Model Predictive Control Wind Turbines
Model Predictive Control of Wind Turbines Martin Klauco Kongens Lyngby 2012 IMM-MSc-2012-65 #12;Summary Wind turbines are the biggest part of the green energy industry. Increasing interest control strategies. Control strategy has a significant impact on the wind turbine operation on many levels
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
Model Predictive Control and Thermal Storage: a Simple 3.3of Building Thermal Storage”. In: ASHRAE Transactions 96.2 (and Passive Building Thermal Storage”. In: International
Autonomous Helicopter Formation using Model Predictive Control
Sastry, S. Shankar
Autonomous Helicopter Formation using Model Predictive Control Hoam Chung and S. Shankar Sastry for teams of helicopters. However, the potential for accidents is greatly increased when helicopter teams to the problem of helicopter formations comprised of heterogenous vehicles. The disturbance attenuation property
Lygeros, John
of High Performance Hybrid Race Cars Background The power unit of a high performance hybrid race carPrerequisites Control Systems, System Modeling, Optimal Control, Model Predictive Control, (Engine consists of an internal combustion engine (ICE) and a kinetic energy recovery system (KERS). The time
Optimal Control of Distributed Energy Resources using Model Predictive Control
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.
Interactive software for model predictive control with simultaneous identification
Echeverria Del Rio, Pablo
2000-01-01
This thesis is a unified practical framework in the theory of Model Predictive Control with Simultaneous Identification. The ability to change and visualize parameters on-line makes this toolbox attractive for control ...
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
Control for Active and Passive Building Thermal Storage”.Control for Active and Passive Building Thermal StorageControl for Active and Passive Building Thermal Storage
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
components that use energy, and thermal energy load. When aLearning Control for Thermal Energy Storage Systems”. In:to validate the energy savings and thermal comfort. Also the
Flood control of the Demer by using Model Predictive Control Maarten Breckpot a,n
rainfall. Also hydraulic structures were built to control the discharges in the river and the water goingFlood control of the Demer by using Model Predictive Control Maarten Breckpot a,n , Oscar Mauricio 2013 Keywords: Model Predictive Control Flood control Kalman filter Open channel flow a b s t r a c
Multiplexed Model Predictive Control Keck Voon Ling
Cambridge, University of
an established control technology in the petrochemical industry, and its use is currently being pioneered in an increasingly wide range of process industries [23, 34]. It is also being proposed for a range of higher. Only an initial portion of that plan is implemented, and the process is repeated, re-planning when new
Value Function Approximation and Model Predictive Control
Todorov, Emanuel
techniques for solving optimal control problems; however, each has limitations. In order to mitigate, Seattle, WA 98195 Abstract--Both global methods and on-line trajectory opti- mization methods are powerful on some problems, there is relatively little improvement to the original MPC. Alternatively, we solve
Model Predictive Control with Prioritised Actuators
Gallieri, Marco; Maciejowski, Jan M.
2015-07-17
(k). The generated implicit control law is referred to as KN (x) ? u?0(x). The following is assumed throughout the paper Assumption 1. (A2) For system (1) (H0) (A,B) is stabilisable, (H1) Q ? 0, R ? 0, S ? Rns×m, (H2) X, U, Xf are polytopic C-sets (convex, compact...
Model Predictive Control of a Wind Lars Christian Henriksen
wind turbines is on the sea as their is a more stable wind. These water based wind farms are confined locations to become potential wind farms. This thesis investigates control of both wind turbines mountedModel Predictive Control of a Wind Turbine Lars Christian Henriksen Kongens Lyngby 2007 IMM
Model Predictive Control of Residential Energy Systems Using
Knobloch,Jürgen
network infrastructure and can lead to a degradation of power quality and even outages. In responseModel Predictive Control of Residential Energy Systems Using Energy Storage & Controllable Loads degree of freedom leads to improved performance. 1 Introduction Widespread uptake of local electricity
Incorporating Control Performance Tuning into Economic Model Predictive Control
Olanrewaju, Olumuyiwa I.; Maciejowski, Jan M.
2015-01-01
[1] A. Singh, J. Forbes, P. Vermeer, and S. Woo, “Model-based real-time optimization of automotive gasoline blending operations,” Journal of Process Control, vol. 10, no. 1, pp. 43 – 58, 2000. [2] A. Toumi and S. Engell, “Optimization-based control...
Chemical and Biological Engineering Model Predictive Control: Background
Grossmann, Ignacio E.
== - - = -- --- = DC C V F CC B k V F k Ckk V F A Bs s AsAfs s As s = f1 = f2 etcCAux Asss C f x f A , 1 ,1 1 11Chemical and Biological Engineering Model Predictive Control: Background B. Wayne Bequette "windup" problems Does not explicitly require a process model #12;Chemical and Biological Engineering
Papalambros, Panos
MODEL PREDICTIVE CONTROL OF A MICROGRID WITH PLUG-IN VEHICLES: ERROR MODELING AND THE ROLE) for a microgrid with plug-in vehicles. A predictive model is de- veloped based on a hub model of the microgrid INTRODUCTION Recently, the control of electrical microgrids has been the focus of research efforts. A microgrid
Flood Prevention of the Demer using Model Predictive Control
Flood Prevention of the Demer using Model Predictive Control Toni Barjas Blanco, ,1 Patrick Willems Abstract: In order to prevent flooding of a river system the local water administration of the Demer reduced the damage and frequency of flooding events, simulations have shown that a better usage
Adaptive model predictive process control using neural networks
Buescher, Kevin L. (Los Alamos, NM); Baum, Christopher C. (Mazomanie, WI); Jones, Roger D. (Espanola, NM)
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.
Adaptive model predictive process control using neural networks
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.
Model Predictive Control of Integrated Gasification Combined Cycle Power Plants
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.
Flood Control with Model Predictive Control for River Systems with Water Reservoirs
Flood Control with Model Predictive Control for River Systems with Water Reservoirs Maarten consisting of multiple channels, gates, and a water reservoir. One controller is used in combination of measured water levels. It was observed that the influence of this estimator on the control performance
Flood control of rivers with nonlinear model predictive control and moving horizon estimation
]. Several studies can be found in literature where MPC is used to control water systems [15], [16] and [5Flood control of rivers with nonlinear model predictive control and moving horizon estimation control (MPC) in combination with moving horizon estimation (MHE) can more effectively be used for flood
Lapp, Tiffany Rae, 1979-
2004-01-01
This thesis presents the design and implementation of a model predictive control based trajectory optimization method for Nap-of-the-Earth (NOE) flight. A NOE trajectory reference is generated over a subspace of the terrain. ...
A Real-time Framework for Model Predictive Control of Continuous-Time Nonlinear Systems
Sontag, Eduardo
for piecewise constant NMPC of continuous-time processes. Index Terms-- nonlinear model predictive control, real-time optimization, optimal control, piecewise constant control I. INTRODUCTION Model predictive control (MPC horizon, open-loop optimal control problem. The unprecedented industrial success of MPC ap- proaches based
VISUALIZING MODEL-BASED PREDICTIVE CONTROLLERS StephanieGuerlain Greg JamjesonandPeter Bullemer
Virginia, University of
control ayd optimize large sections of a petrochemical process;yqng a predictive model. However, current-based predictive controllers (MPC) are becoming very popular in petrochemical refineries, as they simultaneously
Interval Methods for Sensitivity-Based Model-Predictive Control of
Kearfott, R. Baker
Interval Methods for Sensitivity-Based Model-Predictive Control of Solid Oxide Fuel Cell Systems and experiment for the thermal subprocess of a high-temperature solid oxide fuel cell system. Keywords: Interval analysis, model-predictive control, sensitivity analysis, tracking control, solid oxide fuel cells AMS
OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING
Virginia, University of
OPERATOR INTERACTION WITH MODEL-BASED PREDICTIVE CONTROLLERS IN PETROCHEMICAL REFINING Greg A in process control to the more thoroughly studied Flight Management System (FMS) employed in airline cockpits and challenging task. Keywords: Cognitive task analysis; Process control; Predictive control; Optimization
Robust Constrained Model Predictive Control using Linear Matrix Inequalities \\Lambda
Balakrishnan, Venkataramanan "Ragu"
dynamical systems, such as those encountered in chemical process control in the petrochemical, pulp process models as well as many performance criteria of significance to the process industries can
Robust Constrained Model Predictive Control using Linear Matrix Inequalities
Balakrishnan, Venkataramanan "Ragu"
, such as those encountered in chemical process control in the petrochemical, pulp and paper industries, several process models as well as many performance criteria of significance to the process industries can
A data-based approach for multivariate model predictive control performance monitoring$
Chen, Sheng
A data-based approach for multivariate model predictive control performance monitoring$ Xuemin Tian of Petroleum (Hua Dong), Donying, Shandong 257061, China b School of Electronics and Computer Science by J. Zhang Available online 20 October 2010 Keywords: Model predictive control Performance monitoring
NONLINEAR MODEL PREDICTIVE CONTROL WITH MOVING HORIZON STATE AND
Van den Hof, Paul
referred to as air pollution or "post-combustion" control systems). In this paper only the combustion - WITH APPLICATION TO MSW COMBUSTION M. Leskens , L.B.M. van Kessel , P.M.J. Van den Hof and O.H. Bosgra strategy are demonstrated by applying it to a model of a municipal solid waste (MSW) combustion plant under
Economic and Distributed Model Predictive Control of Nonlinear Systems
Heidarinejad, Mohsen
2012-01-01
optimization and control for intentionally transient processpredictive control and optimization of processes : enablingoperation. Within process control, the economic optimization
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01
control for active and passive building thermal storage.control for active and passive building thermal storagecontrollers for active and passive building thermal storage
Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models
ALANQAR, ANAS WAEL
2015-01-01
optimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the processoptimization and feedback control since it is a predictive control scheme that is formulated with an objective function representing the process/
Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant
Johansen, Tor Arne
Scenario-Based Fault-Tolerant Model Predictive Control for Diesel-Electric Marine Power Plant Email: torstein.bo@itk.ntnu.no, tor.arne.johansen@itk.ntnu.no Abstract--Diesel-electric propulsion generation control, Ma- rine safety, Optimal control. I. INTRODUCTION Diesel electric propulsion is a system
Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System.
Paris-Sud XI, Université de
Adaptive Model Predictive Control of the Hybrid Dynamics of a Fuel Cell System. M. Fiacchini, T operation of a fuel cell system is presented. The aim of the control design is to guarantee that the oxygen control to a fuel cell plant is presented. The fuel cell, located in the laboratory of the Department
Model Predictive Control of a Wind Aleksander Gosk
are aiming for maximizing the produced electric power for some range of wind speeds and keeping it constant. This work focuses on one of the most common wind energy conversion systems: horizontal axis wind turbine It's efficiency and longevity relies heavily on the quality of the control approach used. Controller designers
Distributional Analysis for Model Predictive Deferrable Load Control
Low, Steven H.
for demand response. There are two major categories of demand response, direct load control (DLC) and price-based demand response. See [1] for a discussion of the contrasts between these approaches. In this paper we focus on direct load control with the goal of using demand response to reduce variations
Variable horizon model predictive control: robustness and optimality
Shekhar, Rohan Chandra
2012-07-03
. . . . . . . . . . . . . . . . . . . . . . . . . . . 106 6.3 Kinematic vectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 6.4 Mechanism model showing generalised coordinates . . . . . . . . . . . . . . . . 109 6.5 Static balance of material failure forces... .1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 6.1.1 Nomenclature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 6.2 Mechanism Model...
Decentralized model predictive control of a multiple evaporator HVAC system
Elliott, Matthew Stuart
2009-05-15
Vapor compression cooling systems are the primary method used for refrigeration and air conditioning, and as such are a major component of household and commercial building energy consumption. Application of advanced control ...
Unit Commitment and Economic Model Predictive Control for
share of inter- mittent renewable energy sources in the power supply has presented new challenges horizon manner while considering updated and more reliable forecasts of power supply from renewable energy for optimal operation of power systems. Motivated by these challenges, we present a novel control strategy
Terminal Spacecraft Rendezvous and Capture with LASSO Model Predictive Control
Hartley, Edward N.; Gallieri, Marco; Maciejowski, Jan M.
2013-08-20
. Int. Conf. Instrumentation, Communication Information Technology, and Biomedical Engineering, Badung, 23–25 Nov, pp. 435–439. Kawai, F., Ito, H., Nakazawa, C., Matsui, T., Fukuyama, Y., Suzuki, R., and Aiyoshi, E. (2007), “Automatic Tuning for Model...
Linear-quadratic model predictive control for urban traffic , Hai L. Vu a
Nazarathy, Yoni
Accepted 30 June 2013 Keywords: Model predictive control Intelligent transport system Congestion control- tion systems are driving the field of intelligent transport systems (ITS) into the twenty first century for large urban networks containing thousands of sensors and actuators. We demonstrate the essence of our
Hybrid Model Predictive Control Based on Wireless Sensor Feedback: An Experimental Study
Johansson, Karl Henrik
Hybrid Model Predictive Control Based on Wireless Sensor Feedback: An Experimental Study Alberto based on measurements collected by a wireless sensor network. The proposed setup is the prototype of an industrial application in which a remote station controls the process via wireless network links
Model predictive adaptive control of process systems using recurrent neural networks
Parthasarathy, Sanjay
1993-01-01
) controller structure is used for the simulations. The feasibility of the approach is first demonstrated on a, piece-wise linearized model of the UTSG. It is found that the proposed model predictive adaptive PI controller significantly reduces the system set... Summary 41 41 42 45 49 53 54 V CASE-STUDY: THE U-TUBE STEAM GENERATOR LEVEL CONTROL PROBLEM WATER o6 V. 1 Introduction V. 2 Current Practice: The PID Controller 56 60 CHAPTER Page V. 3 Development of the Piece-wise Linearized Model ol...
IEEE TRANSACTIONS ON FUZZY SYSTEMS, VOL. 8, NO. 6, DECEMBER 2000 665 Fuzzy Model Predictive Control
Huang, Yinlun
and petrochemical industries during the past decade. In MPC, a process dynamic model is used to predict future (FMPC) approach is introduced to design a control system for a highly nonlinear process. In this approach, a process system is described by a fuzzy convolution model that consists of a number of quasi
Linear Model-Based Predictive Control of the LHC 1.8 K Cryogenic Loop
Blanco-Viñuela, E; De Prada-Moraga, C
1999-01-01
The LHC accelerator will employ 1800 superconducting magnets (for guidance and focusing of the particle beams) in a pressurized superfluid helium bath at 1.9 K. This temperature is a severely constrained control parameter in order to avoid the transition from the superconducting to the normal state. Cryogenic processes are difficult to regulate due to their highly non-linear physical parameters (heat capacity, thermal conductance, etc.) and undesirable peculiarities like non self-regulating process, inverse response and variable dead time. To reduce the requirements on either temperature sensor or cryogenic system performance, various control strategies have been investigated on a reduced-scale LHC prototype built at CERN (String Test). Model Based Predictive Control (MBPC) is a regulation algorithm based on the explicit use of a process model to forecast the plant output over a certain prediction horizon. This predicted controlled variable is used in an on-line optimization procedure that minimizes an approp...
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.
Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)
Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.
2014-02-01
Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.
Flood regulation using nonlinear model predictive control Toni Barjas Blanco a,, Patrick Willems b
Flood regulation using nonlinear model predictive control Toni Barjas Blanco a,Ã, Patrick Willems b t In this paper the flood problem of the river Demer, a river located in Belgium, is discussed. First a simplified. & 2010 Elsevier Ltd. All rights reserved. 1. Introduction Flooding of rivers are a worldwide cause
Voltage Utilization in Model Predictive Control for Michael Leuer, Joachim Bocker
Noé, Reinhold
Voltage Utilization in Model Predictive Control for IPMSM Michael Leuer, Joachim B¨ocker Power (IPMSM). Besides the good dynamics, the utilization of the DC link voltage is important for these motor types. Since the MPC is able to utilize the available DC link voltage optimally, the MPC is superior
Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks
Grossmann, Ignacio E.
Compressor 4 Commercial Industry Power Plant LDC 3 Suppliers, 12 Demand nodes, 5 Compressors Sinusoidal Flowrates Industry: N6,12,13,19,21 Commercial: N30,32,34,35 Power Plant: N4,25 LDC: N23 Pcontract = 500 kEconomic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks EWO
Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1
Stefanopoulou, Anna
Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1 Ardalan Vahidi 2 current is drawn from a fuel cell, it is critical that the reacted oxygen is replenished rapidly. We formulate distribution of current demand between the fuel cell and the auxiliary source
Sanandaji, Borhan M.
Physically Based Model-Predictive Control for SOFC Stacks and Systems Tyrone L. Vincent, Borhan output tra- jectory. The process is demonstrated for a tubular SOFC stack that could be used, solid-oxide fuel cells (SOFC) must deliver power profiles that meet the demands of transient loads
Energy Savings Through Application of Model Predictive Control to an Air Separation Facility
Hanson, T. C.; Scharf, P. F.
1996-01-01
signs for cryogenic air separation plants. Equally important is the adherence of operating conditions to their optimal values, a task assigned to the plant's control system. This paper addresses the application of Model Predictive Control (MPC... maintain the plant at an optimal operating state. REFERENCE 1. Daryanian, B., Bohn, R.E., and Tabors, R.D., "Op timal Demand-Side Response to Electricity Spot Prices for Storage-Type Customers", IEEE Transac tions on Power Systems, 4(3), 897...
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
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.
Model Predictive Control-based Optimal Coordination of Distributed Energy Resources
Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.
2013-01-07
Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. 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 performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.
Model Predictive Control-based Optimal Coordination of Distributed Energy Resources
Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.
2013-04-03
Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. 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 performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.
Joshi, Praveen Sudhakar
1999-01-01
Predictive Variable Structure and Fuzzy Logic based controllers for the same benchmark problem. Evaluation criteria consist of closed-loop system performance, activity level of the VFC nozzles, ease of controller synthesis, time required to synthesize...
Bone, Gary
actuator Hybrid actuator On/off solenoid valve Position control Robot control a b s t r a c t The design with inexpensive on/off solenoid valves. A variant of inverse dynamics control is proposed for the DC motor and expected valve life. Experimental results are presented for ver- tical rotary cycloidal trajectories. Even
Hespanha, João Pedro
Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control consider the control of two UAVs tracking an evasive moving ground vehicle. The UAVs are small fixed-wing aircraft equipped with gimbaled cameras and must coordinate their control actions so that at least one UAV
ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview
Candanedo, J. A.; Dehkordi, V. R.
2013-01-01
Model-based predictive control (MPC) has emerged in recent years as a promising approach to building operation. MPC uses models of the system(s) under control -and knowledge about future disturbances- to select an optimal set of actions. Despite its...
Haves, Phillip; Hencey, Brandon; Borrell, Francesco; Elliot, John; Ma, Yudong; Coffey, Brian; Bengea, Sorin; Wetter, Michael
2010-06-29
A Model Predictive Control algorithm was developed for the UC Merced campus chilled water plant. Model predictive control (MPC) is an advanced control technology that has proven successful in the chemical process industry and other industries. The main goal of the research was to demonstrate the practical and commercial viability of MPC for optimization of building energy systems. The control algorithms were developed and implemented in MATLAB, allowing for rapid development, performance, and robustness assessment. The UC Merced chilled water plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. The control algorithms determined the optimal chilled water plant operation including chilled water supply (CHWS) temperature set-point, condenser water supply (CWS) temperature set-point and the charging start and stop times to minimize a cost function that includes energy consumption and peak electrical demand over a 3-day prediction horizon. A detailed model of the chilled water plant and simplified models of the buildings served by the plant were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers performance data, and calibrated using measured data collected and archived by the control system. A detailed dynamic model of the chilled water storage tank was also developed and calibrated. Simple, semi-empirical models were developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a model predictive control algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The report describes the development and testing of the algorithm and evaluates the resulting performance, concluding with a discussion of next steps in further research. The experimental results show a small improvement in COP over the baseline policy but it is difficult to draw any strong conclusions about the energy savings potential for MPC with this system only four days of suitable experimental data were obtained once correct operation of the MPC system had been achieved. These data show an improvement in COP of 3.1% {+-} 2.2% relative to a baseline established immediately prior to the period when the MPC was run in its final form. This baseline includes control policy improvements that the plant operators learned by observing the earlier implementations of MPC, including increasing the temperature of the water supplied to the chiller condensers from the cooling towers. The process of data collection and model development, necessary for any MPC project, resulted in the team uncovering various problems with the chilled water system. Although it is difficult to quantify the energy savings resulting from these problems being remedied, they were likely on the same order as the energy savings from the MPC itself. Although the types of problems uncovered and the level of energy savings may differ significantly from other projects, some of the benefits of detecting and diagnosing problems are expected from the use of MPC for any chilled water plant. The degree of chiller loading was found to be a key factor for efficiency. It is more efficient to operate the chillers at or near full load. In order to maximize the chiller load, one would maximize the temperature difference across chillers and the chilled water flow rate through the chillers. Thus, the CHWS set-point and the chilled water flow-rate can be used to limit the chiller loading to prevent chiller surging. Since the flow rate has an upper bound and the CHWS set point has a lower bound, the chiller loading is constrained and often determined by the chilled water return temperature (CHWR). The CHWR temperature
Duong, Thien Chi
2011-02-22
of multimedia services over the Internet. In the past few years, many endeavors have been carried on to solve the problem. One interesting approach focuses on the development of end-to-end congestion control iv strategies for UDP multimedia flows.... Traditionally, packet losses and delays have been commonly used to develop many known control schemes. Each of them only characterizes some different aspects of network congestion; hence, they are not ideal as feedback signals alone. In this research...
Switching Strategy for Direct Model Predictive Control in Power Converter and Drive Applications
Noé, Reinhold
of permanent magnet synchronous motors with interior magnets (IPMSM). Index Terms--Direct Model Predictive Direct-MPC approaches, a more flexible gate-signal generation method which enables switching during
Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models
ALANQAR, ANAS WAEL
2015-01-01
4 Application to a Chemical Process Example 5 Conclusionsnonlinear processes. Chemical Engineering Science 2003, 58,based on Wiener models. Chemical Engineering Science 1998,
Kareem, Ahsan
the wind induced structural response. A shaking table and a small-scale structural model with an active reduction. Finally, a full-scale building for wind-excited benchmark problem was investigated to implement to enhance the performance of structures during earthquakes and strong winds. Efficient control schemes
Distributed Model Predictive Control of Nonlinear and Two-Time-Scale Process Networks
Chen, Xianzhong
2012-01-01
the economic optimization and process control layer. Inoptimization and control for intentionally transient processpredictive control and optimization of processes : Enabling
Haves, Phillip
2010-01-01
13] Wetter, M.. 2009. “Modelica?based Modeling and 14] Wetter, M.. 2009. “Modelica?based Modeling and modeling language Modelica. Steady state models of
Multiplexed Model Predictive Control Keck Voon Ling a, Jan Maciejowski b
Cambridge, University of
Control (MPC) has become an established control technol- ogy in the petrochemical industry, and its use is currently being pioneered in an increasingly wide range of process industries. It is also being proposed
Real-Time Implementation of an Online Model Predictive Control for IPMSM Using Parallel
Paderborn, Universität
computational cost and the associated long control cycle time. This makes MPC unattractive for processes parameters are calculated only once during the de- sign process. Thus the control dynamics are only Control (MPC) is more effective. MPCs are based on the solution of a dynamic optimization problem
Reduced Order Modeling for Prediction and Control of Large-Scale Systems.
Kalashnikova, Irina; Arunajatesan, Srinivasan; Barone, Matthew Franklin; van Bloemen Waanders, Bart Gustaaf; Fike, Jeffrey A.
2014-05-01
This report describes work performed from June 2012 through May 2014 as a part of a Sandia Early Career Laboratory Directed Research and Development (LDRD) project led by the first author. The objective of the project is to investigate methods for building stable and efficient proper orthogonal decomposition (POD)/Galerkin reduced order models (ROMs): models derived from a sequence of high-fidelity simulations but having a much lower computational cost. Since they are, by construction, small and fast, ROMs can enable real-time simulations of complex systems for onthe- spot analysis, control and decision-making in the presence of uncertainty. Of particular interest to Sandia is the use of ROMs for the quantification of the compressible captive-carry environment, simulated for the design and qualification of nuclear weapons systems. It is an unfortunate reality that many ROM techniques are computationally intractable or lack an a priori stability guarantee for compressible flows. For this reason, this LDRD project focuses on the development of techniques for building provably stable projection-based ROMs. Model reduction approaches based on continuous as well as discrete projection are considered. In the first part of this report, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is developed. The key idea is to apply a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. It is shown that, for many PDE systems including the linearized compressible Euler and linearized compressible Navier-Stokes equations, the desired transformation is induced by a special inner product, termed the “symmetry inner product”. Attention is then turned to nonlinear conservation laws. A new transformation and corresponding energy-based inner product for the full nonlinear compressible Navier-Stokes equations is derived, and it is demonstrated that if a Galerkin ROM is constructed in this inner product, the ROM system energy will be bounded in a way that is consistent with the behavior of the exact solution to these PDEs, i.e., the ROM will be energy-stable. The viability of the linear as well as nonlinear continuous projection model reduction approaches developed as a part of this project is evaluated on several test cases, including the cavity configuration of interest in the targeted application area. In the second part of this report, some POD/Galerkin approaches for building stable ROMs using discrete projection are explored. It is shown that, for generic linear time-invariant (LTI) systems, a discrete counterpart of the continuous symmetry inner product is a weighted L2 inner product obtained by solving a Lyapunov equation. This inner product was first proposed by Rowley et al., and is termed herein the “Lyapunov inner product“. Comparisons between the symmetry inner product and the Lyapunov inner product are made, and the performance of ROMs constructed using these inner products is evaluated on several benchmark test cases. Also in the second part of this report, a new ROM stabilization approach, termed “ROM stabilization via optimization-based eigenvalue reassignment“, is developed for generic LTI systems. At the heart of this method is a constrained nonlinear least-squares optimization problem that is formulated and solved numerically to ensure accuracy of the stabilized ROM. Numerical studies reveal that the optimization problem is computationally inexpensive to solve, and that the new stabilization approach delivers ROMs that are stable as well as accurate. Summaries of “lessons learned“ and perspectives for future work motivated by this LDRD project are provided at the end of each of the two main chapters.
Ellis, Matthew
2015-01-01
integration. Computers & Chemical Engineering, 20:315–323,control. Computers & Chemical Engineering, 58:334–343,reactors: a review. Chemical Engineering Communications, 1:
DECENTRALIZED MODEL PREDICTIVE CONTROL OF SWARMS OF SPACECRAFT USING SEQUENTIAL CONVEX
Chung, Soon-Jo
optimizations, which reduces the run time of the algorithm. INTRODUCTION Spacecraft formation flying has been a major area of research over the past decade. Recently, the idea of formation flying has been extended is in a desired formation. However, another important requirement for swarm missions is the guidance and control
Haves, Phillip
2010-01-01
motor speed pump power [W] volumetric flow rate [m 3 /i f f e volumetric flow [m /s] Figure 2.15: Pump model fit volumetric flow?rate and ? p 0 is the nominal pressure across the pump.
Predictive control of supply temperature in district heating systems
Predictive control of supply temperature in district heating systems Torben Skov Nielsen Henrik This report considers a new concept for controlling the supply temperature in district heating systems using stochastic modelling, prediction and control. A district heating systems is a di#30;cult system to control
Tu, TungSheng
2013-01-01
optimization and control for intentionally transient processeconomic optimization and process control is economic modelpredictive control and optimization of processes: enabling
Online prediction and control nonlinear stochastic systems
temperature in district heat- ing systems. · Prediction of power production from the wind turbines located and their application to prediction and control within district heating systems and for prediction of wind power. Here temperature in district heating systems', Techni- cal Report IMM-REP-2002-23, Informatics and Mathematical
Intelligent Predictive Control Methods for Synchronous Power System
Rizvi, Syed Z.
@kfupm.edu.sa Abstract--In this paper, an intelligent Model Predictive Con- troller (MPC) for a Synchronous Power Machine of a Single synchronous Machine on Infinite Bus (SMIB) has been one of the most important problems for powerIntelligent Predictive Control Methods for Synchronous Power System Muhammad S. Yousuf Electrical
Predictive Control for Time-Delayed Switching Control Systems
Barth, Eric J.
Predictive Control for Time-Delayed Switching Control Systems Bobby L. Shields Eric J. Barth A methodology is proposed for the control of switching systems characterized by linear system dynamics period determines the effect that the next control input will have on the future output of the system
Lao, Liangfeng
2015-01-01
for CFD on the simulation of biogas combustion in bluff-bodydevelop its CFD model considering both the combustion in thedevelop its CFD model considering both the combustion in the
MICRO SIMULATION OF CITY TRAFFIC FLOWS IN SUPPORT OF PREDICTIVE OPERATIONAL CONTROL
Bargiela, Andrzej
of the modelling process and the prediction model. Several types of traffic models have been used with demand- responsive traffic control systems. In parallel with the development of new control systems, there have been
Claridge,D.; Chen,W.J
2014-01-01
-IC-14-09-27a Proceedings of the 14th International Conference for Enhanced Building Operations, Beijing, China, September 14-17, 2014 Outline • Prevention of Mold growth • Modeling Building Infiltration • Results, Discussion and Conclusions ESL-IC-14...-09-27a Proceedings of the 14th International Conference for Enhanced Building Operations, Beijing, China, September 14-17, 2014 Prevention of Mold Growth • Battle of dry time and wet time 0 24 Bathroom Door Closed Bathroom Door Open Exhaust Fan On Daily...
Dynamical epidemic suppression using stochastic prediction and control
I. B. Schwartz; L. Billings; E. M. Bollt
2005-10-18
We consider the effects of noise on a model of epidemic outbreaks, where the outbreaks appear. randomly. Using a constructive transition approach that predicts large outbreaks, prior to their occurrence, we derive an adaptive control. scheme that prevents large outbreaks from occurring. The theory inapplicable to a wide range of stochastic processes with underlying deterministic structure.
Towards feasible and effective predictive wavefront control for...
Office of Scientific and Technical Information (OSTI)
Towards feasible and effective predictive wavefront control for adaptive optics Citation Details In-Document Search Title: Towards feasible and effective predictive wavefront...
Predictive Compensation for Communication Outages in Networked Control Systems
Johansson, Karl Henrik
Predictive Compensation for Communication Outages in Networked Control Systems Erik Henriksson Henrik Sandberg Karl Henrik Johansson Abstract-- A predictive outage compensator co time instance, the predictive outage compensator suggests a replacement command based on the history
R.W. Carpick; M.E. Plesha
2007-03-03
This report describes the accomplishments of the DOE BES grant entitled "Development and Integration of Single-Asperity Nanotribology Experiments & Nanoscale Interface Finite Element Modeling for Prediction and Control of Friction and Damage in Micro- and Nano-mechnical Systems". Key results are: the determination of nanoscale frictional properties of MEMS surfaces, self-assembled monolayers, and novel carbon-based films, as well as the development of models to describe this behavior.
Predict-prevent control method for perturbed excitable systems
Marzena Ciszak; Claudio R. Mirasso; Raul Toral; Oscar Calvo
2008-07-15
We present a control method based on two steps: prediction and prevention. For prediction we use the anticipated synchronization scheme, considering unidirectional coupling between excitable systems in a master-slave configuration. The master is the perturbed system to be controlled, meanwhile the slave is an auxiliary system which is used to predict the master's behavior. We demonstrate theoretically and experimentally that an efficient control may be achieved.
Bastin, Georges
Nonlinear Predictive Control of Cement Mills Lalo Magni, Georges Bastin, and Vincent Wertz Abstract--A new multivariable controller for cement milling circuits is presented, which is based on a nonlinear model: a change of hardness of the raw material. Index Terms--Cement industry, multivariable control systems
Voltage control in pulsed system by predict-ahead control
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.
What is the Recent Controversy in Evaluating Risk Prediction Models
Brent, Roger
What is the Recent Controversy in Evaluating Risk Prediction Models All About? Margaret Sullivan Pepe #12;Controversy about Risk Reclassification Techniques · Purpose: To evaluate the addition cases controls C-index = P(riskevent > risknonevent) · Should not be used to evaluate or compare risk
A distributed accelerated gradient algorithm for distributed model predictive
Como, Giacomo
is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied, Distributed model predictive control 1. Introduction Hydro power plants generate electricity from potential river or a water body system to generate the power at different stages. Currently, hydro power is one
Grossman, Robert
The Management and Mining of Multiple Predictive Models Using the Predictive Modeling Markup Language (PMML) Robert Grossman National Center for Data Mining, University of Illinois at Chicago & Magnify, Inc. Stuart Bailey, Ashok Ramu and Balinder Malhi National Center for Data Mining University
Predictive Thermal Control for Real-Time Video Decoding Mehmet H. Suzer
Kang, Kyoung-Don
Predictive Thermal Control for Real-Time Video Decoding Mehmet H. Suzer Harran University msuzer multime- dia data in real-time with the highest possible QoS, while avoiding potential thermal problems for video decoding. Based on the model, we develop a predictive method that avoids deadline misses due
Prediction of regionalized car insurance risks based on control variates
Schmidt, Volker
Prediction of regionalized car insurance risks based on control variates Marcus C. Christiansen, Christian Hirsch, Volker Schmidt October 1, 2013 Abstract We show how regional prediction of car insurance compute such predictors and consider an application to German car insurance data. 1 Introduction
Using micro saint to predict performance in a nuclear power plant control room
Lawless, M.T.; Laughery, K.R.; Persenky, J.J.
1995-09-01
The United States Nuclear Regulatory Commission (NRC) requires a technical basis for regulatory actions. In the area of human factors, one possible technical basis is human performance modeling technology including task network modeling. This study assessed the feasibility and validity of task network modeling to predict the performance of control room crews. Task network models were built that matched the experimental conditions of a study on computerized procedures that was conducted at North Carolina State University. The data from the {open_quotes}paper procedures{close_quotes} conditions were used to calibrate the task network models. Then, the models were manipulated to reflect expected changes when computerized procedures were used. These models` predictions were then compared to the experimental data from the {open_quotes}computerized conditions{close_quotes} of the North Carolina State University study. Analyses indicated that the models predicted some subsets of the data well, but not all. Implications for the use of task network modeling are discussed.
Disease Prediction Models and Operational Readiness
Corley, Courtney D.; Pullum, Laura L.; Hartley, David M.; Benedum, Corey M.; Noonan, Christine F.; Rabinowitz, Peter M.; Lancaster, Mary J.
2014-03-19
INTRODUCTION: The objective of this manuscript is to present a systematic review of biosurveillance models that operate on select agents and can forecast the occurrence of a disease event. One of the primary goals of this research was to characterize the viability of biosurveillance models to provide operationally relevant information for decision makers to identify areas for future research. Two critical characteristics differentiate this work from other infectious disease modeling reviews. First, we reviewed models that attempted to predict the disease event, not merely its transmission dynamics. Second, we considered models involving pathogens of concern as determined by the US National Select Agent Registry (as of June 2011). Methods: We searched dozens of commercial and government databases and harvested Google search results for eligible models utilizing terms and phrases provided by public health analysts relating to biosurveillance, remote sensing, risk assessments, spatial epidemiology, and ecological niche-modeling, The publication date of search results returned are bound by the dates of coverage of each database and the date in which the search was performed, however all searching was completed by December 31, 2010. This returned 13,767 webpages and 12,152 citations. After de-duplication and removal of extraneous material, a core collection of 6,503 items was established and these publications along with their abstracts are presented in a semantic wiki at http://BioCat.pnnl.gov. Next, PNNL’s IN-SPIRE visual analytics software was used to cross-correlate these publications with the definition for a biosurveillance model resulting in the selection of 54 documents that matched the criteria resulting Ten of these documents, However, dealt purely with disease spread models, inactivation of bacteria, or the modeling of human immune system responses to pathogens rather than predicting disease events. As a result, we systematically reviewed 44 papers and the results are presented in this analysis.
Hybrid Modeling and Control of a Hydroelectric Power Plant
Ferrari-Trecate, Giancarlo
Hybrid Modeling and Control of a Hydroelectric Power Plant Giancarlo Ferrari-Trecate, Domenico,mignone,castagnoli,morari}@aut.ee.ethz.ch Abstract In this work we present the model of a hydroelectric power plant in the framework of Mixed Logic with a model predictive control scheme. 1 Introduction The outflow control for hydroelectric power plants
Solid Oxide Fuel Cell: Perspective of Dynamic Modeling and Control
Huang, Biao
Solid Oxide Fuel Cell: Perspective of Dynamic Modeling and Control Biao Huang Yutong Qi Monjur: This paper presents a review of state-of-the-art solid oxide fuel cells (SOFC), from perspective of dynamic. Keywords: Solid Oxide Fuel Cell, Control Relevant Model, Model Predictive Control 1. INTRODUCTION Today
Wood, Robert
GMAO Clouds in Global Models Annual mean Control run Atmospheric models #12;CGCM Problems: NOAA CFS Model CFS Errors SST Prec CLD · The CFS model has significant errors in the SEP · There is a meridional) · These errors adversely affect the skill of CFS climate forecasts (ENSO). What model developments are required
Progress towards a PETN Lifetime Prediction Model
Burnham, A K; Overturf III, G E; Gee, R; Lewis, P; Qiu, R; Phillips, D; Weeks, B; Pitchimani, R; Maiti, A; Zepeda-Ruiz, L; Hrousis, C
2006-09-11
Dinegar (1) showed that decreases in PETN surface area causes EBW detonator function times to increase. Thermal aging causes PETN to agglomerate, shrink, and densify indicating a ''sintering'' process. It has long been a concern that the formation of a gap between the PETN and the bridgewire may lead to EBW detonator failure. These concerns have led us to develop a model to predict the rate of coarsening that occurs with age for thermally driven PETN powder (50% TMD). To understand PETN contributions to detonator aging we need three things: (1) Curves describing function time dependence on specific surface area, density, and gap. (2) A measurement of the critical gap distance for no fire as a function of density and surface area for various wire configurations. (3) A model describing how specific surface area, density and gap change with time and temperature. We've had good success modeling high temperature surface area reduction and function time increase using a phenomenological deceleratory kinetic model based on a distribution of parallel nth-order reactions having evenly spaced activation energies where weighing factors of the reactions follows a Gaussian distribution about the reaction with the mean activation energy (Figure 1). Unfortunately, the mean activation energy derived from this approach is high (typically {approx}75 kcal/mol) so that negligible sintering is predicted for temperatures below 40 C. To make more reliable predictions, we've established a three-part effort to understand PETN mobility. First, we've measured the rates of step movement and pit nucleation as a function of temperature from 30 to 50 C for single crystals. Second, we've measured the evaporation rate from single crystals and powders from 105 to 135 C to obtain an activation energy for evaporation. Third, we've pursued mechanistic kinetic modeling of surface mobility, evaporation, and ripening.
Gamma-Ray Pulsars: Models and Predictions
Alice K. Harding
2000-12-12
Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. Next-generation gamma-ray telescopes sensitive to GeV-TeV emission will provide critical tests of pulsar acceleration and emission mechanisms.
Predicting Protein Folding Kinetics via Temporal Logic Model Checking: Extended
Langmead, Christopher James
Predicting Protein Folding Kinetics via Temporal Logic Model Checking: Extended Abstract Abstract. We present a novel approach for predicting protein folding kinetics using techniques from checking. We tested our method on 19 test proteins. The quantitative predictions regarding folding rates
Predicting Operator Capacity for Supervisory Control of Multiple UAVs
Cummings, Mary "Missy"
Predicting Operator Capacity for Supervisory Control of Multiple UAVs M.L. Cummings, C. E. Nehme, J, uninhabited (also known as unmanned) ae- rial vehicles (UAVs) have become indispensable assets to militarized forces. UAVs require human guidance to varying degrees and often through several operators. However
Prediction of traffic flow for real-time control
Chandrasekaran, Priya
1998-01-01
The prediction of traffic flow on a network and the relationship of these flows to the traffic control signal settings are major factors in the development of an adaptive real-time signal system. PASSER IV is an arterial system optimization package...
Numerical and analytical modeling of sanding onset prediction
Yi, Xianjie
2004-09-30
To provide technical support for sand control decision-making, it is necessary to predict the production condition at which sand production occurs. Sanding onset prediction involves simulating the stress state on the surface of an oil/gas producing...
Predictive Capability Maturity Model for computational modeling and simulation.
Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.
2007-10-01
The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.
A statistically predictive model for future monsoon failure in India
Levermann, Anders
A statistically predictive model for future monsoon failure in India Jacob Schewe1,2 and Anders Information #12;A statistically predictive model for future monsoon failure in India 2 mm/day numberofyears 0 statistically predictive model for future monsoon failure in India 4 30 o S 15o S 0 o 15o N 30o N A dry May B
Statistical surrogate models for prediction of high-consequence...
Office of Scientific and Technical Information (OSTI)
Technical Report: Statistical surrogate models for prediction of high-consequence climate change. Citation Details In-Document Search Title: Statistical surrogate models for...
Bittle, Joshua A
2014-04-18
Attempting to bridge the gap between typical off-line engine simulations and online real-time control strategies a computationally efficient model has been created that predicts the combustion trajectory (path through the ?-T plane). To give...
Predicting the past: archaeological predictive modeling in Central Texas
Werner, Corey M
2002-01-01
Texas has a well-stratified assemblage of Clovis artifacts. The discovery of additional sites like the Gault site could provide valuable information to resolve the debate. Two logistic regression models are created to locate areas with a high...
Settlement Prediction, Gas Modeling and Slope Stability Analysis
Politècnica de Catalunya, Universitat
Settlement Prediction, Gas Modeling and Slope Stability Analysis in Coll Cardús Landfill Li Yu UNIVERSIDAD POLITÉCNICA DE CATALUÑA April, 2007 GEOMODELS #12;Introduction to Coll Cardús landfill Prediction of settlement in Coll Cardús landfill 1) Settlement prediction by empirical method 2) Settlement prediction
Performance-driven control theory and applications
Riggs, Daniel J.
2012-01-01
Non-Linear Predictive Control: Theory and Practice. IET, UK,M. Morari. Model predictive control: Theory and practice – aModel Predictive Control: Theory and Algorithms. Springer-
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
ALC) system. ALC is a building automation system, offering aModern digital building automation systems satisfy thesemore sophisticated building automation systems and building
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
DESCRIPTION volumetric water flow q pump , the pump speed ?of the nominal volumetric water flow q pump ?p 0 pump = c 0given fan speed ? pump and the volumetric water flow rate q
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
Improved Performance of Ice Storage Systems”. In: Energy andfor Thermal Energy Storage Systems”. In: HVAC&R Research
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
solar radiation, occupancy, and electrical devices in the buildings as a function of weather information, time, and date.solar radiation, occupancy, and electrical devices in the buildings as a function of weather information, time, and date.
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
solution”. In: Energy and Buildings 52.0 (2012), pp. 39–49.with GenOpt”. In: Energy and Buildings 42.7 (2010), pp.lation Program”. In: Energy and Buildings 33.4 (2001), pp.
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01
based on mass and energy conservation law is developed andbased on mass and energy conservation laws, and the buildingmass and internal energy conservation laws, m ? CHW S ? m ?
Model Predictability-Form Lorenz System to Operational Ocean and
Chu, Peter C.
Model Predictability- Form Lorenz System to Operational Ocean and Atmospheric Models Peter C Chu. Poberezhny, 2002: Power law decay in model predictability skill. Geophysical Research Letters, 29 (15), 10 Six Months Four-Times Daily Data From July 9, 1998 for Verification #12;Model Generated Velocity
The myth of science-based predictive modeling.
Hemez, F. M. (François M.)
2004-01-01
A key aspect of science-based predictive modeling is the assessment of prediction credibility. This publication argues that the credibility of a family of models and their predictions must combine three components: (1) the fidelity of predictions to test data; (2) the robustness of predictions to variability, uncertainty, and lack-of-knowledge; and (3) the prediction accuracy of models in cases where measurements are not available. Unfortunately, these three objectives are antagonistic. A recently published Theorem that demonstrates the irrevocable trade-offs between fidelity-to-data, robustness-to-uncertainty, and confidence in prediction is summarized. High-fidelity models cannot be made increasingly robust to uncertainty and lack-of-knowledge. Similarly, robustness-to-uncertainty can only be improved at the cost of reducing the confidence in prediction. The concept of confidence in prediction relies on a metric for total uncertainty, capable of aggregating different representations of uncertainty (probabilistic or not). The discussion is illustrated with an engineering application where a family of models is developed to predict the acceleration levels obtained when impacts of varying levels propagate through layers of crushable hyper-foam material of varying thicknesses. Convex modeling is invoked to represent a severe lack-of-knowledge about the constitutive material behavior. The analysis produces intervals of performance metrics from which the total uncertainty and confidence levels are estimated. Finally, performance, robustness and confidence are extrapolated throughout the validation domain to assess the predictive power of the family of models away from tested configurations.
Markovian Models for Electrical Load Prediction in Smart Buildings
California at Santa Barbara, University of
Markovian Models for Electrical Load Prediction in Smart Buildings Muhammad Kumail Haider, Asad,13100004,ihsan.qazi}@lums.edu.pk Abstract. Developing energy consumption models for smart buildings is important develop parsimo- nious Markovian models of smart buildings for different periods in a day for predicting
Predictive Models of Li-ion Battery Lifetime (Presentation) Smith...
Office of Scientific and Technical Information (OSTI)
Predictive Models of Li-ion Battery Lifetime (Presentation) Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Shi, Y.; Pesaran, A. 25 ENERGY STORAGE; 33 ADVANCED PROPULSION...
Martin, A; Venkatesan, Dr V Prasanna
2011-01-01
Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model from financial information of an organization by analyzing the Semantics of the financial statement of a business. One of the best bankruptcy prediction models is Altman Z-score model. Altman Z-score method uses financial rations to predict bankruptcy. From the financial ontological model the relation between financial data is discovered by using data mining algorithm. By combining financial domain ontological model with association rule mining algorithm and Zscore model a new business intelligence model is developed to predict the bankruptcy.
Climate Prediction: The Limits of Ocean Models
Stone, Peter H.
We identify three major areas of ignorance which limit predictability in current ocean GCMs. One is the very crude representation of subgrid-scale mixing processes. These processes are parameterized with coefficients whose ...
Predictive modeling of reactive wetting and metal joining.
van Swol, Frank B.
2013-09-01
The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.
On Predicting the Solar Cycle using Mean-Field Models
Paul J. Bushby; Steven M. Tobias
2007-04-18
We discuss the difficulties of predicting the solar cycle using mean-field models. Here we argue that these difficulties arise owing to the significant modulation of the solar activity cycle, and that this modulation arises owing to either stochastic or deterministic processes. We analyse the implications for predictability in both of these situations by considering two separate solar dynamo models. The first model represents a stochastically-perturbed flux transport dynamo. Here even very weak stochastic perturbations can give rise to significant modulation in the activity cycle. This modulation leads to a loss of predictability. In the second model, we neglect stochastic effects and assume that generation of magnetic field in the Sun can be described by a fully deterministic nonlinear mean-field model -- this is a best case scenario for prediction. We designate the output from this deterministic model (with parameters chosen to produce chaotically modulated cycles) as a target timeseries that subsequent deterministic mean-field models are required to predict. Long-term prediction is impossible even if a model that is correct in all details is utilised in the prediction. Furthermore, we show that even short-term prediction is impossible if there is a small discrepancy in the input parameters from the fiducial model. This is the case even if the predicting model has been tuned to reproduce the output of previous cycles. Given the inherent uncertainties in determining the transport coefficients and nonlinear responses for mean-field models, we argue that this makes predicting the solar cycle using the output from such models impossible.
Switching Between Discrete and Continuous Models To Predict Genetic Activity
Weld, Daniel S.
Molecular biologists use a variety of models when they predict the behavior of genetic systems. A discrete model of the behavior of individual macromolecular elements forms the foundation for their theory of each system. ...
Parametric modeling and control of telescope wind-induced vibration
MacMynowski, Douglas G. - MacMynowski, Douglas G.
-buffeting is presented. The model is being developed to support the design of next generation segmented-mirror optical: Parametric modeling, extremely large telescope, control, wind-buffeting 1. INTRODUCTION Various design the predictions of the former at one or more points in the design space. An initial parametric model of wind
A DETERMINISTIC PREDICTION MODEL FOR THE AMERICAN GAME OF FOOTBALL
Weaver, Adam Lee
A DETERMINISTIC PREDICTION MODEL FOR THE AMERICAN GAME OF FOOTBALL John Am Trono, Saint Michael's College Introduction This article describes a simulation model of the sport known as footballs It was created to predict results of post season football games, most notably college bowl games. By constructing
Predicting Protein Folding Kinetics via Temporal Logic Model Checking
Predicting Protein Folding Kinetics via Temporal Logic Model Checking Christopher James Langmead award from the U.S. Department of Energy. #12;Keywords: protein folding, model checking, temporal logic #12;Abstract We present a novel approach for predicting protein folding kinetics using techniques from
Valerio, Luis G. . E-mail: luis.valerio@FDA.HHS.gov; Arvidson, Kirk B.; Chanderbhan, Ronald F.; Contrera, Joseph F.
2007-07-01
Consistent with the U.S. Food and Drug Administration (FDA) Critical Path Initiative, predictive toxicology software programs employing quantitative structure-activity relationship (QSAR) models are currently under evaluation for regulatory risk assessment and scientific decision support for highly sensitive endpoints such as carcinogenicity, mutagenicity and reproductive toxicity. At the FDA's Center for Food Safety and Applied Nutrition's Office of Food Additive Safety and the Center for Drug Evaluation and Research's Informatics and Computational Safety Analysis Staff (ICSAS), the use of computational SAR tools for both qualitative and quantitative risk assessment applications are being developed and evaluated. One tool of current interest is MDL-QSAR predictive discriminant analysis modeling of rodent carcinogenicity, which has been previously evaluated for pharmaceutical applications by the FDA ICSAS. The study described in this paper aims to evaluate the utility of this software to estimate the carcinogenic potential of small, organic, naturally occurring chemicals found in the human diet. In addition, a group of 19 known synthetic dietary constituents that were positive in rodent carcinogenicity studies served as a control group. In the test group of naturally occurring chemicals, 101 were found to be suitable for predictive modeling using this software's discriminant analysis modeling approach. Predictions performed on these compounds were compared to published experimental evidence of each compound's carcinogenic potential. Experimental evidence included relevant toxicological studies such as rodent cancer bioassays, rodent anti-carcinogenicity studies, genotoxic studies, and the presence of chemical structural alerts. Statistical indices of predictive performance were calculated to assess the utility of the predictive modeling method. Results revealed good predictive performance using this software's rodent carcinogenicity module of over 1200 chemicals, comprised primarily of pharmaceutical, industrial and some natural products developed under an FDA-MDL cooperative research and development agreement (CRADA). The predictive performance for this group of dietary natural products and the control group was 97% sensitivity and 80% concordance. Specificity was marginal at 53%. This study finds that the in silico QSAR analysis employing this software's rodent carcinogenicity database is capable of identifying the rodent carcinogenic potential of naturally occurring organic molecules found in the human diet with a high degree of sensitivity. It is the first study to demonstrate successful QSAR predictive modeling of naturally occurring carcinogens found in the human diet using an external validation test. Further test validation of this software and expansion of the training data set for dietary chemicals will help to support the future use of such QSAR methods for screening and prioritizing the risk of dietary chemicals when actual animal data are inadequate, equivocal, or absent.
Wishart, Gordon C.; Azzato, Elizabeth M.; Greenberg, David C.; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D. P.
2010-01-06
Abstract Introduction The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Methods Using the Eastern Cancer Registration...
CFD Modeling for Mercury Control Technology
Madsen, J.I.
2006-12-01
Compliance with the Clean Air Mercury Rule will require implementation of dedicated mercury control solutions at a significant portion of the U.S. coal-fired utility fleet. Activated Carbon Injection (ACI) upstream of a particulate control device (ESP or baghouse) remains one of the most promising near-term mercury control technologies. The DOE/NETL field testing program has advanced the understanding of mercury control by ACI, but a persistent need remains to develop predictive models that may improve the understanding and practical implementation of this technology. This presentation describes the development of an advanced model of in-flight mercury capture based on Computational Fluid Dynamics (CFD). The model makes detailed predictions of the induct spatial distribution and residence time of sorbent, as well as predictions of mercury capture efficiency for particular sorbent flow rates and injection grid configurations. Hence, CFD enables cost efficient optimization of sorbent injection systems for mercury control to a degree that would otherwise be impractical both for new and existing plants. In this way, modeling tools may directly address the main cost component of operating an ACI system – the sorbent expense. A typical 300 MW system is expected to require between $1 and $2 million of sorbent per year, and so even modest reductions (say 10-20%) in necessary sorbent feed injection rates will quickly make any optimization effort very worthwhile. There are few existing models of mercury capture, and these typically make gross assumptions of plug gas flow, zero velocity slip between particle and gas phase, and uniform sorbent dispersion. All of these assumptions are overcome with the current model, which is based on first principles and includes mass transfer processes occurring at multiple scales, ranging from the large-scale transport in the duct to transport within the porous structure of a sorbent particle. In principle any single one of these processes could limit the overall capture of mercury. For example, capture may be severely limited in situations where the dispersion of sorbent is poor, or where adsorption rates are low because of relatively high temperatures. Application examples taken from the DOE/NETL field test program were considered. The sites considered include Brayton Point, Meramec, Monroe, and Yates. Some general lessons learned concerning the impact of turbulence and flow stratification on dispersion and capture will be presented.
LHC diphoton Higgs signal predicted by little Higgs models
Wang Lei; Yang Jinmin
2011-10-01
Little Higgs theory naturally predicts a light Higgs boson whose most important discovery channel at the LHC is the diphoton signal pp{yields}h{yields}{gamma}{gamma}. In this work, we perform a comparative study for this signal in some typical little Higgs models, namely, the littlest Higgs model, two littlest Higgs models with T-parity (named LHT-I and LHT-II), and the simplest little Higgs models. We find that compared with the standard model prediction, the diphoton signal rate is always suppressed and the suppression extent can be quite different for different models. The suppression is mild (< or approx. 10%) in the littlest Higgs model but can be quite severe ({approx_equal}90%) in other three models. This means that discovering the light Higgs boson predicted by the little Higgs theory through the diphoton channel at the LHC will be more difficult than discovering the standard model Higgs boson.
Modeling probability distributions with predictive state representations
Wiewiora, Eric Walter
2008-01-01
Discovery is the process of choosing the core tests, whose success probabilities will become the state of the learned model.
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE
Neumaier, Arnold
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE ARNOLD NEUMAIERcalled protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possible
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE
Neumaier, Arnold
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE ARNOLD NEUMAIER-called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary) structure of a protein, given its sequence of amino acids. The dynamic aspect asks about the possible
Model Formulation and Predictions for a Pyrotechnically Actuated Pin Puller*
for the simulated firing of an NSI into 1) a pin puller device, 2) a 10 cm3 closed vessel, and 3) an apparatus known as the Dynamic Test Device. The predictions are compared with experiments. The pressure magnitudes and time scales of pressure rise and decay are predicted well by the model. Introduction Pyrotechnically actuated
High Level antitative Hardware Prediction Modeling using Statistical methods
Bertels, Koen
essential to have efficient prediction models to drive early HW-SW partitioning and co-design. In this paper development and HW-SW co-design. Given an application composed of different kernels, in order to map one-level language description as input, enabling hardware prediction in the early design stages. We calibrate
Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction
McGovern, Amy
Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1 dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun, current techniques for predicting severe weather are tied to specific characteristics of the radar systems
Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction
Wirosoetisno, Djoko
Data Assimilation for Idealised Mathematical Models of Numerical Weather Prediction Supervisors). Background: Numerical Weather Prediction (NWP) has seen significant gains in accuracy in recent years due in weather dynamics, e.g., the asymptotic balance seen in high and low pressure systems. Aims of the project
A predictive ocean oil spill model
Sanderson, J.; Barnette, D.; Papodopoulos, P.; Schaudt, K.; Szabo, D.
1996-07-01
This is the final report of a two-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). Initially, the project focused on creating an ocean oil spill model and working with the major oil companies to compare their data with the Los Alamos global ocean model. As a result of this initial effort, Los Alamos worked closely with the Eddy Joint Industry Project (EJIP), a consortium oil and gas producing companies in the US. The central theme of the project was to use output produced from LANL`s global ocean model to look in detail at ocean currents in selected geographic areas of the world of interest to consortium members. Once ocean currents are well understood this information could be used to create oil spill models, improve offshore exploration and drilling equipment, and aid in the design of semi-permanent offshore production platforms.
Colliding cascades model for earthquake prediction
2000-10-12
on a direct cascade that would deliver energy from the largest size scales ... The general objective of the colliding cascades model has been to reproduce the ..... earthquake and critical phase transitions studied in statistical physics, where the
Conformal Higgs model: predicted dark energy density
R. K. Nesbet
2014-11-03
Postulated universal Weyl conformal scaling symmetry provides an alternative to the $\\Lambda$CDM paradigm for cosmology. Recent applications to galactic rotation velocities, Hubble expansion, and a model of dark galactic halos explain qualitative phenomena and fit observed data without invoking dark matter. Significant revision of theory relevant to galactic collisions and clusters is implied, but not yet tested. Dark energy is found to be a consequence of conformal symmetry for the Higgs scalar field of electroweak physics. The present paper tests this implication. The conformal Higgs model acquires a gravitational effect described by a modified Friedmann cosmic evolution equation, shown to fit cosmological data going back to the cosmic microwave background epoch. The tachyonic mass parameter of the Higgs model becomes dark energy in the Friedmann equation. A dynamical model of this parameter, analogous to the Higgs mechanism for gauge boson mass, is derived and tested here. An approximate calculation yields a result consistent with the empirical magnitude inferred from Hubble expansion.
Predictive capacity planning modeling with tactical and strategic applications
Zeppieri, Michael A. (Michael Anthony), 1975-
2004-01-01
The focus of my internship was the development of a predictive capacity planning model to characterize the storage requirements and space utilization for Amazon's Campbellsville (SDF) Fulfillment Center (FC). Amazon currently ...
Land Surface Model Data Assimilation for Atmospheric Prediction
Walker, Jeff
predictions from different models even when using the same parameters, inputs, and initial conditions (Houser remote sensing studies, using visible, thermal infrared (surface temperature) and microwave (passive and active) electromagnetic radiation. Of these, passive microwave soil moisture measurement has been
Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes
Hierarchical Bayesian Models for Predicting The Spread of Ecological Processes Christopher K. Wikle Department of Statistics, University of Missouri To appear: Ecology June 10, 2002 Key Words: Bayesian, Diffusion, Forecast, Hierarchical, House Finch, Invasive, Malthu- sian, State Space, Uncertainty Abstract
QMC Simulations DataBase for Predictive Theory and Modeling ...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
CO monoxide adsorbs on the Pt (111) surface CO monoxide adsorbs on the Pt (111) surface. One application of the QMC Simulations Database for the Predictive Modeling and Theory...
In silico modeling to predict drug-induced phospholipidosis
Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov; Sadrieh, Nakissa
2013-06-01
Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ? 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL.
Predicting species invasions using ecological niche modeling
Peterson, A. Townsend; Vieglais, David A.
2001-05-01
) and commission (including niche space not ,lctually occupied by the 'pecies). Each algorithm for modeling specIes' ecological niches involves a specific com binatiol1 of errors of omission ,md commission. A rel.ltively new approach, called the (;enetic...
PTEC: A System for Predictive Thermal and Energy Control in Data Centers
Xing, Guoliang
1 PTEC: A System for Predictive Thermal and Energy Control in Data Centers Jinzhu Chen Rui Tan presents the design and evaluation of PTEC a system for predictive thermal and energy control in data energy consumption by more than 30%, compared with baseline thermal control strategies. I. INTRODUCTION
Greenberg, Albert
Iterative Multivariate Regression Model for Correlated Responses Prediction S. Tom Au, Guangqin Ma- tive procedure to model multiple responses prediction into correlated multivariate predicting scheme, which is always favorable for responses separations in our multivariate prediction. We also point out
Mathiesen, Patrick; Collier, Craig; Kleissl, Jan
2013-01-01
of numerical weather prediction solar irradiance forecasts numerical weather prediction model for solar irradiance weather prediction for intra?day solar forecasting in the
Predictive models of circulating fluidized bed combustors
Gidaspow, D.
1992-07-01
Steady flows influenced by walls cannot be described by inviscid models. Flows in circulating fluidized beds have significant wall effects. Particles in the form of clusters or layers can be seen to run down the walls. Hence modeling of circulating fluidized beds (CFB) without a viscosity is not possible. However, in interpreting Equations (8-1) and (8-2) it must be kept in mind that CFB or most other two phase flows are never in a true steady state. Then the viscosity in Equations (8-1) and (8-2) may not be the true fluid viscosity to be discussed next, but an Eddy type viscosity caused by two phase flow oscillations usually referred to as turbulence. In view of the transient nature of two-phase flow, the drag and the boundary layer thickness may not be proportional to the square root of the intrinsic viscosity but depend upon it to a much smaller extent. As another example, liquid-solid flow and settling of colloidal particles in a lamella electrosettler the settling process is only moderately affected by viscosity. Inviscid flow with settling is a good first approximation to this electric field driven process. The physical meaning of the particulate phase viscosity is described in detail in the chapter on kinetic theory. Here the conventional derivation resented in single phase fluid mechanics is generalized to multiphase flow.
Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells
Zandstra, Peter W.
Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells microfluidic perfusion culture demonstrated that STAT3 activation and consequently mESC fate were manipulable
Predictive control and thermal energy storage for optimizing a multi-energy district boiler
Paris-Sud XI, Université de
Predictive control and thermal energy storage for optimizing a multi- energy district boiler Julien energy storage. 1. Introduction Managing energy demand, promoting renewable energy and finding ways
Modeling Social Cues: Effective Features for Predicting Listener Nods
Zhu, Xiaojin "Jerry"
Modeling Social Cues: Effective Features for Predicting Listener Nods Faisal Khan, Bilge Mutlu, we present preliminary work in modeling a particular communicative mechanism--listener nods observations of verbal and nonverbal cues from the speaker and listener nods and a hidden sub- structure
Classical Cepheid Pulsation Models. III. The Predictable Scenario
G. Bono; V. Castellani; M. Marconi
1999-08-02
Within the current uncertainties in the treatment of the coupling between pulsation and convection, limiting amplitude, nonlinear, convective models appear the only viable approach for providing theoretical predictions about the intrinsic properties of radial pulsators. In this paper we present the results of a comprehensive set of Cepheid models computed within such theoretical framework for selected assumptions on their original chemical composition.
Coarse graining and control theory model reduction
Carlson, Jean
Coarse graining and control theory model reduction David E. Reynolds 1 ABSTRACT: We explain a method, inspired by control the- ory model reduction and interpolation theory, that rigorously applicable to nonequilibrium systems. KEY WORDS: coarse graining; control theory; model reduc- tion; Hankel
Coarse graining and control theory model reduction
Carlson, Jean
Coarse graining and control theory model reduction David E. Reynolds 1 ABSTRACT: We explain a method, inspired by control theÂ ory model reduction and interpolation theory, that rigorously applicable to nonequilibrium systems. KEY WORDS: coarse graining; control theory; model reducÂ tion; Hankel
Lepton Flavor Violation in Predictive SUSY-GUT Models
Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine
2008-02-01
There have been many theoretical models constructed which aim to explain the neutrino masses and mixing patterns. While many of the models will be eliminated once more accurate determinations of the mixing parameters, especially sin{sup 2} 2{theta}{sub 13}, are obtained, charged lepton flavor violation (LFV) experiments are able to differentiate even further among the models. In this paper, they investigate various rare LFV processes, such as {ell}{sub i} {yields} {ell}{sub j} + {gamma} and {mu} - e conversion, in five predictive SUSY SO(10) models and their allowed soft SUSY breaking parameter space in the constrained minimal SUSY standard model (CMSSM). Utilizing the WMAP dark matter constraints, they obtain lower bounds on the branching ratios of these rare processes and find that at least three of the five models they consider give rise to predictions for {mu} {yields} e + {gamma} that will be tested by the MEG collaboration at PSI. in addition, the next generation {mu} - e conversion experiment has sensitivity to the predictions of all five models, making it an even more robust way to test these models. While generic studies have emphasized the dependence of the branching ratios of these rare processes on the reactor neutrino angle, {theta}{sub 13}, and the mass of the heaviest right-handed neutrino, M{sub 3}, they find very massive M{sub 3} is more significant than large {theta}{sub 13} in leading to branching ratios near to the present upper limits.
Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory
Gregor P. Henze; Moncef Krarti
2005-09-30
Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very simple short-term prediction models to realize almost all of the theoretical potential of this control strategy. Further work evaluated the impact of modeling accuracy on the model-based closed-loop predictive optimal controller to minimize utility cost. The following guidelines have been derived: For an internal heat gain dominated commercial building, reasonable geometry simplifications are acceptable without a loss of cost savings potential. In fact, zoning simplification may improve optimizer performance and save computation time. The mass of the internal structure did not show a strong effect on the optimization. Building construction characteristics were found to impact building passive thermal storage capacity. It is thus advisable to make sure the construction material is well modeled. Zone temperature setpoint profiles and TES performance are strongly affected by mismatches in internal heat gains, especially when they are underestimated. Since they are a key factor in determining the building cooling load, efforts should be made to keep the internal gain mismatch as small as possible. Efficiencies of the building energy systems affect both zone temperature setpoints and active TES operation because of the coupling of the base chiller for building precooling and the icemaking TES chiller. Relative efficiencies of the base and TES chillers will determine the balance of operation of the two chillers. The impact of mismatch in this category may be significant. Next, a parametric analysis was conducted to assess the effects of building mass, utility rate, building location and season, thermal comfort, central plant capacities, and an economizer on the cost saving performance of optimal control for active and passive building thermal storage inventory. The key findings are: (1) Heavy-mass buildings, strong-incentive time-of-use electrical utility rates, and large on-peak cooling loads will likely lead to attractive savings resulting from optimal combined thermal storage control. (2) By using economizer to take advantage of the cool fresh air during the night, the bu
Model based dependability evaluation for automotive control functions
Schlingloff, Holger
Model based dependability evaluation for automotive control functions Sasa Vulinovic 1 , Bernd@informatik.hu-berlin.de Abstract In this paper, we study the evaluation of reliability for embedded functions in automotive. In order to assess fault tolerant designs for automotive software it is essential to be able to predict
A data-driven neuromuscular model of walking and its application to prosthesis control
Markowitz, Jared (Jared John)
2013-01-01
In this thesis we present a data-driven neuromuscular model of human walking and its application to prosthesis control. The model is novel in that it leverages tendon elasticity to more accurately predict the metabolic ...
USING A PHYSIOLOGICAL MODEL FOR PREDICTION OF THERAPY EFFECTS IN
Long, William J.
. Long, Shapur Naimi, M. G. Criscitiello, Robert Jayes M.I.T. Laboratory for Computer Science, Cambridge, based on signal flow analysis, for predicting hemodynamic changes using a model of physiological Library of Medicine. 2 #12; 1 Introduction As the variety of diagnostic and therapeutic modalities
Reference wind farm selection for regional wind power prediction models
Paris-Sud XI, Université de
1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals
The origins of computer weather prediction and climate modeling
Lynch, Peter [Meteorology and Climate Centre, School of Mathematical Sciences, University College Dublin, Belfield (Ireland)], E-mail: Peter.Lynch@ucd.ie
2008-03-20
Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.
Predictive modeling of thermoelastic energy dissipation in tunable MEMS mirrors
Yi, Yun-Bo
Predictive modeling of thermoelastic energy dissipation in tunable MEMS mirrors Houwen Tang is of significant importance in many microelectromechanical sys- tem MEMS applications. Thermoelastic damping can such as MEMS mirrors. We deal with the simulation and analysis of thermoelastic damping of MEMS mirrors based
Penetration rate prediction for percussive drilling via dry friction model
Krivtsov, Anton M.
Penetration rate prediction for percussive drilling via dry friction model Anton M. Krivtsov a of percussive drilling assuming a dry friction mechanism to explain the experimentally observed drop in pene in drilling research is a fall of pene- tration rate for higher static loads. This is known both
Ensemble climate predictions using climate models and observational constraints
REVIEW Ensemble climate predictions using climate models and observational constraints BY PETER A. STOTT 1,* AND CHRIS E. FOREST 2 1 Hadley Centre for Climate Change (Reading Unit), Meteorology Building, Massachusetts Institute of Technology, Cambridge, MA 02139, USA Two different approaches are described
Predicting solar cycle 24 with a solar dynamo model
Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang
2007-01-18
Whether the upcoming cycle 24 of solar activity will be strong or not is being hotly debated. The solar cycle is produced by a complex dynamo mechanism. We model the last few solar cycles by `feeding' observational data of the Sun's polar magnetic field into our solar dynamo model. Our results fit the observed sunspot numbers of cycles 21-23 extremely well and predict that cycle~24 will be about 35% weaker than cycle~23.
ScoPred--Scalable User-Directed Performance Prediction Using Complexity Modeling and Historical Data
Feitelson, Dror
complexity models, good prediction accuracy can be obtained. 1 Introduction The typical approach in parallel, partic
A Prediction of Energy Savings Resulting from Building Infiltration Control
McWatters, K.; Claridge, D. E.; Liu, M.
1996-01-01
, working to reduce or increase it. This study uses simulation to evaluate the potential energy impact of the interaction when several different strategies for controlling air leakage direction and velocity in building envelope components are implemented...
Identification, Prediction and Control of Aero Optical Wavefronts in Laser Beam Propagation
Gordeyev, Stanislav
Identification, Prediction and Control of Aero Optical Wavefronts in Laser Beam Propagation and control of aero-optical wavefronts derived from recent flight-test data. The optimal controller is based the statistics of the aero-optical wavefront sequence. Experimental result in the paper show the improvement
Enhance Computational Efficiency of Neural Network Predictive Control Using PSO with
Li, Yangmin
Enhance Computational Efficiency of Neural Network Predictive Control Using PSO with Controllable velocity (PSO-CREV), to re- place of GDA in NNPC. Therefore for one cycle of control, PSO-CREV needs less iterations than GDA, and less population size than conven- tional PSO. Hence the computational cost of NNPC
Solar cycle prediction using precursors and flux transport models
R. Cameron; M. Schuessler
2006-12-22
We study the origin of the predictive skill of some methods to forecast the strength of solar activity cycles. A simple flux transport model for the azimuthally averaged radial magnetic field at the solar surface is used, which contains a source term describing the emergence of new flux based on observational sunspot data. We consider the magnetic flux diffusing over the equator as a predictor, since this quantity is directly related to the global dipole field from which a Babcock-Leighton dynamo generates the toroidal field for the next activity cycle. If the source is represented schematically by a narrow activity belt drifting with constant speed over a fixed range of latitudes between activity minima, our predictor shows considerable predictive skill with correlation coefficients up to 0.95 for past cycles. However, the predictive skill is completely lost when the actually observed emergence latitudes are used. This result originates from the fact that the precursor amplitude is determined by the sunspot activity a few years before solar minimum. Since stronger cycles tend to rise faster to their maximum activity (known as the Waldmeier effect), the temporal overlapping of cycles leads to a shift of the minimum epochs that depends on the strength of the following cycle. This information is picked up by precursor methods and also by our flux transport model with a schematic source. Therefore, their predictive skill does not require a memory, i.e., a physical connection between the surface manifestations of subsequent activity cycles.
QUALITY PREDICTION AND CONTROL IN ROLLING PROCESSES USING LOGISTIC REGRESSION
Li, Jing
information about the process and product, it is a challenging task to develop a systematic method to model minimum number of process variables in the model, based on which product qualities can be adequately) to collect abundant information of the process, it now becomes possible for knowledge discovery
On the Predictiveness of Single-Field Inflationary Models
C. P. Burgess; Subodh P. Patil; Michael Trott
2015-07-20
We re-examine the predictiveness of single-field inflationary models and discuss how an unknown UV completion can complicate determining inflationary model parameters from observations, even from precision measurements. Besides the usual naturalness issues associated with having a shallow inflationary potential, we describe another issue for inflation, namely, unknown UV physics modifies the running of Standard Model (SM) parameters and thereby introduces uncertainty into the potential inflationary predictions. We illustrate this point using the minimal Higgs Inflationary scenario, which is arguably the most predictive single-field model on the market, because its predictions for $A_s$, $r$ and $n_s$ are made using only one new free parameter beyond those measured in particle physics experiments, and run up to the inflationary regime. We find that this issue can already have observable effects. At the same time, this UV-parameter dependence in the Renormalization Group allows Higgs Inflation to occur (in principle) for a slightly larger range of Higgs masses. We comment on the origin of the various UV scales that arise at large field values for the SM Higgs, clarifying cut off scale arguments by further developing the formalism of a non-linear realization of $\\rm SU_L(2) \\times U(1)$ in curved space. We discuss the interesting fact that, outside of Higgs Inflation, the effect of a non-minimal coupling to gravity, even in the SM, results in a non-linear EFT for the Higgs sector. Finally, we briefly comment on post BICEP2 attempts to modify the Higgs Inflation scenario.
Compiler And Runtime Support For Predictive Control Of Power And Cooling
Dietz, Henry G. "Hank"
1 Compiler And Runtime Support For Predictive Control Of Power And Cooling Henry G. Dietz William R clusters make significant demands on the power and cooling infrastructure. Minimizing the impact achieving the best system performance by predicting and avoiding power and cooling problems. Although
Prediction of interest rate using CKLS model with stochastic parameters
Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)
2014-06-19
The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector ?{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j?-th time point where j?j??j+n. To model the variation of ?{sup (j)}, we assume that ?{sup (j)} depends on ?{sup (j?m)}, ?{sup (j?m+1)},…, ?{sup (j?1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d?2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.
A prediction of energy savings resulting from building infiltration control
McWatters, Kenneth Rob
1995-01-01
This thesis provides a description of the methods of application of theoretical models of heat transfer in computer simulations, to determine the energy performance of a wall or building. The heat transfer simulations include calculation equations...
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity
Bejerano, Gill
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity Qingyuan Zhao Stanford: Algorithms; Experimentation. Keywords: information diffusion; cascade prediction; self-exciting point process
Neutrino minimal standard model predictions for neutrinoless double beta decay
Bezrukov, F. [Institute for Nuclear Research of the Russian Academy of Sciences, 60th October Anniversary prospect 7a, Moscow 117312 (Russian Federation) and Institut de Theorie des Phenomenes Physiques, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland)
2005-10-01
Prediction of the effective Majorana mass for neutrinoless double {beta} decay in a simple extension of the standard model ({nu}MSM) is given. The model adds three right-handed neutrinos with masses smaller than the electroweak scale and explains dark matter of the Universe. This leads to constraints 1.3
Evaluation of a mathematical model in predicting intake of growing and finishing cattle
Bourg, Brandi Marie
2009-05-15
energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model’s accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance...
Modelling and Control of Activated Sludge Processes
Skogestad, Sigurd
Modelling and Control of Activated Sludge Processes Michela Mulas Dottorato di Ricerca of Activated Sludge Processes Michela Mulas Supervisors: Prof. Roberto Baratti Ing. Stefania Tronci Dottorato . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 ASP Models and Simulations 7 2.1 The Activated Sludge Process
arXiv:1307.5640v2[math.OC]18Nov2013 The Scenario Approach for Stochastic Model Predictive
Frei, Christoph
or load mitigation for wind turbines. For such sys- tems, a new control method of Scenario-Based ModelarXiv:1307.5640v2[math.OC]18Nov2013 The Scenario Approach for Stochastic Model Predictive Control. In the presence of model uncertainties or disturbances, for many control applications it suffices to keep
Bayesian System Identification and Response Predictions Robust to Modeling Uncertainty
Beck, James L.
.g. system ID, structural health monitoring, robust control, state &/or parameter estimation ) #12;33 Outline of seismic ground acceleration Finite element model with uncertain parameters Posterior analysis: During;55 System performance measure in the presence of uncertainty: Failure probability + - "Failure" t(t)iy i b i
Internally Electrodynamic Particle Model: Its Experimental Basis and Its Predictions
Zheng-Johansson, J X
2008-01-01
The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts, a) electric charges present with all material particles, b) an accelerated charge generates electromagnetic waves according to Maxwell's equations and Planck energy equation and c)source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first-principles solutions for the IED particles; several key solutions achieved will be outlined, including the de Broglie phase wave, de Broglie relations, Schr\\"odinger equation, mass, mass-energy relation, Newton's law of gravity, single particle self interference, and electromagnetic radiation and absorption; these equations or properties have long been broadly experimentally validated or demonstrated. The IED solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave ...
Modeling and Analysis ofModeling and Analysis of Hybrid Control SystemsHybrid Control Systems
Johansson, Karl Henrik
Modeling and Analysis ofModeling and Analysis of Hybrid Control SystemsHybrid Control Systems Karl.kth.se/~kallej MOVEP 2006, Bordeaux, France Karl H. Johansson, Hybrid control systems, MOVEP, Bordeaux on commands and autonomous actions #12;Karl H. Johansson, Hybrid control systems, MOVEP, Bordeaux, 2006
Development of a Procedure for the Predictive Control Strategy of a Chilled Water Storage System
Wei, G.; Sakuri, Y.; Claridge, D. E.; Turner, W. D.; Liu, M.
2000-01-01
cooling load during peak demand periods. This paper discusses the development of a simplified predictive control strategy for a 7000 ton-hour chilled water storage system serving a hospital. Control strategies are developed for both on-peak and off...
An approach to model validation and model-based prediction -- polyurethane foam case study.
Dowding, Kevin J.; Rutherford, Brian Milne
2003-07-01
Enhanced software methodology and improved computing hardware have advanced the state of simulation technology to a point where large physics-based codes can be a major contributor in many systems analyses. This shift toward the use of computational methods has brought with it new research challenges in a number of areas including characterization of uncertainty, model validation, and the analysis of computer output. It is these challenges that have motivated the work described in this report. Approaches to and methods for model validation and (model-based) prediction have been developed recently in the engineering, mathematics and statistical literatures. In this report we have provided a fairly detailed account of one approach to model validation and prediction applied to an analysis investigating thermal decomposition of polyurethane foam. A model simulates the evolution of the foam in a high temperature environment as it transforms from a solid to a gas phase. The available modeling and experimental results serve as data for a case study focusing our model validation and prediction developmental efforts on this specific thermal application. We discuss several elements of the ''philosophy'' behind the validation and prediction approach: (1) We view the validation process as an activity applying to the use of a specific computational model for a specific application. We do acknowledge, however, that an important part of the overall development of a computational simulation initiative is the feedback provided to model developers and analysts associated with the application. (2) We utilize information obtained for the calibration of model parameters to estimate the parameters and quantify uncertainty in the estimates. We rely, however, on validation data (or data from similar analyses) to measure the variability that contributes to the uncertainty in predictions for specific systems or units (unit-to-unit variability). (3) We perform statistical analyses and hypothesis tests as a part of the validation step to provide feedback to analysts and modelers. Decisions on how to proceed in making model-based predictions are made based on these analyses together with the application requirements. Updating modifying and understanding the boundaries associated with the model are also assisted through this feedback. (4) We include a ''model supplement term'' when model problems are indicated. This term provides a (bias) correction to the model so that it will better match the experimental results and more accurately account for uncertainty. Presumably, as the models continue to develop and are used for future applications, the causes for these apparent biases will be identified and the need for this supplementary modeling will diminish. (5) We use a response-modeling approach for our predictions that allows for general types of prediction and for assessment of prediction uncertainty. This approach is demonstrated through a case study supporting the assessment of a weapons response when subjected to a hydrocarbon fuel fire. The foam decomposition model provides an important element of the response of a weapon system in this abnormal thermal environment. Rigid foam is used to encapsulate critical components in the weapon system providing the needed mechanical support as well as thermal isolation. Because the foam begins to decompose at temperatures above 250 C, modeling the decomposition is critical to assessing a weapons response. In the validation analysis it is indicated that the model tends to ''exaggerate'' the effect of temperature changes when compared to the experimental results. The data, however, are too few and to restricted in terms of experimental design to make confident statements regarding modeling problems. For illustration, we assume these indications are correct and compensate for this apparent bias by constructing a model supplement term for use in the model-based predictions. Several hypothetical prediction problems are created and addressed. Hypothetical problems are used because no guidance was provided concern
MULTIVARIABLE NONLINEAR MODEL REFERENCE CONTROL OF CEMENT MILLS Mehmet nder Efe1
Efe, Mehmet Önder
MULTIVARIABLE NONLINEAR MODEL REFERENCE CONTROL OF CEMENT MILLS Mehmet Önder Efe1 and Okyay Kaynak2 reference control of a cement-milling circuit that has been studied previously. The approach presented studies focusing on cement mills have appeared. Clarke (1988) discusses the predictive control technique
MODELING AND CONTROL OF A O2/CO2 GAS TURBINE CYCLE FOR CO2 CAPTURE
Foss, Bjarne A.
MODELING AND CONTROL OF A O2/CO2 GAS TURBINE CYCLE FOR CO2 CAPTURE Lars Imsland Dagfinn Snarheim and control of a semi-closed O2/CO2 gas turbine cycle for CO2 capture. In the first part the process predictive control, Gas turbines, CO2 capture 1. INTRODUCTION Gas turbines are widely used for power
A Probabilistic Particle Control Approximation of Chance Constrained Stochastic Predictive Control
Williams, Brian C.
and can control a ground vehicle while being robust to brake failures. I. INTRODUCTION Robust control such as failures. We demonstrate in simulation that the new method is able to control an aircraft in turbulence control ensures that failure is prevented under all possible uncertainties. In many cases, for example
Almassalkhi, MR; Hiskens, IA
2015-01-01
A novel model predictive control (MPC) scheme is developed for mitigating the effects of severe line-overload disturbances in electrical power systems. A piece-wise linear convex approximation of line losses is employed to model the effect of transmission line power flow on conductor temperatures. Control is achieved through a receding-horizon model predictive control (MPC) strategy which alleviates line temperature overloads and thereby prevents the propagation of outages. The MPC strategy adjusts line flows by rescheduling generation, energy storage and controllable load, while taking into account ramp-rate limits and network limitations. In Part II of this paper, the MPC strategy is illustrated through simulation of the IEEE RTS-96 network, augmented to incorporate energy storage and renewable generation.
Crucial stages of protein folding through a solvable model: Predicting target sites
Cecconi, Fabio
Crucial stages of protein folding through a solvable model: Predicting target sites for enzyme. Keywords: Protein-folding modeling; prediction of key folding sites; HIV-1 protease; drug resistance One
Development of a fourth generation predictive capability maturity model.
Hills, Richard Guy; Witkowski, Walter R.; Urbina, Angel; Rider, William J.; Trucano, Timothy Guy
2013-09-01
The Predictive Capability Maturity Model (PCMM) is an expert elicitation tool designed to characterize and communicate completeness of the approaches used for computational model definition, verification, validation, and uncertainty quantification associated for an intended application. The primary application of this tool at Sandia National Laboratories (SNL) has been for physics-based computational simulations in support of nuclear weapons applications. The two main goals of a PCMM evaluation are 1) the communication of computational simulation capability, accurately and transparently, and 2) the development of input for effective planning. As a result of the increasing importance of computational simulation to SNL's mission, the PCMM has evolved through multiple generations with the goal to provide more clarity, rigor, and completeness in its application. This report describes the approach used to develop the fourth generation of the PCMM.
SNO+: predictions from standard solar models and spin flavour precession
Marco Picariello; João Pulido; S. Andringa; N. F. Barros; J. Maneira
2007-10-22
Time variability of the solar neutrino flux especially in the low and intermediate energy sector remains an open question and, if it exists, it is likely to be originated from the magnetic moment transition from active to light sterile neutrinos at times of intense solar activity and magnetic field. We examine the prospects for the SNO+ experiment to address this important issue and to distinguish between the two classes of solar models which are currently identified as corresponding to a high (SSM I) and a low (SSM II) heavy element abundance. We also evaluate the predictions from these two models for the Chlorine experiment event rate in the standard LMA and LMA+Spin Flavour Precession (SFP) scenarios. It is found that after three years of SNO+ data taking, the pep flux measurement will be able to discriminate between the standard LMA and LMA+SFP scenarios, independently of which is the correct solar model. If the LMA rate is measured, SFP with $B_0 \\sim 280kG$ for the resonant $\\Delta m^2_{01}$ can be excluded at more than $4\\sigma$. A low rate would signal new physics, excluding all the 90% allowed range of the standard LMA solution at 3$\\sigma$, and a time variability would be a strong signature of the SFP model. The CNO fluxes are the ones for which the two SSM predictions exhibit the largest differences, so their measurement at SNO+ will be important to favour one or the other. The distinction will be clearer after LMA or SFP are confirmed with pep, but still, a CNO measurement at the level of SSM I/LMA will disfavour SSM II at about $3 \\sigma$. We conclude that consistency between future pep and CNO flux measurements at SNO+ and Chlorine would either favour an LMA+SFP scenario or favour SSM II over SSM I.
How Computational Models Predict the Behavior of Complex Systems John Symons 1
Boschetti, Fabio
How Computational Models Predict the Behavior of Complex Systems John Symons 1 Fabio Boschetti2,3 1 of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions
Beating the bookie: A look at statistical models for prediction of football matches
Langseth, Helge
Beating the bookie: A look at statistical models for prediction of football matches Helge LANGSETH, Norway Abstract. In this paper we look at statistical models for predicting the outcome of football. Keywords. Association football, statistical models, predictions, betting 1. Introduction Association
Colliding cascades model for earthquake prediction Andrei Gabrielov,1,2
Gabrielov, Andrei
Colliding cascades model for earthquake prediction Andrei Gabrielov,1,2 Ilya Zaliapin,3 William I Lafayette, IN 47907-1395, USA 3 International Institute of Earthquake Prediction Theory and Mathematical model of seismicity, and their performance in the prediction of major model earthquakes is evaluated
Climate predictions: the chaos and complexity in climate models
Dragutin T. Mihailovi?; Gordan Mimi?; Ilija Arseni?
2013-10-15
Some issues which are relevant for the recent state in climate modeling have been considered. A detailed overview of literature related to this subject is given. The concept in modeling of climate, as a complex system, seen through Godel's Theorem and Rosen's definition of complexity and predictability is discussed. It is pointed out to occurrence of chaos in computing the environmental interface temperature from the energy balance equation given in a difference form. A coupled system of equations, often used in climate models is analyzed. It is shown that the Lyapunov exponent mostly has positive values allowing presence of chaos in this systems. The horizontal energy exchange between environmental interfaces, which is described by the dynamics of driven coupled oscillators, is analyzed. Their behavior and synchronization, when a perturbation is introduced in the system, as a function of the coupling parameters, the logistic parameter and the parameter of exchange, was studied calculating the Lyapunov exponent under simulations with the closed contour of N=100 environmental interfaces. Finally, we have explored possible differences in complexities of two global and two regional climate models using their output time series by applying the algorithm for calculating the Kolmogorov complexity.
Modelling artificial pheromone strategies for SPB control
Isakson, Kyle George
1981-01-01
MODELLING ARTIFICIAL PHEROMONE STRATEGIES FOR SPB CONTROL A Thesis Kyle George Isakson Submitted to the Graduate College of Texas AAM University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE August 19gl... of Department) -August 1981 ABSTRACT Modelling Artificial Pheromone Strategies for SPB Control. (August 1981) Kyle George Isakson, B. S. , Texas A&M University Co-Chairmen of Advisory Committee: Dr. Hain-1 Wu Dr. Youhanna Fares The development...
Kumaran, K.; Babu, V.
2009-04-15
In this numerical study, the influence of chemistry models on the predictions of supersonic combustion in a model combustor is investigated. To this end, 3D, compressible, turbulent, reacting flow calculations with a detailed chemistry model (with 37 reactions and 9 species) and the Spalart-Allmaras turbulence model have been carried out. These results are compared with earlier results obtained using single step chemistry. Hydrogen is used as the fuel and three fuel injection schemes, namely, strut, staged (i.e., strut and wall) and wall injection, are considered to evaluate the impact of the chemistry models on the flow field predictions. Predictions of the mass fractions of major species, minor species, dimensionless stagnation temperature, dimensionless static pressure rise and thrust percentage along the combustor length are presented and discussed. Overall performance metrics such as mixing efficiency and combustion efficiency are used to draw inferences on the nature (whether mixing- or kinetic-controlled) and the completeness of the combustion process. The predicted values of the dimensionless wall static pressure are compared with experimental data reported in the literature. The calculations show that multi step chemistry predicts higher and more wide spread heat release than what is predicted by single step chemistry. In addition, it is also shown that multi step chemistry predicts intricate details of the combustion process such as the ignition distance and induction distance. (author)
Hybrid coupled models of the tropical Paci c | II ENSO prediction
Hsieh, William
Hybrid coupled models of the tropical Paci#12;c | II ENSO prediction by Youmin Tang 1 , William W: ytang@cims.nyu.edu #12; Abstract Two hybrid coupled models (HCMs), a dynamical ocean model coupled Introduction Models for ENSO prediction can be categorized into purely statistical models, hybrid coupled
Internally Electrodynamic Particle Model: Its Experimental Basis and Its Predictions
J. X. Zheng-Johansson
2010-07-13
The internally electrodynamic (IED) particle model was derived based on overall experimental observations, with the IED process itself being built directly on three experimental facts, a) electric charges present with all material particles, b) an accelerated charge generates electromagnetic waves according to Maxwell's equations and Planck energy equation and c) source motion produces Doppler effect. A set of well-known basic particle equations and properties become predictable based on first principles solutions for the IED process; several key solutions achieved are outlined, including the de Broglie phase wave, de Broglie relations, Schr\\"odinger equation, mass, Einstein mass-energy relation, Newton's law of gravity, single particle self interference, and electromagnetic radiation and absorption; these equations and properties have long been broadly experimentally validated or demonstrated. A specific solution also predicts the Doebner-Goldin equation which emerges to represent a form of long-sought quantum wave equation including gravity. A critical review of the key experiments is given which suggests that the IED process underlies the basic particle equations and properties not just sufficiently but also necessarily.
Surussavadee, Chinnawat
2007-01-01
This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for ...
Flood Regulation by means of Model Predictive Control T. Barjas Blanco, P. Willems, P-K. Chiang, K. Cauwenberghs, B. De Moor and J. Berlamont Abstract In this chapter flooding regulation of the river Demer flooding events. Therefore, the local water administration provided the river with flood reservoirs
Nonlinear adaptive internal model control using neural networks
Gandhi, Amit Krushnavadan
2001-01-01
The IMC structure, where the controller implementation includes an explicit model of the plant, has been shown to be very effective for the control of the stable plants typically encountered in process control. A nonlinear internal model control...
Predictive modeling of synergistic effects in nanoscale ion track formation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Zarkadoula, Eva; Pakarinen, Olli H.; Xue, Haizhou; Zhang, Yanwen; Weber, William J.
2015-08-05
Molecular dynamics techniques and the inelastic thermal spike model are used to study the coupled effects of inelastic energy loss due to 21 MeV Ni ion irradiation and pre-existing defects in SrTiO3. We determine the dependence on pre-existing defect concentration of nanoscale track formation occurring from the synergy between the inelastic energy loss and the pre-existing atomic defects. We show that the nanoscale ion tracks’ size can be controlled by the concentration of pre-existing disorder. This work identifies a major gap in fundamental understanding concerning the role played by defects in electronic energy dissipation and electron–lattice coupling.
Modeling of Lean Exhaust Emissions Control Systems | Department...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Lean Exhaust Emissions Control Systems Modeling of Lean Exhaust Emissions Control Systems 2002 DEER Conference Presentation: National Renewable Energy Laboratory...
Bursty Traffic over CDMA: Predictive MAI Temporal Structure, Rate Control and Admission Control
Zhang, Junshan
's capacity laws [30]. Hence, in the wireless environment, one has to very carefully engineer the network the predictive MAI structure to construct a multiple time-scale interference predictor. Rate adaptation perspective based on marginal distributions). This approach cuts across the physical layer, medium access
Young, R. Michael
are built with traditional metrics of complexity, code churn, and fault history. We have performed to the code [17]. Hence, complexity metrics and code churn metrics have been used for fault prediction [5, 17 fault prediction metrics complexity, code churn, and fault history metrics for vulnerability
The Dark Gravity model predictions for Gravity Probe B
Frederic Henry-Couannier
2007-10-23
The previous version of this article gave erroneous predictions. The correct uptodate predictions can be found in the section devoted to gravitomagnetism in the living review of the Dark Gravity theory: gr-qc/0610079 The most natural prediction is zero frame dragging and the same geodetic effect as predicted by GR. However, a straightforward extension of the theory could lead to the same frame-dragging as in GR.
ZEPHYR THE PREDICTION MODELS T.S. Nielsen, H. Madsen, H. Aa. Nielsen
models and methods for predicting the wind power output from wind farms. The system is being developed are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions farms the Prediktor model developed at Risø and the Wind Power Prediction Tool (WPPT) developed at IMM
Selection of Ground Motion Prediction Equations for the Global Earthquake Model
Paris-Sud XI, Université de
1 Selection of Ground Motion Prediction Equations for the Global Earthquake Model Jonathan P are developed. Keywords: Engineering seismology, ground-motion prediction, site effects, Global Earthquake Model.EERI, and Peter J. Stafford, h) M.EERI Ground-motion prediction equations (GMPEs) relate ground-motion intensity
Building risk prediction models -with a focus on Genome-Wide Association Studies
Brent, Roger
Kooperberg Charles Kooperberg Predictive models for GWAS #12;Risk prediction models Based on data: (Di , Xi1;Selection of predictors. Selection of predictors on the same data as training and/or evaluating models can data to evaluate your model as is part of your cross-validation procedure biases your results
Demonstrating and Validating a Next Generation Model-Based Controller...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Demonstrating and Validating a Next Generation Model-Based Controller for Fuel...
Advanced HD Engine Systems and Emissions Control Modeling and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
HD Engine Systems and Emissions Control Modeling and Analysis Advanced HD Engine Systems and Emissions Control Modeling and Analysis 2012 DOE Hydrogen and Fuel Cells Program and...
Advanced LD Engine Systems and Emissions Control Modeling and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
LD Engine Systems and Emissions Control Modeling and Analysis Advanced LD Engine Systems and Emissions Control Modeling and Analysis 2012 DOE Hydrogen and Fuel Cells Program and...
Advanced PHEV Engine Systems and Emissions Control Modeling and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
PHEV Engine Systems and Emissions Control Modeling and Analysis Advanced PHEV Engine Systems and Emissions Control Modeling and Analysis 2011 DOE Hydrogen and Fuel Cells Program,...
Reference Model for Control and Automation Systems in Electrical...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Model for Control and Automation Systems in Electrical Power (October 2005) Reference Model for Control and Automation Systems in Electrical Power (October 2005) Modern...
Experimental Studies for DPF and SCR Model, Control System, and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
DPF and SCR Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels Experimental Studies for DPF and SCR Model, Control System, and OBD...
Aggregated Modeling and Control of Air Conditioning Loads for...
Office of Scientific and Technical Information (OSTI)
Journal Article: Aggregated Modeling and Control of Air Conditioning Loads for Demand Response Citation Details In-Document Search Title: Aggregated Modeling and Control of Air...
Model based control of a coke battery
Stone, P.M.; Srour, J.M.; Zulli, P. [BHP Research, Mulgrave (Australia). Melbourne Labs.; Cunningham, R.; Hockings, K. [BHP Steel, Pt Kembla, New South Wales (Australia). Coal and Coke Technical Development Group
1997-12-31
This paper describes a model-based strategy for coke battery control at BHP Steel`s operations in Pt Kembla, Australia. The strategy uses several models describing the battery thermal and coking behavior. A prototype controller has been installed on the Pt Kembla No. 6 Battery (PK6CO). In trials, the new controller has been well accepted by operators and has resulted in a clear improvement in battery thermal stability, with a halving of the standard deviation of average battery temperature. Along with other improvements to that battery`s operations, this implementation has contributed to a 10% decrease in specific battery energy consumption. A number of enhancements to the low level control systems on that battery are currently being undertaken in order to realize further benefits.
Application of the cumulative risk model in predicting school readiness in Head Start children
Rodriguez-Escobar, Olga Lydia
2009-05-15
This study investigates the degree to which the cumulative risk index predicted school readiness in a Head Start population. In general, the reviewed studies indicated the cumulative risk model was efficacious in predicting adverse developmental...
Predictive models of safety based on audit findings: Part 1: Model development and reliability
Wu, Changxu (Sean)
tools to carry out an ergonomic evaluation of maintenance and inspection operations. It was validated, we developed a Human Factors/Ergonomics classifi- cation framework based on HFACS model (Shappell to proceed with prediction validity testing in Part 2. Ó 2012 Elsevier Ltd and The Ergonomics Society. All
Babiker, Mustafa H.M.; Reilly, John M.; Mayer, Monika.; Eckaus, Richard S.; Sue Wing, Ian.; Hyman, Robert C.
The Emissions Prediction and Policy Analysis (EPPA) model is a component of the MIT Integrated Earth Systems Model (IGSM). Here, we provide an overview of the model accessible to a broad audience and present the detailed ...
A Forward Looking Version of the MIT Emissions Prediction and Policy Analysis (EPPA) Model
Babiker, Mustafa M.H.
This paper documents a forward looking multi-regional general equilibrium model developed from the latest version of the recursive-dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model. The model represents ...
The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4
Paltsev, Sergey.
The Emissions Prediction and Policy Analysis (EPPA) model is the part of the MIT Integrated Global Systems Model (IGSM) that represents the human systems. EPPA is a recursive-dynamic multi-regional general equilibrium model ...
Designing Output-Feedback Predictive Controllers by Reverse-Engineering Existing LTI Controllers
Hartley, Edward N.; Maciejowski, Jan M.
2013-04-17
, pp. 349–351, Jun. 1972. [9] C. Rowe and J. Maciejowski, “Tuning MPC using H? loop shaping,” in Proc. American Control Conf., vol. 2, Chicago, IL, USA, Jun 28–30 2000, pp. 1332–1336. [10] D. McFarlane and K. Glover, “A loop-shaping design procedure... , vol. 79, no. 4, pp. 279–287, Apr. 2006. [15] D. Alazard, “Cross standard form for generalized inverse problem: application to lateral flight control of a highly flexible aircraft,” in Proc. Int. Conf. Nonlinear Problems in Aviation and Aerospace...
Transistor roadmap projection using predictive full-band atomistic modeling
Salmani-Jelodar, M., E-mail: m.salmani@gmail.com; Klimeck, G. [Network for Computational Nanotechnology and School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907 (United States); Kim, S. [Intel Corporation, 2501 Northwest 229th Avenue, Hillsboro, Oregon 97124 (United States); Ng, K. [Semiconductor Research Corporation (SRC), 1101 Slater Rd, Durham, North Carolina 27703 (United States)
2014-08-25
In this letter, a full band atomistic quantum transport tool is used to predict the performance of double gate metal-oxide-semiconductor field-effect transistors (MOSFETs) over the next 15?years for International Technology Roadmap for Semiconductors (ITRS). As MOSFET channel lengths scale below 20?nm, the number of atoms in the device cross-sections becomes finite. At this scale, quantum mechanical effects play an important role in determining the device characteristics. These quantum effects can be captured with the quantum transport tool. Critical results show the ON-current degradation as a result of geometry scaling, which is in contrast to previous ITRS compact model calculations. Geometric scaling has significant effects on the ON-current by increasing source-to-drain (S/D) tunneling and altering the electronic band structure. By shortening the device gate length from 20?nm to 5.1?nm, the ratio of S/D tunneling current to the overall subthreshold OFF-current increases from 18% to 98%. Despite this ON-current degradation by scaling, the intrinsic device speed is projected to increase at a rate of at least 8% per year as a result of the reduction of the quantum capacitance.
Project Profile: Predictive Physico-Chemical Modeling of Intrinsic...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Advanced Reflector Materials NREL logo NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing...
Eulerian CFD Models to Predict Thermophoretic Deposition of Soot...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
This paper describes an Eulerian axisymmetric method in Fluent(R) to predict the overall heat transfer reduction of a surrogate tube due to thermophoretic deposition of submicron...
The Ideal Evaluation of a Risk Prediction Model: A Randomized Clinical Trial
Brent, Roger
The Ideal Evaluation of a Risk Prediction Model: A Randomized Clinical Trial Holly Janes Fred Hutchinson Cancer Research Center 1/25 #12;Context Often a risk prediction model is developed to identify high risk subjects who can benefit from preventative therapy E.g. Framingham risk model to identify
An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries
Pedram, Massoud
An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng cycle-life tends to shrink significantly. The capacities of commercial lithium-ion batteries fade by 10 prediction model to estimate the remaining capacity of a Lithium-Ion battery. The proposed analytical model
A Geologic Prediction Model For Tunneling By Photios G. Ioannou, A.M. ASCE
A Geologic Prediction Model For Tunneling By Photios G. Ioannou, A.M. ASCE Abstract: Geologic to inflated costs. This paper presents a general model for the probabilistic prediction of tunnel geology. The geologic conditions along the tunnel alignment are modeled by a set of geologic parameters (such as rock
Smart Structures: Model Development and Control Applications
Smart Structures: Model Development and Control Applications Ralph C. Smith Center for Research for smart structure which utilize piezoelectric, electrostrictive, magnetostrictive or shape memory alloys of the structure. The limitations on the mass and size of transducers are often relaxed in industrial applications
DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS
Garcia, Gonzalo Andres
2013-05-31
their lift and reduce their induced drag. A formation of UAS could take advantage of these aerodynamic effects, decreasing their energy consumption. Ref. [68] shows that in a V-formation of 25 members, each bird can achieve a reduction of induced drag.... In close formation, the wing aircraft experiences an upwash field generated by the preceding airplane 14 inducing a reduction in required overall energy. The manuscript defines tight formation as one where the lateral separation between aircraft...
MODEL PREDICTIVE CONTROL OF A MECHANICAL PULP BLEACHING PROCESS
Taylor, James H.
, and newsprint is around 55 %ISO. Pulp darkness is due to lignin and lignin degradation products when produced as a market pulp (Persley and Hill, 1996). The single- stage medium-consistency peroxide
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01
and passive building thermal storage. International Journalcooling towers, the thermal storage tank and the electricityand passive building thermal storage inventory: Part 1.
A Tutorial on Model Predictive Control for Spacecraft Rendezvous
Hartley, Edward N.
2015-05-26
by the linear inequalities Hox ? h0. For the chaser to remain outside of this set is a non- convex constraint, and imposing Hox(k) ? ho would be infeasible. If dim(ho) = nh, a workaround is to introduce an nh dimensional vector b(k) of binary variables, a... -based” 1?norm cost was used to improve robustness to uncertainties. The cost function is designed to be zero if the state is inside a hyper-cube ?b ? x ? b containing the setpoint, and a 1-norm penalty placed on the deviation s from this set: `(x, u) = ?Qs...
Model predictive control for energy efficient cooling and dehumidification
Zakula, Tea
2013-01-01
Energy has become a primary concern in countries worldwide, and is a focus of debates on national security, climate change, global economy, and the developing world. With more people in developing countries adopting the ...
Model Predictive Control of a Kaibel Distillation Column
Skogestad, Sigurd
.kvernland@reinertsen.com) and Department of Engineering Cybernetics, Norwegian University of Science and Technology, N-7034 Trondheim, Norway SINTEF ICT Applied Cybernetics, N-7465 Trondheim, Norway (e-mail: ivar.j.halvorsen@sintef.no) Department of Chemical Engineering, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
Model Predictive Control of a Kaibel Distillation Column
Skogestad, Sigurd
.kvernland@reinertsen.com) and Department of Engineering Cybernetics, Norwegian University of Science and Technology, N-7034 Trondheim Skogestad Reinertsen Engineering, N-7492 Trondheim, Norway (e-mail: martin, Norway SINTEF ICT Applied Cybernetics, N-7465 Trondheim, Norway (e-mail: ivar
Constrained model predictive control, state estimation and coordination
Yan, Jun
2006-01-01
of a formation of unmanned aerial vehicles’, Automatica 40,Kumar 2001), unmanned aerial vehicles ( Stipanovi´ ,Kumar 2001), unmanned aerial vehicles (Stipanovi´ , Inalhan,
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20
In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.
Broader source: Energy.gov [DOE]
Modeling the Number of Ignitions Following an Earthquake: Developing Prediction Limits for Overdispersed Count Data Elizabeth J. Kelly and Raymond N. Tell
Liu, Huan
Second International Workshop on Social Computing, Behavioral Modeling, and Prediction Phoenix, Arizona March 31 - April 1, 2009 Phoenix, Arizona Proceedings published by Springer Social computing
A System for Online Power Prediction in Virtualized Environments Using Gaussian Mixture Models
Simunic, Tajana
A System for Online Power Prediction in Virtualized Environments Using Gaussian Mixture Models In this paper we present a system for online power prediction in vir- tualized environments. It is based dynamically by our system to predict both the physical machine and per VM level power consumption. A real
Introduction to the model-free control of microgrids
Michel, Loïc
2011-01-01
This letter presents the application of the model-free control approach to the microgrid control. We show in simulation that the method allows to control, with a simple controller, voltage, current and power of inverter-based microgrids.
Parametric Urban Regulation Models for Predicting Development Performances
Kim, Jong Bum
2014-12-23
are significant indicators for predicting environmental footprints for the resource managements (Fischer and Guy, 2009; Lang, 1994; Punter, 1997). The prescriptive urban regulations such as FBC are less rigid in limiting density than the conventional zoning...
Burlatsky, S F; O'Neill, J; Atrazhev, V V; Varyukhin, A N; Dmitriev, D V; Erikhman, N S
2013-01-01
Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used...
Daigle, Matthew
, and availability. Prognos- tics deals with determining the health state of compo- nents, and projecting) predictions. Model-based prognos- tics approaches perform these tasks with the aid of a model that captures
Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1
Cook, Diane J.
Prediction Models for a Smart Home based Health Care System Vikramaditya R. Jakkula1 , Diane J health care. Smart health care systems at home can be used to provide such solutions. A technology a prediction model in an intelligent smart home system can be used for identifying health trends over time
Genetic Algorithm for Predicting Protein Folding in the 2D HP Model
Emmerich, Michael
Genetic Algorithm for Predicting Protein Folding in the 2D HP Model A Parameter Tuning Case Study of a protein, predicting its tertiary structure is known as the protein folding problem. This problem has been. The protein folding problem in the HP model is to find a conformation (a folded sequence) with the lowest
Budny, Robert
predictions using the GYRO verified and experimentally validated trapped gyro-Landau fluid transport model JITER predictions using the GYRO verified and experimentally validated trapped gyro-Landau fluid transport model This article has been downloaded from IOPscience. Please scroll down to see the full text
The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami)
Miami, University of
The US National Multi-Model Ensemble ISI Prediction System Ben Kirtman (University of Miami) The newly emerging US National Multi-Model Ensemble (NMME) sub-seasonal to interannual (ISI) prediction includes experimental real-time ISI forecasting that leverages existing CTB partner activities. The NMME
Hindi, Haitham; Prabhakar, Shyam; Fox, John D.; Linscott, Ivan; Teytelman, Dmitri; /SLAC
2011-08-31
We present a technique for the design and verification of efficient bunch-by-bunch controllers for damping longitudinal multibunch instabilities. The controllers attempt to optimize the use of available feedback amplifier power - one of the most expensive components of a feedback system - and define the limits of the closed loop system performance. Our design technique alternates between analytic computation of single bunch optimal controllers and verification on a multibunch numerical simulator. The simulator uses PEP-II parameters and identifies unstable coupled bunch modes, their growth rates and their damping rates with feedback. The results from the simulator are shown to be in reasonable agreement with analytical calculations based on the single bunch model. The technique is then used to evaluate the performance of a variety of controllers proposed for PEP-II.
Almassalkhi, MR; Hiskens, IA
2015-01-01
The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior.
Modeling Combustion Control for High Power Diesel Mode Switching...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Combustion Control for High Power Diesel Mode Switching Modeling Combustion Control for High Power Diesel Mode Switching Poster presentation given at the 16th Directions in...
Liu, Y. A.
Predictive Modeling of Large-Scale Commercial Water Desalination Plants: Data-Based Neural Network for developing predictive models for large-scale commercial water desalination plants by (1) a data (MSF) and reverse osmosis (RO) desalination plants in the world. Our resulting neural network
MBGP IN MODELLING AND PREDICTION Carlos OliverMorales
Fernandez, Thomas
(MBGP) encoding. Having multiple branches representing an individual allows us to get simpler), relative humidity (H), solar radiation (R) and wind speed (V) and direction (D) were recorded. The time). Cost function was predictive errorbased metric. For each experiment, 20 runs were evaluated in order
OCEAN PREDICTION WITH THE HYBRID COORDINATE OCEAN MODEL (HYCOM)
. of South Florida, Fugro-GEOS, ROFFS, Orbimage, Shell, ExxonMobil #12;414 ERIC P. CHASSIGNET ET AL-resolving, real-time global and basin-scale ocean prediction system in the context of the Global Ocean Data Assimilation Experiment (GODAE). Keywords: HYCOM, GODAE, LAS, data assimilation, metrics. 1. Introduction
Predicting Solar Flares by Data Assimilation in Avalanche Models. I. Model Design and Validation
Eric Bélanger; Alain Vincent; Paul Charbonneau
2007-08-14
Data assimilation techniques, developed in the last two decades mainly for weather prediction, produce better forecasts by taking advantage of both theoretical/numerical models and real-time observations. In this paper, we explore the possibility of applying the data-assimilation techniques known as 4D-VAR to the prediction of solar flares. We do so in the context of a continuous version of the classical cellular-automaton-based self-organized critical avalanche models of solar flares introduced by Lu and Hamilton (Astrophys. J., 380, L89, 1991). Such models, although a priori far removed from the physics of magnetic reconnection and magneto-hydrodynamical evolution of coronal structures, nonetheless reproduce quite well the observed statistical distribution of flare characteristics. We report here on a large set of data assimilation runs on synthetic energy release time series. Our results indicate that, despite the unpredictable (and unobservable) stochastic nature of the driving/triggering mechanism within the avalanche model, 4D-VAR succeeds in producing optimal initial conditions that reproduce adequately the time series of energy released by avalanches/flares. This is an essential first step towards forecasting real flares.
Watney, W.L.
1992-01-01
Interdisciplinary studies of the Upper Pennsylvanian Lansing and Kansas City groups have been undertaken in order to improve the geologic characterization of petroleum reservoirs and to develop a quantitative understanding of the processes responsible for formation of associated depositional sequences. To this end, concepts and methods of sequence stratigraphy are being used to define and interpret the three-dimensional depositional framework of the Kansas City Group. The investigation includes characterization of reservoir rocks in oil fields in western Kansas, description of analog equivalents in near-surface and surface sites in southeastern Kansas, and construction of regional structural and stratigraphic framework to link the site specific studies. Geologic inverse and simulation models are being developed to integrate quantitative estimates of controls on sedimentation to produce reconstructions of reservoir-bearing strata in an attempt to enhance our ability to predict reservoir characteristics.
A novel mathematical model for controllable near-field electrospinning
Ru, Changhai E-mail: luojun@shu.edu.cn; Robotics and Microsystems Center, Soochow University, Suzhou 215021 ; Chen, Jie; Shao, Zhushuai; Pang, Ming; Luo, Jun E-mail: luojun@shu.edu.cn
2014-01-15
Near-field electrospinning (NFES) had better controllability than conventional electrospinning. However, due to the lack of guidance of theoretical model, precise deposition of micro/nano fibers could only accomplished by experience. To analyze the behavior of charged jet in NFES using mathematical model, the momentum balance equation was simplified and a new expression between jet cross-sectional radius and axial position was derived. Using this new expression and mass conservation equation, expressions for jet cross-sectional radius and velocity were derived in terms of axial position and initial jet acceleration in the form of exponential functions. Based on Slender-body theory and Giesekus model, a quadratic equation for initial jet acceleration was acquired. With the proposed model, it was able to accurately predict the diameter and velocity of polymer fibers in NFES, and mathematical analysis rather than experimental methods could be applied to study the effects of the process parameters in NFES. Moreover, the movement velocity of the collector stage can be regulated by mathematical model rather than experience. Therefore, the model proposed in this paper had important guiding significance to precise deposition of polymer fibers.
Human walking model predicts joint mechanics, electromyography and mechanical economy
Endo, Ken
In this paper, we present an under-actuated model of human walking, comprising only a soleus muscle and flexion/extension monoarticular hip muscles. The remaining muscle groups of the human leg are modeled using quasi-passive, ...
1 Abstract--Eventually, prediction of transformer thermal performance for dynamic loading will be made using models distilled from measure data, rather than models derived from transformer heat for measuring the acceptability of transformer thermal models. For a model to be acceptable, it must have
Sleep Dynamics and Seizure Control in a Mesoscale Cortical Model
Lopour, Beth Ann
2009-01-01
Contributions . . . . . . . . . 2 Mesoscale Cortical Modelstates in h e from the mesoscale cortical model, here- afterand Seizure Control in a Mesoscale Cortical Model by Beth
Reduced-Order Model Based Feedback Control For Modified Hasegawa...
Office of Scientific and Technical Information (OSTI)
design problems) is applied to obtain a low dimensional model of the linearized MHW equation. Then a modelbased feedback controller is designed for the reduced order model using...
Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi; Tucker III, Charles L.; Costa, Franco
2013-12-18
This article illustrates the predictive capabilities for long-fiber thermoplastic (LFT) composites that first simulate the injection molding of LFT structures by Autodesk® Simulation Moldflow® Insight (ASMI) to accurately predict fiber orientation and length distributions in these structures. After validating fiber orientation and length predictions against the experimental data, the predicted results are used by ASMI to compute distributions of elastic properties in the molded structures. In addition, local stress-strain responses and damage accumulation under tensile loading are predicted by an elastic-plastic damage model of EMTA-NLA, a nonlinear analysis tool implemented in ABAQUS® via user-subroutines using an incremental Eshelby-Mori-Tanaka approach. Predicted stress-strain responses up to failure and damage accumulations are compared to the experimental results to validate the model.
Comparison of Uncertainty of Two Precipitation Prediction Models...
Office of Scientific and Technical Information (OSTI)
Lab Technical Area 54 Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has...
On Model Based Synthesis of Embedded Control Software Vadim Alimguzhin
Tronci, Enrico
Systems are indeed Software Based Control Sys- tems (SBCSs), that is control systems whose controller Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time Linear Hybrid System and the implementation specifications (that is, number of bits in the Analog-to-Digital
Predictive Models of Li-ion Battery Lifetime (Presentation) (Conference) |
Office of Scientific and Technical Information (OSTI)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield MunicipalTechnical Report:Speeding access toSmall Reactor forPatents -SciTech Connect Predictive
Predicting hurricane regional landfall rates: comparing local and basin-wide track model approaches
Hall, T; Hall, Tim; Jewson, Stephen
2006-01-01
We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses a basin-wide track model. Using cross-validation we show that the basin-wide track model gives better predictions for almost all parts of the coastline. This is the first time such a comparison has been made, and is the first rigourous justification for the use of basin-wide track models for predicting hurricane landfall rates and hurricane risk.
Validation of model based active control of combustion instability
Fleifil, M.; Ghoneim, Z.; Ghoniem, A.F.
1998-07-01
The demand for efficient, company and clean combustion systems have spurred research into the fundamental mechanisms governing their performance and means of interactively changing their performance characteristics. Thermoacoustic instability which is frequently observed in combustion systems with high power density, when burning close to the lean flammability limit, or using exhaust gas recirculation to meet more stringent emissions regulations, etc. Its occurrence and/or means to mitigate them passively lead to performance degradation such as reduced combustion efficiency, high local heat transfer rates, increase in the mixture equivalence ratio or system failure due to structural damage. This paper reports on their study of the origin of thermoacoustic instability, its dependence on system parameters and the means of actively controlling it. The authors have developed an analytical model of thermoacoustic instability in premixed combustors. The model combines a heat release dynamics model constructed using the kinematics of a premixed flame stabilized behind a perforated plate with the linearized conservation equations governing the system acoustics. This formulation allows model based controller design. In order to test the performance of the analytical model, a numerical solution of the partial differential equations governing the system has been carried out using the principle of harmonic separation and focusing on the dominant unstable mode. This leads to a system of ODEs governing the thermofluid variables. Analytical predictions of the frequency and growth ate of the unstable mode are shown to be in good agreement with the numerical simulations as well s with those obtained using experimental identification techniques when applied to a laboratory combustor. The authors use these results to confirm the validity of the assumptions used in formulating the analytical model. A controller based on the minimization of a cost function using the LQR technique has been designed using the analytical model and implemented on a bench top laboratory combustor. The authors show that the controller is capable of suppressing the pressure oscillations in the combustor with a settling time much shorter than what had been attained before and without exciting secondary peaks.
Unbiased Statistical Comparison of Creep and Shrinkage Prediction Models
, important for designing durable and safe concrete structures. Statistical methods of standard and several to improper data sampling in the database, and then examines Bazant and Baweja's model B3, ACI model, CEB of least squares, which is the standard and the only statistically correct method, dictated by the maximum
AN INTRODUCTION TO HYBRID SYSTEM MODELING, ANALYSIS, AND CONTROL
Pappas, George J.
AN INTRODUCTION TO HYBRID SYSTEM MODELING, ANALYSIS, AND CONTROL JOHN LYGEROS, GEORGE PAPPAS as models of large scale systems. We provide an overview of modeling, analysis, and controller synthesis automatically. Finally, we review a method for designing controllers for hybrid systems with reachability
Corani, Giorgio
2005-01-01
Ecological Modelling 185 (2005) 513529 Air quality prediction in Milan: feed-forward neural December 2004; accepted 3 January 2005 Abstract Ozone and PM10 constitute the major concern for air quality of Milan. This paper addresses the problem of the prediction of such two pollutants, using to this end
Towards Accurate and Practical Predictive Models of Active-Vision-Based Visual Search
Hornof, Anthony
which permit increasingly realistic and accurate predictions for visual human-computer interaction tasks not practical. For as long as human-computer interaction has been studied, researchers have been working@cs.uoregon.edu ABSTRACT Being able to predict the performance of interface designs using models of human cognition
Mixtures of Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems
Baveja, Satinder Singh
Mixtures of Predictive Linear Gaussian Models for Nonlinear Stochastic Dynamical Systems David dynamical systems. The primary contribution of this work is to extend the PLG to nonlinear, stochastic- proves upon traditional linear dynamical system mod- els by using a predictive representation of state
Wind Speed Modelling and Short-term Predic-tion using Wavelets
Nason, Guy
prediction of the wind regime at a proposed wind farm site. Suppose a small amount of wind speed data hasWind Speed Modelling and Short-term Predic- tion using Wavelets Katherine Hunt and Guy P Nason@bristol.ac.uk Abstract The mathematical method of wavelets is explained and used to predict wind condi- tions using short
Scientific Programming 11 (2003) 159176 159 A performance-prediction model for PIC
Vlad, Gregorio
2003-01-01
Scientific Programming 11 (2003) 159176 159 IOS Press A performance-prediction model for PIC hierarchical workload decomposition strategies for particle in cell (PIC) codes on Clusters of Symmetric Multi of parallelization efficiency are compared with the predicted results. 1. Introduction Particle-in-cell (PIC
Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model
Paris-Sud XI, Université de
Prediction of Solid Polycyclic Aromatic Hydrocarbons Solubility in Water with the NRTL-PR Model of solid polycyclic aromatic hydrocarbons in water. For this purpose, we first validate our methodology for fluid phase equilibria predictions of aromatic hydrocarbons and gas (CO2, C2H6) mixtures. Finally, we
Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model
Boyer, Edmond
Predicting the net carbon exchanges of crop rotations in Europe with an agro-ecosystem model S.Lehuger@art.admin.ch. Fax: (+41) 44 377 72 01. Phone: (+41) 44 377 75 13. hal-00414342,version2-1Sep2010 #12;Abstract Carbon and measuring land-atmosphere carbon exchanges from arable lands are important tasks to predict the influence
`TVLSI-00029-2003.R1 An Analytical Model for Predicting the Remaining Battery
Pedram, Massoud
`TVLSI-00029-2003.R1 1 An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries Peng Rong, Student Member, IEEE and Massoud Pedram, Fellow, IEEE Abstract -- Predicting the residual energy of the battery source that powers a portable electronic device is imperative in designing
Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model: An
Zhao, Xuepu
Discrepancies in the Prediction of Solar Wind using Potential Field Source Surface Model. This inverse relation has been made use of in the prediction of solar wind speed at 1 AU using a potential between the magnetic flux tube expansion factor (FTE) at the source surface and the solar wind speed
Modeling Cerebral Blood Flow Control During Posture Change from Sitting to Standing
Modeling Cerebral Blood Flow Control During Posture Change from Sitting to Standing Mette Olufsen that can predict blood flow and pressure during posture change from sitting to standing. The mathematical flow ve- locity during postural change from sitting to standing. The most important short term
Predictive models for power dissipation in optical transceivers
Butler, Katherine, 1981-
2004-01-01
Power dissipation in optical networks is a significant problem for the telecommunications industry. The optical transceiver was selected as a representative device of the network, and a component based power model is ...
Gosavi, Abhijit
Pollution Control in a Manufacturing System Stochastic Models for Analysis and Control of Air Pollution in a Manufacturing System Jan, 1, 2005 Technical Report SOPTL-05-01 Missouri University of Science models that can be used for controlling pollution in a manufacturing system. The models are developed
Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.
2009-07-15
A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled to reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.
Validity of the WEPP model for predicting infiltration on irrigated lands
Ngang, Fidelis Ndemah
1995-01-01
The objective of this research was to establish the validity of the hydrologic component of the YVEPP erosion model for predicting infiltration on irrigated lands. WEPP uses the Green and Ampt equation with ponding to compute infiltration...
How GIS and fire indices can be used in developing a fire prediction model for Scotland
MacKinnon, Frances
2008-12-05
This project looks at how GIS and the six fire indices from the Canadian Forest Fire Weather Index System (FWI) could be used to aid in developing a fire prediction model for Scotland. Information on land cover type, ...
A predictive, size-dependent continuum model for dense granular flows
Henann, David Lee
Dense granular materials display a complicated set of flow properties, which differentiate them from ordinary fluids. Despite their ubiquity, no model has been developed that captures or predicts the complexities of granular ...
ECOLOGICAL NICHE MODELING AS A PREDICTIVE TOOL: ASIATIC FRESHWATER FISHES IN NORTH AMERICA
Chen, Pingfu
2008-05-30
appropriately. After introduction, the most effective way is to predict their spread, to discover populations early, and to adopt measures to eradicate or at least contain them. This dissertation uses ecological niches modeling to estimate the ecological...
Prediction Capabilities of Vulnerability Discovery Models Omar H. Alhazmi, Colorado State University
Malaiya, Yashwant K.
Prediction Capabilities of Vulnerability Discovery Models Omar H. Alhazmi, Colorado State Discovery Models (VDMs) have been proposed to model vulnerability discovery and have has been fitted discovery process, presenting a static approach to estimating the initial values of one of the VDM
Modeling, Analysis, Predictions, and Projections Email: oar.cpo.mapp@noaa.gov
Earth system models to better simulate the climate system? Can we improve intraseasonal to seasonal mission, MAPP supports the development of advanced Earth system models that can predict climate variations, and the external research community. MAPP Objectives · Improve Earth system models · Achieve an integrated Earth
TESTS OF 1-D TRANSPORT MODELS, AND THEIR PREDICTIONS FOR ITER
Vlad, Gregorio
. INTRODUCTION Predictions of ITER based on validated 1-D transport models would provide: 1) a physical research programs. Many transport models have been partially tested against tokamak data [1]. In order to establish how well each model represents the wide range of existing tokamak data we have developed the ITER
Detection and Prediction of Errors in EPCs of the SAP Reference Model
van der Aalst, Wil
as a blueprint for roll-out projects of SAP's ERP system. It reflects Version18 4.6 of SAP R/3 which was marketedDetection and Prediction of Errors in EPCs of the SAP Reference Model J. Mendling a, H.M.W. Verbeek provide empirical evidence for these questions based on the SAP reference model. This model collection
Prediction of tree diameter growth using quantile regression and mixed-effects models
Cao, Quang V.
of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA b School of Renewable Natural ResourcesPrediction of tree diameter growth using quantile regression and mixed-effects models Som B. Bohora is an important component of an individual-tree model. This function can be considered as a mixed-effects model
S. F. Burlatsky; M. Gummalla; J. O'Neill; V. V. Atrazhev; A. N. Varyukhin; D. V. Dmitriev; N. S. Erikhman
2013-06-19
Under typical PEM fuel cell operating conditions, part of membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEM FC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane life-time. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.
On modeling and controlling intelligent systems
Dress, W.B.
1993-11-01
The aim of this paper is to show how certain diverse and advanced techniques of information processing and system theory might be integrated into a model of an intelligent, complex entity capable of materially enhancing an advanced information management system. To this end, we first examine the notion of intelligence and ask whether a semblance thereof can arise in a system consisting of ensembles of finite-state automata. Our goal is to find a functional model of intelligence in an information-management setting that can be used as a tool. The purpose of this tool is to allow us to create systems of increasing complexity and utility, eventually reaching the goal of an intelligent information management system that provides and anticipates needed data and information. We base our attempt on the ideas of general system theory where the four topics of system identification, modeling, optimization, and control provide the theoretical framework for constructing a complex system that will be capable of interacting with complex systems in the real world. These four key topics are discussed within the purview of cellular automata, neural networks, and evolutionary programming. This is a report of ongoing work, and not yet a success story of a synthetic intelligent system.
Huang, C.; Song, Y.; Luo, X.
2006-01-01
Based on the Block model for predicting vertical temperature distribution in a large space, this paper describes an improved Gebhart-Block model for predicting vertical temperature distribution of a large space with natural ventilation...
Comparison of Uncertainty of Two Precipitation Prediction Models
Shield, Stephen
2015-01-01
Meteorological inputs are an important part of subsurface flow and transport modeling. The choice of source for meteorological data used as inputs has significant impacts on the results of subsurface flow and transport studies. One method to obtain the meteorological data required for flow and transport studies is the use of weather generating models. This paper compares the difference in performance of two weather generating models at Technical Area 54 of Los Alamos National Lab. Technical Area 54 is contains several waste pits for low-level radioactive waste and is the site for subsurface flow and transport studies. This makes the comparison of the performance of the two weather generators at this site particularly valuable.
On the Predictive Uncertainty of a Distributed Hydrologic Model
Cho, Huidae
2009-05-15
of the San Jacinto River watershed. . . . . . . . . . . . . . 14 2 Barton Creek and Onion Creek watersheds. . . . . . . . . . . . . . . 15 3 Streamflow versus runoff for selected models out of the 54 cali- brated models...?99 SOL AWC Available water capacity of the soil layer (mm H2O/mm soil) 0.0?1.0 ESCO Soil evaporation compensation factor 0.01?1.0 GWQMN Threshold depth of water in the shallow aquifer re- quired for return flow to occur (mm H2O) 0?5000 GW REVAP...
Toward understanding predictability of climate: a linear stochastic modeling approach
Wang, Faming
2004-11-15
in examining a dynamical system. The origin and growth of small perturbations are often attributed to the 10 existence of unstable modes. In the limit of long times, the ?rst normal mode (least damped mode) dominates the response. The above classical stability... for the linear case. Recently, Neumaier and Schneider (2001) developed a procedure to estimate eigen- modes of high order autoregressive (AR) models, while (2.3) is basically an AR(1) model. Traditionally, the least damped eigenmodes are considered to be the most...
Wenzel, Mike
2013-10-14
This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.
Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com [Academy of Scientific and Innovative Research, Council of Scientific and Industrial Research, New Delhi (India); Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001 (India); Gupta, Shikha; Rai, Premanjali [Academy of Scientific and Innovative Research, Council of Scientific and Industrial Research, New Delhi (India); Environmental Chemistry Division, CSIR-Indian Institute of Toxicology Research, Post Box 80, Mahatma Gandhi Marg, Lucknow 226 001 (India)
2013-10-15
Robust global models capable of discriminating positive and non-positive carcinogens; and predicting carcinogenic potency of chemicals in rodents were developed. The dataset of 834 structurally diverse chemicals extracted from Carcinogenic Potency Database (CPDB) was used which contained 466 positive and 368 non-positive carcinogens. Twelve non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals and nonlinearity in the data were evaluated using Tanimoto similarity index and Brock–Dechert–Scheinkman statistics. Probabilistic neural network (PNN) and generalized regression neural network (GRNN) models were constructed for classification and function optimization problems using the carcinogenicity end point in rat. Validation of the models was performed using the internal and external procedures employing a wide series of statistical checks. PNN constructed using five descriptors rendered classification accuracy of 92.09% in complete rat data. The PNN model rendered classification accuracies of 91.77%, 80.70% and 92.08% in mouse, hamster and pesticide data, respectively. The GRNN constructed with nine descriptors yielded correlation coefficient of 0.896 between the measured and predicted carcinogenic potency with mean squared error (MSE) of 0.44 in complete rat data. The rat carcinogenicity model (GRNN) applied to the mouse and hamster data yielded correlation coefficient and MSE of 0.758, 0.71 and 0.760, 0.46, respectively. The results suggest for wide applicability of the inter-species models in predicting carcinogenic potency of chemicals. Both the PNN and GRNN (inter-species) models constructed here can be useful tools in predicting the carcinogenicity of new chemicals for regulatory purposes. - Graphical abstract: Figure (a) shows classification accuracies (positive and non-positive carcinogens) in rat, mouse, hamster, and pesticide data yielded by optimal PNN model. Figure (b) shows generalization and predictive abilities of the interspecies GRNN model to predict the carcinogenic potency of diverse chemicals. - Highlights: • Global robust models constructed for carcinogenicity prediction of diverse chemicals. • Tanimoto/BDS test revealed structural diversity of chemicals and nonlinearity in data. • PNN/GRNN successfully predicted carcinogenicity/carcinogenic potency of chemicals. • Developed interspecies PNN/GRNN models for carcinogenicity prediction. • Proposed models can be used as tool to predict carcinogenicity of new chemicals.
Comparison between JET Profile Data and the Predictions of a Transport Model Based on ITG and Trapped Electron Modes
Crowdtuning: systematizing auto-tuning using predictive modeling and
Paris-Sud XI, Université de
in a public repository to initiate systematic, reproducible and collaborative R&D with a new publication model, reliability and cost. We present our novel long-term holistic and practical solution to this problem basedTuning.org for collaborative explanation, top-down complexity reduction, incremental problem decomposition and detection
Comparison of Thermal Properties Predicted by Interatomic Potential Models
Cai, Wei
). The state-of-the-art free energy methods are used to determine the melting points of these models within]. In the "free-energy" method, the Gibbs free energies of the solid and liquid phases are computed as functions of temperature, and the melting point is determined by their intersection point. The free energy method has been
New Tools in Non-Linear Modelling and Prediction
Jones, Antonia J.
networks . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 5 A case study: Thames River Valley 28 5.1 The Thames river valley region . . . . . . . . . . . . . . . . . . . 28 5.2 Model identification of attributes, a single run of the Gamma test typically takes a few seconds. Around this essentially simple
Experimental Validation of Stochastic Wireless Urban Channel Model: Estimation and Prediction
Kuruganti, Phani Teja [ORNL] [ORNL; Ma, Xiao [ORNL] [ORNL; Djouadi, Seddik M [ORNL] [ORNL
2012-01-01
Stochastic differential equations (SDE) can be used to describe the time-varying nature of wireless channels. This paper validates a long-term fading channel model for estimation and prediction from solely using measured received signal strength measurements. Such channel models can be used for optimizing wireless networks deployed for industrial automation, public access, and communication. This paper uses two different sets of received signal measurement data to estimate an predict the signal strength based on past measurements. The realworld performance of the estimation and prediction algorithm is demonstrated.
Motor Modeling and Position Control Lab Week 3: Closed Loop Control
Krovi, Venkat
Motor Modeling and Position Control Lab Week 3: Closed Loop Control 1. Review In the first week of motor modeling lab, a mathematical model of a DC motor from first principles was derived to obtain specifically for this motor model. In the second week, a physical DC motor (Quanser SRV-02) was used for open
Rychard J. Bouwens; Laura Cayon; Joseph Silk
1997-09-13
We develop an idealized inside-out formation model for disk galaxies to include a realistic mix of galaxy types and luminosities that provides a fair match to the traditional observables. The predictions of our infall models are compared against identical models with no-size evolution by generating fully realistic simulations of the HDF, from which we recover the angular size distributions. We find that our infall models produce nearly identical angular size distributions to those of our no-size evolution models in the case of a Omega = 0 geometry but produce slightly smaller sizes in the case of a Omega = 1 geometry, a difference we associate with the fact that there is a different amount of cosmic time in our two models for evolving to relatively low redshifts (z \\approx 1-2). Our infall models also predict a slightly smaller (11% - 29%) number of large (disk scale lengths > 4 h_{50} ^{-1} kpc) galaxies at z \\approx 0.7 for the CFRS as well as different increases in the central surface brightness of the disks for early-type spirals, the infall model predicting an increase by 1.2 magnitudes out to z \\approx 2 (Omega = 0), 1 (Omega = 1), while our no-size evolution models predict an increase of only 0.5 magnitude. This result suggests that infall models could be important for explaining the 1.2-1.6 magnitude increase in surface brightness reported by Schade et al. (1995, 1996a, 1996b).
Nonlinear Modeling and Control Design of Active Helicopter Blades
Patil, Mayuresh
Nonlinear Modeling and Control Design of Active Helicopter Blades Matthias Althoff , Mayuresh J dynamic solution and control design of active helicopter blades. Following are the significant new reduction technique is used to derive a low-order, high fidelity nonlinear blade model for control design
Modeling of TCR and VSI Based FACTS Controllers
Cañizares, Claudio A.
and Voltage Sourced In- verter VSI based Flexible AC Transmission System FACTS Controllers. The models to many applications of these controllers to improve the stability of power networks 1, 2 . Thus, many concentrates on presenting transient stability and power ow models of Thyristor Controlled Reactor TCR
In-situ prediction on sensor networks using distributed multiple linear regression models
Basha, Elizabeth (Elizabeth Ann)
2010-01-01
Within sensor networks for environmental monitoring, a class of problems exists that requires in-situ control and modeling. In this thesis, we provide a solution to these problems, enabling model-driven computation where ...
Model predicts space weather and protects satellite hardware
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home Room NewsInformationJessework uses concrete7 AssessmentBusinessAlternativeModel Verification
Scarrott, Carl
ENGXT +++= )F( Temperature at Channel (i,j) Fuel Irradiation for Channel (r,s) Direct and Neutron(.)?How to Model F(.)? l Effect of Fuel Irradiation on Temperatures l Direct Non-Linear Effect l Neutron Diffusion Region Cold Outer Region l Similar Behaviour Sharp Increase Constant l Weak Relationship l Scatter
Comparison of LMA and LOW Solar Solution Predictions in an SO(10) GUT Model
Carl H. Albright; S. Geer
2002-02-15
Within the framework of an SO(10) GUT model that can accommodate both the LMA and LOW solar neutrino mixing solutions by appropriate choice of the right-handed Majorana matrix elements, we present explicit predictions for the neutrino oscillation parameters \\Delta m^2_{21}, \\sin^2 2\\theta_{12}, \\sin^2 2\\theta_{23}, \\sin^2 2\\theta_{13}, and \\delta_{CP}. Given the observed near maximality of the atmospheric mixing, the model favors the LMA solution and predicts that \\delta_{CP} is small. The suitability of Neutrino Superbeams and Neutrino Factories for precision tests of the two model versions is discussed.
Chen, Shu-Hua
Particulate air quality model predictions using prognostic vs. diagnostic meteorology in central a , Michael J. Kleeman c,* a Department of Land, Air and Water Resources, University of California, Davis, 1 Prognostic meteorological fields Data assimilation UCD/CIT air quality model California Regional Particulate
Prediction of Functional Sites Based on the Fuzzy Oil Drop Model
Skolnick, Jeff
Prediction of Functional Sites Based on the Fuzzy Oil Drop Model Michal Brylin´ski1,2 , Katarzyna, Astronomy and Applied Computer Science, Jagiellonian University, Krako´w, Poland, 4 Institute of Medical Oil Drop model. PLoS Comput Biol 3(5): e94. doi:10.1371/journal.pcbi.0030094 Introduction Because
User-click Modeling for Understanding and Predicting Search-behavior
Yang, Qiang
. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: General Terms AlgorithmsUser-click Modeling for Understanding and Predicting Search-behavior Yuchen Zhang1 , Weizhu Chen1 advances in search users' click modeling consider both users' search queries and click/skip behavior
A Novel Industry Grade Dataset for Fault Prediction based on Model-Driven Developed
A Novel Industry Grade Dataset for Fault Prediction based on Model-Driven Developed Automotive a novel industry dataset on static software and change metrics for Matlab/Simulink models and their corresponding auto-generated C source code. The data set comprises data of three automotive projects developed
Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog
Intercomparison of Single-Column Numerical Models for the Prediction of Radiation Fog THIERRY-term forecasting of fog is a difficult issue that can have a large societal impact. Radiation fog appears layers of the atmosphere. Current NWP models poorly forecast the life cycle of fog, and improved NWP
Hamarneh, Ghassan
BIOMECHANICAL KIDNEY MODEL FOR PREDICTING TUMOR DISPLACEMENT IN THE PRESENCE OF EXTERNAL PRESSURE biomechanical model to simulate de- formations under additional external pressure load. A second CT scan that the biomechanical simula- tion improves by 29% the tumor localization. Index Terms-- Partial nephrectomy, image
Weston, Ken
Atomistic Modeling of Macromolecular Crowding Predicts Modest Increases in Protein Folding that macromolecular crowding can increase protein folding stability, but depending on details of the models (e.g., how on the effects of macro- molecular crowding on protein folding and binding stability has been reached. Crowders
Temporal Models for Groundwater Level Prediction in Regions of Maharashtra Dissertation Report
Sohoni, Milind
Temporal Models for Groundwater Level Prediction in Regions of Maharashtra Dissertation Report In this project work we perform analysis of groundwater level data in three districts of Maha- rashtra - Thane of these districts and developed seasonal models to represent the groundwater be- havior. Three different type
Broader source: Energy.gov [DOE]
NREL, under the Physics of Reliability: Evaluating Design Insights for Component Technologies in Solar (PREDICTS) Program will be developing a physics-based computational degradation model to assess the kinetic oxidation rates; realistic model light attenuation and transport; and multi-layer treatment with variable properties Simulation based experimental design.
Critical Fracture Stress and Fracture Strain Models for the Prediction of Lower and
Ritchie, Robert
Critical Fracture Stress and Fracture Strain Models for the Prediction of Lower and Upper Shelf fracture stress and stress modified fracture strain models are utilized to describe the variation of lower and upper shelf fracture toughness with temperature and strain rate for two alloy steels used
Bayesian calibration of a k -turbulence model for predictive jet-in-crossflow simulations
Ray, Jaideep
Bayesian calibration of a k - turbulence model for predictive jet-in-crossflow simulations Jaideep skill in jet-in-crossflow simulations. The method is based on the hypotheses that (1) informative features of jet-in-crossflow interactions and (2) one can construct surrogates of RANS models
Predicting Response to Political Blog Posts with Topic Models Language Technologies Institute
Cohen, William W.
Predicting Response to Political Blog Posts with Topic Models Tae Yano Language Technologies Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15213, USA nasmith@cs.cmu.edu Abstract In this paper we model discussions in online po- litical weblogs (blogs). To do this, we extend La
An Efficient Genetic Algorithm for Predicting Protein Tertiary Structures in the 2D HP Model
Istrail, Sorin
, predicting its tertiary structure is known as the protein folding problem. This problem has been widely genetic algo- rithm for the protein folding problem under the HP model in the two-dimensional square Genetic Algorithm, Protein Folding Problem, 2D HP Model 1. INTRODUCTION Amino acids are the building
Bledsoe, Brian
The Nature Conservancy, Fort Collins, Colorado USA ABSTRACT Dams and water diversions can dramatically alter the hydraulic habitats of stream ecosystems. Predicting how water depth and velocity respond to flow alteration is possible using hydraulic models, such as Physical Habitat Simulation (PHABSIM); however, such models
Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models
Prediction of oxy-coal flame stand-off using high-fidelity thermochemical models and the one Abstract An Eulerian one-dimensional turbulence (ODT) model is applied to simulate oxy-coal combustion temperature and mixing rate on oxy-coal flame is simulated and discussed where flame stand-off is used
Scarrott, Carl
in Magnox nuclear reactors l Establish safe operating limits l Issues: Subset of measurements ControlSpatial Spectral Estimation forSpatial Spectral Estimation for Reactor Modeling and ControlReactor Modeling and Control Carl Scarrott Granville Tunnicliffe-Wilson Lancaster University, UK c
Lall, Pradeep; Wei, Junchao; Davis, J Lynn
2014-06-24
Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.
Conceptual model for prediction of magnetic properties in tropical Remke L. van Dam*a
Borchers, Brian
ABSTRACT In recent years it has become apparent that the performance of detection sensors for land mines to find large concentrations of iron oxide minerals, which are the predominant cause for soil magnetism conditions control soil development. In order to predict whether magnetic-type iron oxide minerals
Langton, C.; Kosson, D.
2009-11-30
Cementitious barriers for nuclear applications are one of the primary controls for preventing or limiting radionuclide release into the environment. At the present time, performance and risk assessments do not fully incorporate the effectiveness of engineered barriers because the processes that influence performance are coupled and complicated. Better understanding the behavior of cementitious barriers is necessary to evaluate and improve the design of materials and structures used for radioactive waste containment, life extension of current nuclear facilities, and design of future nuclear facilities, including those needed for nuclear fuel storage and processing, nuclear power production and waste management. The focus of the Cementitious Barriers Partnership (CBP) literature review is to document the current level of knowledge with respect to: (1) mechanisms and processes that directly influence the performance of cementitious materials (2) methodologies for modeling the performance of these mechanisms and processes and (3) approaches to addressing and quantifying uncertainties associated with performance predictions. This will serve as an important reference document for the professional community responsible for the design and performance assessment of cementitious materials in nuclear applications. This review also provides a multi-disciplinary foundation for identification, research, development and demonstration of improvements in conceptual understanding, measurements and performance modeling that would be lead to significant reductions in the uncertainties and improved confidence in the estimating the long-term performance of cementitious materials in nuclear applications. This report identifies: (1) technology gaps that may be filled by the CBP project and also (2) information and computational methods that are in currently being applied in related fields but have not yet been incorporated into performance assessments of cementitious barriers. The various chapters contain both a description of the mechanism or and a discussion of the current approaches to modeling the phenomena.
Modelling and control of satellite formations
Vaddi, Veera Venkata Sesha Sai
2004-09-30
®erent satellites in a formation. To achieve the various mission objectives it is necessary for a formation to recon¯gure itself periodically. An analytical impulsive control scheme has been developed for this purpose. This control scheme has the distinct advantage... . . . . . . . . . . . . . . . . . . 15 1.4.2 Impulsive Control . . . . . . . . . . . . . . . . . . . 16 1.5 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 1.6 Nonlinearity and Eccentricity Perturbations . . . . . . . . 18 1.7 Linear and Nonlinear Controllers...
Error Control of Iterative Linear Solvers for Integrated Groundwater Models
California at Davis, University of
Error Control of Iterative Linear Solvers for Integrated Groundwater Models by Matthew F. Dixon1 for integrated groundwater models, which are implicitly coupled to another model, such as surface water models in legacy groundwater modeling packages, resulting in the overall simulation speedups as large as 7
A Nonlinear Continuous Time Optimal Control Model of Dynamic Pricing and Inventory Control with no
Adida, Elodie
time optimal control model for studying a dynamic pricing and inventory control problem for a make-to-stock of not introducing any approximation to the real setting: it provides the exact solution of the system. When taking
Experimental Studies for DPF and SCR Model, Control System, and...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Model, Control System, and OBD Development for Engines Using Diesel and Biodiesel Fuels Measuring PM Distribution in a Catalyzed Particulate Filter using a Terahertz Wave Scanner...
Reference Model for Control and Automation Systems in Electrical...
Office of Environmental Management (EM)
Reference Model for Control and Automation Systems in Electrical Power Version 1.2 October 12, 2005 Prepared by: Sandia National Laboratories' Center for SCADA Security Jason...
Modeling control room crews for accident sequence analysis
Huang, Y. (Yuhao)
1991-01-01
This report describes a systems-based operating crew model designed to simulate the behavior of an nuclear power plant control room crew during an accident scenario. This model can lead to an improved treatment of potential ...
Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab; Armstrong, Robert C.; Vanderveen, Keith
2008-09-01
The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.
2015-08-19
Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore »inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less
Aditya Kumar
2010-12-30
This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC fouling). In parallel, an MPC solution was initially developed using ideal sensing to optimize the plant operation during startup pre-heating as well as steady state and transient operation under normal high-pressure conditions, e.g. part-load, base-load, load transition and fuel changes. The MPC simulation studies showed significant improvements both for startup pre-heating and for normal operation. Finally, the EKF and MPC solutions were coupled to achieve the integrated sensing and control solution and its performance was studied through extensive steady state and transient simulations in the presence of sensor and modeling errors. The results of each task in the program and overall conclusions are summarized in this final report.
D'Sousa, Rohan Joseph
2000-01-01
Predictions of rotordynamic-coefficients for annular honeycomb gas seals are compared using different friction-factor models. Analysis shows that the fundamental improvement in predicting the rotordynamic-coefficients ...
CONTROL-RELEVANT SOFC MODELING AND MODEL EVALUATION Rambabu Kandepu, Lars Imsland, Bjarne A. Foss
Foss, Bjarne A.
CONTROL-RELEVANT SOFC MODELING AND MODEL EVALUATION Rambabu Kandepu, Lars Imsland, Bjarne A. Foss, a dynamic, lumped model of a Solide Oxide Fuel Cell (SOFC) is described, as a step towards developing control relevant models for a SOFC integrated in a gas turbine process. Several such lumped models can
Mass-transport models to predict toxicity of inhaled gases in the upper respiratory tract
Hubal, E.A.C.; Fedkiw, P.S.; Kimbell, J.S. [North Carolina State Univ., Raleigh, NC (United States)
1996-04-01
Mass-transport (the movement of a chemical species) plays an important role in determining toxic responses of the upper respiratory tract (URT) to inhaled chemicals. Mathematical dosimetry models incorporate physical characteristics of mass transport and are used to predict quantitative uptake (absorption rate) and distribution of inhaled gases and vapors in the respiratory tract. Because knowledge of dose is an essential component of quantitative risk assessment, dosimetry modeling plays an important role in extrapolation of animal study results to humans. A survey of existing mathematical dosimetry models for the URT is presented, limitations of current models are discussed, and adaptations of existing models to produce a generally applicable model are suggested. Reviewed URT dosimetry models are categorized as early, lumped-parameter, and distributed-parameter models. Specific examples of other relevant modeling work are also presented. 35 refs., 11 figs., 1 tab.
MODELING AND CONTROL OF THE MECHATRONIC VIBRATIONAL UNIT
MODELING AND CONTROL OF THE MECHATRONIC VIBRATIONAL UNIT I.I Blekhman-1 , Yu.A.Bortsov-2 , A.-Petersburg, Russia Abstract: The description of the multi-degree-of-freedom mechatronic vibrational unit is presented low-level control loops destruction. To study the control of vibrations the mechatronic vibrational
Simplifying Discovered Process Models in a Controlled Manner
van der Aalst, Wil
a process model by ob- serving events recorded by some information system. The discovery of process models). Output is a process model that is able to reproduce these traces. The automated discovery of processSimplifying Discovered Process Models in a Controlled Manner Dirk Fahland, Wil M.P. van der Aalst
Transformer Thermal Modeling: Improving Reliability Using Data Quality Control
1 Transformer Thermal Modeling: Improving Reliability Using Data Quality Control Daniel J. Tylavsky--Eventually all large transformers will be dynamically loaded using models updated regularly from field measured data. Models obtained from measured data give more accurate results than models based on transformer
A STOCHASTIC CONTROL MODEL OF INVESTMENT, PRODUCTION AND CONSUMPTION
Pang, Tao
A STOCHASTIC CONTROL MODEL OF INVESTMENT, PRODUCTION AND CONSUMPTION BY WENDELL H. FLEMING, consumption and income from production. Income from production Yt fluctuates randomly, and it is proportional control model in which an economic unit has productive capital and also liabilities in the form of debt
Quadratic Inverse Eigenvalue Problems, Active Vibration Control and Model Updating
Datta, Biswa
is an important practical problem that arises in a wide range of applications, including mechanical vibrations control (AVC) and finite element model updating (FEMU) in mechanical vibration. The active vibrationQuadratic Inverse Eigenvalue Problems, Active Vibration Control and Model Updating Biswa N. Datta,1
Model Transformation with Hierarchical Discrete-Event Control
Model Transformation with Hierarchical Discrete- Event Control Thomas Huining Feng Electrical, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work permission. #12;Model Transformation with Hierarchical Discrete-Event Control by Huining Feng B.S. (Nanjing
Design, Modeling and Preliminary Control of a Compliant Hexapod Robot
Saranlý, Uluç
Design, Modeling and Preliminary Control of a Compliant Hexapod Robot Uluc. Saranli1 , Martin control of RHex, an autonomous dynami- cally stable hexapod possessing merely six actuated de- grees and computational autonomy, critical com- ponents for legged robotics applications. A compliant hexapod model, used
Design, Modeling and Preliminary Control of a Compliant Hexapod Robot
Saranlý, Uluç
Design, Modeling and Preliminary Control of a Compliant Hexapod Robot Uluc . Saranli 1# , Martin control of RHex, an autonomous dynami cally stable hexapod possessing merely six actuated de grees and computational autonomy, critical com ponents for legged robotics applications. A compliant hexapod model, used
Control relevant modeling and nonlinear state estimation applied to
Foss, Bjarne A.
Control relevant modeling and nonlinear state estimation applied to SOFC-GT power systems #12;ii #12;iii Rambabu Kandepu Control relevant modeling and nonlin- ear state estimation applied to SOFC- GT of the most promising fuel cell technologies is the Solid Oxide Fuel Cell (SOFC), due to its solid state
Modeling and Adaptive Control of Indoor Unmanned Aerial Vehicles
Modeling and Adaptive Control of Indoor Unmanned Aerial Vehicles by Bernard Michini B;Modeling and Adaptive Control of Indoor Unmanned Aerial Vehicles by Bernard Michini Submitted for the degree of Master of Science in Aeronautics and Astronautics Abstract The operation of unmanned aerial
Predicting ecological roles in the rhizosphere using metabolome and transportome modeling
Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.
2015-09-02
The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.
Predicting ecological roles in the rhizosphere using metabolome and transportome modeling
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Larsen, Peter E.; Collart, Frank R.; Dai, Yang; Blanchard, Jeffrey L.
2015-09-02
The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. New algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad’s ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter ofmore »plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism’s transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data.« less
The impact of global nuclear mass model uncertainties on $r$-process abundance predictions
M. Mumpower; R. Surman; A. Aprahamian
2014-11-14
Rapid neutron capture or `$r$-process' nucleosynthesis may be responsible for half the production of heavy elements above iron on the periodic table. Masses are one of the most important nuclear physics ingredients that go into calculations of $r$-process nucleosynthesis as they enter into the calculations of reaction rates, decay rates, branching ratios and Q-values. We explore the impact of uncertainties in three nuclear mass models on $r$-process abundances by performing global monte carlo simulations. We show that root-mean-square (rms) errors of current mass models are large so that current $r$-process predictions are insufficient in predicting features found in solar residuals and in $r$-process enhanced metal poor stars. We conclude that the reduction of global rms errors below $100$ keV will allow for more robust $r$-process predictions.
Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling
Jaroslav Solc
2009-06-01
The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.
Predicting System Performance with Uncertainty
Yan, B.; Malkawi, A.
2012-01-01
The main purpose of this research is to include uncertainty that lies in modeling process and that arises from input values when predicting system performance, and to incorporate uncertainty related to system controls in a computationally...
Modelling and Dynamic Simulation for Process Control
Skogestad, Sigurd
principles for model development are outlined, and these principles are applied to a simple ash tank (which. In this paper we consider dynamic process models obtained using fundamental principles (eg. based reactor, a simple trend analysis using temperature measurements may be suÆcient. Dynamic models
Dynamics of Cell Shape and Forces on Micropatterned Substrates Predicted by a Cellular Potts Model
Philipp J. Albert; Ulrich S. Schwarz
2014-05-19
Micropatterned substrates are often used to standardize cell experiments and to quantitatively study the relation between cell shape and function. Moreover, they are increasingly used in combination with traction force microscopy on soft elastic substrates. To predict the dynamics and steady states of cell shape and forces without any a priori knowledge of how the cell will spread on a given micropattern, here we extend earlier formulations of the two-dimensional cellular Potts model. The third dimension is treated as an area reservoir for spreading. To account for local contour reinforcement by peripheral bundles, we augment the cellular Potts model by elements of the tension-elasticity model. We first parameterize our model and show that it accounts for momentum conservation. We then demonstrate that it is in good agreement with experimental data for shape, spreading dynamics, and traction force patterns of cells on micropatterned substrates. We finally predict shapes and forces for micropatterns that have not yet been experimentally studied.
UAV Cooperative Control with Stochastic Risk Models
Geramifard, Alborz
Risk and reward are fundamental concepts in the cooperative control of unmanned systems. This paper focuses on a constructive relationship between a cooperative planner and a learner in order to mitigate the learning risk ...
Adaptive Cruise Control: Experimental Validation of Advanced Controllers on Scale-Model Cars
Ames, Aaron
Adaptive Cruise Control: Experimental Validation of Advanced Controllers on Scale-Model Cars Aakar of correctness. In particular, safety constraints--maintaining a valid following distance from a lead car objectives in an optimal fashion. This methodology is demonstrated on scale-model cars, for which the CBF
Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms.
Daraio, Chiara
measurements in the ETHZ facility compare well with measurements at the Horns Rev offshore wind farm·Wake models are used to improve predictions of Annual Energy Production (AEP) of wind farms. ·Wake and wind turbine wakes in large windfarms offshore, Wind Energy 12, pp. 431-444, 2009. [2] L.P. Chamorro
A predictive analytical friction model from basic theories of interfaces, contacts and dislocations
Marks, Laurence D.
A predictive analytical friction model from basic theories of interfaces, contacts and dislocations of dislocation drag, contact mechanics, and interface theory. An analytic expression for the friction force still see use in basic discus- sions of the phenomenon [1]. Three basic observations have persisted
Predicting pesticide fate in the hive (part 2): development of a dynamic hive model
.g. bees, wax and honey). The proposed model is validated using empirical data on -fluvalinate residues in bees, wax and honey. It predicts with good approximation both the trends over time to measured data. A honeybee hive is a micro-ecosystem com- posed of several components (e.g. bees, wax, honey
PREV'AIR, a modeling platform for the air quality predictability study , C. Honor2
Menut, Laurent
PREV'AIR, a modeling platform for the air quality predictability study Menut L.1 , C. Honoré2 , L Ministère de l'écologie et du développement durable, Paris, France This platform is proposed by the PREV'AIR about PREV'AIR ? please send an e-mail to cecile.honore@ineris.fr 1. Introduction Since 2002, the PREV'AIR
Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy
Stine, Robert A.
Variable Selection in Data Mining: Building a Predictive Model for Bankruptcy Dean P. Foster and Robert A. Stine Department of Statistics The Wharton School of the University of Pennsylvania consequences of over-fitting (e.g. ?). Many in- teresting problems, particularly classification problems
Barber, Stuart
4 th World Congress on Industrial Process Tomography, Aizu, Japan Modelling and predicting flow of Statistics, University of Leeds, Leeds, LS2 9JT, UK, robert@maths.leeds.ac.uk ABSTRACT The aim of industrial without intruding into the industrial process, but produce highly correlated and noisy data, and hence
Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking
Sukhatme, Gaurav S.
Towards a Generalized Regression Model for On-body Energy Prediction from Treadmill Walking sensor data to energy expenditure is the ques- tion of normalizating across physiological parameters. Common approaches such as weight scaling require validation for each new population. An alternative
A comparison of various models in predicting ignition delay in single-particle coal combustion
by the varying properties and chemical structure of different coal types [2], and by the fact that the coal properties change significantly throughout a coal particle's lifetime in a combustor [35]. The coal particleA comparison of various models in predicting ignition delay in single-particle coal combustion
Pedram, Massoud
Trace-Based Analysis and Prediction of Cloud Computing User Behavior Using the Fractal Modeling and technology. In this paper, we investigate the characteristics of the cloud computing requests received the alpha- stable distribution. Keywords- cloud computing; alpha-stable distribution; fractional order
A Novel Virtual Age Reliability Model for Time-to-Failure Prediction
Cotofana, Sorin
counts, devices approaching physical feature size limits and nuclear plant comparable power densityA Novel Virtual Age Reliability Model for Time-to-Failure Prediction Yao Wang, Sorin Cotofana their relatively short operating lifetime. To overcome the MTTF weakness, this paper proposes a novel virtual age
Qiu, Qinru
Binghamton University, State University of New York Binghamton, New York, USA {jlu5, sliu5, qwu, qqiuAccurate Modeling and Prediction of Energy Availability in Energy Harvesting Real-Time Embedded}@binghamton.edu Abstract -- Energy availability is the primary subject that drives the research innovations in energy
Model-predicted distribution of wind-induced internal wave energy in the world's oceans
Miami, University of
Model-predicted distribution of wind-induced internal wave energy in the world's oceans Naoki 9 July 2008; published 30 September 2008. [1] The distribution of wind-induced internal wave energy-scaled kinetic energy are all consistent with the available observations in the regions of significant wind
PREDICTION OF FOG EPISODES AT THE AIRPORT OF MADRID-BARAJAS USING DIFFERENT MODELING APPROACHES
Politècnica de Catalunya, Universitat
PREDICTION OF FOG EPISODES AT THE AIRPORT OF MADRID-BARAJAS USING DIFFERENT MODELING APPROACHES Meteorología (INM) has been investigating for some time the phenomena related to the formation of fog episodes between the development of fog and the establishment of katabatic flows in the region, generally under
Giurgiutiu, Victor
Structural health monitoring with piezoelectric wafer active sensors predictive modeling of the state of the art in structural health monitoring with piezoelectric wafer active sensors and follows with conclusions and suggestions for further work Key Words: structural health monitoring, SHM, nondestructive
Prediction in District Heating Systems with cFIR models Pierre Pinson , Torben S. Nielsen, Henrik Aa. Nielsen, Lyngby, Denmark Abstract Current methodologies for the optimal operation of district heating systems regularization. Results are given for the test case of the Roskilde district heating system, over a period
Paul Smolen; Douglas A. Baxter; John H. Byrne
2012-08-03
Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of the enzyme protein kinase M (PKM) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by an stimulus sufficient for LTP and learning can "capture" PKM. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKM, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKM. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKM enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKM. Second, cross capture requires the induction of LTD to induce dendritic PKM synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKM inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.
2014Science About the cover: A new transcriptomics-based model accurately predicts how much
2014Science Frontiers #12;About the cover: A new transcriptomics-based model accurately predicts's Environmental Molecular Sciences Laboratory: Making Isoprene from Biomass Material Using Bacillus Species. Pacific Northwest National Laboratory (PNNL) is a U.S. Department of Energy (DOE), Office of Science
Predicting Protein Folds with Structural Repeats Using a Chain Graph Model
Carbonell, Jaime
Predicting Protein Folds with Structural Repeats Using a Chain Graph Model Yan Liu yanliu, Carnegie Mellon University, Pittsburgh, PA 15213 USA Abstract Protein fold recognition is a key step to to accurately identify protein folds aris- ing from typical spatial arrangements of well-defined secondary
Three-body interactions improve the prediction of rate and mechanism in protein folding models
Plotkin, Steven S.
Three-body interactions improve the prediction of rate and mechanism in protein folding models M. R-body interactions on rate and mechanism in protein folding by using the results of molecular dynamics simulations that stabilize protein structures and govern protein folding mechanisms is a fundamental problem in molecular
Baer, Ferdinand
Optimizing Computations in Weather and Climate Prediction Models* F. BAER, BANGLIN ZHANG, AND BING scenarios for many time scales, more computer power than is currently available will be needed. One and sometimes with a biosphere included, are very complex and require so much computing power on available
Abdel-Aal, Radwan E.
and boiler operating conditions. Prediction performance compares favourably with neural network models for future work to further improve performance. Index Terms: Mercury speciation, Flue gases, Boiler emissions activities are coal-fired electric utility boilers, where speciation depends on the operating conditions
Modeling Ideology and Predicting Policy Change with Social Media: Case of Same-Sex Marriage
Modeling Ideology and Predicting Policy Change with Social Media: Case of Same-Sex Marriage Amy X of important policy decisions. Focus- ing on the issue of same-sex marriage legalization, we exam- ine almost 2 million public Twitter posts related to same-sex marriage in the U.S. states over the course of 4 years
ARSA: A Sentiment-Aware Model for Predicting Sales Performance Using Blogs
Huang, Jimmy
ARSA: A Sentiment-Aware Model for Predicting Sales Performance Using Blogs Yang Liu1 , Xiangji, Toronto, Canada 2 School of Information Technology York University, Toronto, Canada yliu@cse.yorku.ca, jhuang@yorku.ca, aan@cse.yorku.ca, xhyu@yorku.ca ABSTRACT Due to its high popularity, Weblogs (or blogs
Model to Predict Temperature and Capillary Pressure Driven Water Transport in PEFCs After Shutdown
Mench, Matthew M.
Model to Predict Temperature and Capillary Pressure Driven Water Transport in PEFCs After Shutdown-912 Korea To enhance durability and cold-start performance of polymer electrolyte fuel cells PEFCs in the PEFC components after shutdown, which for the first time includes thermo-osmotic flow in the membrane
A LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL
Paris-Sud XI, Université de
materials tensile, creep and LCF test data at different temperatures. Some parameters, independentA LIFETIME PREDICTION MODEL FOR SINGLE CRYSTAL SUPERALLOYS SUBJECTED TO THERMOMECHANICAL CREEP for Single Crystal Superalloys operated at high temperatures and subjected to creep, fatigue and oxidation
Towards a Predictive Model for Opal Exploration using a Spatio-temporal Data Mining Approach
Müller, Dietmar
Towards a Predictive Model for Opal Exploration using a Spatio-temporal Data Mining Approach Andrew depositional, unclassified Opal deposit 140°E120°E 20°S 40°S Winton Opalton Jundah Eromanga Quilpie Lightning Ridge White Cliffs Stuart Creek LambinaMintabie Coober Pedy Surat Basin Eromanga Basin Opal mining town
A comparison of various models in predicting ignition delay in single-particle coal combustion
A comparison of various models in predicting ignition delay in single-particle coal combustion November 2013 Accepted 7 January 2014 Available online xxxx Keywords: Coal Devolatilization Ignition delay a b s t r a c t In this paper, individual coal particle combustion under laminar conditions
Precipitation sensitivity to autoconversion rate in a Numerical Weather Prediction model
Marsham, John
1 Precipitation sensitivity to autoconversion rate in a Numerical Weather Prediction model Céline;2 Summary Aerosols are known to significantly affect cloud and precipitation patterns and intensity. The impact of changing cloud droplet number concentration (CDNC), on cloud and precipitation evolution can
Baker, Jack W.
Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground-Motion Prediction Models by Ting Lin, Stephen C. Harmsen, Jack W. Baker, and Nicolas Luco Abstract The conditional uncertainties in all earthquake scenarios and resulting ground motions, as well as the epistemic uncertainties
BFEPM:Best Fit Energy Prediction Modeling Based on CPU Utilization Xiao Zhang, Jianjun Lu, Xiao Qin
Qin, Xiao
BFEPM:Best Fit Energy Prediction Modeling Based on CPU Utilization Xiao Zhang, Jianjun Lu, Xiao Qin BFEPM, a best fit energy prediction model. It choose best model based on the power consumption benchmark Engineering Auburn University Auburn, AL USA 36849-5347 Email: xqin@auburn.edu Abstract--Energy cost becomes
Zhang, Da-Lin
Analysis and prediction of hazard risks caused by tropical cyclones in Southern China with fuzzy 2011 Keywords: Combined weights Fuzzy mathematical models Hazard risk analysis Exceeded probability Tropical cyclones Grey prediction model a b s t r a c t A hazard-risk assessment model and a grey hazard
Vassiliadis, Dimitrios
, Modeling, and Prediction for Space Weather Environments Dimitris Vassiliadis Abstract--By now nonlinear dynamical models and neural net- works have been used to predict and model a wide variety of space weather. These developments have prompted the establishment of national space weather programs in the U.S. [21], [22
The Dirac Form Factor Predicts the Pauli Form Factor in the Endpoint Model
Sumeet Dagaonkar; Pankaj Jain; John P. Ralston
2015-03-24
We compute the momentum-transfer dependence of the proton Pauli form factor $F_{2}$ in the endpoint overlap model. We find the model correctly reproduces the scaling of the ratio of $F_{2}$ with the Dirac Form factor $F_{1}$ observed at the Jefferson Laboratory. The calculation uses the leading-power, leading twist Dirac structure of the quark light-cone wave function, and the same endpoint dependence previously determined from the Dirac form factor $F_{1}$. There are no parameters and no adjustable functions in the endpoint model's prediction for $F_{2}$. The model's predicted ratio $F_{2}(Q^{2})/F_{1}(Q^{2})$ is quite insensitive to the endpoint wave function, which explains why the observed ratio scales like $1/Q$ down to rather low momentum transfers. The endpoint model appears to be the only comprehensive model consistent with all form factor information as well as reproducing fixed-angle proton-proton scattering at large momentum transfer. Any one of the processes is capable of predicting the others.
Reliability analysis and prediction of mixed mode load using Markov Chain Model
Nikabdullah, N.; Singh, S. S. K.; Alebrahim, R.; Azizi, M. A.; K, Elwaleed A.; Noorani, M. S. M.
2014-06-19
The aim of this paper is to present the reliability analysis and prediction of mixed mode loading by using a simple two state Markov Chain Model for an automotive crankshaft. The reliability analysis and prediction for any automotive component or structure is important for analyzing and measuring the failure to increase the design life, eliminate or reduce the likelihood of failures and safety risk. The mechanical failures of the crankshaft are due of high bending and torsion stress concentration from high cycle and low rotating bending and torsional stress. The Markov Chain was used to model the two states based on the probability of failure due to bending and torsion stress. In most investigations it revealed that bending stress is much serve than torsional stress, therefore the probability criteria for the bending state would be higher compared to the torsion state. A statistical comparison between the developed Markov Chain Model and field data was done to observe the percentage of error. The reliability analysis and prediction was derived and illustrated from the Markov Chain Model were shown in the Weibull probability and cumulative distribution function, hazard rate and reliability curve and the bathtub curve. It can be concluded that Markov Chain Model has the ability to generate near similar data with minimal percentage of error and for a practical application; the proposed model provides a good accuracy in determining the reliability for the crankshaft under mixed mode loading.
Long-Fiber Thermoplastic Injection Molded Composites: from Process Modeling to Property Prediction
Nguyen, Ba Nghiep; Holbery, Jim D.; Johnson, Kenneth I.; Smith, Mark T.
2005-09-01
Recently, long-fiber filled thermoplastics have become a great interest to the automotive industry since these materials offer much better property performance (e.g. elastic moduli, strength, durability…) than their short-fiber analogues, and they can be processed through injection molding with some specific tool design. However, in order that long-fiber thermoplastic injection molded composites can be used efficiently for automotive applications, there is a tremendous need to develop process and constitutive models as well as computational tools to predict the microstructure of the as-formed composite, and its resulting properties and macroscopic responses from processing to the final product. The microstructure and properties of such a composite are governed by i) flow-induced fiber orientation, ii) fiber breakage during injection molding, and iii) processing conditions (e,g. pressure, mold and melt temperatures, mold geometries, injection speed, etc.). This paper highlights our efforts to address these challenging issues. The work is an integrated part of a research program supported by the US Department of Energy, which includes • The development of process models for long-fiber filled thermoplastics, • The construction of an interface between process modeling and property prediction as well as the development of new constitutive models to perform linear and nonlinear structural analyses, • Experimental characterization of model parameters and verification of the model predictions.
Model-Inspired Research. TES research uses modeling, prediction, and synthesis to identify
in Earth system models (ESMs). TES supports research to advance fundamental understanding of terrestrial-process models, ecosystem models, and the Community Earth System Model). This emphasis on the capture of advanced in Earth system models to increase the quality of climate model projections and to provide the scientific
Celi, Leo Anthony G
2009-01-01
Introduction. Models for mortality prediction are traditionally developed from prospective multi-center observational studies involving a heterogeneous group of patients to optimize external validity. We hypothesize that ...
crosswind flight [18], which essentially consists in extracting power from the airflow by flying an airfoil generation based on crosswind flight over conventional wind turbines is that higher altitude can be reached
Control room habitability system review models
Gilpin, H. )
1990-12-01
This report provides a method of calculating control room operator doses from postulated reactor accidents and chemical spills as part of the resolution of TMI Action Plan III.D.3.4. The computer codes contained in this report use source concentrations calculated by either TACT5, FPFP, or EXTRAN, and transport them via user-defined flow rates to the control room envelope. The codes compute doses to six organs from up to 150 radionuclides (or 1 toxic chemical) for time steps as short as one second. Supporting codes written in Clipper assist in data entry and manipulation, and graphically display the results of the FORTRAN calculations. 7 refs., 22 figs.
.8, a positive predictive value of 27.5% and a negative predictive value of 99.4%. CONCLUSIONS: The logisticThe use of a new logistic regression model for predicting the outcome of pregnancies of unknown, London UK. E-mail: gcondous@hotmail.com BACKGROUND: The aim of this study was to generate and evaluate
Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model
Lipscomb, William
2012-06-19
Coastal stakeholders need defensible predictions of 21st century sea-level rise (SLR). IPCC assessments suggest 21st century SLR of {approx}0.5 m under aggressive emission scenarios. Semi-empirical models project SLR of {approx}1 m or more by 2100. Although some sea-level contributions are fairly well constrained by models, others are highly uncertain. Recent studies suggest a potential large contribution ({approx}0.5 m/century) from the marine-based West Antarctic Ice Sheet, linked to changes in Southern Ocean wind stress. To assess the likelihood of fast retreat of marine ice sheets, we need coupled ice-sheet/ocean models that do not yet exist (but are well under way). CESM is uniquely positioned to provide integrated, physics based sea-level predictions.
M. K. Parida; Sudhanwa Patra
2013-01-14
In TeV scale left-right symmetric models, new dominant predictions to neutrinoless double beta decay and light neutrino masses are in mutual contradiction because of large contribution to the latter through popular seesaw mechanisms. We show that in a class of left-right models with high-scale parity restoration, these results coexist without any contravention with neutrino oscillation data and the relevant formula for light neutrino masses is obtained via gauged inverse seesaw mechanism. The most dominant contribution to the double beta decay is shown to be via $W^-_L- W^-_R$ mediation involving both light and heavy neutrino exchanges, and the model predictions are found to discriminate whether the Dirac neutrino mass is of quark-lepton symmetric origin or without it. We also discuss associated lepton flavor violating decays.
Modeling and Control of Surge and Rotating Stall in Compressors
Gravdahl, Jan Tommy
Modeling and Control of Surge and Rotating Stall in Compressors Dr.ing. thesis Jan Tommy Gravdahl varying disturbances in mass ow and pressure. A novel model for an axial compression system with non-constant compressor speed is derived by extending the Moore-Greitzer model. Rotating stall and surge is studied
Reduced-Order Modelling of Turbulent Jets for Noise Control
École Normale Supérieure
Reduced-Order Modelling of Turbulent Jets for Noise Control Michael Schlegel, Bernd R. Noack, an opportunity for model-based jet noise reduction is opening up by the rapidly evolving field of reduced and Gilead Tadmor Abstract A reduced-order modelling (ROM) strategy is pursued to achieve a mech- anistic
Pérez-Andújar, Angélica [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 (United States)] [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 (United States); Zhang, Rui; Newhauser, Wayne [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030 (United States)] [Department of Radiation Physics, Unit 1202, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences at Houston, 6767 Bertner Avenue, Houston, Texas 77030 (United States)
2013-12-15
Purpose: Stray neutron radiation is of concern after radiation therapy, especially in children, because of the high risk it might carry for secondary cancers. Several previous studies predicted the stray neutron exposure from proton therapy, mostly using Monte Carlo simulations. Promising attempts to develop analytical models have also been reported, but these were limited to only a few proton beam energies. The purpose of this study was to develop an analytical model to predict leakage neutron equivalent dose from passively scattered proton beams in the 100-250-MeV interval.Methods: To develop and validate the analytical model, the authors used values of equivalent dose per therapeutic absorbed dose (H/D) predicted with Monte Carlo simulations. The authors also characterized the behavior of the mean neutron radiation-weighting factor, w{sub R}, as a function of depth in a water phantom and distance from the beam central axis.Results: The simulated and analytical predictions agreed well. On average, the percentage difference between the analytical model and the Monte Carlo simulations was 10% for the energies and positions studied. The authors found that w{sub R} was highest at the shallowest depth and decreased with depth until around 10 cm, where it started to increase slowly with depth. This was consistent among all energies.Conclusion: Simple analytical methods are promising alternatives to complex and slow Monte Carlo simulations to predict H/D values. The authors' results also provide improved understanding of the behavior of w{sub R} which strongly depends on depth, but is nearly independent of lateral distance from the beam central axis.
Bittle, Joshua A.; Gao, Zhiming; Jacobs, Timothy J.
2013-01-01
A pseudo-multi-zone phenomenological model has been created with the ultimate goal of supporting efforts to enable broader commercialization of low temperature combustion modes in diesel engines. The benefits of low temperature combustion are the simultaneous reduction in soot and nitric oxide emissions and increased engine efficiency if combustion is properly controlled. Determining what qualifies as low temperature combustion for any given engine can be difficult without expensive emissions analysis equipment. This determination can be made off-line using computer models or through factory calibration procedures. This process could potentially be simplified if a real-time prediction model could be implemented to run for any engine platform this is the motivation for this study. The major benefit of this model is the ability for it to predict the combustion trajectory, i.e. local temperature and equivalence ratio in the burning zones. The model successfully captures all the expected trends based on the experimental data and even highlights an opportunity for simply using the average reaction temperature and equivalence ratio as an indicator of emissions levels alone - without solving formation sub-models. This general type of modeling effort is not new, but a major effort was made to minimize the calculation duration to enable implementation as an input to real-time next-cycle engine controller Instead of simply using the predicted engine out soot and NOx levels, control decisions could be made based on the trajectory. This has the potential to save large amounts of calibration time because with minor tuning (the model has only one automatically determined constant) it is hoped that the control algorithm would be generally applicable.
Comments on "Min-Max Predictive Control Strategies for Input-Saturated Polytopic Uncertain Systems"
, with similar notation for Algoritm 2 of [1]), it is not guaranteed that the terminal controller will satisfy
A Predictive power control of Doubly Fed Induction Generator for Wave Energy Converter
Brest, Université de
Switchgear Wave converter control Gear hal-01023509,version1-13Jul2014 Author manuscript, published in "IEEE
Neural Modeling and Control of Diesel Engine with Pollution Constraints
Ouladsine, Mustapha; Dovifaaz, Xavier; 10.1007/s10846-005-3806-y
2009-01-01
The paper describes a neural approach for modelling and control of a turbocharged Diesel engine. A neural model, whose structure is mainly based on some physical equations describing the engine behaviour, is built for the rotation speed and the exhaust gas opacity. The model is composed of three interconnected neural submodels, each of them constituting a nonlinear multi-input single-output error model. The structural identi?cation and the parameter estimation from data gathered on a real engine are described. The neural direct model is then used to determine a neural controller of the engine, in a specialized training scheme minimising a multivariable criterion. Simulations show the effect of the pollution constraint weighting on a trajectory tracking of the engine speed. Neural networks, which are ?exible and parsimonious nonlinear black-box models, with universal approximation capabilities, can accurately describe or control complex nonlinear systems, with little a priori theoretical knowledge. The present...
PREDICTING WATER ACTIVITY IN ELECTROLYTE SOLUTIONS WITH THE CISTERNAS-LAM MODEL
REYNOLDS JG; GREER DA; DISSELKAMP RL
2011-03-01
Water activity is an important parameter needed to predict the solubility of hydrated salts in Hanford nuclear waste supernatants. A number of models available in the scientific literature predict water activity from electrolyte solution composition. The Cisternas-Lam model is one of those models and has several advantages for nuclear waste application. One advantage is that it has a single electrolyte specific parameter that is temperature independent. Thus, this parameter can be determined from very limited data and extrapolated widely. The Cisternas-Lam model has five coefficients that are used for all aqueous electrolytes. The present study aims to determine if there is a substantial improvement in making all six coefficients electrolyte specific. The Cisternas-Lam model was fit to data for six major electrolytes in Hanford nuclear waste supernatants. The model was first fit to all data to determine the five global coefficients, when they were held constant for all electrolytes it yielded a substantially better fit. Subsequently, the model was fit to each electrolyte dataset separately, where all six coefficients were allowed to be electrolyte specific. Treating all six coefficients as electrolyte specific did not make sufficient difference, given the complexity of applying the electrolyte specific parameters to multi-solute systems. Revised water specific parameters, optimized to the electrolytes relevant to Hanford waste, are also reported.
Phase Model with Feedback Control for Power Grids
Matsuo, Tatsuma
2013-01-01
A phase model with feedback control is studied as a dynamical model of power grids. As an example, we study a model network corresponding to the power grid in the Kyushu region. The standard frequency is maintained by the mutual synchronization and the feedback control. Electric failures are induced by an overload. We propose a local feedback method in which the strength of feedback control is proportional to the magnitude of generators. We find that the electric failures do not occur until the utilization ratio is close to 1 under this feedback control. We also find that the temporal response for the time-varying input power is suppressed under this feedback control. We explain the mechanisms using the corresponding global feedback method.
Yu, Z.; Peldszus, S.; Huck, P.M. [University of Waterloo, Waterloo, ON (Canada). NSERC Chair in Water Treatment
2009-03-01
The adsorption of two representative pharmaceutically active compounds (PhACs) naproxen and carbamazepine and one endocrine disrupting compound (EDC) nonylphenol was studied in pilot-scale granular activated carbon (GAC) adsorbers using post-sedimentation (PS) water from a full-scale drinking water treatment plant. The GAC adsorbents were coal-based Calgon Filtrasorb 400 and coconut shell-based PICA CTIF TE. Acidic naproxen broke through fastest while nonylphenol was removed best, which was consistent with the degree to which fouling affected compound removals. Model predictions and experimental data were generally in good agreement for all three compounds, which demonstrated the effectiveness and robustness of the pore and surface diffusion model (PSDM) used in combination with the time-variable parameter approach for predicting removals at environmentally relevant concentrations (i.e., ng/L range). Sensitivity analyses suggested that accurate determination of film diffusion coefficients was critical for predicting breakthrough for naproxen and carbamazepine, in particular when high removals are targeted. Model simulations demonstrated that GAC carbon usage rates (CURs) for naproxen were substantially influenced by the empty bed contact time (EBCT) at the investigated conditions. Model-based comparisons between GAC CURs and minimum CURs for powdered activated carbon (PAC) applications suggested that PAC would be most appropriate for achieving 90% removal of naproxen, whereas GAC would be more suitable for nonylphenol. 25 refs., 4 figs., 1 tab.
Predictive models of safety based on audit findings: Part 2: Measurement of model validity
Wu, Changxu (Sean)
prediction Neural network Aviation maintenance a b s t r a c t Part 1 of this study sequence developed predictors of future safety performance in the aviation maintenance field. Ó 2013 Elsevier Ltd, using monthly data on safety performance regarding the maintenance activities of two different airlines
Wang, Chien.; Prinn, Ronald G.
The possible trends for atmospheric carbon monoxide in the next 100 yr have been illustrated using a coupled atmospheric chemistry and climate model driven by emissions predicted by a global economic development model. ...
Boundary conditions control for a Shallow-Water model
Kazantsev, Eugene
2012-01-01
A variational data assimilation technique was used to estimate optimal discretization of interpolation operators and derivatives in the nodes adjacent to the rigid boundary. Assimilation of artificially generated observational data in the shallow-water model in a square box and assimilation of real observations in the model of the Black sea are discussed. It is shown in both experiments that controlling the discretization of operators near a rigid boundary can bring the model solution closer to observations as in the assimilation window and beyond the window. This type of control allows also to improve climatic variability of the model.
GENI: A graphical environment for model-based control
Kleban, S.; Lee, M.; Zambre, Y.
1989-10-01
A new method to operate machine and beam simulation programs for accelerator control has been developed. Existing methods, although cumbersome, have been used in control systems for commissioning and operation of many machines. We developed GENI, a generalized graphical interface to these programs for model-based control. This object-oriented''-like environment is described and some typical applications are presented. 4 refs., 5 figs.
STUDIES ON MODELING AND CONTROL OF CONTINUOUS BIOTECHNICAL PROCESSES
Skogestad, Sigurd
STUDIES ON MODELING AND CONTROL OF CONTINUOUS BIOTECHNICAL PROCESSES by Ying Zhao A T hesis grandmother, Youlian Huya on her centennial birth anniversary , 1 #12; #12; i ABSTRACT Continuous bioreactors to the development of advanced control strategies for continuous bioreactors. Therefore, the field of continuous
Control-Oriented Model for Camless Intake Process (Part I)
Stefanopoulou, Anna
48121 Abstract The improvement of internal combustion engine is largely accomplished though the introduction of innova- tive actuators that allow optimization and control of the ow, mixing, and combustion the control- oriented model for the cylinder air charge and the pump- ing losses assuming uniform air pulses
MODELING AND CONTROL OF A DIESEL HCCI ENGINE
Paris-Sud XI, Université de
MODELING AND CONTROL OF A DIESEL HCCI ENGINE J. Chauvin A. Albrecht G. Corde N. Petit Institut Abstract: This article focuses on the control of a Diesel engine airpath. We propose a detailed description of the airpath of a Diesel HCCI engine supported by experimental results. Moreover, we propose a simple, yet
Optimal control of a dengue epidemic model with vaccination
Rodrigues, Helena Sofia; Torres, Delfim F M
2011-01-01
We present a SIR+ASI epidemic model to describe the interaction between human and dengue fever mosquito populations. A control strategy in the form of vaccination, to decrease the number of infected individuals, is used. An optimal control approach is applied in order to find the best way to fight the disease.
Use of artificial intelligence for process modeling and control
You, Yong
1991-01-01
USE OF ARTIFICIAL INTELLIGENCE FOR PROCESS MODELING AND CONTROL A Thesis by YONG YOU Submitted to the Office of Graduate Stuclies of Texas A&M University in partial fulffllment of the requirement for the degree of IvIASTER OF SCIENCE May... 1991 Major Subject: Chemical Engineering USE OF ARTIFICIAL INTELLIGENCE FOR PROCESS MODELING AND CONTROL A Thesis by YONG YOU Approved as to style and content by: Michael Nikolaou (Chair of Committee) Ralph E. White (Member) Alexande...
MATHEMATICAL PROGRAMMING MODELS FOR ENVIRONMENTAL QUALITY CONTROL
Greenberg, Harvey J.
~ngenvironmental quality. The scope includes air, water, and land quality, stemming from the first works in the 1960s, and the mathematical program is designed to pre- scribe decisions for operations and planning to minimize cost subject. Sections 2-4 sum- marize the literature on mathematical programming models for air, land, and water quality
Modeling Control Mechanisms with Normative Multiagent Systems
van der Torre, Leon
of renewable energy. We apply a conceptual model based on normative multiagent systems (NMAS). We propose to stimulate the production of #12;energy from renewable sources [20]. The ruling involves an obligation for energy sup- pliers to produce evidence of having distributed a certain minimal amount of renewable energy
Use of a biomechanical tongue model to predict the impact of tongue surgery on speech production
Buchaillard, Stéphanie; Perrier, Pascal; Payan, Yohan
2008-01-01
This paper presents predictions of the consequences of tongue surgery on speech production. For this purpose, a 3D finite element model of the tongue is used that represents this articulator as a deformable structure in which tongue muscles anatomy is realistically described. Two examples of tongue surgery, which are common in the treatment of cancers of the oral cavity, are modelled, namely a hemiglossectomy and a large resection of the mouth floor. In both cases, three kinds of possible reconstruction are simulated, assuming flaps with different stiffness. Predictions are computed for the cardinal vowels /i, a, u/ in the absence of any compensatory strategy, i.e. with the same motor commands as the one associated with the production of these vowels in non-pathological conditions. The estimated vocal tract area functions and the corresponding formants are compared to the ones obtained under normal conditions
An Elastic-Plastic and Strength Prediction Model for Injection-Molded Long-Fiber Thermoplastics
Nguyen, Ba Nghiep; Kunc, Vlastimil; Phelps, Jay; Tucker III, Charles L.; Bapanapalli, Satish K.
2008-09-01
This paper applies a recently developed model to predict the elastic-plastic stress/strain response and strength of injection-molded long-fiber thermoplastics (LFTs). The model combines a micro-macro constitutive modeling approach with experimental characterization and modeling of the composite microstructure to determine the composite stress/strain response and strength. Specifically, it accounts for elastic fibers embedded in a thermoplastic resin that exhibits the elastic-plastic behavior obeying the Ramberg-Osgood relation and J-2 deformation theory of plasticity. It also accounts for fiber length, orientation and volume fraction distributions in the composite formed by the injection-molding process. Injection-molded-long-glass-fiber/polypropylene (PP) specimens were prepared for mechanical characterization and testing. Fiber length, orientation, and volume fraction distributions were then measured at some selected locations for use in the computation. Fiber orientations in these specimens were also predicted using an anisotropic rotary diffusion model developed for LFTs. The stress-strain response of the as-formed composite was computed by an incremental procedure that uses the Eshelby’s equivalent inclusion method, the Mori-Tanaka assumption and a fiber orientation averaging technique. The model has been validated against the experimental stress-strain results obtained for these long-glass-fiber/PP specimens.
Results from baseline tests of the SPRE I and comparison with code model predictions
Cairelli, J.E.; Geng, S.M.; Skupinski, R.C.
1994-09-01
The Space Power Research Engine (SPRE), a free-piston Stirling engine with linear alternator, is being tested at the NASA Lewis Research Center as part of the Civil Space Technology Initiative (CSTI) as a candidate for high capacity space power. This paper presents results of base-line engine tests at design and off-design operating conditions. The test results are compared with code model predictions.
A new thermodynamic model to predict wax deposition from crude oils
Loganathan, Narayanan
1993-01-01
. , 1926; Affens et al. , 1984), crystal morphology (Ferris and Cowles, 1945; Edwards, 1957), and physical properties of petroleum wax (Templin, 1956) have been studied in detail. Bem et ak (1980) studied wax deposition in North Sea submarine crude-oil...A NEW THERMODYNAMIC MODEL TO PREDICT WAX DEPOSITION FROM CRUDE OILS A Thesis by NARAYANAN LOGANATHAN Submitted to the Office of Graduate Studies of Texas A&M University in partial fullillment of the requirements for the degree of MASTER...
A comparison of general circulation model predictions to sand drift and dune orientations
Blumberg, D.G.; Greeley, R.
1996-12-01
The growing concern over climate change and decertification stresses the importance of aeolian process prediction. In this paper the use of a general circulation model to predict current aeolian features is examined. A GCM developed at NASA/Goddard Space Flight Center was used in conjunction with White`s aeolian sand flux model to produce a global potential aeolian transport map. Surface wind shear stress predictions were used from the output of a GCM simulation that was performed as part of the Atmospheric Model Intercomparison Project on 1979 climate conditions. The spatial resolution of this study (as driven by the GCM) is 4{degrees} X 5{degrees}; instantaneous 6-hourly wind stress data were saved by the GCM and used in this report. A global map showing potential sand transport was compared to drift potential directions as inferred from Landsat images from the 1980s for several sand seas and a coastal dune field. Generally, results show a good correlation between the simulated sand drift direction and the drift direction inferred for dune forms. Discrepancies between the drift potential and the drift inferred from images were found in the North American deserts and the Arabian peninsula. An attempt to predict the type of dune that would be formed in specific regions was not successful. The model could probably be further improved by incorporating soil moisture, surface roughness, and vegetation information for a better assessment of sand threshold conditions. The correlation may permit use of a GCM to analyze {open_quotes}fossil{close_quotes} dunes or to forecast aeolian processes. 48 refs., 8 figs.
Gravdahl, Jan Tommy
of Engineering Cybernetics, Norwegian University of Science and Technology. Keywords: Control education, modeling) is provided by the De- partment of Engineering Cybernetics in the Faculty of Information Technology in Control Jan Tommy Gravdahl and Olav Egeland Department of Engineering Cybernetics, Norwegian University
Methods to Improve Process Safety Performance through Flange Connection Leak Prediction and Control
Nelson, Jeremy
2014-08-08
by predicting the asset’s expected corrosion rate and its service life. However, this fixed safety margin does not consider the inherent uncertainty in an individual asset’s degradation rate due to variability in the material’s corrosion resistance...
World Wind Energy Conference, Berlin (2002) REGIONAL WIND POWER PREDICTION WITH RISK CONTROL
Heinemann, Detlev
2002-01-01
is to seperately calculate the power output for each wind farm in the region and generate the sum. This wouldWorld Wind Energy Conference, Berlin (2002) PREVIENTO REGIONAL WIND POWER PREDICTION WITH RISK Oldenburg 26111 Oldenburg, Fax: ++49-441-798-3579 email: m.lange@mail.uni-oldenburg.de, http://ehf.uni-oldenburg.de/wind
Transient PVT measurements and model predictions for vessel heat transfer. Part II.
Felver, Todd G.; Paradiso, Nicholas Joseph; Winters, William S., Jr.; Evans, Gregory Herbert; Rice, Steven F.
2010-07-01
Part I of this report focused on the acquisition and presentation of transient PVT data sets that can be used to validate gas transfer models. Here in Part II we focus primarily on describing models and validating these models using the data sets. Our models are intended to describe the high speed transport of compressible gases in arbitrary arrangements of vessels, tubing, valving and flow branches. Our models fall into three categories: (1) network flow models in which flow paths are modeled as one-dimensional flow and vessels are modeled as single control volumes, (2) CFD (Computational Fluid Dynamics) models in which flow in and between vessels is modeled in three dimensions and (3) coupled network/CFD models in which vessels are modeled using CFD and flows between vessels are modeled using a network flow code. In our work we utilized NETFLOW as our network flow code and FUEGO for our CFD code. Since network flow models lack three-dimensional resolution, correlations for heat transfer and tube frictional pressure drop are required to resolve important physics not being captured by the model. Here we describe how vessel heat transfer correlations were improved using the data and present direct model-data comparisons for all tests documented in Part I. Our results show that our network flow models have been substantially improved. The CFD modeling presented here describes the complex nature of vessel heat transfer and for the first time demonstrates that flow and heat transfer in vessels can be modeled directly without the need for correlations.
NONLINEAR CONTROL OF POWER NETWORK MODELS USING FEEDBACK LINEARIZATION
Wedeward, Kevin
network can affect each other. We consider a simple model of a power system derived from singular analysis of large electric power networks is in- creasingly important as power systems become larger construct minimally complicated dynamical models of power networks as affine nonlinear control systems
Modelling and Control of an Inverted Pendulum Turbine
Modelling and Control of an Inverted Pendulum Turbine Sergi Rotger Griful Kongens Lyngby 2012 IMM. In this project the feasibility of a new kind of wind turbine is studied. This thesis deals with the achievement of getting a proper mathematical model of a new kind of wind turbine, called the inverted pendulum turbine
Modelling and control strategy development for fuel cell electric vehicles
Peng, Huei
Modelling and control strategy development for fuel cell electric vehicles Andreas Schell b , Huei applicable to the development of fuel cell electric vehicles (FCEVs) and hybrid electric vehicles (HEVs reserved. Keywords: Fuel cell electric vehicle; Hybrid vehicles; Modelling 1. Introduction Advanced
Nonlinear Hybrid Dynamical Systems: Modeling, Optimal Control, and Applications
Stryk, Oskar von
Nonlinear Hybrid Dynamical Systems: Modeling, Optimal Control, and Applications Martin Buss1¨unchen, Germany Abstract. Nonlinear hybrid dynamical systems are the main focus of this paper. A modeling Introduction The recent interest in nonlinear hybrid dynamical systems has forced the merger of two very
INFS 762 Fall 1993 Lattice-Based Access Control Models
Sandhu, Ravi
H 6 LATTICE STRUCTURES Unclassified Confidential Secret Top Secret Hierarchical Classes can Models Â© 1993 Ravi Sandhu Â© 1993 Ravi Sandhu 7 LATTICE STRUCTURES Unclassified Confidential Secret Top Secret Top Secret can-flowdominance #12;INFS 762 Fall 1993 Lattice-Based Access Control Models Â© 1993
PROCESS MODELING AND CONTROL The Department of Chemical Engineering
Lightsey, Glenn
economic performance · MIMO (vs. SISO) models · Nonlinear (vs. linear) models · Stochastic variables.D. Graduates (2005 - 2008) Student/Supervisor Destination E. Hale (JQ) Ph.D. (8/05) NREL R. Chong (TFE) M.S. (8 (Emerson Process Management) · J. Lee (postdoc) Various topics in multivariable control (e.g., multiloop
Dr. Binh T. Pham; Grant L. Hawkes; Jeffrey J. Einerson
2012-10-01
As part of the Research and Development program for Next Generation High Temperature Reactors (HTR), a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. The data representing the crucial test fuel conditions (e.g., temperature, neutron fast fluence, and burnup) while impossible to obtain from direct measurements are calculated by physics and thermal models. The irradiation and post-irradiation examination (PIE) experimental data are used in model calibration effort to reduce the inherent uncertainty of simulation results. This paper is focused on fuel temperature predicted by the ABAQUS code’s finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for improving qualification of AGR-1 thermocouple data. The present work exercises the idea that the abnormal trends of measured data observed from statistical analysis may be caused by either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. As an example, the uneven reduction of the control gas gap in Capsule 5 revealed by the capsule metrology measurements in PIE helps justify the reduction in TC readings instead of TC drift. This in turn prompts modification of thermal model to better fit with experimental data, thus help increase confidence, and in other word reduce model uncertainties in thermal simulation results of the AGR-1 test.
Observational Tests and Predictive Stellar Evolution II: Non-standard Models
Patrick A. Young; David Arnett
2004-09-27
We examine contributions of second order physical processes to results of stellar evolution calculations amenable to direct observational testing. In the first paper in the series (Young et al. 2001) we established baseline results using only physics which are common to modern stellar evolution codes. In the current paper we establish how much of the discrepancy between observations and baseline models is due to particular elements of new physics. We then consider the impact of the observational uncertainties on the maximum predictive accuracy achievable by a stellar evolution code. The sun is an optimal case because of the precise and abundant observations and the relative simplicity of the underlying stellar physics. The Standard Model is capable of matching the structure of the sun as determined by helioseismology and gross surface observables to better than a percent. Given an initial mass and surface composition within the observational errors, and no additional constraints for which the models can be optimized, it is not possible to predict the sun's current state to better than ~7%. Convectively induced mixing in radiative regions, seen in multidimensional hydrodynamic simulations, dramatically improves the predictions for radii, luminosity, and apsidal motions of eclipsing binaries while simultaneously maintaining consistency with observed light element depletion and turnoff ages in young clusters (Young et al. 2003). Systematic errors in core size for models of massive binaries disappear with more complete mixing physics, and acceptable fits are achieved for all of the binaries without calibration of free parameters. The lack of accurate abundance determinations for binaries is now the main obstacle to improving stellar models using this type of test.
G. R. Odette; G. E. Lucas
2005-11-15
This final report on "In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation" (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: 1) A Transport and Fate Model for Helium and Helium Management; 2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; 3) Multiscale Modeling of Fracture consisting of: 3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), 3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, 3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, 3d) A Model for the KJc(T) of a High Strength NFA MA957, 3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, 3-f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; 4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and 5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES.
Predictive Power Control of Doubly-Fed Induction Generator for Wave Energy Converters
Paris-Sud XI, Université de
Energy Converter Control Main Circuit Breaker Medium Voltage Switchgear Line Coupling Transformer Gear Medium Voltage Switchgear Line Coupling Transformer Fig. 1. An illustrative example of DFIG-based WEC
Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.; Burkes, Douglas
2014-04-23
Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum (U-10Mo) alloy plate-type fuel for the U.S. high-performance research reactors. This work supports the Convert Program of the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) Global Threat Reduction Initiative. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll separating forces and rolling defects. Simulations were performed using a finite-element model developed using the commercial code LS-Dyna. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel have been conducted following two different schedules. Model predictions of the roll-separation force and roll-pack thicknesses at different stages of the rolling process were compared with experimental measurements. This report discusses various attributes of the rolled coupons revealed by the model (e.g., dog-boning and thickness non-uniformity).
Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models
ALANQAR, ANAS WAEL
2015-01-01
define the average economic cost index as: J e = t f Z t f kon the average economic cost index, which are kmol/m 3 , areperiod. LEMPC, the economic cost index is 15.70, while the
Explicit Model Predictive Control for Large-Scale Systems via Model Reduction
Gravdahl, Jan Tommy
Tommy Gravdahl Norwegian University of Science and Technology, N-7491 Trondheim, Norway and Karen E. Willcox Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA In this paper we of Engineering Cybernetics; svein.hovland@itk.ntnu.no. Professor, Department of Engineering Cybernetics; tommy
Watney, W.L.
1994-12-01
Reservoirs in the Lansing-Kansas City limestone result from complex interactions among paleotopography (deposition, concurrent structural deformation), sea level, and diagenesis. Analysis of reservoirs and surface and near-surface analogs has led to developing a {open_quotes}strandline grainstone model{close_quotes} in which relative sea-level stabilized during regressions, resulting in accumulation of multiple grainstone buildups along depositional strike. Resulting stratigraphy in these carbonate units are generally predictable correlating to inferred topographic elevation along the shelf. This model is a valuable predictive tool for (1) locating favorable reservoirs for exploration, and (2) anticipating internal properties of the reservoir for field development. Reservoirs in the Lansing-Kansas City limestones are developed in both oolitic and bioclastic grainstones, however, re-analysis of oomoldic reservoirs provides the greatest opportunity for developing bypassed oil. A new technique, the {open_quotes}Super{close_quotes} Pickett crossplot (formation resistivity vs. porosity) and its use in an integrated petrophysical characterization, has been developed to evaluate extractable oil remaining in these reservoirs. The manual method in combination with 3-D visualization and modeling can help to target production limiting heterogeneities in these complex reservoirs and moreover compute critical parameters for the field such as bulk volume water. Application of this technique indicates that from 6-9 million barrels of Lansing-Kansas City oil remain behind pipe in the Victory-Northeast Lemon Fields. Petroleum geologists are challenged to quantify inferred processes to aid in developing rationale geologically consistent models of sedimentation so that acceptable levels of prediction can be obtained.
Peyret, Thomas [DSEST, Universite de Montreal, Canada H3T 1A8 (Canada); Poulin, Patrick [Consultant, 4009 rue Sylvia Daoust, Quebec City, Quebec, G1X 0A6 (Canada); Krishnan, Kannan, E-mail: kannan.krishnan@umontreal.ca [DSEST, Universite de Montreal, H3T 1A8 (Canada)
2010-12-15
The algorithms in the literature focusing to predict tissue:blood PC (P{sub tb}) for environmental chemicals and tissue:plasma PC based on total (K{sub p}) or unbound concentration (K{sub pu}) for drugs differ in their consideration of binding to hemoglobin, plasma proteins and charged phospholipids. The objective of the present study was to develop a unified algorithm such that P{sub tb}, K{sub p} and K{sub pu} for both drugs and environmental chemicals could be predicted. The development of the unified algorithm was accomplished by integrating all mechanistic algorithms previously published to compute the PCs. Furthermore, the algorithm was structured in such a way as to facilitate predictions of the distribution of organic compounds at the macro (i.e. whole tissue) and micro (i.e. cells and fluids) levels. The resulting unified algorithm was applied to compute the rat P{sub tb}, K{sub p} or K{sub pu} of muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, aliphatic hydrocarbons, aromatic hydrocarbons and ethers. The unified algorithm reproduced adequately the values predicted previously by the published algorithms for a total of 142 drugs and chemicals. The sensitivity analysis demonstrated the relative importance of the various compound properties reflective of specific mechanistic determinants relevant to prediction of PC values of drugs and environmental chemicals. Overall, the present unified algorithm uniquely facilitates the computation of macro and micro level PCs for developing organ and cellular-level PBPK models for both chemicals and drugs.
Carl H. Albright; S. Geer
2001-10-16
Within the framework of an SO(10) GUT model that can accommodate both the atmospheric and the LMA solar neutrino mixing solutions, we present explicit predictions for the neutrino oscillation parameters \\sin^2 2\\theta_{13}, \\sin^2 2\\theta_{12}, \\sin^2 2\\theta_{23}, and \\Delta m^2_{21}. Precise measurements of \\sin^2 2\\theta_{12} and \\Delta m^2_{21} by KamLAND can be used to precisely determine the GUT model parameters. We find that the model can then be tested at Neutrino Superbeams and Neutrino Factories with precision neutrino oscillation measurements of \\sin^2 2\\theta_{23}, \\sin^2 2\\theta_{13}, and the leptonic CP phase \\delta_{CP}.
Bulalo field, Philippines: Reservoir modeling for prediction of limits to sustainable generation
Strobel, Calvin J.
1993-01-28
The Bulalo geothermal field, located in Laguna province, Philippines, supplies 12% of the electricity on the island of Luzon. The first 110 MWe power plant was on line May 1979; current 330 MWe (gross) installed capacity was reached in 1984. Since then, the field has operated at an average plant factor of 76%. The National Power Corporation plans to add 40 MWe base load and 40 MWe standby in 1995. A numerical simulation model for the Bulalo field has been created that matches historic pressure changes, enthalpy and steam flash trends and cumulative steam production. Gravity modeling provided independent verification of mass balances and time rate of change of liquid desaturation in the rock matrix. Gravity modeling, in conjunction with reservoir simulation provides a means of predicting matrix dry out and the time to limiting conditions for sustainable levelized steam deliverability and power generation.
Fronefield Crawford; Marek Demianski
2003-06-11
There are currently two well-accepted models that explain how pulsars exhibit glitches, sudden changes in their regular rotational spin-down. According to the starquake model, the glitch healing parameter, Q, which is measurable in some cases from pulsar timing, should be equal to the ratio of the moment of inertia of the superfluid core of a neutron star (NS) to its total moment of inertia. Measured values of the healing parameter from pulsar glitches can therefore be used in combination with realistic NS structure models as one test of the feasibility of the starquake model as a glitch mechanism. We have constructed NS models using seven representative equations of state of superdense matter to test whether starquakes can account for glitches observed in the Crab and Vela pulsars, for which the most extensive and accurate glitch data are available. We also present a compilation of all measured values of Q for Crab and Vela glitches to date which have been separately published in the literature. We have computed the fractional core moment of inertia for stellar models covering a range of NS masses and find that for stable NSs in the realistic mass range 1.4 +/- 0.2 solar masses, the fraction is greater than 0.55 in all cases. This range is not consistent with the observational restriction Q 0.7) are consistent with the starquake model predictions and support previous conclusions that starquakes can be the cause of Crab glitches.
Failure Predictions for VHTR Core Components using a Probabilistic Contiuum Damage Mechanics Model
Fok, Alex
2013-10-30
The proposed work addresses the key research need for the development of constitutive models and overall failure models for graphite and high temperature structural materials, with the long-term goal being to maximize the design life of the Next Generation Nuclear Plant (NGNP). To this end, the capability of a Continuum Damage Mechanics (CDM) model, which has been used successfully for modeling fracture of virgin graphite, will be extended as a predictive and design tool for the core components of the very high- temperature reactor (VHTR). Specifically, irradiation and environmental effects pertinent to the VHTR will be incorporated into the model to allow fracture of graphite and ceramic components under in-reactor conditions to be modeled explicitly using the finite element method. The model uses a combined stress-based and fracture mechanics-based failure criterion, so it can simulate both the initiation and propagation of cracks. Modern imaging techniques, such as x-ray computed tomography and digital image correlation, will be used during material testing to help define the baseline material damage parameters. Monte Carlo analysis will be performed to address inherent variations in material properties, the aim being to reduce the arbitrariness and uncertainties associated with the current statistical approach. The results can potentially contribute to the current development of American Society of Mechanical Engineers (ASME) codes for the design and construction of VHTR core components.
Traffic Optimization to Control Epidemic Outbreaks in Metapopulation Models
Preciado, Victor M
2013-01-01
We propose a novel framework to study viral spreading processes in metapopulation models. Large subpopulations (i.e., cities) are connected via metalinks (i.e., roads) according to a metagraph structure (i.e., the traffic infrastructure). The problem of containing the propagation of an epidemic outbreak in a metapopulation model by controlling the traffic between subpopulations is considered. Controlling the spread of an epidemic outbreak can be written as a spectral condition involving the eigenvalues of a matrix that depends on the network structure and the parameters of the model. Based on this spectral condition, we propose a convex optimization framework to find cost-optimal approaches to traffic control in epidemic outbreaks.
Threshold Values for Identification of Contamination Predicted by Reduced-Order Models
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Last, George V.; Murray, Christopher J.; Bott, Yi-Ju; Brown, Christopher F.
2014-12-31
The U.S. Department of Energy’s (DOE’s) National Risk Assessment Partnership (NRAP) Project is developing reduced-order models to evaluate potential impacts on underground sources of drinking water (USDWs) if CO2 or brine leaks from deep CO2 storage reservoirs. Threshold values, below which there would be no predicted impacts, were determined for portions of two aquifer systems. These threshold values were calculated using an interwell approach for determining background groundwater concentrations that is an adaptation of methods described in the U.S. Environmental Protection Agency’s Unified Guidance for Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities.
Istrail, Sorin
Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction This paper considers the protein structure prediction problem for lattice and off-lattice protein folding tools for reasoning about protein folding in unrestricted continuous space through anal- ogy. This paper
Baker, Jack W.
Regression models for predicting the probability of near-fault earthquake ground motion pulses to the earthquake magnitude, but other predictive parameters are also considered and discussed. Both empirical University, Stanford, CA, USA ABSTRACT: Near-fault earthquake ground motions containing large velocity pulses
California at Berkeley, University of
Discrepancies in the prediction of solar wind using potential field source surface model expansion factor (FTE) at the source surface and the solar wind speed (SWS) observed at Earth, which has been made use of in the prediction of solar wind speed near the Earth with reasonable accuracy. However
Drover, Damion, Ryan
2011-12-01
One of the largest exports in the Southeast U.S. is forest products. Interest in biofuels using forest biomass has increased recently, leading to more research into better forest management BMPs. The USDA Forest Service, along with the Oak Ridge National Laboratory, University of Georgia and Oregon State University are researching the impacts of intensive forest management for biofuels on water quality and quantity at the Savannah River Site in South Carolina. Surface runoff of saturated areas, transporting excess nutrients and contaminants, is a potential water quality issue under investigation. Detailed maps of variable source areas and soil characteristics would therefore be helpful prior to treatment. The availability of remotely sensed and computed digital elevation models (DEMs) and spatial analysis tools make it easy to calculate terrain attributes. These terrain attributes can be used in models to predict saturated areas or other attributes in the landscape. With laser altimetry, an area can be flown to produce very high resolution data, and the resulting data can be resampled into any resolution of DEM desired. Additionally, there exist many maps that are in various resolutions of DEM, such as those acquired from the U.S. Geological Survey. Problems arise when using maps derived from different resolution DEMs. For example, saturated areas can be under or overestimated depending on the resolution used. The purpose of this study was to examine the effects of DEM resolution on the calculation of topographic wetness indices used to predict variable source areas of saturation, and to find the best resolutions to produce prediction maps of soil attributes like nitrogen, carbon, bulk density and soil texture for low-relief, humid-temperate forested hillslopes. Topographic wetness indices were calculated based on the derived terrain attributes, slope and specific catchment area, from five different DEM resolutions. The DEMs were resampled from LiDAR, which is a laser altimetry remote sensing method, obtained from the USDA Forest Service at Savannah River Site. The specific DEM resolutions were chosen because they are common grid cell sizes (10m, 30m, and 50m) used in mapping for management applications and in research. The finer resolutions (2m and 5m) were chosen for the purpose of determining how finer resolutions performed compared with coarser resolutions at predicting wetness and related soil attributes. The wetness indices were compared across DEMs and with each other in terms of quantile and distribution differences, then in terms of how well they each correlated with measured soil attributes. Spatial and non-spatial analyses were performed, and predictions using regression and geostatistics were examined for efficacy relative to each DEM resolution. Trends in the raw data and analysis results were also revealed.
Broader source: Energy.gov [DOE]
Predictive maintenance aims to detect equipment degradation and address problems as they arise. The result indicates potential issues, which are controlled or eliminated prior to any significant system deterioration.
Ruggero Maria Santilli
2006-02-17
In this note, we propose, apparently for the first time, a new type of controlled nuclear fusion called "intermediate" because occurring at energies intermediate between those of the ''cold'' and ''hot'' fusions, and propose a specific industrial realization. For this purpose: 1) We show that known limitations of quantum mechanics, quantum chemistry and special relativity cause excessive departures from the conditions occurring for all controlled fusions; 2) We outline the covering hadronic mechanics, hadronic chemistry and isorelativity specifically conceived, constructed and verified during the past two decades for new cleans energies and fuels; 3) We identify seven physical laws predicted by the latter disciplines that have to be verified by all controlled nuclear fusions to occur; 4) We review the industrial research conducted to date in the selection of the most promising engineering realization as well as optimization of said seven laws; and 5) We propose with construction details a specific {\\it hadronic reactor} (patented and international patents pending), consisting of actual equipment specifically intended for the possible industrial production of the clean energy released by representative cases of controlled intermediate fusions for independent scrutiny by interested colleagues.
Kamal, Sameer A. (Sameer Ahmed)
2009-01-01
This thesis describes the use of a distributed hydrology model in conjunction with a Factor of Safety (FS) algorithm to predict dynamic landslide susceptibility for a humid basin in Puerto Rico. The Mameyes basin, located ...
Ko, Hanseo
1994-01-01
An analytical model is established to predict an electrostatically charged particle deposition as a function of particle size in fully-developed turbulent pipe flow. The convectivediffusion flux equation is solved for the particle concentration as a...
Wang, Jinrong
1996-01-01
-retrofit weather is generally different from the weather used for model development, the prediction error of the baseline model may be different from the fitting error. Daily and monthly baseline models were developed for a midsize commercial building with (i) dual...
A Predictive Model of Fragmentation using Adaptive Mesh Refinement and a Hierarchical Material Model
Koniges, A E; Masters, N D; Fisher, A C; Anderson, R W; Eder, D C; Benson, D; Kaiser, T B; Gunney, B T; Wang, P; Maddox, B R; Hansen, J F; Kalantar, D H; Dixit, P; Jarmakani, H; Meyers, M A
2009-03-03
Fragmentation is a fundamental material process that naturally spans spatial scales from microscopic to macroscopic. We developed a mathematical framework using an innovative combination of hierarchical material modeling (HMM) and adaptive mesh refinement (AMR) to connect the continuum to microstructural regimes. This framework has been implemented in a new multi-physics, multi-scale, 3D simulation code, NIF ALE-AMR. New multi-material volume fraction and interface reconstruction algorithms were developed for this new code, which is leading the world effort in hydrodynamic simulations that combine AMR with ALE (Arbitrary Lagrangian-Eulerian) techniques. The interface reconstruction algorithm is also used to produce fragments following material failure. In general, the material strength and failure models have history vector components that must be advected along with other properties of the mesh during remap stage of the ALE hydrodynamics. The fragmentation models are validated against an electromagnetically driven expanding ring experiment and dedicated laser-based fragmentation experiments conducted at the Jupiter Laser Facility. As part of the exit plan, the NIF ALE-AMR code was applied to a number of fragmentation problems of interest to the National Ignition Facility (NIF). One example shows the added benefit of multi-material ALE-AMR that relaxes the requirement that material boundaries must be along mesh boundaries.
Bonne, François; Bonnay, Patrick [INAC, SBT, UMR-E 9004 CEA/UJF-Grenoble, 17 rue des Martyrs, 38054 Grenoble (France); Alamir, Mazen [Gipsa-Lab, Control Systems Department, CNRS-University of Grenoble, 11, rue des Mathématiques, BP 46, 38402 Saint Martin d'Hères (France)
2014-01-29
In this paper, a physical method to obtain control-oriented dynamical models of large scale cryogenic refrigerators is proposed, in order to synthesize model-based advanced control schemes. These schemes aim to replace classical user experience designed approaches usually based on many independent PI controllers. This is particularly useful in the case where cryoplants are submitted to large pulsed thermal loads, expected to take place in the cryogenic cooling systems of future fusion reactors such as the International Thermonuclear Experimental Reactor (ITER) or the Japan Torus-60 Super Advanced Fusion Experiment (JT-60SA). Advanced control schemes lead to a better perturbation immunity and rejection, to offer a safer utilization of cryoplants. The paper gives details on how basic components used in the field of large scale helium refrigeration (especially those present on the 400W @1.8K helium test facility at CEA-Grenoble) are modeled and assembled to obtain the complete dynamic description of controllable subsystems of the refrigerator (controllable subsystems are namely the Joule-Thompson Cycle, the Brayton Cycle, the Liquid Nitrogen Precooling Unit and the Warm Compression Station). The complete 400W @1.8K (in the 400W @4.4K configuration) helium test facility model is then validated against experimental data and the optimal control of both the Joule-Thompson valve and the turbine valve is proposed, to stabilize the plant under highly variable thermals loads. This work is partially supported through the European Fusion Development Agreement (EFDA) Goal Oriented Training Program, task agreement WP10-GOT-GIRO.
Muendej, Krisanee
2004-11-15
Thirty convenience stores in College Station, Texas, have been selected as the samples for an energy consumption prediction. The predicted models assist facility energy managers for making decisions of energy demand/supply plans. The models...
Yunovich, M.; Thompson, N.G.
1998-12-31
During the past fifteen years corrosion inhibiting admixtures (CIAs) have become increasingly popular for protection of reinforced components of highway bridges and other structures from damage induced by chlorides. However, there remains considerable debate about the benefits of CIAs in concrete. A variety of testing methods to assess the performance of CIA have been reported in the literature, ranging from tests in simulated pore solutions to long-term exposures of concrete slabs. The paper reviews the published techniques and recommends the methods which would make up a comprehensive CIA effectiveness testing program. The results of this set of tests would provide the data which can be used to rank the presently commercially available CIA and future candidate formulations utilizing a proposed predictive model. The model is based on relatively short-term laboratory testing and considers several phases of a service life of a structure (corrosion initiation, corrosion propagation without damage, and damage to the structure).
Mass predictions of atomic nuclei in the infinite nuclear matter model
Nayak, R.C., E-mail: rcnayak00@yahoo.com [Department of Physics, Berhampur University, Berhampur-760 007 (India); Satpathy, L., E-mail: satpathy@iopb.res.in [Institute of Physics, Bhubaneswar-751 005 (India)
2012-07-15
We present here the mass excesses, binding energies, one- and two-neutron, one- and two-proton and {alpha}-particle separation energies of 6727 nuclei in the ranges 4{<=}Z{<=}120 and 8{<=}A{<=}303 calculated in the infinite nuclear matter model. Compared to our predictions of 1999 mass table, the present ones are obtained using larger data base of 2003 mass table of Wapstra and Audi and resorting to higher accuracy in the solutions of the {eta}-differential equations of the INM model. The local energy {eta}'s supposed to carry signature of the characteristic properties of nuclei are found to possess the predictive capability. In fact {eta}-systematics reveal new magic numbers in the drip-line regions giving rise to new islands of stability supported by relativistic mean field theoretic calculations. This is a manifestation of a new phenomenon where shell-effect overcomes the instability due to repulsive components of the nucleon-nucleon force broadening the stability peninsula. The two-neutron separation energy-systematics derived from the present mass predictions reveal a general new feature for the existence of islands of inversion in the exotic neutron-rich regions of nuclear landscape, apart from supporting the presently known islands around {sup 31}Na and {sup 62}Ti. The five global parameters representing the properties of infinite nuclear matter, the surface, the Coulomb and the pairing terms are retained as per our 1999 mass table. The root-mean-square deviation of the present mass-fit to 2198 known masses is 342 keV, while the mean deviation is 1.3 keV, reminiscent of no left-over systematic effects. This is a substantive improvement over our 1999 mass table having rms deviation of 401 keV and mean deviation of 9 keV for 1884 data nuclei.
Lall, Pradeep [Auburn Univ., Auburn, AL (United States); Wei, Junchao [Auburn Univ., Auburn, AL (United States); Sakalaukus, Peter [Auburn Univ., Auburn, AL (United States)
2014-06-22
A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The ?-? plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.
A voxel-based finite element model for the prediction of bladder deformation
Chai Xiangfei; Herk, Marcel van; Hulshof, Maarten C. C. M.; Bel, Arjan [Radiation Oncology Department, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam (Netherlands); Radiation Oncology Department, Netherlands Cancer Institute, 1066 CX Amsterdam (Netherlands); Radiation Oncology Department, Academic Medical Center, University of Amsterdam, 1105 AZ Amsterdam (Netherlands)
2012-01-15
Purpose: A finite element (FE) bladder model was previously developed to predict bladder deformation caused by bladder filling change. However, two factors prevent a wide application of FE models: (1) the labor required to construct a FE model with high quality mesh and (2) long computation time needed to construct the FE model and solve the FE equations. In this work, we address these issues by constructing a low-resolution voxel-based FE bladder model directly from the binary segmentation images and compare the accuracy and computational efficiency of the voxel-based model used to simulate bladder deformation with those of a classical FE model with a tetrahedral mesh. Methods: For ten healthy volunteers, a series of MRI scans of the pelvic region was recorded at regular intervals of 10 min over 1 h. For this series of scans, the bladder volume gradually increased while rectal volume remained constant. All pelvic structures were defined from a reference image for each volunteer, including bladder wall, small bowel, prostate (male), uterus (female), rectum, pelvic bone, spine, and the rest of the body. Four separate FE models were constructed from these structures: one with a tetrahedral mesh (used in previous study), one with a uniform hexahedral mesh, one with a nonuniform hexahedral mesh, and one with a low-resolution nonuniform hexahedral mesh. Appropriate material properties were assigned to all structures and uniform pressure was applied to the inner bladder wall to simulate bladder deformation from urine inflow. Performance of the hexahedral meshes was evaluated against the performance of the standard tetrahedral mesh by comparing the accuracy of bladder shape prediction and computational efficiency. Results: FE model with a hexahedral mesh can be quickly and automatically constructed. No substantial differences were observed between the simulation results of the tetrahedral mesh and hexahedral meshes (<1% difference in mean dice similarity coefficient to manual contours and <0.02 cm difference in mean standard deviation of residual errors). The average equation solving time (without manual intervention) for the first two types of hexahedral meshes increased to 2.3 h and 2.6 h compared to the 1.1 h needed for the tetrahedral mesh, however, the low-resolution nonuniform hexahedral mesh dramatically decreased the equation solving time to 3 min without reducing accuracy. Conclusions: Voxel-based mesh generation allows fast, automatic, and robust creation of finite element bladder models directly from binary segmentation images without user intervention. Even the low-resolution voxel-based hexahedral mesh yields comparable accuracy in bladder shape prediction and more than 20 times faster in computational speed compared to the tetrahedral mesh. This approach makes it more feasible and accessible to apply FE method to model bladder deformation in adaptive radiotherapy.
Tucker, Susan L., E-mail: sltucker@mdanderson.org [Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Li Minghuan [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China)] [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Xu Ting; Gomez, Daniel [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Yuan Xianglin [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China)] [Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China); Yu Jinming [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China)] [Department of Radiation Oncology, Shandong Cancer Hospital, Jinan, Shandong (China); Liu Zhensheng; Yin Ming; Guan Xiaoxiang; Wang Lie; Wei Qingyi [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mohan, Radhe [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Vinogradskiy, Yevgeniy [University of Colorado School of Medicine, Aurora, Colorado (United States)] [University of Colorado School of Medicine, Aurora, Colorado (United States); Martel, Mary [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao Zhongxing [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)] [Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas (United States)
2013-01-01
Purpose: To determine whether single-nucleotide polymorphisms (SNPs) in genes associated with DNA repair, cell cycle, transforming growth factor-{beta}, tumor necrosis factor and receptor, folic acid metabolism, and angiogenesis can significantly improve the fit of the Lyman-Kutcher-Burman (LKB) normal-tissue complication probability (NTCP) model of radiation pneumonitis (RP) risk among patients with non-small cell lung cancer (NSCLC). Methods and Materials: Sixteen SNPs from 10 different genes (XRCC1, XRCC3, APEX1, MDM2, TGF{beta}, TNF{alpha}, TNFR, MTHFR, MTRR, and VEGF) were genotyped in 141 NSCLC patients treated with definitive radiation therapy, with or without chemotherapy. The LKB model was used to estimate the risk of severe (grade {>=}3) RP as a function of mean lung dose (MLD), with SNPs and patient smoking status incorporated into the model as dose-modifying factors. Multivariate analyses were performed by adding significant factors to the MLD model in a forward stepwise procedure, with significance assessed using the likelihood-ratio test. Bootstrap analyses were used to assess the reproducibility of results under variations in the data. Results: Five SNPs were selected for inclusion in the multivariate NTCP model based on MLD alone. SNPs associated with an increased risk of severe RP were in genes for TGF{beta}, VEGF, TNF{alpha}, XRCC1 and APEX1. With smoking status included in the multivariate model, the SNPs significantly associated with increased risk of RP were in genes for TGF{beta}, VEGF, and XRCC3. Bootstrap analyses selected a median of 4 SNPs per model fit, with the 6 genes listed above selected most often. Conclusions: This study provides evidence that SNPs can significantly improve the predictive ability of the Lyman MLD model. With a small number of SNPs, it was possible to distinguish cohorts with >50% risk vs <10% risk of RP when they were exposed to high MLDs.
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity
Zhao, Qingyuan; He, Hera Y; Rajaraman, Anand; Leskovec, Jure
2015-01-01
Social networking websites allow users to create and share content. Big information cascades of post resharing can form as users of these sites reshare others' posts with their friends and followers. One of the central challenges in understanding such cascading behaviors is in forecasting information outbreaks, where a single post becomes widely popular by being reshared by many users. In this paper, we focus on predicting the final number of reshares of a given post. We build on the theory of self-exciting point processes to develop a statistical model that allows us to make accurate predictions. Our model requires no training or expensive feature engineering. It results in a simple and efficiently computable formula that allows us to answer questions, in real-time, such as: Given a post's resharing history so far, what is our current estimate of its final number of reshares? Is the post resharing cascade past the initial stage of explosive growth? And, which posts will be the most reshared in the future? We...
Phillips, T J; Potter, G L; Williamson, D L; Cederwall, R T; Boyle, J S; Fiorino, M; Hnilo, J J; Olson, J G; Xie, S; Yio, J J
2004-05-06
To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six-hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be tested in the same framework. In order to further this method for evaluating and analyzing parameterizations in climate GCMs, the U.S. Department of Energy is funding a joint venture of its Climate Change Prediction Program (CCPP) and Atmospheric Radiation Measurement (ARM) Program: the CCPP-ARM Parameterization Testbed (CAPT). This article elaborates the scientific rationale for CAPT, discusses technical aspects of its methodology, and presents examples of its implementation in a representative climate GCM.
Electric Water Heater Modeling and Control Strategies for Demand Response
Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.
2012-07-22
Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid
Kusiak, Andrew
35 A. Kusiak, S. Shah, and B. Dixon, Data mining based decision-making approach for predicting, Melbourne, Australia, published by Elsevier, Amsterdam, The Netherlands, August 2003, pp. 35-39. DATA MINING interventions and the dialysis treatment prescription. In this research, a data mining approach is used
ADAPTIVE MODEL BASED CONTROL FOR WASTEWATER TREATMENT PLANTS
Boucherie, Richard J.
that obliged the water boards to increase the energy-efficiency of wastewater treatment plants with at least 2ADAPTIVE MODEL BASED CONTROL FOR WASTEWATER TREATMENT PLANTS Arie de Niet1 , Maartje van de Vrugt2.j.boucherie@utwente.nl Abstract In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge
On Modeling and Robust Control of ARES Raktim Bhattacharya
Valasek, John
Station, Texas 77843-3141. This paper presents the development of a mathematical model and controller Variation of the airplane Side force coefficient with dimensionless yaw rate CL1 Lift coefficient at steady state conditions CLu =CL/(u/U1) Variation of the airplane Lift coefficient with dimensionless speed CL
Error Control Based Model Reduction for Parameter Optimization of Elliptic
of technical devices that rely on multiscale processes, such as fuel cells or batteries. As the solutionError Control Based Model Reduction for Parameter Optimization of Elliptic Homogenization Problems optimization of elliptic multiscale problems with macroscopic optimization functionals and microscopic material
Model checking LTL over controllable linear systems is decidable
Pappas, George J.
Model checking LTL over controllable linear systems is decidable Paulo Tabuada and George J. Pappas Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia, PA 19104 {tabuadap,pappasg}@seas.upenn.edu Abstract. The use of algorithmic verification and synthesis tools for hy- brid systems is currently limited
Learning models of camera control for imitation in football matches
Demiris, Yiannis
Learning models of camera control for imitation in football matches Anthony Dearden and Yiannis of learning from and imitating the movement of a trained cameraman and his director covering a football match to move in a football match. This scenario has useful applications in both sim- ulation and real
A Theory of Impedance Control based on Internal Model Uncertainty
Mitrovic, Djordje; Klanke, Stefan; Vijayakumar, Sethu; Haith, Adrian
2009-01-01
level mechanisms to try to account for observed human co-activation patterns [3]. However these models are of a rather descriptive nature and do not provide us with a general and principled theory of impedance control in the nervous system....
Dynamic Modelling and Control Design of Pre-combustion Power
Foss, Bjarne A.
principles. The pre- combustion gas power cycle plants consist of reformers and separation units, com and control design of two pre-combustion power cycles, i.e., a hydro- gen membrane reformer (HMR) based power- pressors, gas and steam turbines and a heat recovery system. Analysis of dynamic models at an early stage
MODELING AND CONTROL OF A CONTINUOUS BIOREACTOR WITH CROSSFLOW FILTRATION
Skogestad, Sigurd
MODELING AND CONTROL OF A CONTINUOUS BIOREACTOR WITH CROSSFLOW FILTRATION Ying Zhao and Sigurd on an industrial application of a continuous bioreactor with crossflow filtration. In this paper the general pHC LC X, rS L , rS Y Figure 1: A continuous bioreactor with crossflow filtration. The operation
Hybrid Control Models of Next Generation Air Traffic Management ?
Pappas, George J.
Hybrid Control Models of Next Generation Air Traffic Management ? C. Tomlin, G. Pappas, J. Lygeros the overcrowding of large urban airports and the need to more efficiently handle larger numbers of aircraft malfunctions, ATC malfunctions (e.g. power failure), shifting winds (that cause changes in approach patterns
Dynamic Modelling for Control of Fuel Cells Federico Zenith
Skogestad, Sigurd
Dynamic Modelling for Control of Fuel Cells Federico Zenith Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Technology ( ntnu) Trondheim Abstract Fuel-cell dynamics have been investigated with a variable-resistance board applied to a high temperature polymer fuel cell
A nuclear data acquisition system flow control model
Hack, S.N.
1988-02-01
A general Petri Net representation of a nuclear data acquisition system model is presented. This model provides for the unique requirements of a nuclear data acquisition system including the capabilities of concurrently acquiring asynchronous and synchronous data, of providing multiple priority levels of flow control arbitration, and of permitting multiple input sources to reside at the same priority without the problem of channel lockout caused by a high rate data source. Finally, a previously implemented gamma camera/physiological signal data acquisition system is described using the models presented.
Antsaklis, Panos
of Unmanned Aerial Vehicles Current Status and Future Directions," Chapter 9, Modeling and Control of Complex of Unmanned Aerial Vehicles Current Status and Future Directions," Chapter 9, Modeling and Control of Complex of Unmanned Aerial Vehicles Current Status and Future Directions," Chapter 9, Modeling and Control of Complex