvesting device with power from the battery if the power generated by the energy harvesting device is insufficient to fully power the load. A method of operating the power system is also provided.

  13. High accuracy operon prediction method based on STRING database scores.

    PubMed

    Taboada, Blanca; Verde, Cristina; Merino, Enrique

    2010-07-01

    We present a simple and highly accurate computational method for operon prediction, based on intergenic distances and functional relationships between the protein products of contiguous genes, as defined by STRING database (Jensen,L.J., Kuhn,M., Stark,M., Chaffron,S., Creevey,C., Muller,J., Doerks,T., Julien,P., Roth,A., Simonovic,M. et al. (2009) STRING 8-a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res., 37, D412-D416). These two parameters were used to train a neural network on a subset of experimentally characterized Escherichia coli and Bacillus subtilis operons. Our predictive model was successfully tested on the set of experimentally defined operons in E. coli and B. subtilis, with accuracies of 94.6 and 93.3%, respectively. As far as we know, these are the highest accuracies ever obtained for predicting bacterial operons. Furthermore, in order to evaluate the predictable accuracy of our model when using an organism's data set for the training procedure, and a different organism's data set for testing, we repeated the E. coli operon prediction analysis using a neural network trained with B. subtilis data, and a B. subtilis analysis using a neural network trained with E. coli data. Even for these cases, the accuracies reached with our method were outstandingly high, 91.5 and 93%, respectively. These results show the potential use of our method for accurately predicting the operons of any other organism. Our operon predictions for fully-sequenced genomes are available at http://operons.ibt.unam.mx/OperonPredictor/. PMID:20385580

  14. Predicting asthma control: the role of psychological triggers.

    PubMed

    Ritz, Thomas; Bobb, Carol; Griffiths, Chris

    2014-01-01

    Asthma triggers have been linked to adverse health outcomes in asthma, but little is known about their association with asthma control. Because trigger avoidance is an integral part of successful asthma management, psychological triggers in particular may be associated with suboptimal asthma control, given the difficulty of controlling them. We examined cross-sectional and longitudinal associations of perceived asthma triggers with self-report of asthma control impairment, symptoms, and spirometric lung function (forced expiratory volume in the 1st second, [FEV1]) in 179 adult primary care asthma patients. Perceived asthma triggers explained up to 42.5% of the variance in asthma control and symptoms, but not in FEV1 alone. Allergic triggers explained up to 12.1% of the asthma control and symptom variance, three nonallergic trigger types, air pollution/irritants, physical activity, and infection, explained up to 26.2% over and above allergic triggers, and psychological triggers up to 9.5% over and above all other triggers. Psychological triggers alone explained up to 33.9% of the variance and were the only trigger class that was consistently significant in all final multiple regression models predicting control and symptoms. Psychological triggers also predicted lower asthma control 3-6 months later, although controlling for initial asthma control eliminated this association. In free reports of individually relevant triggers, only psychological triggers were associated with suboptimal asthma control. Trigger factors are important predictors of self-reported asthma control and symptoms but not actual lung function. Particular attention should be directed to psychological triggers as indicators of patients' perceptions of suboptimal asthma control.

  15. Sample size considerations of prediction-validation methods in high-dimensional data for survival outcomes.

    PubMed

    Pang, Herbert; Jung, Sin-Ho

    2013-04-01

    A variety of prediction methods are used to relate high-dimensional genome data with a clinical outcome using a prediction model. Once a prediction model is developed from a data set, it should be validated using a resampling method or an independent data set. Although the existing prediction methods have been intensively evaluated by many investigators, there has not been a comprehensive study investigating the performance of the validation methods, especially with a survival clinical outcome. Understanding the properties of the various validation methods can allow researchers to perform more powerful validations while controlling for type I error. In addition, sample size calculation strategy based on these validation methods is lacking. We conduct extensive simulations to examine the statistical properties of these validation strategies. In both simulations and a real data example, we have found that 10-fold cross-validation with permutation gave the best power while controlling type I error close to the nominal level. Based on this, we have also developed a sample size calculation method that will be used to design a validation study with a user-chosen combination of prediction. Microarray and genome-wide association studies data are used as illustrations. The power calculation method in this presentation can be used for the design of any biomedical studies involving high-dimensional data and survival outcomes.

  16. Auxiliary particle filter-model predictive control of the vacuum arc remelting process

    NASA Astrophysics Data System (ADS)

    Lopez, F.; Beaman, J.; Williamson, R.

    2016-07-01

    Solidification control is required for the suppression of segregation defects in vacuum arc remelting of superalloys. In recent years, process controllers for the VAR process have been proposed based on linear models, which are known to be inaccurate in highly-dynamic conditions, e.g. start-up, hot-top and melt rate perturbations. A novel controller is proposed using auxiliary particle filter-model predictive control based on a nonlinear stochastic model. The auxiliary particle filter approximates the probability of the state, which is fed to a model predictive controller that returns an optimal control signal. For simplicity, the estimation and control problems are solved using Sequential Monte Carlo (SMC) methods. The validity of this approach is verified for a 430 mm (17 in) diameter Alloy 718 electrode melted into a 510 mm (20 in) diameter ingot. Simulation shows a more accurate and smoother performance than the one obtained with an earlier version of the controller.

  17. A Method of Recording and Predicting the Pollen Count.

    ERIC Educational Resources Information Center

    Buck, M.

    1985-01-01

    A hair dryer, plastic funnel, and microscope slide can be used for predicting pollen counts on a day-to-day basis. Materials, methods for assembly, collection technique, meteorological influences, and daily patterns are discussed. Data collected using the apparatus suggest that airborne grass products other than pollen also affect hay fever…

  18. Risk prediction with machine learning and regression methods.

    PubMed

    Steyerberg, Ewout W; van der Ploeg, Tjeerd; Van Calster, Ben

    2014-07-01

    This is a discussion of issues in risk prediction based on the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler.

  19. Motivation to control prejudice predicts categorization of multiracials.

    PubMed

    Chen, Jacqueline M; Moons, Wesley G; Gaither, Sarah E; Hamilton, David L; Sherman, Jeffrey W

    2014-05-01

    Multiracial individuals often do not easily fit into existing racial categories. Perceivers may adopt a novel racial category to categorize multiracial targets, but their willingness to do so may depend on their motivations. We investigated whether perceivers' levels of internal motivation to control prejudice (IMS) and external motivation to control prejudice (EMS) predicted their likelihood of categorizing Black-White multiracial faces as Multiracial. Across four studies, IMS positively predicted perceivers' categorizations of multiracial faces as Multiracial. The association between IMS and Multiracial categorizations was strongest when faces were most racially ambiguous. Explicit prejudice, implicit prejudice, and interracial contact were ruled out as explanations for the relationship between IMS and Multiracial categorizations. EMS may be negatively associated with the use of the Multiracial category. Therefore, perceivers' motivations to control prejudice have important implications for racial categorization processes.

  20. Evolutionary computational methods to predict oral bioavailability QSPRs.

    PubMed

    Bains, William; Gilbert, Richard; Sviridenko, Lilya; Gascon, Jose-Miguel; Scoffin, Robert; Birchall, Kris; Harvey, Inman; Caldwell, John

    2002-01-01

    This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico. PMID:11865672

  1. Evolutionary computational methods to predict oral bioavailability QSPRs.

    PubMed

    Bains, William; Gilbert, Richard; Sviridenko, Lilya; Gascon, Jose-Miguel; Scoffin, Robert; Birchall, Kris; Harvey, Inman; Caldwell, John

    2002-01-01

    This review discusses evolutionary and adaptive methods for predicting oral bioavailability (OB) from chemical structure. Genetic Programming (GP), a specific form of evolutionary computing, is compared with some other advanced computational methods for OB prediction. The results show that classifying drugs into 'high' and 'low' OB classes on the basis of their structure alone is solvable, and initial models are already producing output that would be useful for pharmaceutical research. The results also suggest that quantitative prediction of OB will be tractable. Critical aspects of the solution will involve the use of techniques that can: (i) handle problems with a very large number of variables (high dimensionality); (ii) cope with 'noisy' data; and (iii) implement binary choices to sub-classify molecules with behavior that are qualitatively different. Detailed quantitative predictions will emerge from more refined models that are hybrids derived from mechanistic models of the biology of oral absorption and the power of advanced computing techniques to predict the behavior of the components of those models in silico.

  2. Toward the Prediction of FBPase Inhibitory Activity Using Chemoinformatic Methods

    PubMed Central

    Hao, Ming; Zhang, Shuwei; Qiu, Jieshan

    2012-01-01

    Currently, Chemoinformatic methods are used to perform the prediction for FBPase inhibitory activity. A genetic algorithm-random forest coupled method (GA-RF) was proposed to predict fructose 1,6-bisphosphatase (FBPase) inhibitors to treat type 2 diabetes mellitus using the Mold2 molecular descriptors. A data set of 126 oxazole and thiazole analogs was used to derive the GA-RF model, yielding the significant non-cross-validated correlation coefficient r2ncv and cross-validated r2cv values of 0.96 and 0.67 for the training set, respectively. The statistically significant model was validated by a test set of 64 compounds, producing the prediction correlation coefficient r2pred of 0.90. More importantly, the building GA-RF model also passed through various criteria suggested by Tropsha and Roy with r2o and r2m values of 0.90 and 0.83, respectively. In order to compare with the GA-RF model, a pure RF model developed based on the full descriptors was performed as well for the same data set. The resulting GA-RF model with significantly internal and external prediction capacities is beneficial to the prediction of potential oxazole and thiazole series of FBPase inhibitors prior to chemical synthesis in drug discovery programs. PMID:22837677

  3. Autonomous formation flight of helicopters: Model predictive control approach

    NASA Astrophysics Data System (ADS)

    Chung, Hoam

    Formation flight is the primary movement technique for teams of helicopters. However, the potential for accidents is greatly increased when helicopter teams are required to fly in tight formations and under harsh conditions. This dissertation proposes that the automation of helicopter formations is a realistic solution capable of alleviating risks. Helicopter formation flight operations in battlefield situations are highly dynamic and dangerous, and, therefore, we maintain that both a high-level formation management system and a distributed coordinated control algorithm should be implemented to help ensure safe formations. The starting point for safe autonomous formation flights is to design a distributed control law attenuating external disturbances coming into a formation, so that each vehicle can safely maintain sufficient clearance between it and all other vehicles. While conventional methods are limited to homogeneous formations, our decentralized model predictive control (MPC) approach allows for heterogeneity in a formation. In order to avoid the conservative nature inherent in distributed MPC algorithms, we begin by designing a stable MPC for individual vehicles, and then introducing carefully designed inter-agent coupling terms in a performance index. Thus the proposed algorithm works in a decentralized manner, and can be applied to the problem of helicopter formations comprised of heterogenous vehicles. Individual vehicles in a team may be confronted by various emerging situations that will require the capability for in-flight reconfiguration. We propose the concept of a formation manager to manage separation, join, and synchronization of flight course changes. The formation manager accepts an operator's commands, information from neighboring vehicles, and its own vehicle states. Inside the formation manager, there are multiple modes and complex mode switchings represented as a finite state machine (FSM). Based on the current mode and collected

  4. A free wake method for performance prediction of VAWT

    NASA Astrophysics Data System (ADS)

    Ilin, S.; Dumitrescu, H.; Cardos, V.; Dumitrache, A.

    2012-09-01

    Based on the lifting line theory and a free vortex wake model, a method including dynamic stall effects is presented for predicting the performance of a three-dimensional vertical-axis wind turbine (VAWT). A vortex model is used in which the wake is composed of trailing streamwise and shedding spanwise vortices, whose strengths are equal to the change in the bound vortex strength as dictated by Helmholtz and Kelvin's theorems. Performance parameters are calculated by application of the Biot-Savart law along with the Kutta-Joukowski theorem and a semi-empirical dynamic stall model. Predictions are shown to compare favorably with existing experimental data.

  5. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    NASA Technical Reports Server (NTRS)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  6. Global connectivity of prefrontal cortex predicts cognitive control and intelligence

    PubMed Central

    Cole, Michael W.; Yarkoni, Tal; Repovs, Grega; Anticevic, Alan; Braver, Todd S.

    2012-01-01

    Control of thought and behavior is fundamental to human intelligence. Evidence suggests a fronto-parietal brain network implements such cognitive control across diverse contexts. We identify a mechanism – global connectivity – by which components of this network might coordinate control of other networks. A lateral prefrontal cortex (LPFC) region’s activity was found to predict performance in a high control demand working memory task, and also to exhibit high global connectivity. Critically, global connectivity in this LPFC region, involving connections both within and outside the fronto-parietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brain-wide influence that facilitates the ability to implement control processes central to human intelligence. PMID:22745498

  7. Paroxysmal atrial fibrillation prediction method with shorter HRV sequences.

    PubMed

    Boon, K H; Khalil-Hani, M; Malarvili, M B; Sia, C W

    2016-10-01

    This paper proposes a method that predicts the onset of paroxysmal atrial fibrillation (PAF), using heart rate variability (HRV) segments that are shorter than those applied in existing methods, while maintaining good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to stabilize (electrically) and prevent the onset of atrial arrhythmias with different pacing techniques. We investigate the effect of HRV features extracted from different lengths of HRV segments prior to PAF onset with the proposed PAF prediction method. The pre-processing stage of the predictor includes QRS detection, HRV quantification and ectopic beat correction. Time-domain, frequency-domain, non-linear and bispectrum features are then extracted from the quantified HRV. In the feature selection, the HRV feature set and classifier parameters are optimized simultaneously using an optimization procedure based on genetic algorithm (GA). Both full feature set and statistically significant feature subset are optimized by GA respectively. For the statistically significant feature subset, Mann-Whitney U test is used to filter non-statistical significance features that cannot pass the statistical test at 20% significant level. The final stage of our predictor is the classifier that is based on support vector machine (SVM). A 10-fold cross-validation is applied in performance evaluation, and the proposed method achieves 79.3% prediction accuracy using 15-minutes HRV segment. This accuracy is comparable to that achieved by existing methods that use 30-minutes HRV segments, most of which achieves accuracy of around 80%. More importantly, our method significantly outperforms those that applied segments shorter than 30 minutes. PMID:27480743

  8. Evaluation of ride quality prediction methods for operational military helicopters

    NASA Technical Reports Server (NTRS)

    Leatherwood, J. D.; Clevenson, S. A.; Hollenbaugh, D. D.

    1984-01-01

    The results of a simulator study conducted to compare and validate various ride quality prediction methods for use in assessing passenger/crew ride comfort within helicopters are presented. Included are results quantifying 35 helicopter pilots' discomfort responses to helicopter interior noise and vibration typical of routine flights, assessment of various ride quality metrics including the NASA ride comfort model, and examination of possible criteria approaches. Results of the study indicated that crew discomfort results from a complex interaction between vibration and interior noise. Overall measures such as weighted or unweighted root-mean-square acceleration level and A-weighted noise level were not good predictors of discomfort. Accurate prediction required a metric incorporating the interactive effects of both noise and vibration. The best metric for predicting crew comfort to the combined noise and vibration environment was the NASA discomfort index.

  9. Benchmarking B cell epitope prediction: underperformance of existing methods.

    PubMed

    Blythe, Martin J; Flower, Darren R

    2005-01-01

    Sequence profiling is used routinely to predict the location of B-cell epitopes. In the postgenomic era, the need for reliable epitope prediction is clear. We assessed 484 amino acid propensity scales in combination with ranges of plotting parameters to examine exhaustively the correlation of peaks and epitope location within 50 proteins mapped for polyclonal responses. After examining more than 10(6) combinations, we found that even the best set of scales and parameters performed only marginally better than random. Our results confirm the null hypothesis: Single-scale amino acid propensity profiles cannot be used to predict epitope location reliably. The implication for studies using such methods is obvious. PMID:15576553

  10. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    SciTech Connect

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  11. Pedophilia: an evaluation of diagnostic and risk prediction methods.

    PubMed

    Wilson, Robin J; Abracen, Jeffrey; Looman, Jan; Picheca, Janice E; Ferguson, Meaghan

    2011-06-01

    One hundred thirty child sexual abusers were diagnosed using each of following four methods: (a) phallometric testing, (b) strict application of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text revision [DSM-IV-TR]) criteria, (c) Rapid Risk Assessment of Sex Offender Recidivism (RRASOR) scores, and (d) "expert" diagnoses rendered by a seasoned clinician. Comparative utility and intermethod consistency of these methods are reported, along with recidivism data indicating predictive validity for risk management. Results suggest that inconsistency exists in diagnosing pedophilia, leading to diminished accuracy in risk assessment. Although the RRASOR and DSM-IV-TR methods were significantly correlated with expert ratings, RRASOR and DSM-IV-TR were unrelated to each other. Deviant arousal was not associated with any of the other methods. Only the expert ratings and RRASOR scores were predictive of sexual recidivism. Logistic regression analyses showed that expert diagnosis did not add to prediction of sexual offence recidivism over and above RRASOR alone. Findings are discussed within a context of encouragement of clinical consistency and evidence-based practice regarding treatment and risk management of those who sexually abuse children.

  12. A computational method to predict carbonylation sites in yeast proteins.

    PubMed

    Lv, H Q; Liu, J; Han, J Q; Zheng, J G; Liu, R L

    2016-01-01

    Several post-translational modifications (PTM) have been discussed in literature. Among a variety of oxidative stress-induced PTM, protein carbonylation is considered a biomarker of oxidative stress. Only certain proteins can be carbonylated because only four amino acid residues, namely lysine (K), arginine (R), threonine (T) and proline (P), are susceptible to carbonylation. The yeast proteome is an excellent model to explore oxidative stress, especially protein carbonylation. Current experimental approaches in identifying carbonylation sites are expensive, time-consuming and limited in their abilities to process proteins. Furthermore, there is no bioinformational method to predict carbonylation sites in yeast proteins. Therefore, we propose a computational method to predict yeast carbonylation sites. This method has total accuracies of 86.32, 85.89, 84.80, and 86.80% in predicting the carbonylation sites of K, R, T, and P, respectively. These results were confirmed by 10-fold cross-validation. The ability to identify carbonylation sites in different kinds of features was analyzed and the position-specific composition of the modification site-flanking residues was discussed. Additionally, a software tool has been developed to help with the calculations in this method. Datasets and the software are available at https://sourceforge.net/projects/hqlstudio/ files/CarSpred.Y/. PMID:27420944

  13. Model predictive control of a wind turbine modelled in Simpack

    NASA Astrophysics Data System (ADS)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  14. Improved load ratio method for predicting crack length

    SciTech Connect

    Chen, X.; Albrecht, P.; Wright, W.; Joyce, J.A.

    1995-04-01

    The elastic compliance from unloading/reloading sequences in a load-displacement record estimates well crack length in elastic-plastic fracture toughness tests of compact tension [C(T)] and bending type specimens. The need for partial unloading of the specimen makes it difficult to run the test under static loading and impossible under either dynamic loading or very high temperatures. Furthermore, fracture toughness testing in which crack length is determined from elastic compliance requires high precision testing equipment and highly skilled technicians. As a result, such tests are confined usually to research laboratories and seldom used under production settings. To eliminate these problems, an improved load ratio method of predicting crack length is proposed that utilizes only the recorded load versus load-line displacement curve (or load versus crack-mouth-opening displacement curve) without unloading/reloading sequences. As a result, the instrumentation is much simpler than in the elastic compliance or potential drop methods. If only a monotonic load-displacement record is to be measured the fracture toughness test becomes almost as simple to perform as a tension test. The method described here improves in three ways the ``original load ratio method`` proposed by Hu et al. First, a blunting term is added to the crack length before maximum load. Second, a strain hardening correction is included after maximum load. And, third, the initial crack length and the physical (final) crack length measured at the end of the test serve to anchor the predicted crack lengths, forcing agreement between predicted and measured values. The method predicts crack extension with excellent accuracy in specimens fabricated from A302, A508, and A533B piping and pressure vessel steels, A588 and A572 structural steels, and HY-80 ship steel.

  15. A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model

    PubMed Central

    Niu, Jian; Zhao, Jun; Xu, Zuhua; Qian, Jixin

    2009-01-01

    A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. PMID:19834542

  16. Fast prediction unit selection method for HEVC intra prediction based on salient regions

    NASA Astrophysics Data System (ADS)

    Feng, Lei; Dai, Ming; Zhao, Chun-lei; Xiong, Jing-ying

    2016-07-01

    In order to reduce the computational complexity of the high efficiency video coding (HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit (PU) size selection method for HEVC based on salient regions is proposed in this paper. We first build a saliency map for each largest coding unit (LCU) to reduce its texture complexity. Secondly, the optimal PU size is determined via a scheme that implements an information entropy comparison among sub-blocks of saliency maps. Finally, we apply the partitioning result of saliency map on the original LCUs, obtaining the optimal partitioning result. Our algorithm can determine the PU size in advance to the angular prediction in intra coding, reducing computational complexity of HEVC. The experimental results show that our algorithm achieves a 37.9% reduction in encoding time, while producing a negligible loss in Bjontegaard delta bit rate ( BDBR) of 0.62%.

  17. Method to predict external store carriage characteristics at transonic speeds

    NASA Technical Reports Server (NTRS)

    Rosen, Bruce S.

    1988-01-01

    Development of a computational method for prediction of external store carriage characteristics at transonic speeds is described. The geometric flexibility required for treatment of pylon-mounted stores is achieved by computing finite difference solutions on a five-level embedded grid arrangement. A completely automated grid generation procedure facilitates applications. Store modeling capability consists of bodies of revolution with multiple fore and aft fins. A body-conforming grid improves the accuracy of the computed store body flow field. A nonlinear relaxation scheme developed specifically for modified transonic small disturbance flow equations enhances the method's numerical stability and accuracy. As a result, treatment of lower aspect ratio, more highly swept and tapered wings is possible. A limited supersonic freestream capability is also provided. Pressure, load distribution, and force/moment correlations show good agreement with experimental data for several test cases. A detailed computer program description for the Transonic Store Carriage Loads Prediction (TSCLP) Code is included.

  18. Coastal cliff recession: the use of probabilistic prediction methods

    NASA Astrophysics Data System (ADS)

    Lee, E. M.; Hall, J. W.; Meadowcroft, I. C.

    2001-10-01

    A range of probabilistic methods is introduced for predicting coastal cliff recession, which provide a means of demonstrating the potential variability in such predictions. They form the basis for risk-based land-use planning, cliff management and engineering decision-making. Examples of probabilistic models are presented for a number of different cliff settings: the simulation of recession on eroding cliffs; the use of historical records and statistical experiments to model the behaviour of cliffs affected by rare, episodic landslide events; the adaptation of an event tree approach to assess the probability of failure of protected cliffs, taking into account the residual life of the existing defences; and the evaluation of the probability of landslide reactivation in areas of pre-existing landslide systems. These methods are based on a geomorphological assessment of the episodic nature of the recession process, together with historical records.

  19. Punishment sensitivity predicts the impact of punishment on cognitive control.

    PubMed

    Braem, Senne; Duthoo, Wout; Notebaert, Wim

    2013-01-01

    Cognitive control theories predict enhanced conflict adaptation after punishment. However, no such effect was found in previous work. In the present study, we demonstrate in a flanker task how behavioural adjustments following punishment signals are highly dependent on punishment sensitivity (as measured by the Behavioural Inhibition System (BIS) scale): Whereas low punishment-sensitive participants do show increased conflict adaptation after punishment, high punishment-sensitive participants show no such modulation. Interestingly, participants with a high punishment-sensitivity showed an overall reaction time increase after punishments. Our results stress the role of individual differences in explaining motivational modulations of cognitive control.

  20. Experimental Investigations of Generalized Predictive Control for Tiltrotor Stability Augmentation

    NASA Technical Reports Server (NTRS)

    Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Piatak, David J.; Kvaternik, Raymond G.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    A team of researchers from the Army Research Laboratory, NASA Langley Research Center (LaRC), and Bell Helicopter-Textron, Inc. have completed hover-cell and wind-tunnel testing of a 1/5-size aeroelastically-scaled tiltrotor model using a new active control system for stability augmentation. The active system is based on a generalized predictive control (GPC) algorithm originally developed at NASA LaRC in 1997 for un-known disturbance rejection. Results of these investigations show that GPC combined with an active swashplate can significantly augment the damping and stability of tiltrotors in both hover and high-speed flight.

  1. Adaptive Pole Placement Controllers For Robotic Manipulators With Predictive Action

    NASA Astrophysics Data System (ADS)

    Kaynak, Okyay; Hoyer, Helmut

    1987-10-01

    This paper proposes two pole assignment control schemes for robotic manipulators, based on an anticipatory action. In one, the control objective is for the velocity tracking error to decay with a prespecified dynamics. In the other, a generalised cost function is minimized and the weighting factors in the cost function are determined to achieve desired closed loop pole locations for the tracking error. The prediction scheme used ensures a high degree of robustness against system-model mismatch as demonstrated by the simulation results presented.

  2. Prediction and control of chaotic processes using nonlinear adaptive networks

    SciTech Connect

    Jones, R.D.; Barnes, C.W.; Flake, G.W.; Lee, K.; Lewis, P.S.; O'Rouke, M.K.; Qian, S.

    1990-01-01

    We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

  3. Epileptic seizure prediction by non-linear methods

    DOEpatents

    Hively, L.M.; Clapp, N.E.; Day, C.S.; Lawkins, W.F.

    1999-01-12

    This research discloses methods and apparatus for automatically predicting epileptic seizures monitor and analyze brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis tools; obtaining time serial trends in the nonlinear measures; comparison of the trend to known seizure predictors; and providing notification that a seizure is forthcoming. 76 figs.

  4. Epileptic seizure prediction by non-linear methods

    DOEpatents

    Hively, Lee M.; Clapp, Ned E.; Daw, C. Stuart; Lawkins, William F.

    1999-01-01

    Methods and apparatus for automatically predicting epileptic seizures monitor and analyze brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis tools; obtaining time serial trends in the nonlinear measures; comparison of the trend to known seizure predictors; and providing notification that a seizure is forthcoming.

  5. Model reduction methods for control design

    NASA Technical Reports Server (NTRS)

    Dunipace, K. R.

    1988-01-01

    Several different model reduction methods are developed and detailed implementation information is provided for those methods. Command files to implement the model reduction methods in a proprietary control law analysis and design package are presented. A comparison and discussion of the various reduction techniques is included.

  6. An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands

    PubMed Central

    Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias

    2015-01-01

    The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences. PMID:26391305

  7. Control of nonlinear processes by using linear model predictive control algorithms.

    PubMed

    Gu, Bingfeng; Gupta, Yash P

    2008-04-01

    Most chemical processes are inherently nonlinear. However, because of their simplicity, linear control algorithms have been used for the control of nonlinear processes. In this study, the use of the dynamic matrix control algorithm and a simplified model predictive control algorithm for control of a bench-scale pH neutralization process is investigated. The nonlinearity is handled by dividing the operating region into sub-regions and by switching the controller model as the process moves from one sub-region to another. A simple modification for model predictive control algorithms is presented to handle the switching. The simulation and experimental results show that the modification can provide a significant improvement in the control of nonlinear processes. PMID:18255068

  8. Real-time implementation of model predictive control on Maricopa-Stanfield irrigation and drainage district's WM canal

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Water resources are limited in many agricultural areas. One method to improve the effective use of water is to improve delivery service from irrigation canals. This can be done by applying automatic control methods that control the gates in an irrigation canal. The model predictive control MPC is ...

  9. CREME96 and Related Error Rate Prediction Methods

    NASA Technical Reports Server (NTRS)

    Adams, James H., Jr.

    2012-01-01

    Predicting the rate of occurrence of single event effects (SEEs) in space requires knowledge of the radiation environment and the response of electronic devices to that environment. Several analytical models have been developed over the past 36 years to predict SEE rates. The first error rate calculations were performed by Binder, Smith and Holman. Bradford and Pickel and Blandford, in their CRIER (Cosmic-Ray-Induced-Error-Rate) analysis code introduced the basic Rectangular ParallelePiped (RPP) method for error rate calculations. For the radiation environment at the part, both made use of the Cosmic Ray LET (Linear Energy Transfer) spectra calculated by Heinrich for various absorber Depths. A more detailed model for the space radiation environment within spacecraft was developed by Adams and co-workers. This model, together with a reformulation of the RPP method published by Pickel and Blandford, was used to create the CR ME (Cosmic Ray Effects on Micro-Electronics) code. About the same time Shapiro wrote the CRUP (Cosmic Ray Upset Program) based on the RPP method published by Bradford. It was the first code to specifically take into account charge collection from outside the depletion region due to deformation of the electric field caused by the incident cosmic ray. Other early rate prediction methods and codes include the Single Event Figure of Merit, NOVICE, the Space Radiation code and the effective flux method of Binder which is the basis of the SEFA (Scott Effective Flux Approximation) model. By the early 1990s it was becoming clear that CREME and the other early models needed Revision. This revision, CREME96, was completed and released as a WWW-based tool, one of the first of its kind. The revisions in CREME96 included improved environmental models and improved models for calculating single event effects. The need for a revision of CREME also stimulated the development of the CHIME (CRRES/SPACERAD Heavy Ion Model of the Environment) and MACREE (Modeling and

  10. Nonlinear Predictive Control of Wind Energy Conversion System Using Dfig with Aerodynamic Torque Observer

    NASA Astrophysics Data System (ADS)

    Kamel, Ouari; Mohand, Ouhrouche; Toufik, Rekioua; Taib, Nabil

    2015-01-01

    In order to improvement of the performances for wind energy conversions systems (WECS), an advanced control techniques must be used. In this paper, as an alternative to conventional PI-type control methods, a nonlinear predictive control (NPC) approach is developed for DFIG-based wind turbine. To enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. An explicitly analytical form of the optimal predictive controller is given consequently on-line optimization is not necessary The DFIG is fed through the rotor windings by a back-to-back converter controlled by Pulse Width Modulation (PWM), where the stator winding is directly connected to the grid. The presented simulation results show a good performance in trajectory tracking of the proposed strategy and rejection of disturbances is successfully achieved.

  11. Two Efficient Twin ELM Methods With Prediction Interval.

    PubMed

    Ning, Kefeng; Liu, Min; Dong, Mingyu; Wu, Cheng; Wu, ZhanSong

    2015-09-01

    In the operational optimization and scheduling problems of actual industrial processes, such as iron and steel, and microelectronics, the operational indices and process parameters usually need to be predicted. However, for some input and output variables of these prediction models, there may exist a lot of uncertainties coming from themselves, the measurement error, the rough representation, and so on. In such cases, constructing a prediction interval (PI) for the output of the corresponding prediction model is very necessary. In this paper, two twin extreme learning machine (TELM) models for constructing PIs are proposed. First, we propose a regularized asymmetric least squares extreme learning machine (RALS-ELM) method, in which different weights of its squared error loss function are set according to whether the error of the model output is positive or negative in order that the above error can be differentiated in the parameter learning process, and Tikhonov regularization is introduced to reduce overfitting. Then, we propose an asymmetric Bayesian extreme learning machine (AB-ELM) method based on the Bayesian framework with the asymmetric Gaussian distribution (AB-ELM), in which the weights of its likelihood function are determined as the same method in RALS-ELM, and the type II maximum likelihood algorithm is derived to learn the parameters of AB-ELM. Based on RALS-ELM and AB-ELM, we use a pair of weights following the reciprocal relationship to obtain two nonparallel regressors, including a lower-bound regressor and an upper-bound regressor, respectively, which can be used for calculating the PIs. Finally, some discussions are given, about how to adjust the weights adaptively to meet the desired PI, how to use the proposed TELMs for nonlinear quantile regression, and so on. Results of numerical comparison on data from one synthetic regression problem, three University of California Irvine benchmark regression problems, and two actual industrial regression

  12. Method of predicting mechanical properties of decayed wood

    DOEpatents

    Kelley, Stephen S.

    2003-07-15

    A method for determining the mechanical properties of decayed wood that has been exposed to wood decay microorganisms, comprising: a) illuminating a surface of decayed wood that has been exposed to wood decay microorganisms with wavelengths from visible and near infrared (VIS-NIR) spectra; b) analyzing the surface of the decayed wood using a spectrometric method, the method generating a first spectral data of wavelengths in VIS-NIR spectra region; and c) using a multivariate analysis to predict mechanical properties of decayed wood by comparing the first spectral data with a calibration model, the calibration model comprising a second spectrometric method of spectral data of wavelengths in VIS-NIR spectra obtained from a reference decay wood, the second spectral data being correlated with a known mechanical property analytical result obtained from the reference decayed wood.

  13. A model predictive control approach for the Italian LBE XADS

    NASA Astrophysics Data System (ADS)

    Cammi, Antonio; Casella, Francesco; Luzzi, Lelio; Milano, Alessandro; Ricotti, Marco E.

    2008-06-01

    In this paper, model predictive control (MPC) is applied to the Italian 80 MW th experimental accelerator driven system (XADS), referring to a simple, non-linear model for the dynamic simulation of the plant, which has been developed and described in a previous work [A. Cammi, L. Luzzi, A.A. Porta, M.E. Ricotti, Prog. Nucl. Energ. 48 (2006) 578], in order to describe the interactions among the different subsystems: i.e., the accelerator-core coupling, the lead bismuth eutectic (LBE) primary system, the secondary system with diathermic oil and air coolers batteries, which reject the thermal power to the environment. Hereinafter, a model predictive controller is proposed, with the objective to minimize the difference between the average temperature of the diathermic oil and its reference value, while also minimizing the variations of the control input, which is the air coolers mass flow rate. The dynamic response of the LBE-XADS has been evaluated with reference to a reduction of 20% in the reactor power from nominal load conditions: this transient is very demanding for the overall plant, nevertheless the obtained results indicate the effectiveness of the proposed controller.

  14. Unity power factor converter based on a fuzzy controller and predictive input current.

    PubMed

    Bouafassa, Amar; Rahmani, Lazhar; Kessal, Abdelhalim; Babes, Badreddine

    2014-11-01

    This paper proposes analysis and control of a single-phase power factor corrector (PFC). The proposed control is capable of achieving a unity power factor for each DC link voltage or load fluctuation. The method under study is composed of two intelligent approaches, a fuzzy logic controller to ensure an output voltage at a suitable value and predictive current control. The fuzzy controller is used with minimum rules to attain a low cost. The method is verified and discussed through simulation on the MATLAB/Simulink platform. It presents high dynamic performance under various parameter changes. Moreover, in order to examine and evaluate the method in real-time, a test bench is built using dSPACE 1104. The implantation of the proposed method is very easy and flexible and allows for operation under parameter variations. Additionally, the obtained results are very significant.

  15. Method for controlled hydrogen charging of metals

    DOEpatents

    Cheng, Bo-Ching; Adamson, Ronald B.

    1984-05-29

    A method for controlling hydrogen charging of hydride forming metals through a window of a superimposed layer of a non-hydriding metal overlying the portion of the hydride forming metals to be charged.

  16. Simple method for model reference adaptive control

    NASA Technical Reports Server (NTRS)

    Seraji, H.

    1989-01-01

    A simple method is presented for combined signal synthesis and parameter adaptation within the framework of model reference adaptive control theory. The results are obtained using a simple derivation based on an improved Liapunov function.

  17. Prediction and control of neural responses to pulsatile electrical stimulation

    NASA Astrophysics Data System (ADS)

    Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  18. Limits of Executive Control: Sequential Effects in Predictable Environments.

    PubMed

    Verbruggen, Frederick; McAndrew, Amy; Weidemann, Gabrielle; Stevens, Tobias; McLaren, Ian P L

    2016-05-01

    Cognitive-control theories attribute action control to executive processes that modulate behavior on the basis of expectancy or task rules. In the current study, we examined corticospinal excitability and behavioral performance in a go/no-go task. Go and no-go trials were presented in runs of five, and go and no-go runs alternated predictably. At the beginning of each trial, subjects indicated whether they expected a go trial or a no-go trial. Analyses revealed that subjects immediately adjusted their expectancy ratings when a new run started. However, motor excitability was primarily associated with the properties of the previous trial, rather than the predicted properties of the current trial. We also observed a large latency cost at the beginning of a go run (i.e., reaction times were longer for the first trial in a go run than for the second trial). These findings indicate that actions in predictable environments are substantially influenced by previous events, even if this influence conflicts with conscious expectancies about upcoming events. PMID:27000177

  19. Structural Acoustic Prediction and Interior Noise Control Technology

    NASA Technical Reports Server (NTRS)

    Mathur, G. P.; Chin, C. L.; Simpson, M. A.; Lee, J. T.; Palumbo, Daniel L. (Technical Monitor)

    2001-01-01

    This report documents the results of Task 14, "Structural Acoustic Prediction and Interior Noise Control Technology". The task was to evaluate the performance of tuned foam elements (termed Smart Foam) both analytically and experimentally. Results taken from a three-dimensional finite element model of an active, tuned foam element are presented. Measurements of sound absorption and sound transmission loss were taken using the model. These results agree well with published data. Experimental performance data were taken in Boeing's Interior Noise Test Facility where 12 smart foam elements were applied to a 757 sidewall. Several configurations were tested. Noise reductions of 5-10 dB were achieved over the 200-800 Hz bandwidth of the controller. Accelerometers mounted on the panel provided a good reference for the controller. Configurations with far-field error microphones outperformed near-field cases.

  20. Self-Tuning of Design Variables for Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Lin, Chaung; Juang, Jer-Nan

    2000-01-01

    Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper.

  1. Energy-efficient container handling using hybrid model predictive control

    NASA Astrophysics Data System (ADS)

    Xin, Jianbin; Negenborn, Rudy R.; Lodewijks, Gabriel

    2015-11-01

    The performance of container terminals needs to be improved to adapt the growth of containers while maintaining sustainability. This paper provides a methodology for determining the trajectory of three key interacting machines for carrying out the so-called bay handling task, involving transporting containers between a vessel and the stacking area in an automated container terminal. The behaviours of the interacting machines are modelled as a collection of interconnected hybrid systems. Hybrid model predictive control (MPC) is proposed to achieve optimal performance, balancing the handling capacity and energy consumption. The underlying control problem is hereby formulated as a mixed-integer linear programming problem. Simulation studies illustrate that a higher penalty on energy consumption indeed leads to improved sustainability using less energy. Moreover, simulations illustrate how the proposed energy-efficient hybrid MPC controller performs under different types of uncertainties.

  2. Terminal spacecraft rendezvous and capture with LASSO model predictive control

    NASA Astrophysics Data System (ADS)

    Hartley, Edward N.; Gallieri, Marco; Maciejowski, Jan M.

    2013-11-01

    The recently investigated ℓasso model predictive control (MPC) is applied to the terminal phase of a spacecraft rendezvous and capture mission. The interaction between the cost function and the treatment of minimum impulse bit is also investigated. The propellant consumption with ℓasso MPC for the considered scenario is noticeably less than with a conventional quadratic cost and control actions are sparser in time. Propellant consumption and sparsity are competitive with those achieved using a zone-based ℓ1 cost function, whilst requiring fewer decision variables in the optimisation problem than the latter. The ℓasso MPC is demonstrated to meet tighter specifications on control precision and also avoids the risk of undesirable behaviours often associated with pure ℓ1 stage costs.

  3. Efficient Unstructured Grid Adaptation Methods for Sonic Boom Prediction

    NASA Technical Reports Server (NTRS)

    Campbell, Richard L.; Carter, Melissa B.; Deere, Karen A.; Waithe, Kenrick A.

    2008-01-01

    This paper examines the use of two grid adaptation methods to improve the accuracy of the near-to-mid field pressure signature prediction of supersonic aircraft computed using the USM3D unstructured grid flow solver. The first method (ADV) is an interactive adaptation process that uses grid movement rather than enrichment to more accurately resolve the expansion and compression waves. The second method (SSGRID) uses an a priori adaptation approach to stretch and shear the original unstructured grid to align the grid with the pressure waves and reduce the cell count required to achieve an accurate signature prediction at a given distance from the vehicle. Both methods initially create negative volume cells that are repaired in a module in the ADV code. While both approaches provide significant improvements in the near field signature (< 3 body lengths) relative to a baseline grid without increasing the number of grid points, only the SSGRID approach allows the details of the signature to be accurately computed at mid-field distances (3-10 body lengths) for direct use with mid-field-to-ground boom propagation codes.

  4. Method of controlling fusion reaction rates

    DOEpatents

    Kulsrud, Russell M.; Furth, Harold P.; Valeo, Ernest J.; Goldhaber, Maurice

    1988-01-01

    A method of controlling the reaction rates of the fuel atoms in a fusion reactor comprises the step of polarizing the nuclei of the fuel atoms in a particular direction relative to the plasma confining magnetic field. Fusion reaction rates can be increased or decreased, and the direction of emission of the reaction products can be controlled, depending on the choice of polarization direction.

  5. Method of controlling fusion reaction rates

    DOEpatents

    Kulsrud, Russell M.; Furth, Harold P.; Valeo, Ernest J.; Goldhaber, Maurice

    1988-03-01

    A method of controlling the reaction rates of the fuel atoms in a fusion reactor comprises the step of polarizing the nuclei of the fuel atoms in a particular direction relative to the plasma confining magnetic field. Fusion reaction rates can be increased or decreased, and the direction of emission of the reaction products can be controlled, depending on the choice of polarization direction.

  6. Method and apparatus for controlling electroslag remelting

    DOEpatents

    Maguire, Michael C.; Zanner, Frank J.; Damkroger, Brian K.; Miszkiel, Mark E.; Aronson, Eugene A.

    1994-01-01

    Method and apparatus for controlling electrode immersion depth in an electroslag remelting furnace. The phase difference of the alternating current circuit established in the furnace is calculated in real time and employed to more accurately control immersion depth than possible with voltage-swing systems.

  7. Barrier methods of birth control - slideshow

    MedlinePlus

    ... gov/ency/presentations/100107.htm Barrier methods of birth control - series—Female normal anatomy To use the sharing ... A.M. Editorial team. Related MedlinePlus Health Topics Birth Control A.D.A.M., Inc. is accredited by ...

  8. Method for predicting photocatalytic oxidation rates of organic compounds.

    PubMed

    Sattler, Melanie L; Liljestrand, Howard M

    2003-01-01

    In designing a photocatalytic oxidation (PCO) system for a given air pollution source, destruction rates for volatile organic compounds (VOCs) are required. The objective of this research was to develop a systematic method of predicting PCO rate constants by correlating rate constants with physical-chemical characteristics of compounds. Accordingly, reaction rate constants were determined for destruction of volatile organics over a titanium dioxide (TiO2) catalyst in a continuous mixed-batch reactor. It was found that PCO rate constants for alkanes and alkenes vary linearly with gas-phase ionization potential (IP) and with gas-phase hydroxyl radical reaction rate constant. The correlations allow rates of destruction of compounds not tested in this research to be predicted based on physical-chemical characteristics. PMID:12568248

  9. Methods for exploring uncertainty in groundwater management predictions

    USGS Publications Warehouse

    Guillaume, Joseph H. A.; Hunt, Randall J.; Comunian, Alessandro; Fu, Baihua; Blakers, Rachel S; Jakeman, Anthony J; Barreteau, Olivier; Hunt, Randall J.; Rinaudo, Jean-Daniel; Ross, Andrew

    2016-01-01

    Models of groundwater systems help to integrate knowledge about the natural and human system covering different spatial and temporal scales, often from multiple disciplines, in order to address a range of issues of concern to various stakeholders. A model is simply a tool to express what we think we know. Uncertainty, due to lack of knowledge or natural variability, means that there are always alternative models that may need to be considered. This chapter provides an overview of uncertainty in models and in the definition of a problem to model, highlights approaches to communicating and using predictions of uncertain outcomes and summarises commonly used methods to explore uncertainty in groundwater management predictions. It is intended to raise awareness of how alternative models and hence uncertainty can be explored in order to facilitate the integration of these techniques with groundwater management.

  10. A MODEL AND CONTROLLER REDUCTION METHOD FOR ROBUST CONTROL DESIGN.

    SciTech Connect

    YUE,M.; SCHLUETER,R.

    2003-10-20

    A bifurcation subsystem based model and controller reduction approach is presented. Using this approach a robust {micro}-synthesis SVC control is designed for interarea oscillation and voltage control based on a small reduced order bifurcation subsystem model of the full system. The control synthesis problem is posed by structured uncertainty modeling and control configuration formulation using the bifurcation subsystem knowledge of the nature of the interarea oscillation caused by a specific uncertainty parameter. Bifurcation subsystem method plays a key role in this paper because it provides (1) a bifurcation parameter for uncertainty modeling; (2) a criterion to reduce the order of the resulting MSVC control; and (3) a low order model for a bifurcation subsystem based SVC (BMSVC) design. The use of the model of the bifurcation subsystem to produce a low order controller simplifies the control design and reduces the computation efforts so significantly that the robust {micro}-synthesis control can be applied to large system where the computation makes robust control design impractical. The RGA analysis and time simulation show that the reduced BMSVC control design captures the center manifold dynamics and uncertainty structure of the full system model and is capable of stabilizing the full system and achieving satisfactory control performance.

  11. COMSAC: Computational Methods for Stability and Control. Part 2

    NASA Technical Reports Server (NTRS)

    Fremaux, C. Michael (Compiler); Hall, Robert M. (Compiler)

    2004-01-01

    The unprecedented advances being made in computational fluid dynamic (CFD) technology have demonstrated the powerful capabilities of codes in applications to civil and military aircraft. Used in conjunction with wind-tunnel and flight investigations, many codes are now routinely used by designers in diverse applications such as aerodynamic performance predictions and propulsion integration. Typically, these codes are most reliable for attached, steady, and predominantly turbulent flows. As a result of increasing reliability and confidence in CFD, wind-tunnel testing for some new configurations has been substantially reduced in key areas, such as wing trade studies for mission performance guarantees. Interest is now growing in the application of computational methods to other critical design challenges. One of the most important disciplinary elements for civil and military aircraft is prediction of stability and control characteristics. CFD offers the potential for significantly increasing the basic understanding, prediction, and control of flow phenomena associated with requirements for satisfactory aircraft handling characteristics.

  12. Predicting changes in hypertension control using electronic health records from a chronic disease management program

    PubMed Central

    Sun, Jimeng; McNaughton, Candace D; Zhang, Ping; Perer, Adam; Gkoulalas-Divanis, Aris; Denny, Joshua C; Kirby, Jacqueline; Lasko, Thomas; Saip, Alexander; Malin, Bradley A

    2014-01-01

    Objective Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control. Method In a cohort of 1294 patients with hypertension enrolled in a chronic disease management program at the Vanderbilt University Medical Center, patients are modeled as an array of features derived from the clinical domain over time, which are distilled into a core set using an information gain criteria regarding their predictive performance. A model for transition point prediction was then computed using a random forest classifier. Results The most predictive features for transitions in hypertension control status included hypertension assessment patterns, comorbid diagnoses, procedures and medication history. The final random forest model achieved a c-statistic of 0.836 (95% CI 0.830 to 0.842) and an accuracy of 0.773 (95% CI 0.766 to 0.780). Conclusions This study achieved accurate prediction of transition points of hypertension control status, an important first step in the long-term goal of developing personalized hypertension management plans. PMID:24045907

  13. Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

    PubMed Central

    2010-01-01

    Background All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. Results The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. Conclusions This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant

  14. LED lamp color control system and method

    DOEpatents

    Gaines, James; Clauberg, Bernd; Van Erp, Josephus A.M.

    2013-02-05

    An LED lamp color control system and method including an LED lamp having an LED controller 58; and a plurality of LED channels 60 operably connected to the LED controller 58, each of the plurality of LED channels 60 having a channel switch 62 in series with at least one shunted LED circuit 83, the shunted LED circuit 83 having a shunt switch 68 in parallel with an LED source 80. The LED controller 58 determines whether the LED source 80 is in a feedback controllable range, stores measured optical flux for the LED source 80 when the LED source 80 is in the feedback controllable range, and bypasses storing the measured optical flux when the LED source 80 is not in the feedback controllable range.

  15. Daylight control system, device and method

    DOEpatents

    Paton, John Douglas

    2012-08-28

    A system and device for and a method of programming and controlling light fixtures is disclosed. A system in accordance with the present invention includes a stationary controller unit that is electrically coupled to the light fixtures. The stationary controller unit is configured to be remotely programmed with a portable commissioning device to automatically control the lights fixtures. The stationary controller unit and the portable commissioning device include light sensors, micro-computers and transceivers for measuring light levels, running programs, storing data and transmitting data between the stationary controller unit and the portable commissioning device. In operation, target light levels selected with the portable commissioning device and the controller unit is remotely programmed to automatically maintain the target level.

  16. Daylight control system device and method

    DOEpatents

    Paton, John Douglas

    2007-03-13

    A system and device for and a method of programming and controlling light fixtures is disclosed. A system in accordance with the present invention includes a stationary controller unit that is electrically coupled to the light fixtures. The stationary controller unit is configured to be remotely programmed with a portable commissioning device to automatically control the lights fixtures. The stationary controller unit and the portable commissioning device include light sensors, micro-computers and transceivers for measuring light levels, running programs, storing data and transmitting data between the stationary controller unit and the portable commissioning device. In operation, target light levels selected with the portable commissioning device and the controller unit is remotely programmed to automatically maintain the target level.

  17. Daylight control system device and method

    DOEpatents

    Paton, John Douglas

    2009-12-01

    A system and device for and a method of programming and controlling light fixtures is disclosed. A system in accordance with the present invention includes a stationary controller unit that is electrically coupled to the light fixtures. The stationary controller unit is configured to be remotely programmed with a portable commissioning device to automatically control the lights fixtures. The stationary controller unit and the portable commissioning device include light sensors, micro-computers and transceivers for measuring light levels, running programs, storing data and transmitting data between the stationary controller unit and the portable commissioning device. In operation, target light levels selected with the portable commissioning device and the controller unit is remotely programmed to automatically maintain the target level.

  18. Predicting recreational water quality advisories: A comparison of statistical methods

    USGS Publications Warehouse

    Brooks, Wesley R.; Corsi, Steven R.; Fienen, Michael N.; Carvin, Rebecca B.

    2016-01-01

    Epidemiological studies indicate that fecal indicator bacteria (FIB) in beach water are associated with illnesses among people having contact with the water. In order to mitigate public health impacts, many beaches are posted with an advisory when the concentration of FIB exceeds a beach action value. The most commonly used method of measuring FIB concentration takes 18–24 h before returning a result. In order to avoid the 24 h lag, it has become common to ”nowcast” the FIB concentration using statistical regressions on environmental surrogate variables. Most commonly, nowcast models are estimated using ordinary least squares regression, but other regression methods from the statistical and machine learning literature are sometimes used. This study compares 14 regression methods across 7 Wisconsin beaches to identify which consistently produces the most accurate predictions. A random forest model is identified as the most accurate, followed by multiple regression fit using the adaptive LASSO.

  19. Adaptive Control of the Packet Transmission Period with Solar Energy Harvesting Prediction in Wireless Sensor Networks

    PubMed Central

    Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

    2015-01-01

    A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%. PMID:25919372

  20. Adaptive control of the packet transmission period with solar energy harvesting prediction in wireless sensor networks.

    PubMed

    Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

    2015-04-24

    A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%.

  1. Model predictive control of non-linear systems over networks with data quantization and packet loss.

    PubMed

    Yu, Jimin; Nan, Liangsheng; Tang, Xiaoming; Wang, Ping

    2015-11-01

    This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method.

  2. Model predictive control of non-linear systems over networks with data quantization and packet loss.

    PubMed

    Yu, Jimin; Nan, Liangsheng; Tang, Xiaoming; Wang, Ping

    2015-11-01

    This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method. PMID:26341070

  3. Method to control artifacts of microstructural fabrication

    DOEpatents

    Shul, Randy J.; Willison, Christi G.; Schubert, W. Kent; Manginell, Ronald P.; Mitchell, Mary-Anne; Galambos, Paul C.

    2006-09-12

    New methods for fabrication of silicon microstructures have been developed. In these methods, an etching delay layer is deposited and patterned so as to provide differential control on the depth of features being etched into a substrate material. Compensation for etching-related structural artifacts can be accomplished by proper use of such an etching delay layer.

  4. OVERVIEW ON ALTERNATIVE ASBESTOS CONTROL METHOD RESEARCH

    EPA Science Inventory

    The alternative asbestos control method (AACM) is an experimental approach to building demolition. Unlike the NESHAP method, the AACM allows some regulated asbestos-containing material to remain in the building and a surfactant-water solution is used to suppress asbestos fibers ...

  5. Programmable logic controller implementation of an auto-tuned predictive control based on minimal plant information.

    PubMed

    Valencia-Palomo, G; Rossiter, J A

    2011-01-01

    This paper makes two key contributions. First, it tackles the issue of the availability of constrained predictive control for low-level control loops. Hence, it describes how the constrained control algorithm is embedded in an industrial programmable logic controller (PLC) using the IEC 61131-3 programming standard. Second, there is a definition and implementation of a novel auto-tuned predictive controller; the key novelty is that the modelling is based on relatively crude but pragmatic plant information. Laboratory experiment tests were carried out in two bench-scale laboratory systems to prove the effectiveness of the combined algorithm and hardware solution. For completeness, the results are compared with a commercial proportional-integral-derivative (PID) controller (also embedded in the PLC) using the most up to date auto-tuning rules.

  6. Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

    NASA Technical Reports Server (NTRS)

    He, Yuning

    2015-01-01

    Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

  7. A predictive control framework for optimal energy extraction of wind farms

    NASA Astrophysics Data System (ADS)

    Vali, M.; van Wingerden, J. W.; Boersma, S.; Petrović, V.; Kühn, M.

    2016-09-01

    This paper proposes an adjoint-based model predictive control for optimal energy extraction of wind farms. It employs the axial induction factor of wind turbines to influence their aerodynamic interactions through the wake. The performance index is defined here as the total power production of the wind farm over a finite prediction horizon. A medium-fidelity wind farm model is utilized to predict the inflow propagation in advance. The adjoint method is employed to solve the formulated optimization problem in a cost effective way and the first part of the optimal solution is implemented over the control horizon. This procedure is repeated at the next controller sample time providing the feedback into the optimization. The effectiveness and some key features of the proposed approach are studied for a two turbine test case through simulations.

  8. Non-animal test methods for predicting skin sensitization potentials.

    PubMed

    Mehling, Annette; Eriksson, Tove; Eltze, Tobias; Kolle, Susanne; Ramirez, Tzutzuy; Teubner, Wera; van Ravenzwaay, Bennard; Landsiedel, Robert

    2012-08-01

    Contact allergies are complex diseases, and it is estimated that 15-20 % of the general population suffers from contact allergy, with increasing prevalence. Evaluation of the sensitization potential of a substance is usually carried out in animal models. Nowadays, there is much interest in reducing and ultimately replacing current animal tests. Furthermore, as of 2013, the EU has posed a ban on animal testing of cosmetic ingredients that includes skin sensitization. Therefore, predictive and robust in vitro tests are urgently needed. In order to establish alternatives to animal testing, the in vitro tests must mimic the very complex interactions between the sensitizing chemical and the different parts of the immune system. This review article summarizes recent efforts to develop in vitro tests for predicting skin sensitizers. Cell-based assays, in chemico methods and, to a lesser extent, in silico methods are presented together with a discussion of their current status. With considerable progress having been achieved during the last years, the rationale today is that data from different non-animal test methods will have to be combined in order to obtain reliable hazard and potency information on potential skin sensitizers. PMID:22707154

  9. Unstructured CFD and Noise Prediction Methods for Propulsion Airframe Aeroacoustics

    NASA Technical Reports Server (NTRS)

    Pao, S. Paul; Abdol-Hamid, Khaled S.; Campbell, Richard L.; Hunter, Craig A.; Massey, Steven J.; Elmiligui, Alaa A.

    2006-01-01

    Using unstructured mesh CFD methods for Propulsion Airframe Aeroacoustics (PAA) analysis has the distinct advantage of precise and fast computational mesh generation for complex propulsion and airframe integration arrangements that include engine inlet, exhaust nozzles, pylon, wing, flaps, and flap deployment mechanical parts. However, accurate solution values of shear layer velocity, temperature and turbulence are extremely important for evaluating the usually small noise differentials of potential applications to commercial transport aircraft propulsion integration. This paper describes a set of calibration computations for an isolated separate flow bypass ratio five engine nozzle model and the same nozzle system with a pylon. These configurations have measured data along with prior CFD solutions and noise predictions using a proven structured mesh method, which can be used for comparison to the unstructured mesh solutions obtained in this investigation. This numerical investigation utilized the TetrUSS system that includes a Navier-Stokes solver, the associated unstructured mesh generation tools, post-processing utilities, plus some recently added enhancements to the system. New features necessary for this study include the addition of two equation turbulence models to the USM3D code, an h-refinement utility to enhance mesh density in the shear mixing region, and a flow adaptive mesh redistribution method. In addition, a computational procedure was developed to optimize both solution accuracy and mesh economy. Noise predictions were completed using an unstructured mesh version of the JeT3D code.

  10. Predictive control and estimation algorithms for the NASA/JPL 70-meter antennas

    NASA Technical Reports Server (NTRS)

    Gawronski, W.

    1991-01-01

    A modified output prediction procedure and a new controller design is presented based on the predictive control law. Also, a new predictive estimator is developed to complement the controller and to enhance system performance. The predictive controller is designed and applied to the tracking control of the Deep Space Network 70 m antennas. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

  11. Predictive control and estimation algorithms for the NASA/JPL Deep Space Network antennas

    NASA Technical Reports Server (NTRS)

    Gawronski, W.

    1991-01-01

    A modified output prediction procedure, and a new controller design based on the predictive control law are presented. Also, the predictive estimator is developed to complement the controller, and to enhance the system performance. The predictive controller was designed and applied to the tracking control of the National Aeronautics and Space Administration (NASA)/Jet Propulsion Laboratory (JPL) 70-m antenna. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

  12. Model Predictive Control for the Operation of Building Cooling Systems

    SciTech Connect

    Ma, Yudong; Borrelli, Francesco; Hencey, Brandon; Coffey, Brian; Bengea, Sorin; Haves, Philip

    2010-06-29

    A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

  13. [The quality control based on the predictable performance].

    PubMed

    Zheng, D X

    2016-09-01

    The clinical performance can only be evaluated when it comes to the last step in the conventional way of prosthesis. However, it often causes the failure because of the unconformity between the expectation and final performance. Resulting from this kind of situation, quality control based on the predictable results has been suggested. It is a new idea based on the way of reverse thinking, and focuses on the need of patient and puts the final performance of the prosthesis to the first place. With the prosthodontically driven prodedure, dentists can complete the unification with the expectation and the final performance. PMID:27596338

  14. An experiment in hurricane track prediction using parallel computing methods

    NASA Technical Reports Server (NTRS)

    Song, Chang G.; Jwo, Jung-Sing; Lakshmivarahan, S.; Dhall, S. K.; Lewis, John M.; Velden, Christopher S.

    1994-01-01

    The barotropic model is used to explore the advantages of parallel processing in deterministic forecasting. We apply this model to the track forecasting of hurricane Elena (1985). In this particular application, solutions to systems of elliptic equations are the essence of the computational mechanics. One set of equations is associated with the decomposition of the wind into irrotational and nondivergent components - this determines the initial nondivergent state. Another set is associated with recovery of the streamfunction from the forecasted vorticity. We demonstrate that direct parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to this decomposition and forecast problem. A 72-h track prediction was made using incremental time steps of 16 min on a network of 3000 grid points nominally separated by 100 km. The prediction took 30 sec on the 8-processor Alliant FX/8 computer. This was a speed-up of 3.7 when compared to the one-processor version. The 72-h prediction of Elena's track was made as the storm moved toward Florida's west coast. Approximately 200 km west of Tampa Bay, Elena executed a dramatic recurvature that ultimately changed its course toward the northwest. Although the barotropic track forecast was unable to capture the hurricane's tight cycloidal looping maneuver, the subsequent northwesterly movement was accurately forecasted as was the location and timing of landfall near Mobile Bay.

  15. A Primer In Advanced Fatigue Life Prediction Methods

    NASA Technical Reports Server (NTRS)

    Halford, Gary R.

    2000-01-01

    Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable more cost effective, and better performing products. In other words, as the envelop is expanded, components are then designed to operate just as close to the newly expanded envelop as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

  16. Method for predicting peptide detection in mass spectrometry

    DOEpatents

    Kangas, Lars [West Richland, WA; Smith, Richard D [Richland, WA; Petritis, Konstantinos [Richland, WA

    2010-07-13

    A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.

  17. Low inhibitory control and restrictive feeding practices predict weight outcomes

    PubMed Central

    Anzman, Stephanie L.; Birch, Leann L.

    2009-01-01

    Objective A priority for research is to identify individuals early in development who are particularly susceptible to weight gain in the current, obesogenic environment. This longitudinal study investigated whether early individual differences in inhibitory control, an aspect of temperament, predicted weight outcomes and whether parents’ restrictive feeding practices moderated this relation. Study design Participants included 197 non-Hispanic White girls and their parents; families were assessed when girls were 5, 7, 9, 11, 13, and 15 years old. Measures included mothers’ reports of girls’ inhibitory control levels, girls’ reports of parental restriction in feeding, girls’ body mass indexes (BMIs), and parents’ BMIs, education, and income. Results Girls with lower inhibitory control at age 7 had higher concurrent BMIs, greater weight gain, higher BMIs at all subsequent time points, and were 1.95 times more likely to be overweight at age 15. Girls who perceived higher parental restriction exhibited the strongest inverse relation between inhibitory control and weight status. Conclusion Variability in inhibitory control could help identify individuals who are predisposed to obesity risk; the current findings also highlight the importance of parenting practices as potentially modifiable factors which exacerbate or attenuate this risk. PMID:19595373

  18. Jet Noise Diagnostics Supporting Statistical Noise Prediction Methods

    NASA Technical Reports Server (NTRS)

    Bridges, James E.

    2006-01-01

    compared against measurements of mean and rms velocity statistics over a range of jet speeds and temperatures. Models for flow parameters used in the acoustic analogy, most notably the space-time correlations of velocity, have been compared against direct measurements, and modified to better fit the observed data. These measurements have been extremely challenging for hot, high speed jets, and represent a sizeable investment in instrumentation development. As an intermediate check that the analysis is predicting the physics intended, phased arrays have been employed to measure source distributions for a wide range of jet cases. And finally, careful far-field spectral directivity measurements have been taken for final validation of the prediction code. Examples of each of these experimental efforts will be presented. The main result of these efforts is a noise prediction code, named JeNo, which is in middevelopment. JeNo is able to consistently predict spectral directivity, including aft angle directivity, for subsonic cold jets of most geometries. Current development on JeNo is focused on extending its capability to hot jets, requiring inclusion of a previously neglected second source associated with thermal fluctuations. A secondary result of the intensive experimentation is the archiving of various flow statistics applicable to other acoustic analogies and to development of time-resolved prediction methods. These will be of lasting value as we look ahead at future challenges to the aeroacoustic experimentalist.

  19. An automatic method for CASP9 free modeling structure prediction assessment

    PubMed Central

    Cong, Qian; Kinch, Lisa N.; Pei, Jimin; Shi, Shuoyong; Grishin, Vyacheslav N.; Li, Wenlin; Grishin, Nick V.

    2011-01-01

    Motivation: Manual inspection has been applied to and is well accepted for assessing critical assessment of protein structure prediction (CASP) free modeling (FM) category predictions over the years. Such manual assessment requires expertise and significant time investment, yet has the problems of being subjective and unable to differentiate models of similar quality. It is beneficial to incorporate the ideas behind manual inspection to an automatic score system, which could provide objective and reproducible assessment of structure models. Results: Inspired by our experience in CASP9 FM category assessment, we developed an automatic superimposition independent method named Quality Control Score (QCS) for structure prediction assessment. QCS captures both global and local structural features, with emphasis on global topology. We applied this method to all FM targets from CASP9, and overall the results showed the best agreement with Manual Inspection Scores among automatic prediction assessment methods previously applied in CASPs, such as Global Distance Test Total Score (GDT_TS) and Contact Score (CS). As one of the important components to guide our assessment of CASP9 FM category predictions, this method correlates well with other scoring methods and yet is able to reveal good-quality models that are missed by GDT_TS. Availability: The script for QCS calculation is available at http://prodata.swmed.edu/QCS/. Contact: grishin@chop.swmed.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21994223

  20. Evidence for predictive control in lifting series of virtual objects.

    PubMed

    Mawase, Firas; Karniel, Amir

    2010-06-01

    The human motor control system gracefully behaves in a dynamic and time varying environment. Here, we explored the predictive capabilities of the motor system in a simple motor task of lifting a series of virtual objects. When a subject lifts an object, she/he uses an expectation of the weight of the object to generate a motor command. All models of motor learning employ learning algorithms that essentially expect the future to be similar to the previously experienced environment. In this study, we asked subjects to lift a series of increasing weights and determined whether they extrapolated from past experience and predicted the next weight in the series even though that weight had never been experienced. The grip force at the beginning of the lifting task is a clean indication of the motor expectation. In contrast to the motor learning literature asserting adaptation by means of expecting a weighted average based on past experience, our results suggest that the motor system is able to predict the subsequent weight that follows a series of increasing weights.

  1. Predictive and reinforcement learning for magneto-hydrodynamic control of hypersonic flows

    NASA Astrophysics Data System (ADS)

    Kulkarni, Nilesh Vijay

    Increasing needs for autonomy in future aerospace systems and immense progress in computing technology have motivated the development of on-line adaptive control techniques to account for modeling errors, changes in system dynamics, and faults occurring during system operation. After extensive treatment of the inner-loop adaptive control dealing mainly with stable adaptation towards desired transient behavior, adaptive optimal control has started receiving attention in literature. Motivated by the problem of optimal control of the magneto-hydrodynamic (MHD) generator at the inlet of the scramjet engine of a hypersonic flight vehicle, this thesis treats the general problem of efficiently combining off-line and on-line optimal control methods. The predictive control approach is chosen as the off-line method for designing optimal controllers using all the existing system knowledge. This controller is then adapted on-line using policy-iteration-based Q-learning, which is a stable model-free reinforcement learning approach. The combined approach is first illustrated in the optimal control of linear systems, which helps in the analysis as well as the validation of the method. A novel neural-networks-based parametric predictive control approach is then designed for the off-line optimal control of non-linear systems. The off-line approach is illustrated by applications to aircraft and spacecraft systems. This is followed by an extensive treatment of the off-line optimal control of the MHD generator using this neuro-control approach. On-line adaptation of the controller is implemented using several novel schemes derived from the policy-iteration-based Q-learning. The implementation results demonstrate the success of these on-line algorithms for adapting towards modeling errors in the off-line design.

  2. Control method for physical systems and devices

    DOEpatents

    Guckenheimer, John

    1997-01-01

    A control method for stabilizing systems or devices that are outside the control domain of a linear controller is provided. When applied to nonlinear systems, the effectiveness of this method depends upon the size of the domain of stability that is produced for the stabilized equilibrium. If this domain is small compared to the accuracy of measurements or the size of disturbances within the system, then the linear controller is likely to fail within a short period. Failure of the system or device can be catastrophic: the system or device can wander far from the desired equilibrium. The method of the invention presents a general procedure to recapture the stability of a linear controller, when the trajectory of a system or device leaves its region of stability. By using a hybrid strategy based upon discrete switching events within the state space of the system or device, the system or device will return from a much larger domain to the region of stability utilized by the linear controller. The control procedure is robust and remains effective under large classes of perturbations of a given underlying system or device.

  3. Decision tree methods: applications for classification and prediction.

    PubMed

    Song, Yan-Yan; Lu, Ying

    2015-04-25

    Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure. PMID:26120265

  4. Mathematical analysis method for predicting temperature rise in BIPV

    NASA Astrophysics Data System (ADS)

    Ibarahim, Zahari; Ruslan, Mohd Hafidz; Ibrahim, Zamry

    2013-05-01

    In order to estimate the airflow rate and temperature in the channel of building an integrated photovoltaic (BIPV) system, a simplified mathematical method has been derived in which the buoyancy force balances the friction along the channel. The channel is represented as a closed duct and the pressure losses are calculated in a similar fashion to those in a pipe circuit. Pressure losses at ventilation inlets and outlets are calculated using pressure loss factors, Kf. The effect of wind pressure on mass flow rate and temperature in the channel can be estimated with the inclusion of the wind speed pressure into the formulation. The benefit of wind pressure applied normal to the inlet and tangential to the outlet of the channel can be seen. The procedure yields the mass flow rate and temperature directly by solution of a simple cubic equation. This method allows the engineers and scientist to predict optimum configuration of their PV cladding design.

  5. Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus

    NASA Astrophysics Data System (ADS)

    Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin

    2015-08-01

    Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.

  6. Conditional Weather Resampling Method for Seasonal Ensemble Streamflow Prediction

    NASA Astrophysics Data System (ADS)

    Beckers, Joost; Weerts, Albrecht; Welles, Edwin

    2014-05-01

    Ensemble Streamflow Prediction (ESP) is a commonly used method for water resources planning on the seasonal time scale. The starting point for the ESP is the current state of the hydrological system, which is generated form a short historical simulation up to the time of forecast. Starting from this initial state, a hydrologic model is run to produce an ensemble of possible realizations of future streamflows, taking meteorological time series from historical years as input. It is assumed that these historical weather time series represent climatology. One disadvantage of the original ESP method is that an expected deviation from average climatology is not accounted for. Here, we propose a variation to the ESP, in which shorter periods from historical time years are resampled and assembled to generate additional possible realizations of future weather. The resampling is done in such a way as to incorporate statistical deviations from the average climate that are linked to climate modes, such as El Niño Southern Oscillation (ENSO) or Pacific Decadal Oscillation (PDO). These climate modes are known to affect the local weather in many regions around the world. The resampling of historical weather periods is conditioned on the climate mode indices, starting with the current climate index value and searching for historical years with similar climate indices. The resampled weather time series are used as input for the hydrological model, similar to the original ESP procedure. The method was implemented in the operational forecasting environment of Bonneville Power Administration (BPA), which based on Delft-FEWS. The method was run for 55 non-operational years of hindcasts (forecasts in retrospect) for the Columbia River in the North-West of the U.S. An increase in forecast skill up to 5% was found relative to the standard ESP for streamflow predictions at three test-locations.

  7. Striatal prediction errors support dynamic control of declarative memory decisions

    PubMed Central

    Scimeca, Jason M.; Katzman, Perri L.; Badre, David

    2016-01-01

    Adaptive memory requires context-dependent control over how information is retrieved, evaluated and used to guide action, yet the signals that drive adjustments to memory decisions remain unknown. Here we show that prediction errors (PEs) coded by the striatum support control over memory decisions. Human participants completed a recognition memory test that incorporated biased feedback to influence participants' recognition criterion. Using model-based fMRI, we find that PEs—the deviation between the outcome and expected value of a memory decision—correlate with striatal activity and predict individuals' final criterion. Importantly, the striatal PEs are scaled relative to memory strength rather than the expected trial outcome. Follow-up experiments show that the learned recognition criterion transfers to free recall, and targeting biased feedback to experimentally manipulate the magnitude of PEs influences criterion consistent with PEs scaled relative to memory strength. This provides convergent evidence that declarative memory decisions can be regulated via striatally mediated reinforcement learning signals. PMID:27713407

  8. Predictive models of procedural human supervisory control behavior

    NASA Astrophysics Data System (ADS)

    Boussemart, Yves

    Human supervisory control systems are characterized by the computer-mediated nature of the interactions between one or more operators and a given task. Nuclear power plants, air traffic management and unmanned vehicles operations are examples of such systems. In this context, the role of the operators is typically highly proceduralized due to the time and mission-critical nature of the tasks. Therefore, the ability to continuously monitor operator behavior so as to detect and predict anomalous situations is a critical safeguard for proper system operation. In particular, such models can help support the decision J]l8king process of a supervisor of a team of operators by providing alerts when likely anomalous behaviors are detected By exploiting the operator behavioral patterns which are typically reinforced through standard operating procedures, this thesis proposes a methodology that uses statistical learning techniques in order to detect and predict anomalous operator conditions. More specifically, the proposed methodology relies on hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) to generate predictive models of unmanned vehicle systems operators. Through the exploration of the resulting HMMs in two distinct single operator scenarios, the methodology presented in this thesis is validated and shown to provide models capable of reliably predicting operator behavior. In addition, the use of HSMMs on the same data scenarios provides the temporal component of the predictions missing from the HMMs. The final step of this work is to examine how the proposed methodology scales to more complex scenarios involving teams of operators. Adopting a holistic team modeling approach, both HMMs and HSMMs are learned based on two team-based data sets. The results show that the HSMMs can provide valuable timing information in the single operator case, whereas HMMs tend to be more robust to increased team complexity. In addition, this thesis discusses the

  9. Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

    NASA Astrophysics Data System (ADS)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2016-12-01

    Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

  10. Temperature Effects and Compensation-Control Methods

    PubMed Central

    Xia, Dunzhu; Chen, Shuling; Wang, Shourong; Li, Hongsheng

    2009-01-01

    In the analysis of the effects of temperature on the performance of microgyroscopes, it is found that the resonant frequency of the microgyroscope decreases linearly as the temperature increases, and the quality factor changes drastically at low temperatures. Moreover, the zero bias changes greatly with temperature variations. To reduce the temperature effects on the microgyroscope, temperature compensation-control methods are proposed. In the first place, a BP (Back Propagation) neural network and polynomial fitting are utilized for building the temperature model of the microgyroscope. Considering the simplicity and real-time requirements, piecewise polynomial fitting is applied in the temperature compensation system. Then, an integral-separated PID (Proportion Integration Differentiation) control algorithm is adopted in the temperature control system, which can stabilize the temperature inside the microgyrocope in pursuing its optimal performance. Experimental results reveal that the combination of microgyroscope temperature compensation and control methods is both realizable and effective in a miniaturized microgyroscope prototype. PMID:22408509

  11. A Survey of Quantum Lyapunov Control Methods

    PubMed Central

    2013-01-01

    The condition of a quantum Lyapunov-based control which can be well used in a closed quantum system is that the method can make the system convergent but not just stable. In the convergence study of the quantum Lyapunov control, two situations are classified: nondegenerate cases and degenerate cases. For these two situations, respectively, in this paper the target state is divided into four categories: the eigenstate, the mixed state which commutes with the internal Hamiltonian, the superposition state, and the mixed state which does not commute with the internal Hamiltonian. For these four categories, the quantum Lyapunov control methods for the closed quantum systems are summarized and analyzed. Particularly, the convergence of the control system to the different target states is reviewed, and how to make the convergence conditions be satisfied is summarized and analyzed. PMID:23766732

  12. Control system health test system and method

    DOEpatents

    Hoff, Brian D.; Johnson, Kris W.; Akasam, Sivaprasad; Baker, Thomas M.

    2006-08-15

    A method is provided for testing multiple elements of a work machine, including a control system, a component, a sub-component that is influenced by operations of the component, and a sensor that monitors a characteristic of the sub-component. In one embodiment, the method is performed by the control system and includes sending a command to the component to adjust a first parameter associated with an operation of the component. Also, the method includes detecting a sensor signal from the sensor reflecting a second parameter associated with a characteristic of the sub-component and determining whether the second parameter is acceptable based on the command. The control system may diagnose at least one of the elements of the work machine when the second parameter of the sub-component is not acceptable.

  13. A GIS modeling method applied to predicting forest songbird habitat

    USGS Publications Warehouse

    Dettmers, Randy; Bart, Jonathan

    1999-01-01

    We have developed an approach for using a??presencea?? data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators a??anda?? and a??or.a?? We use an approach similar to forward stepwise regression to select the best overall model. We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on speciesa?? microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models. The performance of these

  14. Neural Network-Based Resistance Spot Welding Control and Quality Prediction

    SciTech Connect

    Allen, J.D., Jr.; Ivezic, N.D.; Zacharia, T.

    1999-07-10

    This paper describes the development and evaluation of neural network-based systems for industrial resistance spot welding process control and weld quality assessment. The developed systems utilize recurrent neural networks for process control and both recurrent networks and static networks for quality prediction. The first section describes a system capable of both welding process control and real-time weld quality assessment, The second describes the development and evaluation of a static neural network-based weld quality assessment system that relied on experimental design to limit the influence of environmental variability. Relevant data analysis methods are also discussed. The weld classifier resulting from the analysis successfldly balances predictive power and simplicity of interpretation. The results presented for both systems demonstrate clearly that neural networks can be employed to address two significant problems common to the resistance spot welding industry, control of the process itself, and non-destructive determination of resulting weld quality.

  15. Proposal for a recovery prediction method for patients affected by acute mediastinitis

    PubMed Central

    2012-01-01

    Background An attempt to find a prediction method of death risk in patients affected by acute mediastinitis. There is not such a tool described in available literature for that serious disease. Methods The study comprised 44 consecutive cases of acute mediastinitis. General anamnesis and biochemical data were included. Factor analysis was used to extract the risk characteristic for the patients. The most valuable results were obtained for 8 parameters which were selected for further statistical analysis (all collected during few hours after admission). Three factors reached Eigenvalue >1. Clinical explanations of these combined statistical factors are: Factor1 - proteinic status (serum total protein, albumin, and hemoglobin level), Factor2 - inflammatory status (white blood cells, CRP, procalcitonin), and Factor3 - general risk (age, number of coexisting diseases). Threshold values of prediction factors were estimated by means of statistical analysis (factor analysis, Statgraphics Centurion XVI). Results The final prediction result for the patients is constructed as simultaneous evaluation of all factor scores. High probability of death should be predicted if factor 1 value decreases with simultaneous increase of factors 2 and 3. The diagnostic power of the proposed method was revealed to be high [sensitivity =90%, specificity =64%], for Factor1 [SNC = 87%, SPC = 79%]; for Factor2 [SNC = 87%, SPC = 50%] and for Factor3 [SNC = 73%, SPC = 71%]. Conclusion The proposed prediction method seems a useful emergency signal during acute mediastinitis control in affected patients. PMID:22574625

  16. Extremely Randomized Machine Learning Methods for Compound Activity Prediction.

    PubMed

    Czarnecki, Wojciech M; Podlewska, Sabina; Bojarski, Andrzej J

    2015-11-09

    Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called 'extremely randomized methods'-Extreme Entropy Machine and Extremely Randomized Trees-for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their 'non-extreme' competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  17. Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

    NASA Technical Reports Server (NTRS)

    Pirzadeh, Shahyar Z.

    2003-01-01

    A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65 delta wing with different values of leading-edge radius. Although the geometry is quite simple, it poses a challenging problem for computing vortices originating from blunt leading edges. The second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the wind-tunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

  18. Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

    NASA Technical Reports Server (NTRS)

    Pirzadeh, Shahyar Z.

    2001-01-01

    A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

  19. Predicting human height by Victorian and genomic methods.

    PubMed

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-08-01

    In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, ... is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified. PMID:19223933

  20. Predicting human height by Victorian and genomic methods

    PubMed Central

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-01-01

    In the Victorian era, Sir Francis Galton showed that ‘when dealing with the transmission of stature from parents to children, the average height of the two parents, … is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4–6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified. PMID:19223933

  1. Predicting human height by Victorian and genomic methods.

    PubMed

    Aulchenko, Yurii S; Struchalin, Maksim V; Belonogova, Nadezhda M; Axenovich, Tatiana I; Weedon, Michael N; Hofman, Albert; Uitterlinden, Andre G; Kayser, Manfred; Oostra, Ben A; van Duijn, Cornelia M; Janssens, A Cecile J W; Borodin, Pavel M

    2009-08-01

    In the Victorian era, Sir Francis Galton showed that 'when dealing with the transmission of stature from parents to children, the average height of the two parents, ... is all we need care to know about them' (1886). One hundred and twenty-two years after Galton's work was published, 54 loci showing strong statistical evidence for association to human height were described, providing us with potential genomic means of human height prediction. In a population-based study of 5748 people, we find that a 54-loci genomic profile explained 4-6% of the sex- and age-adjusted height variance, and had limited ability to discriminate tall/short people, as characterized by the area under the receiver-operating characteristic curve (AUC). In a family-based study of 550 people, with both parents having height measurements, we find that the Galtonian mid-parental prediction method explained 40% of the sex- and age-adjusted height variance, and showed high discriminative accuracy. We have also explored how much variance a genomic profile should explain to reach certain AUC values. For highly heritable traits such as height, we conclude that in applications in which parental phenotypic information is available (eg, medicine), the Victorian Galton's method will long stay unsurpassed, in terms of both discriminative accuracy and costs. For less heritable traits, and in situations in which parental information is not available (eg, forensics), genomic methods may provide an alternative, given that the variants determining an essential proportion of the trait's variation can be identified.

  2. Control when it counts: Change in executive control under stress predicts depression symptoms.

    PubMed

    Quinn, Meghan E; Joormann, Jutta

    2015-08-01

    Individual differences in the ability to regulate affect following stressful life events have been associated with an increased risk for experiencing depression symptoms. Research further suggests that emotion regulation may depend on executive control which, in turn, has been shown to decline following stress exposure. Whether individual differences in stress-induced change in executive control predict depression symptoms, however, remains unknown. The current study examined whether trait executive control as well as stress-induced change in executive control predicts depression symptoms during a stressful time of life. The current study recruited 43 individuals during their first year of college. Participants completed an executive control task before and after a laboratory stress induction. Participants reported baseline depression symptoms during the laboratory session and follow-up depression symptoms during the final weeks of the semester. Results demonstrate that stress-induced change in executive control predicted an increase in depression symptoms at the end of the semester. The findings suggest that individual differences in the degree of decline in executive control following stress exposure may be a key factor in explaining why some individuals are vulnerable to depression during a stressful time of life. PMID:26098731

  3. Control when it counts: Change in executive control under stress predicts depression symptoms.

    PubMed

    Quinn, Meghan E; Joormann, Jutta

    2015-08-01

    Individual differences in the ability to regulate affect following stressful life events have been associated with an increased risk for experiencing depression symptoms. Research further suggests that emotion regulation may depend on executive control which, in turn, has been shown to decline following stress exposure. Whether individual differences in stress-induced change in executive control predict depression symptoms, however, remains unknown. The current study examined whether trait executive control as well as stress-induced change in executive control predicts depression symptoms during a stressful time of life. The current study recruited 43 individuals during their first year of college. Participants completed an executive control task before and after a laboratory stress induction. Participants reported baseline depression symptoms during the laboratory session and follow-up depression symptoms during the final weeks of the semester. Results demonstrate that stress-induced change in executive control predicted an increase in depression symptoms at the end of the semester. The findings suggest that individual differences in the degree of decline in executive control following stress exposure may be a key factor in explaining why some individuals are vulnerable to depression during a stressful time of life.

  4. Prediction of forces and moments for hypersonic flight vehicle control effectors

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.; Long, Lyle N.; Pagano, Peter J.

    1991-01-01

    Developing methods of predicting flight control forces and moments for hypersonic vehicles, included a preliminary assessment of subsonic/supersonic panel methods and hypersonic local flow inclination methods for such predictions. While these findings clearly indicate the usefulness of such methods for conceptual design activities, deficiencies exist in some areas. Thus, a second phase of research was proposed in which a better understanding is sought for the reasons of the successes and failures of the methods considered, particularly for the cases at hypersonic Mach numbers. To obtain this additional understanding, a more careful study of the results obtained relative to the methods used was undertaken. In addition, where appropriate and necessary, a more complete modeling of the flow was performed using well proven methods of computational fluid dynamics. As a result, assessments will be made which are more quantitative than those of phase 1 regarding the uncertainty involved in the prediction of the aerodynamic derivatives. In addition, with improved understanding, it is anticipated that improvements resulting in better accuracy will be made to the simple force and moment prediction.

  5. New technologies in predicting, preventing and controlling emerging infectious diseases

    PubMed Central

    Christaki, Eirini

    2015-01-01

    Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats. PMID:26068569

  6. Evolutionary method for predicting surface reconstructions with variable stoichiometry

    NASA Astrophysics Data System (ADS)

    Zhu, Qiang; Li, Li; Oganov, Artem R.; Allen, Philip B.

    2013-05-01

    We present a specially designed evolutionary algorithm for the prediction of surface reconstructions. This technique allows one to automatically explore stable and low-energy metastable configurations with variable surface atoms and variable surface unit cells through the whole chemical potential range. The power of evolutionary search is demonstrated by the efficient identification of diamond 2×1 (100) and 2×1 (111) surface reconstructions with a fixed number of surface atoms and a fixed cell size. With further variation of surface unit cells, we study the reconstructions of the polar surface MgO (111). Experiment has detected an oxygen trimer (ozone) motif [Plass , Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.81.4891 81, 4891 (1998)]. We predict another version of this motif which can be thermodynamically stable in extreme oxygen-rich conditions. Finally, we perform a variable stoichiometry search for a complex ternary system: semipolar GaN (101¯1) with and without adsorbed oxygen. The search yields a counterintuitive reconstruction based on N3 trimers. These examples demonstrate that an automated scheme to explore the energy landscape of surfaces will improve our understanding of surface reconstructions. The method presented in this paper can be generally applied to binary and multicomponent systems.

  7. Methods and Techniques for Risk Prediction of Space Shuttle Upgrades

    NASA Technical Reports Server (NTRS)

    Hoffman, Chad R.; Pugh, Rich; Safie, Fayssal

    1998-01-01

    Since the Space Shuttle Accident in 1986, NASA has been trying to incorporate probabilistic risk assessment (PRA) in decisions concerning the Space Shuttle and other NASA projects. One major study NASA is currently conducting is in the PRA area in establishing an overall risk model for the Space Shuttle System. The model is intended to provide a tool to predict the Shuttle risk and to perform sensitivity analyses and trade studies including evaluation of upgrades. Marshall Space Flight Center (MSFC) and its prime contractors including Pratt and Whitney (P&W) are part of the NASA team conducting the PRA study. MSFC responsibility involves modeling the External Tank (ET), the Solid Rocket Booster (SRB), the Reusable Solid Rocket Motor (RSRM), and the Space Shuttle Main Engine (SSME). A major challenge that faced the PRA team is modeling the shuttle upgrades. This mainly includes the P&W High Pressure Fuel Turbopump (HPFTP) and the High Pressure Oxidizer Turbopump (HPOTP). The purpose of this paper is to discuss the various methods and techniques used for predicting the risk of the P&W redesigned HPFTP and HPOTP.

  8. Predicting lattice thermal conductivity with help from ab initio methods

    NASA Astrophysics Data System (ADS)

    Broido, David

    2015-03-01

    The lattice thermal conductivity is a fundamental transport parameter that determines the utility a material for specific thermal management applications. Materials with low thermal conductivity find applicability in thermoelectric cooling and energy harvesting. High thermal conductivity materials are urgently needed to help address the ever-growing heat dissipation problem in microelectronic devices. Predictive computational approaches can provide critical guidance in the search and development of new materials for such applications. Ab initio methods for calculating lattice thermal conductivity have demonstrated predictive capability, but while they are becoming increasingly efficient, they are still computationally expensive particularly for complex crystals with large unit cells . In this talk, I will review our work on first principles phonon transport for which the intrinsic lattice thermal conductivity is limited only by phonon-phonon scattering arising from anharmonicity. I will examine use of the phase space for anharmonic phonon scattering and the Grüneisen parameters as measures of the thermal conductivities for a range of materials and compare these to the widely used guidelines stemming from the theory of Liebfried and Schölmann. This research was supported primarily by the NSF under Grant CBET-1402949, and by the S3TEC, an Energy Frontier Research Center funded by the US DOE, office of Basic Energy Sciences under Award No. DE-SC0001299.

  9. Study of improved methods for predicting chemical equilibria

    NASA Astrophysics Data System (ADS)

    Lenz, Terry G.; Vaughan, John D.

    The research involves developing general computational methods for predicting the thermodynamic properties of condensed state chemically reactive systems. The overall effort has encompassed both computer studies, and parallel laboratory experimental work to support the evolving computational models. To date, the soundness of molecular mechanics/force-field techniques were demonstrated for accurate prediction of the thermodynamic properties of chemically reactive systems. Extensive work was done with three molecular mechanics models, Boyd's MOLBD3, Allinger's MMP2 and the Warshel/Lifson/Karplus QCFF/PI program. Not one of these programs at present has general full thermodynamic output capability. Modification of the QCFF/PI is well on its way to full thermodynamic capability. Supporting laboratory studies have involved careful bomb calorimetry for H(sub f) information, X-ray structure determination for accurate molecular geometry data, and kinetics/equilibrium determinations for various prototypical Diels-Alder reactions. Vapor pressure studies for candidate Diels-Alder compounds are also underway. The bomb calorimetric and greater initial effort on vapor pressure studies have replaced the original solvent effect and hindered rotation NMR studies planned, on the basis of most critical data needs for correct computational model development.

  10. Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

    NASA Technical Reports Server (NTRS)

    McMillan, Michelle L.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James

    2010-01-01

    Fail-safe inlet flow control may enable high-speed cruise efficiency, low noise signature, and reduced fuel-burn goals for hybrid wing-body aircraft. The objectives of this program are to develop flow control and prediction methodologies for boundary-layer ingesting (BLI) inlets used in these aircraft. This report covers the second of a three year program. The approach integrates experiments and numerical simulations. Both passive and active flow-control devices were tested in a small-scale wind tunnel. Hybrid actuation approaches, combining a passive microvane and active synthetic jet, were tested in various geometric arrangements. Detailed flow measurements were taken to provide insight into the flow physics. Results of the numerical simulations were correlated against experimental data. The sensitivity of results to grid resolution and turbulence models was examined. Aerodynamic benefits from microvanes and microramps were assessed when installed in an offset BLI inlet. Benefits were quantified in terms of recovery and distortion changes. Microvanes were more effective than microramps at improving recovery and distortion.

  11. Critical evaluation of in silico methods for prediction of coiled-coil domains in proteins.

    PubMed

    Li, Chen; Ching Han Chang, Catherine; Nagel, Jeremy; Porebski, Benjamin T; Hayashida, Morihiro; Akutsu, Tatsuya; Song, Jiangning; Buckle, Ashley M

    2016-03-01

    Coiled-coils refer to a bundle of helices coiled together like strands of a rope. It has been estimated that nearly 3% of protein-encoding regions of genes harbour coiled-coil domains (CCDs). Experimental studies have confirmed that CCDs play a fundamental role in subcellular infrastructure and controlling trafficking of eukaryotic cells. Given the importance of coiled-coils, multiple bioinformatics tools have been developed to facilitate the systematic and high-throughput prediction of CCDs in proteins. In this article, we review and compare 12 sequence-based bioinformatics approaches and tools for coiled-coil prediction. These approaches can be categorized into two classes: coiled-coil detection and coiled-coil oligomeric state prediction. We evaluated and compared these methods in terms of their input/output, algorithm, prediction performance, validation methods and software utility. All the independent testing data sets are available at http://lightning.med.monash.edu/coiledcoil/. In addition, we conducted a case study of nine human polyglutamine (PolyQ) disease-related proteins and predicted CCDs and oligomeric states using various predictors. Prediction results for CCDs were highly variable among different predictors. Only two peptides from two proteins were confirmed to be CCDs by majority voting. Both domains were predicted to form dimeric coiled-coils using oligomeric state prediction. We anticipate that this comprehensive analysis will be an insightful resource for structural biologists with limited prior experience in bioinformatics tools, and for bioinformaticians who are interested in designing novel approaches for coiled-coil and its oligomeric state prediction. PMID:26177815

  12. New method for prediction of shale gas content in continental shale formation using well logs

    NASA Astrophysics Data System (ADS)

    Li, Sheng-Jie; Cui, Zhe; Jiang, Zhen-Xue; Shao, Yu; Liao, Wei; Li, Li

    2016-06-01

    Shale needs to contain a sufficient amount of gas to make it viable for exploitation. The continental heterogeneous shale formation in the Yan-chang (YC) area is investigated by firstly measuring the shale gas content in a laboratory and then investigating use of a theoretical prediction model. Key factors controlling the shale gas content are determined, and a prediction model for free gas content is established according to the equation of gas state and a new petrophysical volume model. Application of the Langmuir volume constant and pressure constant obtained from results of adsorption isotherms is found to be limited because these constants are greatly affected by experimental temperature and pressures. Therefore, using measurements of adsorption isotherms and thermodynamic theory, the influence of temperature, total organic carbon (TOC), and mineralogy on Langmuir volume constants and pressure constants are investigated in detail. A prediction model for the Langmuir pressure constant with a correction of temperatures is then established, and a prediction model for the Langmuir volume constant with correction of temperature, TOC, and quartz contents is also proposed. Using these corrected Langmuir constants, application of the Langmuir model determined using experimental adsorption isotherms is extrapolated to reservoir temperature, pressure, and lithological conditions, and a method for the prediction of shale gas content using well logs is established. Finally, this method is successfully applied to predict the shale gas content of the continental shale formation in the YC area, and practical application is shown to deliver good results with high precision.

  13. Alternative Asbestos Control Method (AACM), Washington

    EPA Science Inventory

    This presentation describes the status to date of the Alternative Asbestos Control Method research, which is intended as a possible alternative technology for use in the demolition of buildings that contain asbestos and are covered under the regulatory requirements of the Asbesto...

  14. Methods for evaluating the predictive accuracy of structural dynamic models

    NASA Technical Reports Server (NTRS)

    Hasselman, T. K.; Chrostowski, Jon D.

    1990-01-01

    Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

  15. Development of methods to predict agglomeration and disposition in FBCs

    SciTech Connect

    Mann, M.D.; Henderson, A.K.; Swanson, M.K.; Erickson, T.A.

    1995-11-01

    This 3-year, multiclient program is providing the information needed to determine the behavior of inorganic components in FBC units using advanced methods of analysis coupled with bench-scale combustion experiments. The major objectives of the program are as follows: (1) To develop further our advanced ash and deposit characterization techniques to quantify the effects of the liquid-phase components in terms of agglomerate formation and ash deposits, (2) To determine the mechanisms of inorganic transformations that lead to bed agglomeration and ash deposition in FBC systems, and (3) To develop a better means to predict the behavior of inorganic components as a function of coal composition, bed material characteristics, and combustion conditions.

  16. Adaptive Accommodation Control Method for Complex Assembly

    NASA Astrophysics Data System (ADS)

    Kang, Sungchul; Kim, Munsang; Park, Shinsuk

    Robotic systems have been used to automate assembly tasks in manufacturing and in teleoperation. Conventional robotic systems, however, have been ineffective in controlling contact force in multiple contact states of complex assemblythat involves interactions between complex-shaped parts. Unlike robots, humans excel at complex assembly tasks by utilizing their intrinsic impedance, forces and torque sensation, and tactile contact clues. By examining the human behavior in assembling complex parts, this study proposes a novel geometry-independent control method for robotic assembly using adaptive accommodation (or damping) algorithm. Two important conditions for complex assembly, target approachability and bounded contact force, can be met by the proposed control scheme. It generates target approachable motion that leads the object to move closer to a desired target position, while contact force is kept under a predetermined value. Experimental results from complex assembly tests have confirmed the feasibility and applicability of the proposed method.

  17. Survey on large scale system control methods

    NASA Technical Reports Server (NTRS)

    Mercadal, Mathieu

    1987-01-01

    The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

  18. Prediction of forces and moments for hypersonic flight vehicle control effectors

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.; Long, Lyle N.; Guilmette, Neal; Pagano, Peter

    1993-01-01

    This research project includes three distinct phases. For completeness, all three phases of the work are briefly described in this report. The goal was to develop methods of predicting flight control forces and moments for hypersonic vehicles which could be used in a preliminary design environment. The first phase included a preliminary assessment of subsonic/supersonic panel methods and hypersonic local flow inclination methods for such predictions. While these findings clearly indicated the usefulness of such methods for conceptual design activities, deficiencies exist in some areas. Thus, a second phase of research was conducted in which a better understanding was sought for the reasons behind the successes and failures of the methods considered, particularly for the cases at hypersonic Mach numbers. This second phase involved using computational fluid dynamics methods to examine the flow fields in detail. Through these detailed predictions, the deficiencies in the simple surface inclination methods were determined. In the third phase of this work, an improvement to the surface inclination methods was developed. This used a novel method for including viscous effects by modifying the geometry to include the viscous/shock layer.

  19. Actively controlled vibration welding system and method

    DOEpatents

    Cai, Wayne W.; Kang, Bongsu; Tan, Chin-An

    2013-04-02

    A vibration welding system includes a controller, welding horn, an active material element, and anvil assembly. The assembly may include an anvil body connected to a back plate and support member. The element, e.g., a piezoelectric stack or shape memory alloy, is positioned with respect to the assembly. The horn vibrates in a desirable first direction to form a weld on a work piece. The element controls any vibrations in a second direction by applying calibrated response to the anvil body in the second direction. A method for controlling undesirable vibrations in the system includes positioning the element with respect to the anvil assembly, connecting the anvil body to the support member through the back plate, vibrating the horn in a desirable first direction, and transmitting an input signal to the element to control vibration in an undesirable second direction.

  20. A new methane control and prediction software suite for longwall mines

    NASA Astrophysics Data System (ADS)

    Dougherty, Heather N.; Özgen Karacan, C.

    2011-09-01

    This paper presents technical and application aspects of a new software suite, MCP (Methane Control and Prediction), developed for addressing some of the methane and methane control issues in longwall coal mines. The software suite consists of dynamic link library (DLL) extensions to MS-Access TM, written in C++. In order to create the DLLs, various statistical, mathematical approaches, prediction and classification artificial neural network (ANN) methods were used. The current version of MCP suite (version 1.3) discussed in this paper has four separate modules that (a) predict the dynamic elastic properties of coal-measure rocks, (b) predict ventilation emissions from longwall mines, (c) determine the type of degasification system that needs to be utilized for given situations and (d) assess the production performance of gob gas ventholes that are used to extract methane from longwall gobs. These modules can be used with the data from basic logs, mining, longwall panel, productivity, and coal bed characteristics. The applications of these modules separately or in combination for methane capture and control related problems will help improve the safety of mines. The software suite's version 1.3 is discussed in this paper. Currently, it's new version 2.0 is available and can be downloaded from http://www.cdc.gov/niosh/mining/products/product180.htm free of charge. The models discussed in this paper can be found under "ancillary models" and under "methane prediction models" for specific U.S. conditions in the new version.

  1. Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2006-01-01

    This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

  2. Predicting methyl iodide emission, soil concentration, and pest control in a two-dimensional chamber system.

    PubMed

    Luo, Lifang; Yates, Scott R; Ashworth, Daniel J

    2011-01-01

    Due to ever-increasing state and federal regulations, the future use of fumigants is predicted on reducing negative environmental impacts while offering sufficient pestcontrol efficacy. To foster the development of a best management practice, an integrated tool is needed to simultaneously predict fumigant movement and pest control without having to conduct elaborate and costly experiments. The objective of this study was (i) to present a two-dimensional (2-D) mathematical model to describe both fumigant movement and pestcontrol and (ii) to evaluate the model by comparing the simulated and observed results. Both analytical and numerical methods were used to predict methyl iodide (MeI) transport and fate. To predict pest control efficacy, the concentration-time index (CT) was defined and a two-parameter logistic survival model was used. Dose-response curves were experimentally determined for MeI against three types of pests (barnyardgrass [Echinochloa crus-galli] seed, citrus nematode [Tylenchulus semipenetrans], and fungi [Fusarium oxysporum]). Methyl iodide transport and pest control measurements collected from a 2-D experiimental system (60 by 60 cm) were used to test the model. Methyl iodide volatilization rates and soil gas-phase concentrations over time were accurately simulated by the model. The mass balance analysis indicates that the fraction of MeI degrading in the soil was underestimated when determined by the appearance of iodide concentration. The experimental results showed that after 24 h of MeI fumigation in the 2-D soil chamber, fungal population was not suppressed; > 90% of citrus nematodes were killed; and barnyardgrass seeds within 20-cm distance from the center were affected. These experimental results were consistent with the predicted results. The model accurately estimated the MeI movement and control of various pests and is a powerful tool to evaluate pesticides in terms of their negative environmental impacts and pest control under various

  3. Predictive functional control for active queue management in congested TCP/IP networks.

    PubMed

    Bigdeli, N; Haeri, M

    2009-01-01

    Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison.

  4. System and method for controlling remote devices

    DOEpatents

    Carrender, Curtis Lee; Gilbert, Ronald W.; Scott, Jeff W.; Clark, David A.

    2006-02-07

    A system and method for controlling remote devices utilizing a radio frequency identification (RFID) tag device having a control circuit adapted to render the tag device, and associated objects, permanently inoperable in response to radio-frequency control signals. The control circuit is configured to receive the control signals that can include an enable signal, and in response thereto enable an associated object, such as a weapon; and in response to a disable signal, to disable the tag itself, or, if desired, to disable the associated weapon or both the device and the weapon. Permanent disabling of the tag can be accomplished by several methods, including, but not limited to, fusing a fusable link, breaking an electrically conductive path, permanently altering the modulation or backscattering characteristics of the antenna circuit, and permanently erasing an associated memory. In this manner, tags in the possession of unauthorized employees can be remotely disabled, and weapons lost on a battlefield can be easily tracked and enabled or disabled automatically or at will.

  5. Predictive wavefront control for Adaptive Optics with arbitrary control loop delays

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-10-30

    We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.

  6. Effective variable switching point predictive current control for ac low-voltage drives

    NASA Astrophysics Data System (ADS)

    Stolze, Peter; Karamanakos, Petros; Kennel, Ralph; Manias, Stefanos; Endisch, Christian

    2015-07-01

    This paper presents an effective model predictive current control scheme for induction machines driven by a three-level neutral point clamped inverter, called variable switching point predictive current control. Despite the fact that direct, enumeration-based model predictive control (MPC) strategies are very popular in the field of power electronics due to their numerous advantages such as design simplicity and straightforward implementation procedure, they carry two major drawbacks. These are the increased computational effort and the high ripples on the controlled variables, resulting in a limited applicability of such methods. The high ripples occur because in direct MPC algorithms the actuating variable can only be changed at the beginning of a sampling interval. A possible remedy for this would be to change the applied control input within the sampling interval, and thus to apply it for a shorter time than one sample. However, since such a solution would lead to an additional overhead which is crucial especially for multilevel inverters, a heuristic preselection of the optimal control action is adopted to keep the computational complexity at bay. Experimental results are provided to verify the potential advantages of the proposed strategy.

  7. Predicting postoperative vomiting among orthopedic patients receiving patient-controlled epidural analgesia using SVM and LR.

    PubMed

    Wu, Hsin-Yun; Gong, Cihun-Siyong Alex; Lin, Shih-Pin; Chang, Kuang-Yi; Tsou, Mei-Yung; Ting, Chien-Kun

    2016-01-01

    Patient-controlled epidural analgesia (PCEA) has been applied to reduce postoperative pain in orthopedic surgical patients. Unfortunately, PCEA is occasionally accompanied by nausea and vomiting. The logistic regression (LR) model is widely used to predict vomiting, and recently support vector machines (SVM), a supervised machine learning method, has been used for classification and prediction. Unlike our previous work which compared Artificial Neural Networks (ANNs) with LR, this study uses a SVM-based predictive model to identify patients with high risk of vomiting during PCEA and comparing results with those derived from the LR-based model. From January to March 2007, data from 195 patients undergoing PCEA following orthopedic surgery were applied to develop two predictive models. 75% of the data were randomly selected for training, while the remainder was used for testing to validate predictive performance. The area under curve (AUC) was measured using the Receiver Operating Characteristic curve (ROC). The area under ROC curves of LR and SVM models were 0.734 and 0.929, respectively. A computer-based predictive model can be used to identify those who are at high risk for vomiting after PCEA, allowing for patient-specific therapeutic intervention or the use of alternative analgesic methods. PMID:27247165

  8. Predicting postoperative vomiting among orthopedic patients receiving patient-controlled epidural analgesia using SVM and LR

    PubMed Central

    Wu, Hsin-Yun; Gong, Cihun-Siyong Alex; Lin, Shih-Pin; Chang, Kuang-Yi; Tsou, Mei-Yung; Ting, Chien-Kun

    2016-01-01

    Patient-controlled epidural analgesia (PCEA) has been applied to reduce postoperative pain in orthopedic surgical patients. Unfortunately, PCEA is occasionally accompanied by nausea and vomiting. The logistic regression (LR) model is widely used to predict vomiting, and recently support vector machines (SVM), a supervised machine learning method, has been used for classification and prediction. Unlike our previous work which compared Artificial Neural Networks (ANNs) with LR, this study uses a SVM-based predictive model to identify patients with high risk of vomiting during PCEA and comparing results with those derived from the LR-based model. From January to March 2007, data from 195 patients undergoing PCEA following orthopedic surgery were applied to develop two predictive models. 75% of the data were randomly selected for training, while the remainder was used for testing to validate predictive performance. The area under curve (AUC) was measured using the Receiver Operating Characteristic curve (ROC). The area under ROC curves of LR and SVM models were 0.734 and 0.929, respectively. A computer-based predictive model can be used to identify those who are at high risk for vomiting after PCEA, allowing for patient-specific therapeutic intervention or the use of alternative analgesic methods. PMID:27247165

  9. An analytical method for predicting postwildfire peak discharges

    USGS Publications Warehouse

    Moody, John A.

    2012-01-01

    An analytical method presented here that predicts postwildfire peak discharge was developed from analysis of paired rainfall and runoff measurements collected from selected burned basins. Data were collected from 19 mountainous basins burned by eight wildfires in different hydroclimatic regimes in the western United States (California, Colorado, Nevada, New Mexico, and South Dakota). Most of the data were collected for the year of the wildfire and for 3 to 4 years after the wildfire. These data provide some estimate of the changes with time of postwildfire peak discharges, which are known to be transient but have received little documentation. The only required inputs for the analytical method are the burned area and a quantitative measure of soil burn severity (change in the normalized burn ratio), which is derived from Landsat reflectance data and is available from either the U.S. Department of Agriculture Forest Service or the U.S. Geological Survey. The method predicts the postwildfire peak discharge per unit burned area for the year of a wildfire, the first year after a wildfire, and the second year after a wildfire. It can be used at three levels of information depending on the data available to the user; each subsequent level requires either more data or more processing of the data. Level 1 requires only the burned area. Level 2 requires the burned area and the basin average value of the change in the normalized burn ratio. Level 3 requires the burned area and the calculation of the hydraulic functional connectivity, which is a variable that incorporates the sequence of soil burn severity along hillslope flow paths within the burned basin. Measurements indicate that the unit peak discharge response increases abruptly when the 30-minute maximum rainfall intensity is greater than about 5 millimeters per hour (0.2 inches per hour). This threshold may relate to a change in runoff generation from saturated-excess to infiltration-excess overland flow. The

  10. Investigation of the Multiple Method Adaptive Control (MMAC) method for flight control systems

    NASA Technical Reports Server (NTRS)

    Athans, M.; Baram, Y.; Castanon, D.; Dunn, K. P.; Green, C. S.; Lee, W. H.; Sandell, N. R., Jr.; Willsky, A. S.

    1979-01-01

    The stochastic adaptive control of the NASA F-8C digital-fly-by-wire aircraft using the multiple model adaptive control (MMAC) method is presented. The selection of the performance criteria for the lateral and the longitudinal dynamics, the design of the Kalman filters for different operating conditions, the identification algorithm associated with the MMAC method, the control system design, and simulation results obtained using the real time simulator of the F-8 aircraft at the NASA Langley Research Center are discussed.

  11. Method for controlling a vehicle attitude

    SciTech Connect

    Ise, K.; Minegishi, H.; Harada, H.

    1989-02-14

    This patent describes a method for controlling a suspension characteristic of a vehicle comprising the steps of: detecting a slippage of the one drive wheel of the vehicle; determining whether or not the detected slippage is greater than a reference value; controlling a drive force of the drive wheel by means of the braking system when the slippage is determined to be greater than the reference value; and altering an original state suspension characteristic of at least the drive wheel to a harder state when the slippage is determined to be greater than the reference value.

  12. Modeling a multivariable reactor and on-line model predictive control.

    PubMed

    Yu, D W; Yu, D L

    2005-10-01

    A nonlinear first principle model is developed for a laboratory-scaled multivariable chemical reactor rig in this paper and the on-line model predictive control (MPC) is implemented to the rig. The reactor has three variables-temperature, pH, and dissolved oxygen with nonlinear dynamics-and is therefore used as a pilot system for the biochemical industry. A nonlinear discrete-time model is derived for each of the three output variables and their model parameters are estimated from the real data using an adaptive optimization method. The developed model is used in a nonlinear MPC scheme. An accurate multistep-ahead prediction is obtained for MPC, where the extended Kalman filter is used to estimate system unknown states. The on-line control is implemented and a satisfactory tracking performance is achieved. The MPC is compared with three decentralized PID controllers and the advantage of the nonlinear MPC over the PID is clearly shown.

  13. Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

    NASA Astrophysics Data System (ADS)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2015-10-01

    A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

  14. Prediction of plantar shear stress distribution by artificial intelligence methods.

    PubMed

    Yavuz, Metin; Ocak, Hasan; Hetherington, Vincent J; Davis, Brian L

    2009-09-01

    Shear forces under the human foot are thought to be responsible for various foot pathologies such as diabetic plantar ulcers and athletic blisters. Frictional shear forces might also play a role in the metatarsalgia observed among hallux valgus (HaV) and rheumatoid arthritis (RA) patients. Due to the absence of commercial devices capable of measuring shear stress distribution, a number of linear models were developed. All of these have met with limited success. This study used nonlinear methods, specifically neural network and fuzzy logic schemes, to predict the distribution of plantar shear forces based on vertical loading parameters. In total, 73 subjects were recruited; 17 had diabetic neuropathy, 14 had HaV, 9 had RA, 11 had frequent foot blisters, and 22 were healthy. A feed-forward neural network (NN) and adaptive neurofuzzy inference system (NFIS) were built. These systems were then applied to a custom-built platform, which collected plantar pressure and shear stress data as subjects walked over the device. The inputs to both models were peak pressure, peak pressure-time integral, and time to peak pressure, and the output was peak resultant shear. Root-mean-square error (RMSE) values were calculated to test the models' accuracy. RMSE/actual shear ratio varied between 0.27 and 0.40 for NN predictions. Similarly, NFIS estimations resulted in a 0.28-0.37 ratio for local peak values in all subject groups. On the other hand, error percentages for global peak shear values were found to be in the range 11.4-44.1. These results indicate that there is no direct relationship between pressure and shear magnitudes. Future research should aim to decrease error levels by introducing shear stress dependent variables into the models. PMID:19725696

  15. Prediction of forces and moments for flight vehicle control effectors: Workplan

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.

    1989-01-01

    Two research activities directed at hypersonic vehicle configurations are currently underway. The first involves the validation of a number of classical local surface inclination methods commonly employed in preliminary design studies of hypersonic flight vehicles. Unlike studies aimed at validating such methods for predicting overall vehicle aerodynamics, this effort emphasizes validating the prediction of forces and moments for flight control studies. Specifically, several vehicle configurations for which experimental or flight-test data are available are being examined. By comparing the theoretical predictions with these data, the strengths and weaknesses of the local surface inclination methods can be ascertained and possible improvements suggested. The second research effort, of significance to control during take-off and landing of most proposed hypersonic vehicle configurations, is aimed at determining the change due to ground effect in control effectiveness of highly swept delta planforms. Central to this research is the development of a vortex-lattice computer program which incorporates an unforced trailing vortex sheet and an image ground plane. With this program, the change in pitching moment of the basic vehicle due to ground proximity, and whether or not there is sufficient control power available to trim, can be determined. In addition to the current work, two different research directions are suggested for future study. The first is aimed at developing an interactive computer program to assist the flight controls engineer in determining the forces and moments generated by different types of control effectors that might be used on hypersonic vehicles. The first phase of this work would deal in the subsonic portion of the flight envelope, while later efforts would explore the supersonic/hypersonic flight regimes. The second proposed research direction would explore methods for determining the aerodynamic trim drag of a generic hypersonic flight vehicle

  16. CELSS system control: issues, methods, and directions.

    PubMed

    Blackwell, C C; Blackwell, A L

    1992-01-01

    In the general control perspective, the CELSS concept implies a very complex system and presents challenges at every level. These challenges are generated by: (1) the prospect that the system will be inherently unstable, (2) the prospective difficulty of establishing an adequate mathematical model of the system for the purpose of control law synthesis (dimensionality is high, and the dynamics and interactive processes of some of the subsystems are not understood well), (3) assuring control law robustness (assuring that the resulting control law(s) will be effective over the domain of the specified uncertainties), (4) hardware realization of the control law, (5) hardware system robustness ("fault tolerance") and (6) achieving the logistics of the automation (or "management") aspects of the problem. A suggested organization of the problem, a sketch of the issues related to perceived difficulties, a commentary/evaluation of the issues, a review of methods available to address the issues, and a suggested strategy to address the broad CELSS systems control problem are presented.

  17. CELSS system control: issues, methods, and directions

    NASA Technical Reports Server (NTRS)

    Blackwell, C. C.; Blackwell, A. L.

    1992-01-01

    In the general control perspective, the CELSS concept implies a very complex system and presents challenges at every level. These challenges are generated by: (1) the prospect that the system will be inherently unstable, (2) the prospective difficulty of establishing an adequate mathematical model of the system for the purpose of control law synthesis (dimensionality is high, and the dynamics and interactive processes of some of the subsystems are not understood well), (3) assuring control law robustness (assuring that the resulting control law(s) will be effective over the domain of the specified uncertainties), (4) hardware realization of the control law, (5) hardware system robustness ("fault tolerance") and (6) achieving the logistics of the automation (or "management") aspects of the problem. A suggested organization of the problem, a sketch of the issues related to perceived difficulties, a commentary/evaluation of the issues, a review of methods available to address the issues, and a suggested strategy to address the broad CELSS systems control problem are presented.

  18. Numerical Weather Predictions Evaluation Using Spatial Verification Methods

    NASA Astrophysics Data System (ADS)

    Tegoulias, I.; Pytharoulis, I.; Kotsopoulos, S.; Kartsios, S.; Bampzelis, D.; Karacostas, T.

    2014-12-01

    During the last years high-resolution numerical weather prediction simulations have been used to examine meteorological events with increased convective activity. Traditional verification methods do not provide the desired level of information to evaluate those high-resolution simulations. To assess those limitations new spatial verification methods have been proposed. In the present study an attempt is made to estimate the ability of the WRF model (WRF -ARW ver3.5.1) to reproduce selected days with high convective activity during the year 2010 using those feature-based verification methods. Three model domains, covering Europe, the Mediterranean Sea and northern Africa (d01), the wider area of Greece (d02) and central Greece - Thessaly region (d03) are used at horizontal grid-spacings of 15km, 5km and 1km respectively. By alternating microphysics (Ferrier, WSM6, Goddard), boundary layer (YSU, MYJ) and cumulus convection (Kain-­-Fritsch, BMJ) schemes, a set of twelve model setups is obtained. The results of those simulations are evaluated against data obtained using a C-Band (5cm) radar located at the centre of the innermost domain. Spatial characteristics are well captured but with a variable time lag between simulation results and radar data. Acknowledgements: This research is co­financed by the European Union (European Regional Development Fund) and Greek national funds, through the action "COOPERATION 2011: Partnerships of Production and Research Institutions in Focused Research and Technology Sectors" (contract number 11SYN_8_1088 - DAPHNE) in the framework of the operational programme "Competitiveness and Entrepreneurship" and Regions in Transition (OPC II, NSRF 2007-­-2013).

  19. Evaluation of a two-point method for prediction of lithium maintenance dosage.

    PubMed

    Karki, S D; Carson, S W; Holden, J M; Nanavati, D

    1987-10-01

    A lithium test dose method, based on the two-point method of Perry et al. (1982), was evaluated in 20 patients for the prediction of maintenance dosage of slow-release lithium carbonate tablets. These predictions were compared with the predictions obtained from the dosing chart of Cooper et al. (1973). The two-point method accurately predicted the maintenance dosage within clinically acceptable limits, but dosages predicted from the dosing chart would have yielded much higher serum lithium concentrations. PMID:3121719

  20. Method and apparatus for large motor control

    DOEpatents

    Rose, Chris R.; Nelson, Ronald O.

    2003-08-12

    Apparatus and method for providing digital signal processing method for controlling the speed and phase of a motor involves inputting a reference signal having a frequency and relative phase indicative of a time based signal; modifying the reference signal to introduce a slew-rate limited portion of each cycle of the reference signal; inputting a feedback signal having a frequency and relative phase indicative of the operation of said motor; modifying the feedback signal to introduce a slew-rate limited portion of each cycle of the feedback signal; analyzing the modified reference signal and the modified feedback signal to determine the frequency of the modified reference signal and of the modified feedback signal and said relative phase between said modified reference signal and said modified feedback signal; and outputting control signals to the motor for adjusting said speed and phase of the motor based on the frequency determination and determination of the relative phase.

  1. New method of control of tooth whitening

    NASA Astrophysics Data System (ADS)

    Angelov, I.; Mantareva, V.; Gisbrecht, A.; Valkanov, S.; Uzunov, Tz.

    2010-10-01

    New methods of control of tooth bleaching stages through simultaneous measurements of a reflected light and a fluorescence signal are proposed. It is shown that the bleaching process leads to significant changes in the intensity of a scattered signal and also in the shape and intensity of the fluorescence spectra. Experimental data illustrate that the bleaching process causes essential changes in the teeth discoloration in short time as 8-10 min from the beginning of the application procedure. The continuation of the treatment is not necessary moreover the probability of the enamel destroy increases considerably. The proposed optical back control of tooth surface is a base for development of a practical set up to control the duration of the bleaching procedure.

  2. A novel predictive control algorithm and robust stability criteria for integrating processes.

    PubMed

    Zhang, Bin; Yang, Weimin; Zong, Hongyuan; Wu, Zhiyong; Zhang, Weidong

    2011-07-01

    This paper introduces a novel predictive controller for single-input/single-output (SISO) integrating systems, which can be directly applied without pre-stabilizing the process. The control algorithm is designed on the basis of the tested step response model. To produce a bounded system response along the finite predictive horizon, the effect of the integrating mode must be zeroed while unmeasured disturbances exist. Here, a novel predictive feedback error compensation method is proposed to eliminate the permanent offset between the setpoint and the process output while the integrating system is affected by load disturbance. Also, a rotator factor is introduced in the performance index, which is contributed to the improvement robustness of the closed-loop system. Then on the basis of Jury's dominant coefficient criterion, a robust stability condition of the resulted closed loop system is given. There are only two parameters which need to be tuned for the controller, and each has a clear physical meaning, which is convenient for implementation of the control algorithm. Lastly, simulations are given to illustrate that the proposed algorithm can provide excellent closed loop performance compared with some reported methods. PMID:21353217

  3. A Rate Feedback Predictive Control Scheme Based on Neural Network and Control Theory for Autonomic Communication

    NASA Astrophysics Data System (ADS)

    Xiong, Naixue; Vasilakos, Athanasios V.; Yang, Laurence T.; Long, Fei; Shu, Lei; Li, Yingshu

    The main difficulty arising in designing an efficient congestion control scheme lies in the large propagation delay in data transfer which usually leads to a mismatch between the network resources and the amount of admitted traffic. To attack this problem, this chapter describes a novel congestion control scheme that is based on a Back Propagation (BP) neural network technique.We consider a general computer communication model with multiple sources and one destination node. The dynamic buffer occupancy of the bottleneck node is predicted and controlled by using a BP neural network. The controlled best-effort traffic of the sources uses the bandwidth, which is left over by the guaranteed traffic. This control mechanism is shown to be able to avoid network congestion efficiently and to optimize the transfer performance both by the theoretic analyzing procedures and by the simulation studies.

  4. Digging Soil Experiments for Micro Hydraulic Excavators based on Model Predictive Tracking Control

    NASA Astrophysics Data System (ADS)

    Tomatsu, Takumi; Nonaka, Kenichiro; Sekiguchi, Kazuma; Suzuki, Katsumasa

    2016-09-01

    Recently, the increase of burden to operators and lack of skilled operators are the issue in the work of the hydraulic excavator. These problems are expected to be improved by autonomous control. In this paper, we present experimental results of hydraulic excavators using model predictive control (MPC) which incorporates servo mechanism. MPC optimizes digging operations by the optimal control input which is calculated by predicting the future states and satisfying the constraints. However, it is difficult for MPC to cope with the reaction force from soil when a hydraulic excavator performs excavation. Servo mechanism suppresses the influence of the constant disturbance using the error integration. However, the bucket tip deviates from a specified shape by the sudden change of the disturbance. We can expect that the tracking performance is improved by combining MPC and servo mechanism. Path-tracking controls of the bucket tip are performed using the optimal control input. We apply the proposed method to the Komatsu- made micro hydraulic excavator PC01 by experiments. We show the effectiveness of the proposed method through the experiment of digging soil by comparing servo mechanism and pure MPC with the proposed method.

  5. Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

    USGS Publications Warehouse

    Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

    1997-01-01

    One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

  6. Methods and kits for predicting a response to an erythropoietic agent

    DOEpatents

    Merchant, Michael L.; Klein, Jon B.; Brier, Michael E.; Gaweda, Adam E.

    2015-06-16

    Methods for predicting a response to an erythropoietic agent in a subject include providing a biological sample from the subject, and determining an amount in the sample of at least one peptide selected from the group consisting of SEQ ID NOS: 1-17. If there is a measurable difference in the amount of the at least one peptide in the sample, when compared to a control level of the same peptide, the subject is then predicted to have a good response or a poor response to the erythropoietic agent. Kits for predicting a response to an erythropoietic agent are further provided and include one or more antibodies, or fragments thereof, that specifically recognize a peptide of SEQ ID NOS: 1-17.

  7. Model Predictive Control considering Reachable Range of Wheels for Leg / Wheel Mobile Robots

    NASA Astrophysics Data System (ADS)

    Suzuki, Naito; Nonaka, Kenichiro; Sekiguchi, Kazuma

    2016-09-01

    Obstacle avoidance is one of the important tasks for mobile robots. In this paper, we study obstacle avoidance control for mobile robots equipped with four legs comprised of three DoF SCARA leg/wheel mechanism, which enables the robot to change its shape adapting to environments. Our previous method achieves obstacle avoidance by model predictive control (MPC) considering obstacle size and lateral wheel positions. However, this method does not ensure existence of joint angles which achieves reference wheel positions calculated by MPC. In this study, we propose a model predictive control considering reachable mobile ranges of wheels positions by combining multiple linear constraints, where each reachable mobile range is approximated as a convex trapezoid. Thus, we achieve to formulate a MPC as a quadratic problem with linear constraints for nonlinear problem of longitudinal and lateral wheel position control. By optimization of MPC, the reference wheel positions are calculated, while each joint angle is determined by inverse kinematics. Considering reachable mobile ranges explicitly, the optimal joint angles are calculated, which enables wheels to reach the reference wheel positions. We verify its advantages by comparing the proposed method with the previous method through numerical simulations.

  8. Controlled source electromagnetic methods in geothermal exploration

    SciTech Connect

    Ward, S.H.

    1983-04-01

    The objective of this manuscript is to sketch the problems inherent in application of controlled source electromagnetic methods (CSEM) to geothermal exploration. Measurements have been made in both the time and frequency domains with time domain measurements currently enjoying an advantage over frequency domain measurements for shallow applications. Application of CSEM methods is impeded by natural field, electrification, geological, cultural, and topographic noise. Lateral resolution of parameters of adjacent steeply dipping bodies and vertical resolution of parameters of adjacent beds in a flatly dipping sequence are concerns with any CSEM method. Current channeling into a localized good conductor form a surrounding, overlying, or underlying conductor poses problems for the interpreter. In selecting a transmitter-receiver configuration for CSEM in a particular application, a compromise is usually achieved between such factors as domain of data acquisition, rejection of noise, resolution, current channeling, and depth of exploration. Not surprisingly there is only marginal agreement on the optimum selection of each of these variables. However, one of the more promising techniques for application in geothermal exploration is the controlled source audiomagnetotelluric method (CSAMT).

  9. Hybrid methods for B-cell epitope prediction.

    PubMed

    Caoili, Salvador Eugenio C

    2014-01-01

    Many computational approaches to B-cell epitope prediction have been published, including combinations of previously proposed methods, which complicates the tasks of further developing such computational approaches and of selecting those most appropriate for practical applications (e.g., the design of novel immunodiagnostics and vaccines). These tasks are considered together herein to clarify their close but often overlooked interrelationship, thereby providing a guide to their performance in mutual support of one another, with emphasis on key physicochemical and biological considerations that are relevant from an applications perspective. This aims to assist investigators in performing either or both tasks, with the overall goals of successfully applying computational tools towards practical ends and of generating informative new data towards iterative improvement of the tools, particularly as regards the design of peptide-based immunogens for eliciting the production of antipeptide antibodies that modulate biological activity of protein targets via functionally relevant cross-reactivity in relation to the phenomena of protein folding and protein disorder.

  10. A Low-Cost Method for Multiple Disease Prediction

    PubMed Central

    Bayati, Mohsen; Bhaskar, Sonia; Montanari, Andrea

    2015-01-01

    Recently, in response to the rising costs of healthcare services, employers that are financially responsible for the healthcare costs of their workforce have been investing in health improvement programs for their employees. A main objective of these so called “wellness programs” is to reduce the incidence of chronic illnesses such as cardiovascular disease, cancer, diabetes, and obesity, with the goal of reducing future medical costs. The majority of these wellness programs include an annual screening to detect individuals with the highest risk of developing chronic disease. Once these individuals are identified, the company can invest in interventions to reduce the risk of those individuals. However, capturing many biomarkers per employee creates a costly screening procedure. We propose a statistical data-driven method to address this challenge by minimizing the number of biomarkers in the screening procedure while maximizing the predictive power over a broad spectrum of diseases. Our solution uses multi-task learning and group dimensionality reduction from machine learning and statistics. We provide empirical validation of the proposed solution using data from two different electronic medical records systems, with comparisons to a statistical benchmark. PMID:26958164

  11. Predictive methods for estimating pesticide flux to air

    SciTech Connect

    Woodrow, J.E.; Seiber, J.N.

    1996-10-01

    Published evaporative flux values for pesticides volatilizing from soil, plants, and water were correlated with compound vapor pressures (VP), modified by compound properties appropriate to the treated matrix (e.g., soil adsorption coefficient [K{sub oc}], water solubility [S{sub w}]). These correlations were formulated as Ln-Ln plots with correlation (r{sup 2}) coefficients in the range 0.93-0.99: (1) Soil surface - Ln flux vs Ln (VP/[K{sub oc} x S{sub w}]); (2) soil incorporation - Ln flux vs Ln [(VP x AR)/(K{sub oc} x S{sub w} x d)] (AR = application rate, d = incorporation depth); (3) plants - Ln flux vs Ln VP; and (4) water - Ln (flux/water conc) vs Ln (VP/Sw). Using estimated flux values from the plant correlation as source terms in the EPA`s SCREEN-2 dispersion model gave downwind concentrations that agreed to within 65-114% with measured concentrations. Further validation using other treated matrices is in progress. These predictive methods for estimating flux, when coupled with downwind dispersion modeling, provide tools for limiting downwind exposures.

  12. Predicting sulphur and nitrogen deposition using a simple statistical method

    NASA Astrophysics Data System (ADS)

    Oulehle, Filip; Kopáček, Jiří; Chuman, Tomáš; Černohous, Vladimír; Hůnová, Iva; Hruška, Jakub; Krám, Pavel; Lachmanová, Zora; Navrátil, Tomáš; Štěpánek, Petr; Tesař, Miroslav; Evans, Christopher D.

    2016-09-01

    Data from 32 long-term (1994-2012) monitoring sites were used to assess temporal development and spatial variability of sulphur (S) and inorganic nitrogen (N) concentrations in bulk precipitation, and S in throughfall, for the Czech Republic. Despite large variance in absolute S and N concentration/deposition among sites, temporal coherence using standardised data (Z score) was demonstrated. Overall significant declines of SO4 concentration in bulk and throughfall precipitation, as well as NO3 and NH4 concentration in bulk precipitation, were observed. Median Z score values of bulk SO4, NO3 and NH4 and throughfall SO4 derived from observations and the respective emission rates of SO2, NOx and NH3 in the Czech Republic and Slovakia showed highly significant (p < 0.001) relationships. Using linear regression models, Z score values were calculated for the whole period 1900-2012 and then back-transformed to give estimates of concentration for the individual sites. Uncertainty associated with the concentration calculations was estimated as 20% for SO4 bulk precipitation, 22% for throughfall SO4, 18% for bulk NO3 and 28% for bulk NH4. The application of the method suggested that it is effective in the long-term reconstruction and prediction of S and N deposition at a variety of sites. Multiple regression modelling was used to extrapolate site characteristics (mean precipitation chemistry and its standard deviation) from monitored to unmonitored sites. Spatially distributed temporal development of S and N depositions were calculated since 1900. The method allows spatio-temporal estimation of the acid deposition in regions with extensive monitoring of precipitation chemistry.

  13. EPR oxygen images predict tumor control by a 50 percent tumor control radiation dose

    PubMed Central

    Elas, Martyna; Magwood, Jessica M.; Butler, Brandi; Li, Chanel; Wardak, Rona; Barth, Eugene D.; Epel, Boris; Rubinstein, Samuel; Pelizzari, Charles A.; Weichselbaum, Ralph R.; Halpern, Howard J.

    2013-01-01

    Clinical trials to ameliorate hypoxia as a strategy to relieve the radiation resistance it causes have prompted a need to assay the precise extent and location of hypoxia in tumors. Electron Paramagnetic Resonance oxygen imaging (EPR O2 imaging) provides a non-invasive means to address this need. To obtain a preclinical proof of principle that EPR O2 images could predict radiation control, we treated mouse tumors at or near doses required to achieve 50 percent control (TCD50). Mice with FSa fibrosarcoma or MCa4 carcinoma were subjected to EPR O2 imaging and immediately radiated to a TCD50 or TCD50 ±10 Gy.. Statistical analysis was permitted by collection of ~ 1300 tumor pO2 image voxels, including the fraction of tumor voxels with pO2 less than 10 mm Hg (HF10). Tumors were followed for 90 days (FSa) or 120 days (MCa4) to determine local control or failure. HF10 obtained from EPR images showed statistically significant differences between tumors that were controlled by the TCD50 and those that were not controlled for both FSa and MCa4. Kaplan-Meier analysis of both types of tumors showed ~90% of mildly hypoxic tumors were controlled (HF10<10%), and only 37% (FSA) and 23% (MCa4) tumors controlled if hypoxic. EPR pO2 image voxel distributions in these ~0.5 ml tumors provide a prediction of radiation curability independent of radiation dose. These data confirm the significance of EPR pO2 hypoxic fractions. The ~90% control of low HF10 tumors argue that ½ ml subvolumes of tumors may be more sensitive to radiation and may need less radiation for high tumor control rates. PMID:23861469

  14. Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

    NASA Technical Reports Server (NTRS)

    Schweikhard, W. G.; Chen, Y. S.

    1986-01-01

    The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

  15. Predictable SCR co-benefits for mercury control

    SciTech Connect

    Pritchard, S.

    2009-01-15

    A test program, performed in cooperation with Dominion Power and the Babcock and Wilcox Co., was executed at Dominion Power's Mount Storm power plant in Grant County, W. Va. The program was focused on both the selective catalytic reduction (SCR) catalyst capability to oxide mercury as well as the scrubber's capability to capture and retain the oxidized mercury. This article focuses on the SCR catalyst performance aspects. The Mount Storm site consists of three units totaling approximately 1,660 MW. All units are equipped with SCR systems for NOx control. A full-scale test to evaluate the effect of the SCR was performed on Unit 2, a 550 MWT-fired boiler firing a medium sulfur bituminous coal. This test program demonstrated that the presence of an SCR catalyst can significantly affect the mercury speciation profile. Observation showed that in the absence of an SCR catalyst, the extent of oxidation of element a mercury at the inlet of the flue gas desulfurization system was about 64%. The presence of a Cornertech SCR catalyst improved this oxidation to levels greater than 95% almost all of which was captured by the downstream wet FGD system. Cornertech's proprietary SCR Hg oxidation model was used to accurately predict the field results. 1 ref., 2 figs., 1 tab.

  16. An extrapolation method for compressive strength prediction of hydraulic cement products

    SciTech Connect

    Siqueira Tango, C.E. de

    1998-07-01

    The basis for the AMEBA Method is presented. A strength-time function is used to extrapolate the predicted cementitious material strength for a late (ALTA) age, based on two earlier age strengths--medium (MEDIA) and low (BAIXA) ages. The experimental basis for the method is data from the IPT-Brazil laboratory and the field, including a long-term study on concrete, research on limestone, slag, and fly-ash additions, and quality control data from a cement factory, a shotcrete tunnel lining, and a grout for structural repair. The method applicability was also verified for high-performance concrete with silica fume. The formula for predicting late age (e.g., 28 days) strength, for a given set of involved ages (e.g., 28,7, and 2 days) is normally a function only of the two earlier ages` (e.g., 7 and 2 days) strengths. This equation has been shown to be independent on materials variations, including cement brand, and is easy to use also graphically. Using the AMEBA method, and only needing to know the type of cement used, it has been possible to predict strengths satisfactorily, even without the preliminary tests which are required in other methods.

  17. Analytical Failure Prediction Method Developed for Woven and Braided Composites

    NASA Technical Reports Server (NTRS)

    Min, James B.

    2003-01-01

    Historically, advances in aerospace engine performance and durability have been linked to improvements in materials. Recent developments in ceramic matrix composites (CMCs) have led to increased interest in CMCs to achieve revolutionary gains in engine performance. The use of CMCs promises many advantages for advanced turbomachinery engine development and may be especially beneficial for aerospace engines. The most beneficial aspects of CMC material may be its ability to maintain its strength to over 2500 F, its internal material damping, and its relatively low density. Ceramic matrix composites reinforced with two-dimensional woven and braided fabric preforms are being considered for NASA s next-generation reusable rocket turbomachinery applications (for example, see the preceding figure). However, the architecture of a textile composite is complex, and therefore, the parameters controlling its strength properties are numerous. This necessitates the development of engineering approaches that combine analytical methods with limited testing to provide effective, validated design analyses for the textile composite structures development.

  18. Exploratory Studies in Generalized Predictive Control for Active Aeroelastic Control of Tiltrotor Aircraft

    NASA Technical Reports Server (NTRS)

    Kvaternik, Raymond G.; Juang, Jer-Nan; Bennett, Richard L.

    2000-01-01

    The Aeroelasticity Branch at NASA Langley Research Center has a long and substantive history of tiltrotor aeroelastic research. That research has included a broad range of experimental investigations in the Langley Transonic Dynamics Tunnel (TDT) using a variety of scale models and the development of essential analyses. Since 1994, the tiltrotor research program has been using a 1/5-scale, semispan aeroelastic model of the V-22 designed and built by Bell Helicopter Textron Inc. (BHTI) in 1981. That model has been refurbished to form a tiltrotor research testbed called the Wing and Rotor Aeroelastic Test System (WRATS) for use in the TDT. In collaboration with BHTI, studies under the current tiltrotor research program are focused on aeroelastic technology areas having the potential for enhancing the commercial and military viability of tiltrotor aircraft. Among the areas being addressed, considerable emphasis is being directed to the evaluation of modern adaptive multi-input multi- output (MIMO) control techniques for active stability augmentation and vibration control of tiltrotor aircraft. As part of this investigation, a predictive control technique known as Generalized Predictive Control (GPC) is being studied to assess its potential for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in both helicopter and airplane modes of flight. This paper summarizes the exploratory numerical and experimental studies that were conducted as part of that investigation.

  19. Modeling for Airframe Noise Prediction Using Vortex Methods

    NASA Astrophysics Data System (ADS)

    Zheng, Z. Charlie

    2002-12-01

    Various components of the airframe are known to be a significant source of noise. With the advent of technology in quieting modern engines, airframe generated noise competes and, in certain instances, surpasses the engine noise. Airframe noise is most pronounced during aircraft approach when the engines are operating at reduced thrust, and airframe components such as high-lift devices and landing gears are in deployed conditions. Recent experimental studies have reaffirmed that the most significant sources of high-lift noise are from the leading-edge slat and the side edges of flaps. Studies of flow field around these structures have consistently shown that there are complicated unsteady vortical flows such as vortex shedding, secondary vortices and vortex breakdown, which are susceptible to far-field radiated sound. The near-field CFD computational data have been used to calculate the far-field acoustics by employing Ffowcs-Williams/Hawkings equation using Lighthill's analogy. However, because of the limit of current computing capacity, it is very time consuming to generate unsteady Navier-Stokes (N-S) computational data for aeroacoustics. Although the N-S simulations are probably necessary to reveal many complex flow phenomena that are unsteady and fully nonlinear, these simulations are not feasible to be used for parametric design. purposes. The objective of this study is thus to develop theoretical models for airframe noise predictions which have quick turn-around computing time. Since it is known that vorticity is a major mechanism responsible for noise generation on high-lift devices, vortex methods have been chosen as modeling tools. Vortex methods are much faster in comparison with other numerical methods, yet they are able to incorporate nonlinear interactions between vortices. Obviously, as with any theoretical model, assumptions have to be made and justified when such models are used in complex flow. The merit and applicability of the models for

  20. Corrosion fatigue behavior and life prediction method under changing temperature condition

    SciTech Connect

    Kanasaki, Hiroshi; Hirano, Akihiko; Iida, Kunihiro; Asada, Yasuhide

    1997-12-01

    Axially strain controlled low cycle fatigue tests of a carbon steel in oxygenated high temperature water were carried out under changing temperature conditions. Two patterns of triangular wave were selected for temperature cycling. One was in-phase pattern synchronizing with strain cycling and the other was an out-of-phase pattern in which temperature was changed in anti-phase to the strain cycling. The fatigue life under changing temperature condition was in the range of the fatigue life under various constant temperature within the range of the changing temperature. The fatigue life of in-phase pattern was equivalent to that of out-of-phase pattern. The corrosion fatigue life prediction method was proposed for changing temperature condition, and was based on the assumption that the fatigue damage increased in linear proportion to increment of strain during cycling. The fatigue life predicted by this method was in good agreement with the test results.

  1. One-level prediction-A numerical method for estimating undiscovered metal endowment

    USGS Publications Warehouse

    McCammon, R.B.; Kork, J.O.

    1992-01-01

    One-level prediction has been developed as a numerical method for estimating undiscovered metal endowment within large areas. The method is based on a presumed relationship between a numerical measure of geologic favorability and the spatial distribution of metal endowment. Metal endowment within an unexplored area for which the favorability measure is greater than a favorability threshold level is estimated to be proportional to the area of that unexplored portion. The constant of proportionality is the ratio of the discovered endowment found within a suitably chosen control region, which has been explored, to the area of that explored region. In addition to the estimate of undiscovered endowment, a measure of the error of the estimate is also calculated. One-level prediction has been used to estimate the undiscovered uranium endowment in the San Juan basin, New Mexico, U.S.A. A subroutine to perform the necessary calculations is included. ?? 1992 Oxford University Press.

  2. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    PubMed

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.

  3. Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes

    NASA Technical Reports Server (NTRS)

    Kvaternik, Raymond G.

    2013-01-01

    Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.

  4. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    PubMed

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration. PMID:26336152

  5. Model Predictive Obstacle Avoidance and Wheel Allocation Control of Mobile Robots Using Embedded CPU

    NASA Astrophysics Data System (ADS)

    Takahashi, Naoki; Nonaka, Kenichiro

    In this study, we propose a real-time model predictive control method for leg/wheel mobile robots which simultaneously achieves both obstacle avoidance and wheel allocation at a flexible position. The proposed method generates both obstacle avoidance path and dynamical wheel positions, and controls the heading angle depending on the slope of the predicted path so that the robot can keep a good balance between stability and mobility in narrow and complex spaces like indoor environments. Moreover, we reduce the computational effort of the algorithm by deleting usage of mathematical function in the repetitive numerical computation. Thus the proposed real-time optimization method can be applied to low speed on-board CPUs used in commercially-produced vehicles. We conducted experiments to verify efficacy and feasibility of the real-time implementation of the proposed method. We used a leg/wheel mobile robot which is equipped with two laser range finders to detect obstacles and an embedded CPU whose clock speed is only 80MHz. Experiments indicate that the proposed method achieves improved obstacle avoidance comparing with the previous method in the sense that it generates an avoidance path with balanced allocation of right and left side wheels.

  6. Does the Current Minimum Validate (or Invalidate) Cycle Prediction Methods?

    NASA Technical Reports Server (NTRS)

    Hathaway, David H.

    2010-01-01

    This deep, extended solar minimum and the slow start to Cycle 24 strongly suggest that Cycle 24 will be a small cycle. A wide array of solar cycle prediction techniques have been applied to predicting the amplitude of Cycle 24 with widely different results. Current conditions and new observations indicate that some highly regarded techniques now appear to have doubtful utility. Geomagnetic precursors have been reliable in the past and can be tested with 12 cycles of data. Of the three primary geomagnetic precursors only one (the minimum level of geomagnetic activity) suggests a small cycle. The Sun's polar field strength has also been used to successfully predict the last three cycles. The current weak polar fields are indicative of a small cycle. For the first time, dynamo models have been used to predict the size of a solar cycle but with opposite predictions depending on the model and the data assimilation. However, new measurements of the surface meridional flow indicate that the flow was substantially faster on the approach to Cycle 24 minimum than at Cycle 23 minimum. In both dynamo predictions a faster meridional flow should have given a shorter cycle 23 with stronger polar fields. This suggests that these dynamo models are not yet ready for solar cycle prediction.

  7. Skill forecasting from different wind power ensemble prediction methods

    NASA Astrophysics Data System (ADS)

    Pinson, Pierre; Nielsen, Henrik Aa; Madsen, Henrik; Kariniotakis, George

    2007-07-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed.

  8. An empirical method for prediction of cheese yield.

    PubMed

    Melilli, C; Lynch, J M; Carpino, S; Barbano, D M; Licitra, G; Cappa, A

    2002-10-01

    Theoretical cheese yield can be estimated from the milk fat and casein or protein content of milk using classical formulae, such as the VanSlyke formula. These equations are reliable predictors of theoretical or actual yield based on accurately measured milk fat and casein content. Many cheese makers desire to base payment for milk to dairy farmers on the yield of cheese. In small factories, however, accurate measurement of fat and casein content of milk by either chemical methods or infrared milk analysis is too time consuming and expensive. Therefore, an empirical test to predict cheese yield was developed which uses simple equipment (i.e., clinical centrifuge, analytical balance, and forced air oven) to carry out a miniature cheese making, followed by a gravimetric measurement of dry weight yield. A linear regression of calculated theoretical versus dry weight yields for milks of known fat and casein content was calculated. A regression equation of y = 1.275x + 1.528, where y is theoretical yield and x is measured dry solids yield (r2 = 0.981), for Cheddar cheese was developed using milks with a range of theoretical yield from 7 to 11.8%. The standard deviation of the difference (SDD) between theoretical cheese yield and dry solids yield was 0.194 and the coefficient of variation (SDD/mean x 100) was 1.95% upon cross validation. For cheeses without a well-established theoretical cheese yield equation, the measured dry weight yields could be directly correlated to the observed yields in the factory; this would more accurately reflect the expected yield performance. Payments for milk based on these measurements would more accurately reflect quality and composition of the milk and the actual average recovery of fat and casein achieved under practical cheese making conditions. PMID:12416825

  9. Method for predicting cracking in waste glass canisters

    SciTech Connect

    Faletti, D.W.; Ethridge, L.J.

    1986-08-01

    A correlation has been developed that predicts the surface area created by cracking to within the accuracy of the existing data. The correlation is a simple linear equation; the surface area can be computed from a knowledge of the steady-state radial temperature difference and the radial temperature difference when the glass centerline temperature was at 500/sup 0/C. This correlation should be easy to use for waste glass canister applications since, in many cases, a two-dimensional heat transfer analysis can be used to determine the radial temperature differences. Although the correlation is useful for scoping purposes, there is a need to validate the correlation against additional canister cracking data, particularly in the case of stainless steel canisters. The use of Fiberfrax liners deserves serious consideration for use in stainless steel waste glass canisters. The amount of cracking is reduced because the liner eliminates the metal-glass interactions that produce significant stresses in the glass. Another less obvious, but very important, advantage of using Fiberfrax is that thermal shocking during decontamination and post-fill operations is reduced because of the liner's insulating capacity. More extensive studies to verify these results are recommended; canisters should be produced, under identical cooling conditions, that differ only in the use of liners. The data for any canister type are extremely sparse, and there is considerable uncertainty about the accuracy of the different methods that have been used to obtain surface area estimates. The comparative roles played by batch and continuous filling of the canisters also need to be clarified. There is a need for accurate thermal data to validate computer codes for determining the temperature histories of canisters. Suggestions for future cracking studies are given.

  10. Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

    NASA Astrophysics Data System (ADS)

    Manal, Messadi; Adel, Mellit; Karim, Kemih; Malek, Ghanes

    2015-01-01

    This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. Project supported by the CMEP-TASSILI Project (Grant No. 14MDU920).

  11. Method for controlling gas metal arc welding

    DOEpatents

    Smartt, Herschel B.; Einerson, Carolyn J.; Watkins, Arthur D.

    1989-01-01

    The heat input and mass input in a Gas Metal Arc welding process are controlled by a method that comprises calculating appropriate values for weld speed, filler wire feed rate and an expected value for the welding current by algorithmic function means, applying such values for weld speed and filler wire feed rate to the welding process, measuring the welding current, comparing the measured current to the calculated current, using said comparison to calculate corrections for the weld speed and filler wire feed rate, and applying corrections.

  12. Method for controlling gas metal arc welding

    DOEpatents

    Smartt, H.B.; Einerson, C.J.; Watkins, A.D.

    1987-08-10

    The heat input and mass input in a Gas Metal Arc welding process are controlled by a method that comprises calculating appropriate values for weld speed, filler wire feed rate and an expected value for the welding current by algorithmic function means, applying such values for weld speed and filler wire feed rate to the welding process, measuring the welding current, comparing the measured current to the calculated current, using said comparison to calculate corrections for the weld speed and filler wire feed rate, and applying corrections. 3 figs., 1 tab.

  13. Flatness Control Using Roll Coolant Based on Predicted Flatness Variation in Cold Rolling Mills

    NASA Astrophysics Data System (ADS)

    Dohmae, Yukihiro; Okamura, Yoshihide

    Flatness control for cold rolling mills is one of the important technologies for improving of product quality and productivity. In particular, poor flatness leads to strip tearing in the extreme case and, moreover, it significantly reduces productivity. Therefore, various flatness control system has been developed. The main actuators for flatness control are classified into two types; one is mechanical equipment such as roll bender, the other is roll coolant, which controls thermal expansion of roll. Flatness variation such as center buckle or edge wave is mainly controlled by mechanical actuator which has high response characteristics. On another front, flatness variation of local zone can be controlled by roll coolant although one's response is lower than the response of mechanical actuator. For accomplishing good flatness accuracy in cold rolling mills, it is important to improve the performance of coolant control moreover. In this paper, a new coolant control method based on flatness variation model is described. In proposed method, the state of coolant spray on or off is selected to minimize the flatness deviation by using predicted flatness variation. The effectiveness of developed system has been demonstrated by application in actual plant.

  14. Accelerating ab initio molecular dynamics simulations by linear prediction methods

    NASA Astrophysics Data System (ADS)

    Herr, Jonathan D.; Steele, Ryan P.

    2016-09-01

    Acceleration of ab initio molecular dynamics (AIMD) simulations can be reliably achieved by extrapolation of electronic data from previous timesteps. Existing techniques utilize polynomial least-squares regression to fit previous steps' Fock or density matrix elements. In this work, the recursive Burg 'linear prediction' technique is shown to be a viable alternative to polynomial regression, and the extrapolation-predicted Fock matrix elements were three orders of magnitude closer to converged elements. Accelerations of 1.8-3.4× were observed in test systems, and in all cases, linear prediction outperformed polynomial extrapolation. Importantly, these accelerations were achieved without reducing the MD integration timestep.

  15. Performance and robustness of hybrid model predictive control for controllable dampers in building models

    NASA Astrophysics Data System (ADS)

    Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

    2016-04-01

    A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

  16. Robust model predictive control by iterative optimisation for polytopic uncertain systems

    NASA Astrophysics Data System (ADS)

    Wang, Chuanxu

    2012-09-01

    This article addresses robust model predictive control (MPC) for constrained systems with polytopic uncertainty description. Firstly, in the technique which parametrises the infinite horizon control moves into a single state feedback law and invokes the parameter-dependent Lyapunov method for achieving closed-loop stability, the slack matrices are iteratively solved at each sampling time. Secondly, in the technique which parametrises the infinite horizon control moves into a set of free perturbations followed by a single state feedback law, the feedback gains within the switch horizon are iteratively found at each sampling time, rather than just inherited from the previous sampling time. Numerical examples show that iterative MPC can not only improve the control performance, but also enlarge the region of attraction.

  17. The engine performance prediction by quasi-steady method

    NASA Astrophysics Data System (ADS)

    Ye, Ai-Yun; Zhang, Yanqin

    1995-01-01

    In this paper, the theory of Quasi-steady is applied to the calculations of turbochargers matching to the diesel engines and performance prediction. The engine performance prediction programs written in language C have been used for calculations of various turbocharged diesel engines. It has been confirmed by the comparisons with experimental data that the results of the calculation are reasonable, reliable and satisfied for the engineering applications.

  18. The role of prediction and outcomes in adaptive cognitive control.

    PubMed

    Schiffer, Anne-Marike; Waszak, Florian; Yeung, Nick

    2015-01-01

    Humans adaptively perform actions to achieve their goals. This flexible behaviour requires two core abilities: the ability to anticipate the outcomes of candidate actions and the ability to select and implement actions in a goal-directed manner. The ability to predict outcomes has been extensively researched in reinforcement learning paradigms, but this work has often focused on simple actions that are not embedded in hierarchical and sequential structures that are characteristic of goal-directed human behaviour. On the other hand, the ability to select actions in accordance with high-level task goals, particularly in the presence of alternative responses and salient distractors, has been widely researched in cognitive control paradigms. Cognitive control research, however, has often paid less attention to the role of action outcomes. The present review attempts to bridge these accounts by proposing an outcome-guided mechanism for selection of extended actions. Our proposal builds on constructs from the hierarchical reinforcement learning literature, which emphasises the concept of reaching and evaluating informative states, i.e., states that constitute subgoals in complex actions. We develop an account of the neural mechanisms that allow outcome-guided action selection to be achieved in a network that relies on projections from cortical areas to the basal ganglia and back-projections from the basal ganglia to the cortex. These cortico-basal ganglia-thalamo-cortical 'loops' allow convergence - and thus integration - of information from non-adjacent cortical areas (for example between sensory and motor representations). This integration is essential in action sequences, for which achieving an anticipated sensory state signals the successful completion of an action. We further describe how projection pathways within the basal ganglia allow selection between representations, which may pertain to movements, actions, or extended action plans. The model lastly envisages

  19. Method for enhanced control of welding processes

    DOEpatents

    Sheaffer, Donald A.; Renzi, Ronald F.; Tung, David M.; Schroder, Kevin

    2000-01-01

    Method and system for producing high quality welds in welding processes, in general, and gas tungsten arc (GTA) welding, in particular by controlling weld penetration. Light emitted from a weld pool is collected from the backside of a workpiece by optical means during welding and transmitted to a digital video camera for further processing, after the emitted light is first passed through a short wavelength pass filter to remove infrared radiation. By filtering out the infrared component of the light emitted from the backside weld pool image, the present invention provides for the accurate determination of the weld pool boundary. Data from the digital camera is fed to an imaging board which focuses on a 100.times.100 pixel portion of the image. The board performs a thresholding operation and provides this information to a digital signal processor to compute the backside weld pool dimensions and area. This information is used by a control system, in a dynamic feedback mode, to automatically adjust appropriate parameters of a welding system, such as the welding current, to control weld penetration and thus, create a uniform weld bead and high quality weld.

  20. Distributed model predictive control with hierarchical architecture for communication: application in automated irrigation channels

    NASA Astrophysics Data System (ADS)

    Farhadi, Alireza; Khodabandehlou, Ali

    2016-08-01

    This paper is concerned with a distributed model predictive control (DMPC) method that is based on a distributed optimisation method with two-level architecture for communication. Feasibility (constraints satisfaction by the approximated solution), convergence and optimality of this distributed optimisation method are mathematically proved. For an automated irrigation channel, the satisfactory performance of the proposed DMPC method in attenuation of the undesired upstream transient error propagation and amplification phenomenon is illustrated and compared with the performance of another DMPC method that exploits a single-level architecture for communication. It is illustrated that the DMPC that exploits a two-level architecture for communication has a better performance by better managing communication overhead.

  1. Evaluation of two methods of predicting MLC leaf positions using EPID measurements

    SciTech Connect

    Parent, Laure; Seco, Joao; Evans, Phil M.; Dance, David R.; Fielding, Andrew

    2006-09-15

    In intensity modulated radiation treatments (IMRT), the position of the field edges and the modulation within the beam are often achieved with a multileaf collimator (MLC). During the MLC calibration process, due to the finite accuracy of leaf position measurements, a systematic error may be introduced to leaf positions. Thereafter leaf positions of the MLC depend on the systematic error introduced on each leaf during MLC calibration and on the accuracy of the leaf position control system (random errors). This study presents and evaluates two methods to predict the systematic errors on the leaf positions introduced during the MLC calibration. The two presented methods are based on a series of electronic portal imaging device (EPID) measurements. A comparison with film measurements showed that the EPID could be used to measure leaf positions without introducing any bias. The first method, referred to as the 'central leaf method', is based on the method currently used at this center for MLC leaf calibration. It mimics the manner in which leaf calibration parameters are specified in the MLC control system and consequently is also used by other centers. The second method, a new method proposed by the authors and referred to as the ''individual leaf method,'' involves the measurement of two positions for each leaf (-5 and +15 cm) and the interpolation and extrapolation from these two points to any other given position. The central leaf method and the individual leaf method predicted leaf positions at prescribed positions of -11, 0, 5, and 10 cm within 2.3 and 1.0 mm, respectively, with a standard deviation (SD) of 0.3 and 0.2 mm, respectively. The individual leaf method provided a better prediction of the leaf positions than the central leaf method. Reproducibility tests for leaf positions of -5 and +15 cm were performed. The reproducibility was within 0.4 mm on the same day and 0.4 mm six weeks later (1 SD). Measurements at gantry angles of 0 deg., 90 deg., and 270 deg

  2. Control system and method for prosthetic devices

    NASA Technical Reports Server (NTRS)

    Bozeman, Richard J., Jr. (Inventor)

    1992-01-01

    A control system and method for prosthetic devices is provided. The control system comprises a transducer for receiving movement from a body part for generating a sensing signal associated with that movement. The sensing signal is processed by a linearizer for linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part. The linearized sensing signal is normalized to be a function of the entire range of body part movement from the no-shrug position of the movable body part through the full-shrug position of the movable body part. The normalized signal is divided into a plurality of discrete command signals. The discrete command signals are used by typical converter devices which are in operational association with the prosthetic device. The converter device uses the discrete command signals for driving the movable portions of the prosthetic device and its sub-prosthesis. The method for controlling a prosthetic device associated with the present invention comprises the steps of receiving the movement from the body part, generating a sensing signal in association with the movement of the body part, linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part, normalizing the linear signal to be a function of the entire range of the body part movement, dividing the normalized signal into a plurality of discrete command signals, and implementing the plurality of discrete command signals for driving the respective movable prosthesis device and its sub-prosthesis.

  3. Analysis, prediction and control of radio frequency interference with respect to DSN

    NASA Astrophysics Data System (ADS)

    Degroot, N. F.

    1982-06-01

    Susceptibility modeling, prediction of radio frequency interference from satellites, operational radio frequency interference control, and international regulations are considered. The existing satellite interference prediction program DSIP2 is emphasized. A summary status evaluation and recommendations for future work are given.

  4. Modeling and Control Systems Design by Model Predictive Control for Air-path System of Diesel Engine

    NASA Astrophysics Data System (ADS)

    Iwadare, Mitsuhiro; Ueno, Masaki; Hattori, Yasuharu; Adachi, Shuichi

    Research has been conducted on a variety of combustion technologies in order to reduce diesel engine emissions. These technologies should precisely control the state of in-cylinder gas (EGR mass flow, air mass flow, and so on). However, because the controlled object is a multi-input, multi-output (MIMO) system and a coupled system, the use of control systems based on the conventional methods that employ PID controllers represents a challenge. Model predictive control (MPC) is well known as an MIMO algorithm. An intake control system that could be applied to the intake system of a diesel engine was constructed by supplementing MPC with a feedback function using a disturbance observer and compensator for the nonlinear characteristic of the actuators. Performance tests using an actual vehicle verified that, when applied to a two-input (throttle valve and EGR valve), two-output (air mass flow and intake chamber pressure) system, the proposed MPC is able to rapidly control each output independently to the target value.

  5. Comparison of several methods for predicting separation in a compressible turbulent boundary layer

    NASA Technical Reports Server (NTRS)

    Gerhart, P. M.; Bober, L. J.

    1974-01-01

    Several methods for predicting the separation point for a compressible turbulent boundary layer were applied to the flow over a bump on a wind-tunnel wall. Measured pressure distributions were used as input. Two integral boundary-layer methods, three finite-difference boundary-layer methods, and three simple methods were applied at five free-stream Mach numbers ranging from 0.354 to 0.7325. Each of the boundary-layer methods failed to explicitly predict separation. However, by relaxing the theoretical separation criteria, several boundary-layer methods were made to yield reasonable separation predictions, but none of the methods accurately predicted the important boundary-layer parameters at separation. Only one of the simple methods consistently predicted separation with reasonable accuracy in a manner consistent with the theory. The other methods either indicated several possible separation locations or only sometimes predicted separation.

  6. Control method for video guidance sensor system

    NASA Technical Reports Server (NTRS)

    Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

    2005-01-01

    A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are carried out. Further, acceptance of reset and diagnostic commands is permitted only when the system is in the standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

  7. Control Method for Video Guidance Sensor System

    NASA Technical Reports Server (NTRS)

    Howard, Richard T. (Inventor); Book, Michael L. (Inventor); Bryan, Thomas C. (Inventor)

    2005-01-01

    A method is provided for controlling operations in a video guidance sensor system wherein images of laser output signals transmitted by the system and returned from a target are captured and processed by the system to produce data used in tracking of the target. Six modes of operation are provided as follows: (i) a reset mode; (ii) a diagnostic mode; (iii) a standby mode; (iv) an acquisition mode; (v) a tracking mode; and (vi) a spot mode wherein captured images of returned laser signals are processed to produce data for all spots found in the image. The method provides for automatic transition to the standby mode from the reset mode after integrity checks are performed and from the diagnostic mode to the reset mode after diagnostic operations are commands is permitted only when the system is in the carried out. Further, acceptance of reset and diagnostic standby mode. The method also provides for automatic transition from the acquisition mode to the tracking mode when an acceptable target is found.

  8. Comparisons of Prediction Models of Myofascial Pain Control after Dry Needling: A Prospective Study

    PubMed Central

    Huang, Yuan-Ting; Neoh, Choo-Aun; Lin, Shun-Yuan

    2013-01-01

    Background. This study purposed to validate the use of artificial neural network (ANN) models for predicting myofascial pain control after dry needling and to compare the predictive capability of ANNs with that of support vector machine (SVM) and multiple linear regression (MLR). Methods. Totally 400 patients who have received dry needling treatments completed the Brief Pain Inventory (BPI) at baseline and at 1 year postoperatively. Results. Compared to the MLR and SVM models, the ANN model generally had smaller mean square error (MSE) and mean absolute percentage error (MAPE) values in the training dataset and testing dataset. Most ANN models had MAPE values ranging from 3.4% to 4.6% and most had high prediction accuracy. The global sensitivity analysis also showed that pretreatment BPI score was the best parameter for predicting pain after dry needling. Conclusion. Compared with the MLR and SVM models, the ANN model in this study was more accurate in predicting patient-reported BPI scores and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data. PMID:23853659

  9. Implicit methods for efficient musculoskeletal simulation and optimal control

    PubMed Central

    van den Bogert, Antonie J.; Blana, Dimitra; Heinrich, Dieter

    2011-01-01

    The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers. PMID:22102983

  10. Implicit methods for efficient musculoskeletal simulation and optimal control.

    PubMed

    van den Bogert, Antonie J; Blana, Dimitra; Heinrich, Dieter

    2011-01-01

    The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers.

  11. Methods for evaluating the predictive accuracy of structural dynamic models

    NASA Technical Reports Server (NTRS)

    Hasselman, Timothy K.; Chrostowski, Jon D.

    1991-01-01

    Modeling uncertainty is defined in terms of the difference between predicted and measured eigenvalues and eigenvectors. Data compiled from 22 sets of analysis/test results was used to create statistical databases for large truss-type space structures and both pretest and posttest models of conventional satellite-type space structures. Modeling uncertainty is propagated through the model to produce intervals of uncertainty on frequency response functions, both amplitude and phase. This methodology was used successfully to evaluate the predictive accuracy of several structures, including the NASA CSI Evolutionary Structure tested at Langley Research Center. Test measurements for this structure were within + one-sigma intervals of predicted accuracy for the most part, demonstrating the validity of the methodology and computer code.

  12. Prediction and control as determinants of behavioural uncertainty: effects on task performance and heart rate reactivity.

    PubMed

    Baker, S R; Stephenson, D

    2000-01-01

    Control or control-belief is often viewed as being directly instrumental in facilitating coping mechanisms in aversive situations, and yet the empirical evidence for the beneficial effects of control is inconclusive. In this study we investigated the role of predictability in determining the effects of perceived control during an aversive reaction time task. Fifty-six subjects were allocated to one of four groups; predictable-control, predictable-no control, unpredictable-control, unpredictable-no control. In the predictable conditions, subjects could temporally predict the occurrence of an aversive noise. In the perceived control conditions, duration of the aversive tone was contingent on subject's performance. All subjects were matched in terms of the nature of the task and in the number and time of receipt of both the warning signal and noise. Heart rate reactivity and two performance parameters were measured, reaction time and performance increase. Both predictability and control-belief led to a reduction in heart rate reactivity, although they appeared to function independently and at different points in the sequence of events. That is, predictability or perceived control was sufficient to mitigate the effects of an aversive situation. Neither perception of control or predictability led to better task performance. These results are discussed in terms of behavioural uncertainty explanations.

  13. Predictive Techniques for Spacecraft Cabin Air Quality Control

    NASA Technical Reports Server (NTRS)

    Perry, J. L.; Cromes, Scott D. (Technical Monitor)

    2001-01-01

    As assembly of the International Space Station (ISS) proceeds, predictive techniques are used to determine the best approach for handling a variety of cabin air quality challenges. These techniques use equipment offgassing data collected from each ISS module before flight to characterize the trace chemical contaminant load. Combined with crew metabolic loads, these data serve as input to a predictive model for assessing the capability of the onboard atmosphere revitalization systems to handle the overall trace contaminant load as station assembly progresses. The techniques for predicting in-flight air quality are summarized along with results from early ISS mission analyses. Results from groundbased analyses of in-flight air quality samples are compared to the predictions to demonstrate the technique's relative conservatism.

  14. Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

    NASA Technical Reports Server (NTRS)

    Morey, Susan; Prevot, Thomas; Mercer, Joey; Martin, Lynne; Bienert, Nancy; Cabrall, Christopher; Hunt, Sarah; Homola, Jeffrey; Kraut, Joshua

    2013-01-01

    A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

  15. Higher Executive Control and Visual Memory Performance Predict Treatment Completion in Borderline Personality Disorder

    PubMed Central

    Fertuck, Eric A.; Keilp, John; Song, Inkyung; Morris, Melissa C.; Wilson, Scott T.; Brodsky, Beth S.; Stanley, Barbara

    2011-01-01

    Background Non-completion of a prescribed course of treatment occurs in 20–60% of individuals diagnosed with borderline personality disorder (BPD). While symptom severity, personality traits and environmental factors have been implicated as predictors of treatment non-completion (TNC), there have been no studies of neuropsychological predictors in this population. Methods From a randomized controlled trial, a subsample of 31, unmedicated outpatients diagnosed with BPD with recent self-injurious behavior was assessed on 5 neuropsychological domains. Patients were also assessed for general IQ, demographic and other salient clinical variables. Patients were randomized to one of four treatment conditions, which lasted up to 1 year. Number of weeks in treatment (WIT) up to 1 year was utilized as the index of TNC. Results Thirty-three percent of the subsample (n = 12) did not complete 1 year of treatment. However, more WIT were predicted by better baseline executive control (Trails B; p < 0.01) and visual memory performance (Benton visual retention; p < 0.001); other neuropsychological domains did not predict WIT. Conclusion In the treatment of outpatients with BPD, better executive control and visual memory performance predict more WIT. Assessing and addressing these neurocognitive factors in treatment may reduce TNC in this high-risk population. PMID:22116411

  16. Indoor environmental quality (IEQ) and building energy optimization through model predictive control (MPC)

    NASA Astrophysics Data System (ADS)

    Woldekidan, Korbaga

    This dissertation aims at developing a novel and systematic approach to apply Model Predictive Control (MPC) to improve energy efficiency and indoor environmental quality in office buildings. Model predictive control is one of the advanced optimal control approaches that use models to predict the behavior of the process beyond the current time to optimize the system operation at the present time. In building system, MPC helps to exploit buildings' thermal storage capacity and to use the information on future disturbances like weather and internal heat gains to estimate optimal control inputs ahead of time. In this research the major challenges of applying MPC to building systems are addressed. A systematic framework has been developed for ease of implementation. New methods are proposed to develop simple and yet reasonably accurate models that can minimize the MPC development effort as well as computational time. The developed MPC is used to control a detailed building model represented by whole building performance simulation tool, EnergyPlus. A co-simulation strategy is used to communicate the MPC control developed in Matlab platform with the case building model in EnergyPlus. The co-simulation tool used (MLE+) also has the ability to talk to actual building management systems that support the BACnet communication protocol which makes it easy to implement the developed MPC control in actual buildings. A building that features an integrated lighting and window control and HVAC system with a dedicated outdoor air system and ceiling radiant panels was used as a case building. Though this study is specifically focused on the case building, the framework developed can be applied to any building type. The performance of the developed MPC was compared against a baseline control strategy using Proportional Integral and Derivative (PID) control. Various conventional and advanced thermal comfort as well as ventilation strategies were considered for the comparison. These

  17. The application study on the multi-scales integrated prediction method to fractured reservoir description

    NASA Astrophysics Data System (ADS)

    Chen, Shuang-Quan; Zeng, Lian-Bo; Huang, Ping; Sun, Shao-Han; Zhang, Wan-Lu; Li, Xiang-Yang

    2016-03-01

    In this paper, we implement three scales of fracture integrated prediction study by classifying it to macro- (> 1/4 λ), meso- (> 1/100 λ and < 1/4 λ) and micro- (< 1/100 λ) scales. Based on the multi-scales rock physics modelling technique, the seismic azimuthal anisotropy characteristic is analyzed for distinguishing the fractures of meso-scale. Furthermore, by integrating geological core fracture description, image well-logging fracture interpretation, seismic attributes macro-scale fracture prediction and core slice micro-scale fracture characterization, an comprehensive multi-scale fracture prediction methodology and technique workflow are proposed by using geology, well-logging and seismic multi-attributes. Firstly, utilizing the geology core slice observation (Fractures description) and image well-logging data interpretation results, the main governing factors of fracture development are obtained, and then the control factors of the development of regional macro-scale fractures are carried out via modelling of the tectonic stress field. For the meso-scale fracture description, the poststack geometric attributes are used to describe the macro-scale fracture as well, the prestack attenuation seismic attribute is used to predict the meso-scale fracture. Finally, by combining lithological statistic inversion with superposed results of faults, the relationship of the meso-scale fractures, lithology and faults can be reasonably interpreted and the cause of meso-scale fractures can be verified. The micro-scale fracture description is mainly implemented by using the electron microscope scanning of cores. Therefore, the development of fractures in reservoirs is assessed by valuating three classes of fracture prediction results. An integrated fracture prediction application to a real field in Sichuan basin, where limestone reservoir fractures developed, is implemented. The application results in the study area indicates that the proposed multi-scales integrated

  18. Method and apparatus for controlling multiple motors

    DOEpatents

    Jones, Rollin G.; Kortegaard, Bert L.; Jones, David F.

    1987-01-01

    A method and apparatus are provided for simultaneously controlling a plurality of stepper motors. Addressing circuitry generates address data for each motor in a periodic address sequence. Memory circuits respond to the address data for each motor by accessing a corresponding memory location containing a first operational data set functionally related to a direction for moving the motor, speed data, and rate of speed change. First logic circuits respond to the first data set to generate a motor step command. Second logic circuits respond to the command from the first logic circuits to generate a third data set for replacing the first data set in memory with a current operational motor status, which becomes the first data set when the motor is next addressed.

  19. What Predicts Method Effects in Child Behavior Ratings

    ERIC Educational Resources Information Center

    Low, Justin A.; Keith, Timothy Z.; Jensen, Megan

    2015-01-01

    The purpose of this research was to determine whether child, parent, and teacher characteristics such as sex, socioeconomic status (SES), parental depressive symptoms, the number of years of teaching experience, number of children in the classroom, and teachers' disciplinary self-efficacy predict deviations from maternal ratings in a…

  20. Experimental implementation of the modified independent modal space control method

    NASA Technical Reports Server (NTRS)

    Baz, A.; Poh, S.

    1990-01-01

    An experimental realization of a modified independent modal space control (MIMSC) method to control the vibration of a flexible cantilevered beam is presented. In its operation the method relies on the use of one piezoelectric actuator to control several vibration modes through a time-sharing strategy. The effectiveness of the MIMSC method in damping out the beam vibration is demonstrated by comparing the results with those obtained by other modal control methods. Two methods are considered, the independent modal space control method and the pseudo-inverse method. The feasibility of the MIMSC method as a viable alternative for controlling large flexible structures with a very small number of actuators is emphasized.

  1. Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

    PubMed Central

    Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

    2015-01-01

    Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used

  2. Speech recognition control system and method

    SciTech Connect

    Lemelson, J.H.

    1986-08-12

    This invention relates to a system and method for weighing articles and quantities of material wherein computing functions are performed to effect calculations and the control of a visual presentation means such as a display or printer or the generation of signals for use in recording a transaction. In particular, the invention relates to such a weighing and computing apparatus and method which operates or varies in response to speech signals generated by selected words of speech spoken into a microphone by an operator of the apparatus. It is known in the art to electronically detect the weight of articles and containers of material and to generate electrical signals which are indicative of such weight. It is also known to effect a computation with respect to such signals and additional signals generated by manually operating selected keys of a keyboard wherein the additional signals represent one or more additional variables which must be divided into or multiplied by the numerical representation of the weights of articles weighed by such apparatus.

  3. Methods and apparatus for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOEpatents

    Robertson, Eric P; Christiansen, Richard L.

    2007-05-29

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  4. Methods for measurement of a dimensional characteristic and methods of predictive modeling related thereto

    DOEpatents

    Robertson, Eric P; Christiansen, Richard L.

    2007-10-23

    A method of optically determining a change in magnitude of at least one dimensional characteristic of a sample in response to a selected chamber environment. A magnitude of at least one dimension of the at least one sample may be optically determined subsequent to altering the at least one environmental condition within the chamber. A maximum change in dimension of the at least one sample may be predicted. A dimensional measurement apparatus for indicating a change in at least one dimension of at least one sample. The dimensional measurement apparatus may include a housing with a chamber configured for accommodating pressure changes and an optical perception device for measuring a dimension of at least one sample disposed in the chamber. Methods of simulating injection of a gas into a subterranean formation, injecting gas into a subterranean formation, and producing methane from a coal bed are also disclosed.

  5. A Simple Method for Predicting Transmembrane Proteins Based on Wavelet Transform

    PubMed Central

    Yu, Bin; Zhang, Yan

    2013-01-01

    The increasing protein sequences from the genome project require theoretical methods to predict transmembrane helical segments (TMHs). So far, several prediction methods have been reported, but there are some deficiencies in prediction accuracy and adaptability in these methods. In this paper, a method based on discrete wavelet transform (DWT) has been developed to predict the number and location of TMHs in membrane proteins. PDB coded as 1KQG is chosen as an example to describe the prediction process by this method. 80 proteins with known 3D structure from Mptopo database are chosen at random as data sets (including 325 TMHs) and 80 sequences are divided into 13 groups according to their function and type. TMHs prediction is carried out for each group of membrane protein sequences and obtain satisfactory result. To verify the feasibility of this method, 80 membrane protein sequences are treated as test sets, 308 TMHs can be predicted and the prediction accuracy is 96.3%. Compared with the main prediction results of seven popular prediction methods, the obtained results indicate that the proposed method in this paper has higher prediction accuracy. PMID:23289014

  6. Jet Engine Noise Generation, Prediction and Control. Chapter 86

    NASA Technical Reports Server (NTRS)

    Huff, Dennis L.; Envia, Edmane

    2004-01-01

    . An example of this type of engine is shown in Figure IC, which is a schematic of the Honeywell T55 engine that powers the CH-47 Chinook helicopter. Since the noise from the propellers or helicopter rotors is usually dominant for turbo-shaft engines, less attention has been paid to these engines in so far as community noise considerations are concerned. This chapter will concentrate mostly on turbofan engine noise and will highlight common methods for their noise prediction and reduction.

  7. Predictive control for voltage collapse avoidance using a modified discrete multi-valued PSO algorithm.

    PubMed

    Pourjafari, Ebrahim; Mojallali, Hamed

    2011-04-01

    Voltage stability is one of the most challenging concerns that power utilities are confronted with, and this paper proposes a voltage control scheme based on Model Predictive Control (MPC) to overcome this kind of instability. Voltage instability has a close relation with the adequacy of reactive power and the response of Under Load Tap Changers (ULTCs) to the voltage drop after the occurrence of a contingency. Therefore, the proposed method utilizes reactive power injection and tap changing to avoid voltage collapse. Considering discrete nature of the changes in the tap ratio and also in the reactive power injected by capacitor banks, the search area for the optimizer of MPC will be an integer area; consequently, a modified discrete multi-valued Particle Swarm Optimization (PSO) is considered to perform this optimization. Simulation results of applying the proposed control scheme to a 4-bus system confirm its capability to prevent voltage collapse. PMID:21251650

  8. High Accuracy Liquid Propellant Slosh Predictions Using an Integrated CFD and Controls Analysis Interface

    NASA Technical Reports Server (NTRS)

    Marsell, Brandon; Griffin, David; Schallhorn, Dr. Paul; Roth, Jacob

    2012-01-01

    Coupling computational fluid dynamics (CFD) with a controls analysis tool elegantly allows for high accuracy predictions of the interaction between sloshing liquid propellants and th e control system of a launch vehicle. Instead of relying on mechanical analogs which are not valid during aU stages of flight, this method allows for a direct link between the vehicle dynamic environments calculated by the solver in the controls analysis tool to the fluid flow equations solved by the CFD code. This paper describes such a coupling methodology, presents the results of a series of test cases, and compares said results against equivalent results from extensively validated tools. The coupling methodology, described herein, has proven to be highly accurate in a variety of different cases.

  9. Integrated CFD and Controls Analysis Interface for High Accuracy Liquid Propellant Slosh Predictions

    NASA Technical Reports Server (NTRS)

    Marsell, Brandon; Griffin, David; Schallhorn, Paul; Roth, Jacob

    2012-01-01

    Coupling computational fluid dynamics (CFD) with a controls analysis tool elegantly allows for high accuracy predictions of the interaction between sloshing liquid propellants and the control system of a launch vehicle. Instead of relying on mechanical analogs which are n0t va lid during all stages of flight, this method allows for a direct link between the vehicle dynamic environments calculated by the solver in the controls analysis tool to the fluid now equations solved by the CFD code. This paper describes such a coupling methodology, presents the results of a series of test cases, and compares said results against equivalent results from extensively validated tools. The coupling methodology, described herein, has proven to be highly accurate in a variety of different cases.

  10. DO TIE LABORATORY BASED ASSESSMENT METHODS REALLY PREDICT FIELD EFFECTS?

    EPA Science Inventory

    Sediment Toxicity Identification and Evaluation (TIE) methods have been developed for both porewaters and whole sediments. These relatively simple laboratory methods are designed to identify specific toxicants or classes of toxicants in sediments; however, the question of whethe...

  11. Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

    EPA Science Inventory

    Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

  12. Correlation of Puma airloads: Evaluation of CFD prediction methods

    NASA Technical Reports Server (NTRS)

    Strawn, Roger C.; Desopper, Andre; Miller, Judith; Jones, Alan

    1989-01-01

    A cooperative program was undertaken by research organizations in England, France, Australia and the U.S. to study the capabilities of computational fluid dynamics codes (CFD) to predict the aerodynamic loading on helicopter rotor blades. The program goal is to compare predictions with experimental data for flight tests of a research Puma helicopter with rectangular and swept tip blades. Two topics are studied. First, computed results from three CFD codes are compared for flight test cases where all three codes use the same partial inflow-angle boundary conditions. Second, one of the CFD codes (FPR) is iteratively coupled with the CAMRAD/JA helicopter performance code. These results are compared with experimental data and with an uncoupled CAMRAD/JA solution. The influence of flow field unsteadiness is found to play an important role in the blade aerodynamics. Alternate boundary conditions are suggested in order to properly model this unsteadiness in the CFD codes.

  13. Correlation of Puma airfoils - Evaluation of CFD prediction methods

    NASA Technical Reports Server (NTRS)

    Strawn, Roger C.; Desopper, Andre; Miller, Judith; Jones, Alan

    1989-01-01

    A cooperative program was undertaken by research organizations in England, France, Australia and the U.S. to study the capabilities of computational fluid dynamics codes (CFD) to predict the aerodynamic loading on helicopter rotor blades. The program goal is to compare predictions with experimental data for flight tests of a research Puma helicopter with rectangular and swept tip blades. Two topics are studied. First, computed results from three CFD codes are compared for flight test cases where all three codes use the same partial inflow-angle boundary conditions. Second, one of the CFD codes (FPR) is iteratively coupled with the CAMRAD/JA heilcopter performance code. These results are compared with experimental data and with an uncoupled CAMRAD/JA solution. The influence of flow field unsteadiness is found to play an important role in the blade aerodynamics. Alternate boundary conditions are suggested in order to properly model this unsteadiness in the CFD codes.

  14. Pattern recognition methods for protein functional site prediction.

    PubMed

    Yang, Zheng Rong; Wang, Lipo; Young, Natasha; Trudgian, Dave; Chou, Kuo-Chen

    2005-10-01

    Protein functional site prediction is closely related to drug design, hence to public health. In order to save the cost and the time spent on identifying the functional sites in sequenced proteins in biology laboratory, computer programs have been widely used for decades. Many of them are implemented using the state-of-the-art pattern recognition algorithms, including decision trees, neural networks and support vector machines. Although the success of this effort has been obvious, advanced and new algorithms are still under development for addressing some difficult issues. This review will go through the major stages in developing pattern recognition algorithms for protein functional site prediction and outline the future research directions in this important area. PMID:16248799

  15. Grasp and release with surface functional electrical stimulation using a Model Predictive Control approach.

    PubMed

    Westerveld, Ard J; Kuck, Alexander; Schouten, Alfred C; Veltink, Peter H; van der Kooij, Herman

    2012-01-01

    Stroke often has a disabling effect on the ability to use the hand in a functional manner. Accurate finger and thumb positioning is necessary for many activities of daily living. In the current study, the feasibility of novel FES based approaches for positioning the thumb and fingers for grasp and release of differently sized objects is evaluated. Assistance based on these approaches may be used in rehabilitation of grasp and release after stroke. A model predictive controller (MPC) is compared with a proportional (P) feedback controller. Both methods are compared on their performance in tracking reference trajectories and in the capability of grasping, holding and releasing objects. Both methods are able to selectively activate the fingers such that differently sized objects, selected from the Action Research Arm test, can be grasped. The MPC method is easier to use in practice, as this method is based on a single identification of a model of the biological system. The P-controller has more parameters which need to be set correctly, and therefore needs more time to initialise. The current results are very promising. Evaluation in patients will be done to explore the possibilities to apply these methods in rehabilitation of grasp and release after stroke.

  16. Mechanisms of Intentional Binding and Sensory Attenuation: The Role of Temporal Prediction, Temporal Control, Identity Prediction, and Motor Prediction

    ERIC Educational Resources Information Center

    Hughes, Gethin; Desantis, Andrea; Waszak, Florian

    2013-01-01

    Sensory processing of action effects has been shown to differ from that of externally triggered stimuli, with respect both to the perceived timing of their occurrence (intentional binding) and to their intensity (sensory attenuation). These phenomena are normally attributed to forward action models, such that when action prediction is consistent…

  17. Prediction of Protein-DNA binding by Monte Carlo method

    NASA Astrophysics Data System (ADS)

    Deng, Yuefan; Eisenberg, Moises; Korobka, Alex

    1997-08-01

    We present an analysis and prediction of protein-DNA binding specificity based on the hydrogen bonding between DNA, protein, and auxillary clusters of water molecules. Zif268, glucocorticoid receptor, λ-repressor mutant, HIN-recombinase, and tramtrack protein-DNA complexes are studied. Hydrogen bonds are approximated by the Lennard-Jones potential with a cutoff distance between the hydrogen and the acceptor atoms set to 3.2 Åand an angular component based on a dipole-dipole interaction. We use a three-stage docking algorithm: geometric hashing that matches pairs of hydrogen bonding sites; (2) least-squares minimization of pairwise distances to filter out insignificant matches; and (3) Monte Carlo stochastic search to minimize the energy of the system. More information can be obtained from our first paper on this subject [Y.Deng et all, J.Computational Chemistry (1995)]. Results show that the biologically correct base pair is selected preferentially when there are two or more strong hydrogen bonds (with LJ potential lower than -0.20) that bind it to the protein. Predicted sequences are less stable in the case of weaker bonding sites. In general the inclusion of water bridges does increase the number of base pairs for which correct specificity is predicted.

  18. Hurricane prediction and control: impact of large computers.

    PubMed

    Hammond, A L

    1973-08-17

    This is the third is a continuing series of articles on natural disasters, their prediction and mnodification, and progress in understanding the physical bases of these phenomena. Two earlier articles (Science, 25 May, p. 851, and 1 June, p. 940) reported advances in earthquake prediction. Hurricanes are the subject here. Generally less devastating than major earthquakes-although a single hurricane in 1970 killed an estimated 200,000 persons in Bangladesh-these storms are still the most destructive of all atmospheric phenomena. A recent report of the National Academy of Sciences (see box) recommends that efforts to modify hurricanes and other severe storms become a national goal.

  19. Enhanced perceptions of control and predictability reduce motion-induced nausea and gastric dysrhythmia.

    PubMed

    Levine, Max E; Stern, Robert M; Koch, Kenneth L

    2014-08-01

    Nausea is a debilitating condition that is typically accompanied by gastric dysrhythmia. The enhancement of perceived control and predictability has generally been found to attenuate the physiological stress response. The aim of the present study was to test the effect of these psychosocial variables in the context of nausea, motion sickness, and gastric dysrhythmia. A 2x2, independent-groups, factorial design was employed in which perceived control and predictability were each provided at high or low levels to 80 participants before exposure to a rotating optokinetic drum. Ratings of nausea were obtained throughout a 6-min baseline period and a 16-min drum rotation period. Noninvasive recordings of the electrical activity of the stomach called electrogastrograms were also obtained throughout the study. Nausea scores were significantly lower among participants with high control than among those with low control, and were significantly lower among participants with high predictability than among those with low predictability. Estimates of gastric dysrhythmia obtained from the EGG during drum rotation were significantly lower among participants with high predictability than among those with low predictability. A significant interaction effect of control and predictability on gastric dysrhythmia was also observed, such that high control was only effective for arresting the development of gastric dysrhythmia when high predictability was also available. Stronger perceptions of control and predictability may temper the development of nausea and gastric dysrhythmia during exposure to provocative motion. Psychosocial interventions in a variety of nausea contexts may represent an alternative means of symptom control. PMID:24748483

  20. Enhanced perceptions of control and predictability reduce motion-induced nausea and gastric dysrhythmia.

    PubMed

    Levine, Max E; Stern, Robert M; Koch, Kenneth L

    2014-08-01

    Nausea is a debilitating condition that is typically accompanied by gastric dysrhythmia. The enhancement of perceived control and predictability has generally been found to attenuate the physiological stress response. The aim of the present study was to test the effect of these psychosocial variables in the context of nausea, motion sickness, and gastric dysrhythmia. A 2x2, independent-groups, factorial design was employed in which perceived control and predictability were each provided at high or low levels to 80 participants before exposure to a rotating optokinetic drum. Ratings of nausea were obtained throughout a 6-min baseline period and a 16-min drum rotation period. Noninvasive recordings of the electrical activity of the stomach called electrogastrograms were also obtained throughout the study. Nausea scores were significantly lower among participants with high control than among those with low control, and were significantly lower among participants with high predictability than among those with low predictability. Estimates of gastric dysrhythmia obtained from the EGG during drum rotation were significantly lower among participants with high predictability than among those with low predictability. A significant interaction effect of control and predictability on gastric dysrhythmia was also observed, such that high control was only effective for arresting the development of gastric dysrhythmia when high predictability was also available. Stronger perceptions of control and predictability may temper the development of nausea and gastric dysrhythmia during exposure to provocative motion. Psychosocial interventions in a variety of nausea contexts may represent an alternative means of symptom control.

  1. Active control: an investigation method for combustion instabilities

    NASA Astrophysics Data System (ADS)

    Poinsot, T.; Yip, B.; Veynante, D.; Trouvé, A.; Samaniego, J. M.; Candel, S.

    1992-07-01

    Closed-loop active control methods and their application to combustion instabilities are discussed. In these methods the instability development is impeded with a feedback control loop: the signal provided by a sensor monitoring the flame or pressure oscillations is processed and sent back to actuators mounted on the combustor or on the feeding system. Different active control systems tested on a non-premixed multiple-flame turbulent combustor are described. These systems can suppress all unstable plane modes of oscillation (i.e. low frequency modes). The active instability control (AIC) also constitutes an original and powerful technique for studies of mechanisms leading to instability or resulting from the instability. Two basic applications of this kind are described. In the first case the flame is initially controlled with AIC, the feedback loop is then switched off and the growth of the instability is analysed through high speed Schlieren cinematography and simultaneous sound pressure and reaction rate measurements. Three phases are identified during th growth of the oscillations: (1) a linear phase where acoustic waves induce a flapping motion of the flame sheets without interaction between sheets, (2) a modulation phase, where flame sheets interact randomly and (3) a nonlinear phase where the flame sheets are broken and a limit cycle is reached. In the second case we investigate different types of flame extinctions associated with combustion instability. It is shown that pressure oscillations may lead to partial or total extinctions. Extinctions occur in various forms but usually follow a rapid growth of pressure oscillations. The flame is extinguished during the modulation phase observed in the initiation experiments. In these studies devoted to transient instability phenomena, the control system constitutes a unique investigation tool because it is difficult to obtain the same information by other means. Implications for modelling and prediction of

  2. An application of generalized predictive control to rotorcraft terrain-following flight

    NASA Technical Reports Server (NTRS)

    Hess, Ronald A.; Jung, Yoon C.

    1989-01-01

    Generalized predictive control (GPC) describes an algorithm for the control of dynamic systems in which a control input is generated which minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. The GPC algorithm is first applied to a simplified rotorcraft terrain-following problem, and GPC performance is compared to that of a conventional compensatory automatic system in terms of flight-path following, control activity, and control law implementation. Next, more realistic vehicle dynamics are utilized, and the GPC algorithm is applied to simultaneous terrain following and velocity control in the presence of atmospheric disturbances and errors in the internal model of the vehicle. The online computational and sensing requirements for implementing the GPC algorithm are minimal. Its use for manual control models appears promising.

  3. Synchronous Control Method and Realization of Automated Pharmacy Elevator

    NASA Astrophysics Data System (ADS)

    Liu, Xiang-Quan

    Firstly, the control method of elevator's synchronous motion is provided, the synchronous control structure of double servo motor based on PMAC is accomplished. Secondly, synchronous control program of elevator is implemented by using PMAC linear interpolation motion model and position error compensation method. Finally, the PID parameters of servo motor were adjusted. The experiment proves the control method has high stability and reliability.

  4. Self-tuning Generalized Predictive Control applied to terrain following flight

    NASA Technical Reports Server (NTRS)

    Hess, R. A.; Jung, Y. C.

    1989-01-01

    Generalized Predictive Control (GPC) describes an algorithm for the control of dynamic systems in which a control input is generated which minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. Self-tuning GPC refers to an implementation of the GPC algorithm in which the parameters of the internal model(s) are estimated on-line and the predictive control law tuned to the parameters so identified. The self-tuning GPC algorithm is applied to a problem of rotorcraft longitudinal/vertical terrain-following flight. The ability of the algorithm to tune to the initial vehicle parameters and to successfully adapt to a stability augmentation failure is demonstrated. Flight path performance is compared to a conventional, classically designed flight path control system.

  5. Development of an integrated method for long-term water quality prediction using seasonal climate forecast

    NASA Astrophysics Data System (ADS)

    Cho, Jaepil; Shin, Chang-Min; Choi, Hwan-Kyu; Kim, Kyong-Hyeon; Choi, Ji-Yong

    2016-10-01

    The APEC Climate Center (APCC) produces climate prediction information utilizing a multi-climate model ensemble (MME) technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1) the Simple Bias Correction (SBC) method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2) the Moving Window Regression (MWR) method, which indirectly utilizes dynamic prediction data; (3) the Climate Index Regression (CIR) method, which predominantly uses observation-based climate indices; and (4) the Integrated Time Regression (ITR) method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT) model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

  6. Methods of Si based ceramic components volatilization control in a gas turbine engine

    DOEpatents

    Garcia-Crespo, Andres Jose; Delvaux, John; Dion Ouellet, Noemie

    2016-09-06

    A method of controlling volatilization of silicon based components in a gas turbine engine includes measuring, estimating and/or predicting a variable related to operation of the gas turbine engine; correlating the variable to determine an amount of silicon to control volatilization of the silicon based components in the gas turbine engine; and injecting silicon into the gas turbine engine to control volatilization of the silicon based components. A gas turbine with a compressor, combustion system, turbine section and silicon injection system may be controlled by a controller that implements the control method.

  7. Simple numerical method for predicting steady compressible flows

    NASA Technical Reports Server (NTRS)

    Vonlavante, Ernst; Nelson, N. Duane

    1986-01-01

    A numerical method for solving the isenthalpic form of the governing equations for compressible viscous and inviscid flows was developed. The method was based on the concept of flux vector splitting in its implicit form. The method was tested on several demanding inviscid and viscous configurations. Two different forms of the implicit operator were investigated. The time marching to steady state was accelerated by the implementation of the multigrid procedure. Its various forms very effectively increased the rate of convergence of the present scheme. High quality steady state results were obtained in most of the test cases; these required only short computational times due to the relative efficiency of the basic method.

  8. Underwater Sound Propagation Modeling Methods for Predicting Marine Animal Exposure.

    PubMed

    Hamm, Craig A; McCammon, Diana F; Taillefer, Martin L

    2016-01-01

    The offshore exploration and production (E&P) industry requires comprehensive and accurate ocean acoustic models for determining the exposure of marine life to the high levels of sound used in seismic surveys and other E&P activities. This paper reviews the types of acoustic models most useful for predicting the propagation of undersea noise sources and describes current exposure models. The severe problems caused by model sensitivity to the uncertainty in the environment are highlighted to support the conclusion that it is vital that risk assessments include transmission loss estimates with statistical measures of confidence.

  9. Method of predicting a change in an economy

    DOEpatents

    Pryor, Richard J; Basu, Nipa

    2006-01-10

    An economy whose activity is to be predicted comprises a plurality of decision makers. Decision makers include, for example, households, government, industry, and banks. The decision makers are represented by agents, where an agent can represent one or more decision makers. Each agent has decision rules that determine the agent's actions. Each agent can affect the economy by affecting variable conditions characteristic of the economy or the internal state of other agents. Agents can communicate actions through messages. On a multiprocessor computer, the agents can be assigned to processing elements.

  10. Underwater Sound Propagation Modeling Methods for Predicting Marine Animal Exposure.

    PubMed

    Hamm, Craig A; McCammon, Diana F; Taillefer, Martin L

    2016-01-01

    The offshore exploration and production (E&P) industry requires comprehensive and accurate ocean acoustic models for determining the exposure of marine life to the high levels of sound used in seismic surveys and other E&P activities. This paper reviews the types of acoustic models most useful for predicting the propagation of undersea noise sources and describes current exposure models. The severe problems caused by model sensitivity to the uncertainty in the environment are highlighted to support the conclusion that it is vital that risk assessments include transmission loss estimates with statistical measures of confidence. PMID:26610982

  11. Can Self-Prediction Overcome Barriers to Hepatitis B Vaccination? A Randomized Controlled Trial

    PubMed Central

    Cox, Anthony D.; Cox, Dena; Cyrier, Rosalie; Graham-Dotson, Yolanda; Zimet, Gregory D.

    2011-01-01

    Objective Hepatitis B virus (HBV) infection remains a serious public health problem, due in part to low vaccination rates among high-risk adults, many of whom decline vaccination because of barriers such as perceived inconvenience or discomfort. This study evaluates the efficacy of a self-prediction intervention to increase HBV vaccination rates among high-risk adults. Method Randomized controlled trial of 1175 adults recruited from three STD clinics in the United States over 28 months. Participants completed an audio-computer-assisted self-interview (A-CASI), which presented information about HBV infection and vaccination, and measured relevant beliefs, behaviors and demographics. Half of participants were assigned randomly to a "self-prediction" intervention, asking them to predict their future acceptance of HBV vaccination. The main outcome measure was subsequent vaccination behavior. Other measures included perceived barriers to HBV vaccination, measured prior to the intervention. Results There was a significant interaction between the intervention and vaccination barriers, indicating the effect of the intervention differed depending on perceived vaccination barriers. Among high-barriers patients, the intervention significantly increased vaccination acceptance. Among low-barrier patients, the intervention did not influence vaccination acceptance. Conclusions The self-prediction intervention significantly increased vaccination acceptance among "high-barriers" patients, who typically have very low vaccination rates. This brief intervention could be a useful tool in increasing vaccine uptake among high-barriers patients. PMID:21875205

  12. Method for controlling an internal combustion engine

    SciTech Connect

    Krebs, S.; Achleitner, E.

    1993-07-13

    In a method for controlling an internal combustion engine having cylinders operating in cycles and an intake tube for intake air, which includes determining a fuel mass to be injected into each cylinder for each cycle as a function of operating parameters of the internal combustion engine by reading a basic fuel value out of a basic family of characteristics and correcting the basic fuel value as a function of a temperature of the intake air, and multiplying the basic fuel value by a correction factor FK = A/B, wherein the denominator B is a temperature value, the improvement is described which comprises: selecting the variables of the basic family of characteristics as a pressure in the intake tube and an rpm, and reading a correction temperature contained in the temperature value out of a family of temperature characteristics in dependence on a variable dependent on an air flow and of a heating temperature being determinative for heating up the intake air in the intake tube.

  13. Real time optimal guidance of low-thrust spacecraft: an application of nonlinear model predictive control.

    PubMed

    Arrieta-Camacho, Juan José; Biegler, Lorenz T

    2005-12-01

    Real time optimal guidance is considered for a class of low thrust spacecraft. In particular, nonlinear model predictive control (NMPC) is utilized for computing the optimal control actions required to transfer a spacecraft from a low Earth orbit to a mission orbit. The NMPC methodology presented is able to cope with unmodeled disturbances. The dynamics of the transfer are modeled using a set of modified equinoctial elements because they do not exhibit singularities for zero inclination and zero eccentricity. The idea behind NMPC is the repeated solution of optimal control problems; at each time step, a new control action is computed. The optimal control problem is solved using a direct method-fully discretizing the equations of motion. The large scale nonlinear program resulting from the discretization procedure is solved using IPOPT--a primal-dual interior point algorithm. Stability and robustness characteristics of the NMPC algorithm are reviewed. A numerical example is presented that encourages further development of the proposed methodology: the transfer from low-Earth orbit to a molniya orbit. PMID:16510409

  14. Hedonic Hunger Prospectively Predicts Onset and Maintenance of Loss of Control Eating among College Women

    PubMed Central

    Lowe, Michael R.; Arigo, Danielle; Butryn, Meghan L.; Gilbert, Jennifer R; Sarwer, David; Stice, Eric

    2016-01-01

    Objective The subjective feeling of loss of control (LOC) over eating is common among eating disordered individuals and has predicted weight gain in past research. Restrained eating and negative affect are risk factors for binge eating (which involves LOC), but intense feelings of pleasure derived from palatable foods might also predict the emergence or intensification of LOC eating. The Power of Food Scale (PFS; Lowe et al., 2009) assesses preoccupation with the pleasure derived from palatable food. Method The current sample (n = 294) comprised female college freshmen at risk for weight gain. LOC was assessed using an abbreviated version of the Eating Disorders Examination interview. LOC was assessed at baseline, 6 weeks and 6, 12 and 24 months follow-ups. Results Among those exhibiting LOC eating at baseline, (and controlling for baseline depression, restrained eating and body image dissatisfaction), those scoring higher on the PFS at baseline showed a smaller reduction in LOC frequency over time relative to those scoring lower. Using the same covariates, the PFS predicted the first emergence of LOC over two years among those showing no LOC at baseline. Conclusions These results suggest that powerful hedonic attraction to palatable foods may represent a risk factor for the maintenance of LOC in those initially experiencing it and the emergence of LOC eating in those who are not. An enhanced ability to identify individuals at increased risk of developing or maintaining LOC eating could be useful in prevention programs. PMID:26690638

  15. Development of hybrid method for the prediction of underwater propeller noise

    NASA Astrophysics Data System (ADS)

    Seol, Hanshin; Suh, Jung-Chun; Lee, Soogab

    2005-11-01

    Noise reduction and control is an important problem in the performance of underwater acoustic systems and in the habitability of the passenger ship for crew and passenger. Furthermore, sound generated by a propeller is critical in underwater detection and it is often related to the survivability of the vessel especially for military purpose. This paper presents a numerical study on the non-cavitating and blade sheet cavitation noises of the underwater propeller. A brief summary of numerical method with verification and results are presented. The noise is predicted using time-domain acoustic analogy. The flow field is analyzed with potential-based panel method, and then the time-dependent pressure and sheet cavity volume data are used as the input for Ffowcs Williams-Hawkings formulation to predict the far-field acoustics. Noise characteristics are presented according to noise sources and conditions. Through this study, the dominant noise source of the underwater propeller is analyzed, which will provide a basis for proper noise control strategies.

  16. Internal combustion engine and method for control

    SciTech Connect

    Brennan, Daniel G

    2013-05-21

    In one exemplary embodiment of the invention an internal combustion engine includes a piston disposed in a cylinder, a valve configured to control flow of air into the cylinder and an actuator coupled to the valve to control a position of the valve. The internal combustion engine also includes a controller coupled to the actuator, wherein the controller is configured to close the valve when an uncontrolled condition for the internal engine is determined.

  17. A Method of Analyzing Tests Using the Teacher's Predictions.

    ERIC Educational Resources Information Center

    Zehavi, Nurit; Bruckheimer, Maxim

    1981-01-01

    A method of evaluation that permits some penetration into the teaching/learning process that connects the student, teacher, and program is described. The conclusions reached by this method can be applied to improving teaching strategies, inservice training, curriculum development, and evaluation. (MP)

  18. Predicting Academic Library Circulations: A Forecasting Methods Competition.

    ERIC Educational Resources Information Center

    Brooks, Terrence A.; Forys, John W., Jr.

    Based on sample data representing five years of monthly circulation totals from 50 academic libraries in Illinois, Iowa, Michigan, Minnesota, Missouri, and Ohio, a study was conducted to determine the most efficient smoothing forecasting methods for academic libraries. Smoothing forecasting methods were chosen because they have been characterized…

  19. Verifying a computational method for predicting extreme ground motion

    USGS Publications Warehouse

    Harris, R.A.; Barall, M.; Andrews, D.J.; Duan, B.; Ma, S.; Dunham, E.M.; Gabriel, A.-A.; Kaneko, Y.; Kase, Y.; Aagaard, B.T.; Oglesby, D.D.; Ampuero, J.-P.; Hanks, T.C.; Abrahamson, N.

    2011-01-01

    In situations where seismological data is rare or nonexistent, computer simulations may be used to predict ground motions caused by future earthquakes. This is particularly practical in the case of extreme ground motions, where engineers of special buildings may need to design for an event that has not been historically observed but which may occur in the far-distant future. Once the simulations have been performed, however, they still need to be tested. The SCEC-USGS dynamic rupture code verification exercise provides a testing mechanism for simulations that involve spontaneous earthquake rupture. We have performed this examination for the specific computer code that was used to predict maximum possible ground motion near Yucca Mountain. Our SCEC-USGS group exercises have demonstrated that the specific computer code that was used for the Yucca Mountain simulations produces similar results to those produced by other computer codes when tackling the same science problem. We also found that the 3D ground motion simulations produced smaller ground motions than the 2D simulations.

  20. Improved Methods for Classification, Prediction and Design of Antimicrobial Peptides

    PubMed Central

    Wang, Guangshun

    2015-01-01

    Peptides with diverse amino acid sequences, structures and functions are essential players in biological systems. The construction of well-annotated databases not only facilitates effective information management, search and mining, but also lays the foundation for developing and testing new peptide algorithms and machines. The antimicrobial peptide database (APD) is an original construction in terms of both database design and peptide entries. The host defense antimicrobial peptides (AMPs) registered in the APD cover the five kingdoms (bacteria, protists, fungi, plants, and animals) or three domains of life (bacteria, archaea, and eukaryota). This comprehensive database (http://aps.unmc.edu/AP) provides useful information on peptide discovery timeline, nomenclature, classification, glossary, calculation tools, and statistics. The APD enables effective search, prediction, and design of peptides with antibacterial, antiviral, antifungal, antiparasitic, insecticidal, spermicidal, anticancer activities, chemotactic, immune modulation, or anti-oxidative properties. A universal classification scheme is proposed herein to unify innate immunity peptides from a variety of biological sources. As an improvement, the upgraded APD makes predictions based on the database-defined parameter space and provides a list of the sequences most similar to natural AMPs. In addition, the powerful pipeline design of the database search engine laid a solid basis for designing novel antimicrobials to combat resistant superbugs, viruses, fungi or parasites. This comprehensive AMP database is a useful tool for both research and education. PMID:25555720

  1. Improved methods for classification, prediction, and design of antimicrobial peptides.

    PubMed

    Wang, Guangshun

    2015-01-01

    Peptides with diverse amino acid sequences, structures, and functions are essential players in biological systems. The construction of well-annotated databases not only facilitates effective information management, search, and mining but also lays the foundation for developing and testing new peptide algorithms and machines. The antimicrobial peptide database (APD) is an original construction in terms of both database design and peptide entries. The host defense antimicrobial peptides (AMPs) registered in the APD cover the five kingdoms (bacteria, protists, fungi, plants, and animals) or three domains of life (bacteria, archaea, and eukaryota). This comprehensive database ( http://aps.unmc.edu/AP ) provides useful information on peptide discovery timeline, nomenclature, classification, glossary, calculation tools, and statistics. The APD enables effective search, prediction, and design of peptides with antibacterial, antiviral, antifungal, antiparasitic, insecticidal, spermicidal, anticancer activities, chemotactic, immune modulation, or antioxidative properties. A universal classification scheme is proposed herein to unify innate immunity peptides from a variety of biological sources. As an improvement, the upgraded APD makes predictions based on the database-defined parameter space and provides a list of the sequences most similar to natural AMPs. In addition, the powerful pipeline design of the database search engine laid a solid basis for designing novel antimicrobials to combat resistant superbugs, viruses, fungi, or parasites. This comprehensive AMP database is a useful tool for both research and education.

  2. Inhibitory Control Predicts Language Switching Performance in Trilingual Speech Production

    ERIC Educational Resources Information Center

    Linck, Jared A.; Schwieter, John W.; Sunderman, Gretchen

    2012-01-01

    This study investigated the role of domain-general inhibitory control in trilingual speech production. Taking an individual differences approach, we examined the relationship between performance on a non-linguistic measure of inhibitory control (the Simon task) and a multilingual language switching task for a group of fifty-six native English (L1)…

  3. Predicting preschool effortful control from toddler temperament and parenting behavior

    PubMed Central

    Cipriano, Elizabeth A.; Stifter, Cynthia A.

    2010-01-01

    This longitudinal study assessed whether maternal behavior and emotional tone moderated the relationship between toddler temperament and preschooler's effortful control. Maternal behavior and emotional tone were observed during a parent-child competing demands task when children were 2 years of age. Child temperament was also assessed at 2 years of age, and three temperament groups were formed: inhibited, exuberant, and low reactive. At 4.5 years of age, children's effortful control was measured from parent-report and observational measures. Results indicated that parental behavior and emotional tone appear to be especially influential on exuberant children's effortful control development. Exuberant children whose mothers used commands and prohibitive statements with a positive emotional tone were more likely to be rated higher on parent-reported effortful control 2.5 years later. When mothers conveyed redirections and reasoning-explanations in a neutral tone, their exuberant children showed poorer effortful control at 4.5 years. PMID:23814350

  4. A Pressure Control Method for Emulsion Pump Station Based on Elman Neural Network

    PubMed Central

    Tan, Chao; Qi, Nan; Yao, Xingang; Wang, Zhongbin; Si, Lei

    2015-01-01

    In order to realize pressure control of emulsion pump station which is key equipment of coal mine in the safety production, the control requirements were analyzed and a pressure control method based on Elman neural network was proposed. The key techniques such as system framework, pressure prediction model, pressure control model, and the flowchart of proposed approach were presented. Finally, a simulation example was carried out and comparison results indicated that the proposed approach was feasible and efficient and outperformed others. PMID:25861253

  5. Feedwater temperature control methods and systems

    DOEpatents

    Moen, Stephan Craig; Noonan, Jack Patrick; Saha, Pradip

    2014-04-22

    A system for controlling the power level of a natural circulation boiling water nuclear reactor (NCBWR) is disclosed. The system, in accordance with an example embodiment of the present invention, may include a controller configured to control a power output level of the NCBWR by controlling a heating subsystem to adjust a temperature of feedwater flowing into an annulus of the NCBWR. The heating subsystem may include a steam diversion line configured to receive steam generated by a core of the NCBWR and a steam bypass valve configured to receive commands from the controller to control a flow of the steam in the steam diversion line, wherein the steam received by the steam diversion line has not passed through a turbine. Additional embodiments of the invention may include a feedwater bypass valve for controlling an amount of flow of the feedwater through a heater bypass line to the annulus.

  6. A Nonlinear Reduced Order Method for Prediction of Acoustic Fatigue

    NASA Technical Reports Server (NTRS)

    Przekop, Adam; Rizzi, Stephen A.

    2006-01-01

    The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing geometrically nonlinear random vibrations. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

  7. A predictive and feedback control algorithm maintains a constant glucose concentration in fed-batch fermentations.

    PubMed

    Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R

    1991-04-01

    A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049

  8. A predictive and feedback control algorithm maintains a constant glucose concentration in fed-batch fermentations.

    PubMed Central

    Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R

    1991-01-01

    A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049

  9. An Improved Numerical Integration Method for Springback Predictions

    NASA Astrophysics Data System (ADS)

    Ibrahim, R.; Smith, L. M.; Golovashchenko, Sergey F.

    2011-08-01

    In this investigation, the focus is on the springback of steel sheets in V-die air bending. A full replication to a numerical integration algorithm presented rigorously in [1] to predict the springback in air bending was performed and confirmed successfully. Algorithm alteration and extensions were proposed here. The altered approach used in solving the moment equation numerically resulted in springback values much closer to the trend presented by the experimental data, Although investigation here extended to use a more realistic work-hardening model, the differences in the springback values obtained by both hardening models were almost negligible. The algorithm was extended to be applied on thin sheets down to 0.8 mm. Results show that this extension is possible as verified by FEA and other published experiments on TRIP steel sheets.

  10. Method for Predicting and Optimizing System Parameters for Electrospinning System

    NASA Technical Reports Server (NTRS)

    Wincheski, Russell A. (Inventor)

    2011-01-01

    An electrospinning system using a spinneret and a counter electrode is first operated for a fixed amount of time at known system and operational parameters to generate a fiber mat having a measured fiber mat width associated therewith. Next, acceleration of the fiberizable material at the spinneret is modeled to determine values of mass, drag, and surface tension associated with the fiberizable material at the spinneret output. The model is then applied in an inversion process to generate predicted values of an electric charge at the spinneret output and an electric field between the spinneret and electrode required to fabricate a selected fiber mat design. The electric charge and electric field are indicative of design values for system and operational parameters needed to fabricate the selected fiber mat design.

  11. Small Engine Technology (Set) Task 8 Aeroelastic Prediction Methods

    NASA Technical Reports Server (NTRS)

    Eick, Chris D.; Liu, Jong-Shang

    1998-01-01

    AlliedSignal Engines, in cooperation with NASA LeRC, completed an evaluation of recently developed aeroelastic computer codes using test cases from the AlliedSignal Engines fan blisk database. Test data for this task includes strain gage, light probe, performance, and steady-state pressure information obtained for conditions where synchronous or flutter vibratory conditions were found to occur. Aeroelastic codes evaluated include the quasi 3-D UNSFLO (developed at MIT and modified to include blade motion by AlliedSignal), the 2-D FREPS (developed by NASA LeRC), and the 3-D TURBO-AE (under development at NASA LeRC). Six test cases each where flutter and synchronous vibrations were found to occur were used for evaluation of UNSFLO and FREPS. In addition, one of the flutter cases was evaluated using TURBO-AE. The UNSFLO flutter evaluations were completed for 75 percent radial span and provided good agreement with the experimental test data. Synchronous evaluations were completed for UNSFLO but further enhancement needs to be added to the code before the unsteady pressures can be used to predict forced response vibratory stresses. The FREPS evaluations were hindered as the steady flow solver (SFLOW) was unable to converge to a solution for the transonic flow conditions in the fan blisk. This situation resulted in all FREPS test cases being attempted but no results were obtained during the present program. Currently, AlliedSignal is evaluating integrating FREPS with our existing steady flow solvers to bypass the SFLOW difficulties. ne TURBO-AE steady flow solution provided an excellent match with the AlliedSignal Engines calibrated DAWES 3-D viscous solver. Finally, the TURBO-AE unsteady analyses also matched experimental observations by predicting flutter for the single test case evaluated.

  12. The Interplay of Maternal Sensitivity and Gentle Control When Predicting Children's Subsequent Academic Functioning: Evidence of Mediation by Effortful Control

    ERIC Educational Resources Information Center

    Kopystynska, Olena; Spinrad, Tracy L.; Seay, Danielle M.; Eisenberg, Nancy

    2016-01-01

    The goal of this work was to examine the complex interrelation of mothers' early gentle control and sensitivity in predicting children's effortful control (EC) and academic functioning. Maternal gentle control, maternal sensitivity, and children's EC were measured when children were 18, 30, and 42 months of age (T1, T2, and T3, respectively), and…

  13. Intentions and Trait Self-Control Predict Fruit and Vegetable Consumption during the Transition to First-Year University

    ERIC Educational Resources Information Center

    Tomasone, Jennifer R.; Meikle, Natasha; Bray, Steven R.

    2015-01-01

    Objective: To examine the independent and combined effects of Theory of Planned Behavior (TPB) variables and trait self-control (TSC) in the prediction of fruit and vegetable consumption (FVC) among first-year university students. Participants: Seventy-six first-year undergraduate university students. Methods: In their first week of class…

  14. Perceived Sexual Control, Sex-Related Alcohol Expectancies and Behavior Predict Substance-Related Sexual Revictimization

    PubMed Central

    Walsh, Kate; Messman-Moore, Terri; Zerubavel, Noga; Chandley, Rachel B.; DeNardi, Kathleen A.; Walker, Dave P.

    2013-01-01

    Objectives Although numerous studies have documented linkages between childhood sexual abuse (CSA) and later sexual revictimization, mechanisms underlying revictimization, particularly assaults occurring in the context of substance use, are not well-understood. Consistent with Traumagenic Dynamics theory, the present study tested a path model positing that lowered perceptions of sexual control resulting from CSA may be associated with increased sex-related alcohol expectancies and heightened likelihood of risky sexual behavior, which in turn, may predict adult substance-related rape. Methods Participants were 546 female college students who completed anonymous surveys regarding CSA and adult rape, perceptions of sexual control, sex-related alcohol expectancies, and likelihood of engaging in risky sexual behavior. Results The data fit the hypothesized model well and all hypothesized path coefficients were significant and in the expected directions. As expected, sex-related alcohol expectancies and likelihood of risky sexual behavior only predicted substance-related rape, not forcible rape. Conclusions Findings suggested that low perceived sexual control stemming from CSA is associated with increased sex-related alcohol expectancies and a higher likelihood of engaging in sexual behavior in the context of alcohol use. In turn these proximal risk factors heighten vulnerability to substance-related rape. Programs which aim to reduce risk for substance-related rape could be improved by addressing expectancies and motivations for risky sexual behavior in the context of substance use. Implications and future directions are discussed. PMID:23312991

  15. System and method for controlling microgrid

    DOEpatents

    Bose, Sumit; Achilles, Alfredo Sebastian; Liu, Yan; Ahmed, Emad Ezzat; Garces, Luis Jose

    2011-07-19

    A system for controlling a microgrid includes microgrid assets and a tieline for coupling the microgrid to a bulk grid; and a tieline controller coupled to the tieline. At least one of the microgrid assets comprises a different type of asset than another one of the microgrid assets. The tieline controller is configured for providing tieline control signals to adjust active and reactive power in respective microgrid assets in response to commands from the bulk grid operating entity, microgrid system conditions, bulk grid conditions, or combinations thereof.

  16. Predicting the operations alert levels for dengue surveillance and control.

    PubMed

    Sampath, Kameshwaran; Dayama, Pankaj

    2014-01-01

    Operations alert level is a discrete measure that quantifies the severity of epidemic outbreak with respect to operational measures. The alert levels are ordered based on the amount of response operations required. In this paper, we develop multi-class classification models based on ordinal multinomial logistic regression for predicting the alert levels for dengue at twenty weeks in advance. The regression uses the dynamic lag non-linear models to account for the non-linearity of the dengue incidence, along with its lagged values. The performance of the models is tested for the dengue case count data of Singapore.

  17. Performance prediction of electrohydrodynamic thrusters by the perturbation method

    NASA Astrophysics Data System (ADS)

    Shibata, H.; Watanabe, Y.; Suzuki, K.

    2016-05-01

    In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

  18. Reduced Order Methods for Prediction of Thermal-Acoustic Fatigue

    NASA Technical Reports Server (NTRS)

    Przekop, A.; Rizzi, S. A.

    2004-01-01

    The goal of this investigation is to assess the quality of high-cycle-fatigue life estimation via a reduced order method, for structures undergoing random nonlinear vibrations in a presence of thermal loading. Modal reduction is performed with several different suites of basis functions. After numerically solving the reduced order system equations of motion, the physical displacement time history is obtained by an inverse transformation and stresses are recovered. Stress ranges obtained through the rainflow counting procedure are used in a linear damage accumulation method to yield fatigue estimates. Fatigue life estimates obtained using various basis functions in the reduced order method are compared with those obtained from numerical simulation in physical degrees-of-freedom.

  19. Interior noise control prediction study for high-speed propeller-driven aircraft

    NASA Technical Reports Server (NTRS)

    Rennison, D. C.; Wilby, J. F.; Marsh, A. H.; Wilby, E. G.

    1979-01-01

    An analytical model was developed to predict the noise levels inside propeller-driven aircraft during cruise at M = 0.8. The model was applied to three study aircraft with fuselages of different size (wide body, narrow body and small diameter) in order to determine the noise reductions required to achieve the goal of an A-weighted sound level which does not exceed 80 dB. The model was then used to determine noise control methods which could achieve the required noise reductions. Two classes of noise control treatments were investigated: add-on treatments which can be added to existing structures, and advanced concepts which would require changes to the fuselage primary structure. Only one treatment, a double wall with limp panel, provided the required noise reductions. Weight penalties associated with the treatment were estimated for the three study aircraft.

  20. Simulation of complex glazing products; from optical data measurements to model based predictive controls

    SciTech Connect

    Kohler, Christian

    2012-08-01

    Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.

  1. Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

    NASA Technical Reports Server (NTRS)

    Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

    1992-01-01

    Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

  2. Computational methods to obtain time optimal jet engine control

    NASA Technical Reports Server (NTRS)

    Basso, R. J.; Leake, R. J.

    1976-01-01

    Dynamic Programming and the Fletcher-Reeves Conjugate Gradient Method are two existing methods which can be applied to solve a general class of unconstrained fixed time, free right end optimal control problems. New techniques are developed to adapt these methods to solve a time optimal control problem with state variable and control constraints. Specifically, they are applied to compute a time optimal control for a jet engine control problem.

  3. Predicting the effects of unmodeled dynamics on an aircraft flight control system design using eigenspace assignment

    NASA Technical Reports Server (NTRS)

    Johnson, Eric N.; Davidson, John B.; Murphy, Patrick C.

    1994-01-01

    When using eigenspace assignment to design an aircraft flight control system, one must first develop a model of the plant. Certain questions arise when creating this model as to which dynamics of the plant need to be included in the model and which dynamics can be left out or approximated. The answers to these questions are important because a poor choice can lead to closed-loop dynamics that are unpredicted by the design model. To alleviate this problem, a method has been developed for predicting the effect of not including certain dynamics in the design model on the final closed-loop eigenspace. This development provides insight as to which characteristics of unmodeled dynamics will ultimately affect the closed-loop rigid-body dynamics. What results from this insight is a guide for eigenstructure control law designers to aid them in determining which dynamics need or do not need to be included and a new way to include these dynamics in the flight control system design model to achieve a required accuracy in the closed-loop rigid-body dynamics. The method is illustrated for a lateral-directional flight control system design using eigenspace assignment for the NASA High Alpha Research Vehicle (HARV).

  4. Approximate methods for predicting interlaminar shear stiffness of laminated and sandwich beams

    NASA Astrophysics Data System (ADS)

    Roy, Ajit K.; Verchery, Georges

    1993-01-01

    Several approximate closed form expressions exist in the literature for predicting the effective interlaminar shear stiffness (G13) of laminated composite beams. The accuracy of these approximate methods depends on the number of layers present in the laminated beam, the relative layer thickness and layer stacking sequence, and the beam length to depth ratio. The objective of this work is to evaluate approximate methods for predicting G13 by comparing its predictions with that of an accurate method, and then find the range where the simple closed form expressions for predicting G13 can be applicable. A comparative study indicates that all the approximate methods included here give good prediction of G13 when the laminate is made of a large number of repeated sublaminates. Further, the parabolic shear stress distribution function yields a reasonably accurate prediction of G13 even for a relatively small number of layers in the laminate. A similar result is also presented for sandwich beams.

  5. Transition prediction and control in subsonic flow over a hump

    NASA Technical Reports Server (NTRS)

    Masad, Jamal A.; Iyer, Venkit

    1993-01-01

    The influence of a surface roughness element in the form of a two-dimensional hump on the transition location in a two-dimensional subsonic flow with a free-stream Mach number up to 0.8 is evaluated. Linear stability theory, coupled with the N-factor transition criterion, is used in the evaluation. The mean flow over the hump is calculated by solving the interacting boundary-layer equations; the viscous-inviscid coupling is taken into consideration, and the flow is solved within the separation bubble. The effects of hump height, length, location, and shape; unit Reynolds number; free-stream Mach number, continuous suction level; location of a suction strip; continuous cooling level; and location of a heating strip on the transition location are evaluated. The N-factor criterion predictions agree well with the experimental correlation of Fage; in addition, the N-factor criterion is more general and powerful than experimental correlations. The theoretically predicted effects of the hump's parameters and flow conditions on transition location are consistent and in agreement with both wind-tunnel and flight observations.

  6. A Consensus Method for the Prediction of ‘Aggregation-Prone’ Peptides in Globular Proteins

    PubMed Central

    Tsolis, Antonios C.; Papandreou, Nikos C.; Iconomidou, Vassiliki A.; Hamodrakas, Stavros J.

    2013-01-01

    The purpose of this work was to construct a consensus prediction algorithm of ‘aggregation-prone’ peptides in globular proteins, combining existing tools. This allows comparison of the different algorithms and the production of more objective and accurate results. Eleven (11) individual methods are combined and produce AMYLPRED2, a publicly, freely available web tool to academic users (http://biophysics.biol.uoa.gr/AMYLPRED2), for the consensus prediction of amyloidogenic determinants/‘aggregation-prone’ peptides in proteins, from sequence alone. The performance of AMYLPRED2 indicates that it functions better than individual aggregation-prediction algorithms, as perhaps expected. AMYLPRED2 is a useful tool for identifying amyloid-forming regions in proteins that are associated with several conformational diseases, called amyloidoses, such as Altzheimer's, Parkinson's, prion diseases and type II diabetes. It may also be useful for understanding the properties of protein folding and misfolding and for helping to the control of protein aggregation/solubility in biotechnology (recombinant proteins forming bacterial inclusion bodies) and biotherapeutics (monoclonal antibodies and biopharmaceutical proteins). PMID:23326595

  7. A novel conformational B-cell epitope prediction method based on mimotope and patch analysis.

    PubMed

    Sun, Pingping; Qi, Jialiang; Zhao, Yizhu; Huang, Yanxin; Yang, Guifu; Ma, Zhiqiang; Li, Yuxin

    2016-04-01

    A B-cell epitope is a group of residues on the surface of an antigen that stimulates humoral immune responses. Identifying B-cell epitopes is important for effective vaccine design. Predicting epitopes by experimental methods is expensive in terms of time, cost and effort; therefore, computational methods that have a low cost and high speed are widely used to predict B-cell epitopes. Recently, epitope prediction based on random peptide library screening has been viewed as a promising method. Some novel software and web-based servers have been proposed that have succeeded in some test cases. Herein, we propose a novel epitope prediction method based on amino acid pairs and patch analysis. The method first divides antigen surfaces into overlapping patches based on both radius (R) and number (N), then predict epitopes based on Amino Acid Pairs (AAPs) from mimotopes and the surface patch. The proposed method yields a mean sensitivity of 0.53, specificity of 0.77, ACC of 0.75 and F-measure of 0.45 for 39 test cases. Compared with mimotope-based methods, patch-based methods and two other prediction methods, the sensitivity of the new method offers a certain improvement. Our findings demonstrate that this proposed method was successful for patch and AAPs analysis and allowed for conformational B-cell epitope prediction. PMID:26804644

  8. EVALUATION OF TWO METHODS FOR PREDICTION OF BIOACCUMULATION FACTORS

    EPA Science Inventory

    Two methods for deriving bioaccumulation factors (BAFs) used by the U.S. Environmental Protection Agency (EPA) in development of water quality criteria were evaluated using polychlorinated biphenyls (PCB) data from the Hudson River and Green Bay ecosystems. Greater than 90% of th...

  9. Wing flutter boundary prediction using unsteady Euler aerodynamic method

    NASA Technical Reports Server (NTRS)

    Lee-Rausch, Elizabeth M.; Batina, John T.

    1993-01-01

    Modifications to an existing 3D implicit upwind Euler/Navier-Stokes code for the aeroelastic analysis of wings are described. These modifications include the incorporation of a deforming mesh algorithm and the addition of the structural equations of motion for their simultaneous time-integration with the governing flow equations. The paper gives a brief description of these modifications and presents unsteady calculations which check the modifications to the code. Euler flutter results for an isolated 45 deg swept-back wing are compared with experimental data for seven freestream Mach numbers which define the flutter boundary over a range of Mach number from 0.499 to 1.14. These comparisons show good agreement in flutter characteristics for freestream Mach numbers below unity. For freestream Mach numbers above unity, the computed aeroelastic results predict a premature rise in the flutter boundary as compared with the experimental boundary. Steady and unsteady contours of surface Mach number and pressure are included to illustrate the basic flow characteristics of the time-marching flutter calculations and to aid in identifying possible causes for the premature rise in the computational flutter boundary.

  10. Bridge Frost Prediction by Heat and Mass Transfer Methods

    NASA Astrophysics Data System (ADS)

    Greenfield, Tina M.; Takle, Eugene S.

    2006-03-01

    Frost on roadways and bridges can present hazardous conditions to motorists, particularly when it occurs in patches or on bridges when adjacent roadways are clear of frost. To minimize materials costs, vehicle corrosion, and negative environmental impacts, frost-suppression chemicals should be applied only when, where, and in the appropriate amounts needed to maintain roadways in a safe condition for motorists. Accurate forecasts of frost onset times, frost intensity, and frost disappearance (e.g., melting or sublimation) are needed to help roadway maintenance personnel decide when, where, and how much frost-suppression chemical to use. A finite-difference algorithm (BridgeT) has been developed that simulates vertical heat transfer in a bridge based on evolving meteorological conditions at its top and bottom as supplied by a weather forecast model. BridgeT simulates bridge temperatures at numerous points within the bridge (including its upper and lower surface) at each time step of the weather forecast model and calculates volume per unit area (i.e., depth) of deposited, melted, or sublimed frost. This model produces forecasts of bridge surface temperature, frost depth, and bridge condition (i.e., dry, wet, icy/snowy). Bridge frost predictions and bridge surface temperature are compared with observed and measured values to assess BridgeT's skill in forecasting bridge frost and associated conditions.

  11. Wing flutter boundary prediction using an unsteady Euler aerodynamic method

    NASA Technical Reports Server (NTRS)

    Lee-Rausch, Elizabeth M.; Batina, John T.

    1993-01-01

    Modifications to an existing three-dimensional, implicit, upwind Euler/Navier-Stokes code (CFL3D Version 2.1) for the aeroelastic analysis of wings are described. These modifications, which were previously added to CFL3D Version 1.0, include the incorporation of a deforming mesh algorithm and the addition of the structural equations of motion for their simultaneous time-integration with the government flow equations. The paper gives a brief description of these modifications and presents unsteady calculations which check the modifications to the code. Euler flutter results for an isolated 45 degree swept-back wing are compared with experimental data for seven freestream Mach numbers which define the flutter boundary over a range of Mach number from 0.499 to 1.14. These comparisons show good agreement in flutter characteristics for freestream Mach numbers below unity. For freestream Mach numbers above unity, the computed aeroelastic results predict a premature rise in the flutter boundary as compared with the experimental boundary. Steady and unsteady contours of surface Mach number and pressure are included to illustrate the basic flow characteristics of the time-marching flutter calculations and to aid in identifying possible causes for the premature rise in the computational flutter boundary.

  12. Investigation of energy management strategies for photovoltaic systems - A predictive control algorithm

    NASA Technical Reports Server (NTRS)

    Cull, R. C.; Eltimsahy, A. H.

    1983-01-01

    The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.

  13. A Novel, Nondestructive, Dried Blood Spot-Based Hematocrit Prediction Method Using Noncontact Diffuse Reflectance Spectroscopy.

    PubMed

    Capiau, Sara; Wilk, Leah S; Aalders, Maurice C G; Stove, Christophe P

    2016-06-21

    Dried blood spot (DBS) sampling is recognized as a valuable alternative sampling strategy both in research and in clinical routine. Although many advantages are associated with DBS sampling, its more widespread use is hampered by several issues, of which the hematocrit effect on DBS-based quantitation remains undoubtedly the most widely discussed one. Previously, we developed a method to derive the approximate hematocrit from a nonvolumetrically applied DBS based on its potassium content. Although this method yielded good results and was straightforward to perform, it was also destructive and required sample preparation. Therefore, we now developed a nondestructive method which allows to predict the hematocrit of a DBS based on its hemoglobin content, measured via noncontact diffuse reflectance spectroscopy. The developed method was thoroughly validated. A linear calibration curve was established after log/log transformation. The bias, intraday and interday imprecision of quality controls at three hematocrit levels and at the lower and upper limit of quantitation (0.20 and 0.67, respectively) were less than 11%. In addition, the influence of storage and the volume spotted was evaluated, as well as DBS homogeneity. Application of the method to venous DBSs prepared from whole blood patient samples (n = 233) revealed a good correlation between the actual and the predicted hematocrit. Limits of agreement obtained after Bland and Altman analysis were -0.076 and +0.018. Incurred sample reanalysis demonstrated good method reproducibility. In conclusion, mere scanning of a DBS suffices to derive its approximate hematocrit, one of the most important variables in DBS analysis.

  14. Accuracy assessment of the ERP prediction method based on analysis of 100-year ERP series

    NASA Astrophysics Data System (ADS)

    Malkin, Z.; Tissen, V. M.

    2012-12-01

    A new method has been developed at the Siberian Research Institute of Metrology (SNIIM) for highly accurate prediction of UT1 and Pole motion (PM). In this study, a detailed comparison was made of real-time UT1 predictions made in 2006-2011 and PMpredictions made in 2009-2011making use of the SNIIM method with simultaneous predictions computed at the International Earth Rotation and Reference Systems Service (IERS), USNO. Obtained results have shown that proposed method provides better accuracy at different prediction lengths.

  15. Comparison of measured efficiencies of nine turbine designs with efficiencies predicted by two empirical methods

    NASA Technical Reports Server (NTRS)

    English, Robert E; Cavicchi, Richard H

    1951-01-01

    Empirical methods of Ainley and Kochendorfer and Nettles were used to predict performances of nine turbine designs. Measured and predicted performances were compared. Appropriate values of blade-loss parameter were determined for the method of Kochendorfer and Nettles. The measured design-point efficiencies were lower than predicted by as much as 0.09 (Ainley and 0.07 (Kochendorfer and Nettles). For the method of Kochendorfer and Nettles, appropriate values of blade-loss parameter ranged from 0.63 to 0.87 and the off-design performance was accurately predicted.

  16. New method for predicting melting points of polynitro arene and polynitro heteroarene compounds.

    PubMed

    Keshavarz, Mohammad Hossein

    2009-11-15

    This work introduces a new method for prediction of melting points of nitroaromatic compounds, including polynitro arenes and polynitro heteroarenes, through their molecular structures. The new model extends earlier work, which was used for carbocyclic nitroaromatic compounds, to estimate melting points of heterocyclic aromatic compounds. Some specific functional groups and structural parameters can be used to improve the predicted values on the basis of the number of carbon, hydrogen and nitrogen atoms. The predicted results show that this method gives reliable prediction of melting points with respect to previous work and well-developed group additivity methods for different nitroaromatic explosives with complex molecular structures.

  17. Cognitive task load in a naval ship control centre: from identification to prediction.

    PubMed

    Grootjen, M; Neerincx, M A; Veltman, J A

    Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support. PMID:17008255

  18. Meditation-induced states predict attentional control over time.

    PubMed

    Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Baas, Matthijs; Hommel, Bernhard

    2015-12-01

    Meditation is becoming an increasingly popular topic for scientific research and various effects of extensive meditation practice (ranging from weeks to several years) on cognitive processes have been demonstrated. Here we show that extensive practice may not be necessary to achieve those effects. Healthy adult non-meditators underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing an Attentional Blink (AB) task - which assesses the efficiency of allocating attention over time. The size of the AB was considerably smaller after OMM than after FAM, which suggests that engaging in meditation immediately creates a cognitive-control state that has a specific impact on how people allocate their attention over time.

  19. A recursive method for updating apple firmness prediction models based on spectral scattering images

    NASA Astrophysics Data System (ADS)

    Peng, Yankun; Lu, Renfu

    2007-09-01

    Multispectral scattering is effective for nondestructive prediction of fruit firmness. However, the established prediction models for multispectral scattering are variety specific and may not perform appropriately for fruit harvested from different orchards or at different times. In this research, a recursive least squares method was proposed to update the existing prediction model by adding samples from a new population to assure good performance of the model for predicting fruit from the new population. Multispectral scattering images acquired by a multispectral imaging system from Golden Delicious apples that were harvested at the same time but had different postharvest storage time periods were used to develop the updating method. Radial scattering profiles were described by the modified Lorentzian distribution (MLD) function with four profile parameters for eight wavelengths. Multi-linear regression was performed on MLD parameters to establish prediction models for fruit firmness for each group. The prediction model established in the first group was then updated by using selected samples from the second group, and four different sampling methods were compared and validated with the rest apples. The prediction model corrected by the model-updating method gave good firmness predictions with the correlation coefficient (r) of 0.86 and the standard error of prediction (SEP) of 6.11 N. This model updating method is promising for implementing the spectral scattering technique for real-time prediction of apple fruit firmness.

  20. Autonomy and control: augmenting the validity of the theory of planned behaviour in predicting exercise.

    PubMed

    Brickell, Tracey A; Chatzisarantis, Nikos L D; Pretty, Grace M

    2006-01-01

    This study examined the utility of the theory of planned behaviour (TPB) along with additional constructs in predicting exercise, and explored the motivational antecedents of exercise intentions. Participants included 162 Canadian University College students (61% females). Measures of TPB, autonomous and controlling intention, perceived autonomy support and core autonomous intention were completed during phase 1 of data collection. Two and three weeks later behaviour was assessed. Hierarchical regression analyses revealed that: (a) attitude and perceived behavioural control significantly predicted TPB intention and core autonomous intention; (b) subjective norm predicted controlling intention; and (c) perceived autonomy support predicted autonomous and core autonomous intention. TPB intention significantly predicted behaviour. TPB is a fairly useful model for predicting behaviour and important information can be gained when other measures of intention are explored.

  1. Happiness as a motivator: positive affect predicts primary control striving for career and educational goals.

    PubMed

    Haase, Claudia M; Poulin, Michael J; Heckhausen, Jutta

    2012-08-01

    What motivates individuals to invest time and effort and overcome obstacles (i.e., strive for primary control) when pursuing important goals? We propose that positive affect predicts primary control striving for career and educational goals, and we explore the mediating role of control beliefs. In Study 1, positive affect predicted primary control striving for career goals in a two-wave longitudinal study of a U.S. sample. In Study 2, positive affect predicted primary control striving for career and educational goals and objective career outcomes in a six-wave longitudinal study of a German sample. Control beliefs partially mediated the longitudinal associations with primary control striving. Thus, when individuals experience positive affect, they become more motivated to invest time and effort, and overcome obstacles when pursuing their goals, in part because they believe they have more control over attaining their goals. PMID:22569224

  2. Prediction-driven coordination of distributed MPC controllers for linear unconstrained dynamic systems

    NASA Astrophysics Data System (ADS)

    Marcos, Natalia I.; Fraser Forbes, J.; Guay, Martin

    2014-08-01

    In this paper, a coordinated-distributed model predictive control (CDMPC) scheme is proposed for discrete-time, linear, unconstrained dynamic systems. The proposed control scheme incorporates a coordinator that communicates with local CDMPC controllers. With the assistance of the coordinator, the local CDMPC controllers adjust their calculated control actions iteratively to achieve the optimal plant-wide operation. A 'prediction-driven' algorithm is used to coordinate the local CDMPC controllers. Convergence of the prediction-driven algorithm is shown along with a stability analysis of the closed-loop system under coordinated-distributed control. A simulation example is used to illustrate the effectiveness of the proposed coordinated-distributed control scheme.

  3. A method for balloon trajectory control

    NASA Astrophysics Data System (ADS)

    Aaron, K. M.; Heun, M. K.; Nock, K. T.

    A balloon trajectory control system is discussed that is under development for use on NASA's Ultra Long Duration Balloon Project. The trajectory control system exploits the natural wind field variation with altitude to generate passive lateral control forces on a balloon using a tether-deployed aerodynamic surface below the balloon. A lifting device, such as a wing on end, is suspended on a tether well beneath the balloon to take advantage of this variation in wind velocity with altitude. The wing generates a horizontal lift force that can be directed over a wide range of angles. This force, transmitted to the balloon by a tether, alters the balloon's path providing a bias velocity of a few meters per second to the balloon drift rate. The trajectory control system enables the balloon to avoid hazards, reach targets, steer around avoidance countries and select convenient landing zones. No longer will balloons be totally at the mercy of the winds. Tests in April 1999 of a dynamically-scaled model of the trajectory control system were carried out by Global Aerospace Corporation in ground level winds up to 15 m/s. The size of the scale model was designed to simulate the behavior of the full scale trajectory control system operating at 20 km altitude. The model confirmed many aspects of trajectory control system performance and the results will be incorporated into future development.

  4. Prediction of skin sensitizers using alternative methods to animal experimentation.

    PubMed

    Johansson, Henrik; Lindstedt, Malin

    2014-07-01

    Regulatory frameworks within the European Union demand that chemical substances are investigated for their ability to induce sensitization, an adverse health effect caused by the human immune system in response to chemical exposure. A recent ban on the use of animal tests within the cosmetics industry has led to an urgent need for alternative animal-free test methods that can be used for assessment of chemical sensitizers. To date, no such alternative assay has yet completed formal validation. However, a number of assays are in development and the understanding of the biological mechanisms of chemical sensitization has greatly increased during the last decade. In this MiniReview, we aim to summarize and give our view on the recent progress of method development for alternative assessment of chemical sensitizers. We propose that integrated testing strategies should comprise complementary assays, providing measurements of a wide range of mechanistic events, to perform well-educated risk assessments based on weight of evidence. PMID:24548737

  5. Prediction of skin sensitizers using alternative methods to animal experimentation.

    PubMed

    Johansson, Henrik; Lindstedt, Malin

    2014-07-01

    Regulatory frameworks within the European Union demand that chemical substances are investigated for their ability to induce sensitization, an adverse health effect caused by the human immune system in response to chemical exposure. A recent ban on the use of animal tests within the cosmetics industry has led to an urgent need for alternative animal-free test methods that can be used for assessment of chemical sensitizers. To date, no such alternative assay has yet completed formal validation. However, a number of assays are in development and the understanding of the biological mechanisms of chemical sensitization has greatly increased during the last decade. In this MiniReview, we aim to summarize and give our view on the recent progress of method development for alternative assessment of chemical sensitizers. We propose that integrated testing strategies should comprise complementary assays, providing measurements of a wide range of mechanistic events, to perform well-educated risk assessments based on weight of evidence.

  6. Utilization of vortex methods for parachute aerodynamic predictions

    SciTech Connect

    Strickland, J.H.; Meyer, J.

    1986-01-01

    The purpose of this paper is to provide a brief review of vortex methods with application to parachute aerodynamics. A somewhat generalized discussion of analysis techniques which are applicable to development of both two- and three-dimensional numerical solutions will be presented. A brief review of results from several bluff body simulations will be presented along with very recent results from work being conducted by Sandia National Laboratories in this area. 32 refs.

  7. Method of Testing and Predicting Failures of Electronic Mechanical Systems

    NASA Technical Reports Server (NTRS)

    Iverson, David L.; Patterson-Hine, Frances A.

    1996-01-01

    A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

  8. Cognitive Control Predicts Academic Achievement in Kindergarten Children

    ERIC Educational Resources Information Center

    Coldren, Jeffrey T.

    2013-01-01

    Children's ability to shift behavior in response to changing environmental demands is critical for successful intellectual functioning. While the processes underlying the development of cognitive control have been thoroughly investigated, its functioning in an ecologically relevant setting such as school is less well understood. Given the alarming…

  9. Predicting Preschool Effortful Control from Toddler Temperament and Parenting Behavior

    ERIC Educational Resources Information Center

    Cipriano, Elizabeth A.; Stifter, Cynthia A.

    2010-01-01

    This longitudinal study assessed whether maternal behavior and emotional tone moderated the relationship between toddler temperament and preschooler's effortful control. Maternal behavior and emotional tone were observed during a parent-child competing demands task when children were 2 years of age. Child temperament was also assessed at 2 years…

  10. Adaptive and predictive control of a simulated robot arm.

    PubMed

    Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo

    2013-06-01

    In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs).

  11. BOILING SLURRY REACTOR AND METHOD FO CONTROL

    DOEpatents

    Petrick, M.; Marchaterre, J.F.

    1963-05-01

    The control of a boiling slurry nuclear reactor is described. The reactor consists of a vertical tube having an enlarged portion, a steam drum at the top of the vertical tube, and at least one downcomer connecting the steam drum and the bottom of the vertical tube, the reactor being filled with a slurry of fissionabie material in water of such concentration that the enlarged portion of the vertical tube contains a critical mass. The slurry boils in the vertical tube and circulates upwardly therein and downwardly in the downcomer. To control the reactor by controlling the circulation of the slurry, a gas is introduced into the downcomer. (AEC)

  12. Modelling and control issues of dynamically substructured systems: adaptive forward prediction taken as an example

    PubMed Central

    Tu, Jia-Ying; Hsiao, Wei-De; Chen, Chih-Ying

    2014-01-01

    Testing techniques of dynamically substructured systems dissects an entire engineering system into parts. Components can be tested via numerical simulation or physical experiments and run synchronously. Additional actuator systems, which interface numerical and physical parts, are required within the physical substructure. A high-quality controller, which is designed to cancel unwanted dynamics introduced by the actuators, is important in order to synchronize the numerical and physical outputs and ensure successful tests. An adaptive forward prediction (AFP) algorithm based on delay compensation concepts has been proposed to deal with substructuring control issues. Although the settling performance and numerical conditions of the AFP controller are improved using new direct-compensation and singular value decomposition methods, the experimental results show that a linear dynamics-based controller still outperforms the AFP controller. Based on experimental observations, the least-squares fitting technique, effectiveness of the AFP compensation and differences between delay and ordinary differential equations are discussed herein, in order to reflect the fundamental issues of actuator modelling in relevant literature and, more specifically, to show that the actuator and numerical substructure are heterogeneous dynamic components and should not be collectively modelled as a homogeneous delay differential equation. PMID:25104902

  13. Controllability modulates the neural response to predictable but not unpredictable threat in humans.

    PubMed

    Wood, Kimberly H; Wheelock, Muriah D; Shumen, Joshua R; Bowen, Kenton H; Ver Hoef, Lawrence W; Knight, David C

    2015-10-01

    Stress resilience is mediated, in part, by our ability to predict and control threats within our environment. Therefore, determining the neural mechanisms that regulate the emotional response to predictable and controllable threats may provide important new insight into the processes that mediate resilience to emotional dysfunction and guide the future development of interventions for anxiety disorders. To better understand the effect of predictability and controllability on threat-related brain activity in humans, two groups of healthy volunteers participated in a yoked Pavlovian fear conditioning study during functional magnetic resonance imaging (fMRI). Threat predictability was manipulated by presenting an aversive unconditioned stimulus (UCS) that was either preceded by a conditioned stimulus (i.e., predictable) or by presenting the UCS alone (i.e., unpredictable). Similar to animal model research that has employed yoked fear conditioning procedures, one group (controllable condition; CC), but not the other group (uncontrollable condition; UC) was able to terminate the UCS. The fMRI signal response within the dorsolateral prefrontal cortex (PFC), dorsomedial PFC, ventromedial PFC, and posterior cingulate was diminished during predictable compared to unpredictable threat (i.e., UCS). In addition, threat-related activity within the ventromedial PFC and bilateral hippocampus was diminished only to threats that were both predictable and controllable. These findings provide insight into how threat predictability and controllability affects the activity of brain regions (i.e., ventromedial PFC and hippocampus) involved in emotion regulation, and may have important implications for better understanding neural processes that mediate emotional resilience to stress.

  14. Low Vitamin D Levels Do Not Predict Hyperglycemia in Elderly Endurance Athletes (but in Controls)

    PubMed Central

    Nistler, Sonja; Batmyagmar, Delgerdalai; Ponocny-Seliger, Elisabeth; Perkmann, Thomas; Scherzer, Thomas M.; Kundi, Michael; Endler, Georg; Ratzinger, Franz; Pilger, Alexander; Wagner, Oswald F.; Winker, Robert

    2016-01-01

    Background and Aim Recent studies revealed a link between hypovitaminosis D3 and the risk for hyperglycemia. Further mechanistic and interventional investigations suggested a common reason for both conditions rather than a causal relationship. Exposure to sunlight is the most relevant source of vitamin D3 (25(OH)D), whereas adipose tissue is able to store relevant amounts of the lipophilic vitamin. Since running/bicycling leads to increased out-door time and alters physiological response mechanisms, it can be hypothesized that the correlation between hypovitaminosis D3 and hyperglycemia might be disturbed in outdoor athletes. Methods 47 elderly marathoners/bicyclists and 47 age/sex matched controls were studied in a longitudinal setting at baseline and after three years. HbA1c as a surrogate for (pre-)diabetic states was quantified via HPLC, 25(OH)D levels were measured by means of chemiluminescent assays. Physical performance was assessed by ergometry. Results When adjusted for seasonal variations, 25(OH)D was significantly higher in athletes than in controls. 25(OH)D levels inversely correlated with triglycerides in both groups, whereas only in controls an association between high BMI or low physical performance with hypovitaminosis D3 had been found. Likewise, the presence of hypovitaminosis D3 at baseline successfully predicted hyperglycemia at the follow up examinations within the control group (AUC = 0.85, 95% CI [0.74, 0.96], p < .001, statistically independent from BMI), but not in athletes. Conclusion Our data suggest that mechanisms of HbA1c elevation might differ between athletes and controls. Thus, intense physical activity must be taken into account as a potential pre-analytic confounder when it is aimed to predict metabolic risk by vitamin D3 levels. PMID:27304888

  15. An optimal control method for real-time irrigation scheduling

    SciTech Connect

    Protopapas, A.L.; Georgakakos, A.P. )

    1990-04-01

    In this paper a systematic methodology for making real-time irrigation decisions is presented. A physically based representation of the dynamics of the soil-crop-atmosphere system is used. The variables characterizing the crop and soil status are concurrently simulated with an integrated state space model. Soil moisture and salinity conditions, which synergistically control the plant water uptake, are obtained by using lumped parameter mass balance models for the root zone. Crop yield is predicted by explicitly modeling the plant growth processes, such as assimilation, respiration, and transpiration, which are driven by the climatic inputs. The control model is an analytical optimization method for multistage multidimensional sequential decision-making problems. It is suitable for systems with nonlinear dynamics and objective functions. The method is based on local iterative approximations of the nonlinear problem with a linear quadratic problem. This approach is evaluated in a series of case studies, where optimal irrigation schedules are obtained on an hourly basis over the growing season.

  16. Attributions of control and seropositivity among Latinos: examining the predictive utility of the locus of control construct.

    PubMed

    Burns, S M; Maniss, S; Young, L R L; Gaubatz, M

    2005-02-01

    This investigation explored the utility of the health locus of control construct in predicting the mental health quality of life (MHQOL) ratings of 72 Latinos living with HIV/AIDS. After controlling for patient CD4 count, viral load, time since diagnosis, Physical Health Quality of Life and acculturative status, Powerful Others Locus of Control beliefs accounted for a significant increment of the variance in Mental Health Quality of Life. In a similar model, Internal Locus of Control failed to predict MHQOL. Discussion and implications highlight how cultural considerations may broaden investigations of health among diverse, minority populations.

  17. A data-driven epidemiological prediction method for dengue outbreaks using local and remote sensing data

    PubMed Central

    2012-01-01

    Background Dengue is the most common arboviral disease of humans, with more than one third of the world’s population at risk. Accurate prediction of dengue outbreaks may lead to public health interventions that mitigate the effect of the disease. Predicting infectious disease outbreaks is a challenging task; truly predictive methods are still in their infancy. Methods We describe a novel prediction method utilizing Fuzzy Association Rule Mining to extract relationships between clinical, meteorological, climatic, and socio-political data from Peru. These relationships are in the form of rules. The best set of rules is automatically chosen and forms a classifier. That classifier is then used to predict future dengue incidence as either HIGH (outbreak) or LOW (no outbreak), where these values are defined as being above and below the mean previous dengue incidence plus two standard deviations, respectively. Results Our automated method built three different fuzzy association rule models. Using the first two weekly models, we predicted dengue incidence three and four weeks in advance, respectively. The third prediction encompassed a four-week period, specifically four to seven weeks from time of prediction. Using previously unused test data for the period 4–7 weeks from time of prediction yielded a positive predictive value of 0.686, a negative predictive value of 0.976, a sensitivity of 0.615, and a specificity of 0.982. Conclusions We have developed a novel approach for dengue outbreak prediction. The method is general, could be extended for use in any geographical region, and has the potential to be extended to other environmentally influenced infections. The variables used in our method are widely available for most, if not all countries, enhancing the generalizability of our method. PMID:23126401

  18. Prediction and control of slender-wing rock

    NASA Technical Reports Server (NTRS)

    Kandil, Osama A.; Salman, Ahmed A.

    1992-01-01

    The unsteady Euler equations and the Euler equations of rigid-body dynamics, both written in the moving frame of reference, are sequentially solved to simulate the limit-cycle rock motion of slender delta wings. The governing equations of the fluid flow and the dynamics of the present multidisciplinary problem are solved using an implicit, approximately-factored, central-difference-like, finite-volume scheme and a four-stage Runge-Kutta scheme, respectively. For the control of wing-rock motion, leading-edge flaps are forced to oscillate anti-symmetrically at prescribed frequency and amplitude, which are tuned in order to suppress the rock motion. Since the computational grid deforms due to the leading-edge flaps motion, the grid is dynamically deformed using the Navier-displacement equations. Computational applications cover locally-conical and three-dimensional solutions for the wing-rock simulation and its control.

  19. A Computerized Test of Self-Control Predicts Classroom Behavior

    PubMed Central

    Hoerger, Marguerite L; Mace, F. Charles

    2006-01-01

    We assessed choices on a computerized test of self-control (CTSC) for a group of children with features of attention deficit hyperactivity disorder (ADHD) and a group of controls. Thirty boys participated in the study. Fifteen of the children had been rated by their parents as hyperactive and inattentive, and 15 were age- and gender-matched controls in the same classroom. The children were observed in the classroom for three consecutive mornings, and data were collected on their activity levels and attention. The CTSC consisted of two tasks. In the delay condition, children chose to receive three rewards after a delay of 60 s or one reward immediately. In the task-difficulty condition, the children chose to complete a difficult math problem and receive three rewards or complete an easier problem for one reward. The children with ADHD features made more impulsive choices than their peers during both conditions, and these choices correlated with measures of their activity and attention in the classroom. PMID:16813037

  20. Battery available power prediction of hybrid electric vehicle based on improved Dynamic Matrix Control algorithms

    NASA Astrophysics Data System (ADS)

    Wang, Limei; Cheng, Yong; Zou, Ju

    2014-09-01

    The core technology to any hybrid engine vehicle (HEV) is the design of energy management strategy (EMS). To develop a reasonable EMS, it is necessary to monitor the state of capacity, state of health and instantaneous available power of battery packs. A new method that linearizes RC equivalent circuit model and predicts battery available power according to original Dynamic Matrix Control algorithm is proposed. To verify the validity of the new algorithm, a bench test with lithium-ion battery cell and a HEV test with lithium-ion battery packs are carried out. The bench test results indicate that a single RC block equivalent circuit model could be used to describe the dynamic and the steady state characteristics of a battery under testing conditions. However, lacking of long time constant of RC modules, there is a sample deviation in the open-circuit voltage identified and that measured. The HEV testing results show that the battery voltage predicted is in good agreement with that measured, the maximum difference is within 3.7%. Fixing the time constant to a numeric value, satisfactory results can still be achieved. After setting a battery discharge cut-off voltage, the instantaneous available power of the battery can be predicted.