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
Optimization Online - Nonlinear Model Predictive Control via ...
M. J. Tenny
2002-08-15T23:59:59.000Z
Aug 15, 2002 ... Nonlinear Model Predictive Control via Feasibility-Perturbed Sequential Quadratic Programming. M. J. Tenny (tenny ***at*** bevo.che.wisc.edu)
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
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
Model Predictive Control of Variable Density Multiphase Flows Governed by
Hinze, Michael
of model predictive control (MPC) consists in steering or keeping the state of a dynamical systemModel Predictive Control of Variable Density Multiphase Flows Governed by Diffuse Interface Models appearing in the model predictive control strategy. The resulting control concept is known as instantaneous
Model Predictive Control for Smooth Distributed Power Adaptation
Boyer, Edmond
1 Model Predictive Control for Smooth Distributed Power Adaptation Virgile Garcia1,2,3 , Nikolai the variations of other BS powers. The trajectories are then updated using a Model Predictive Control (MPC-based power control, no inter-cell cooperation, power trajectory, model predictive control, smooth power
NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITYPERTURBED SEQUENTIAL QUADRATIC
Wright, Steve
NONLINEAR MODEL PREDICTIVE CONTROL VIA FEASIBILITYÂPERTURBED SEQUENTIAL QUADRATIC PROGRAMMINGÂ06, AUGUST 2002, COMPUTER SCIENCES DEPT, UNIV. OF WISCONSIN TEXASÂWISCONSIN MODELING AND CONTROL CONSORTIUM REPORT TWMCCÂ2002Â02 Abstract. Model predictive control requires the solution of a sequence of continuous
Flood control of the Demer by using Model Predictive Control Maarten Breckpot a,n
Flood 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 t It is shown how Model Predictive Control can be used for flood control of river systems modelled with real
Model Predictive Control in Power Electronics: A Hybrid Systems Approach
Sontag, Eduardo
Model Predictive Control in Power Electronics: A Hybrid Systems Approach Tobias Geyer, Georgios- ologies to power electronics systems. More specifically, we show how Model Predictive Control (MPC) [1 the control point of view, power electronics circuits and systems constitute excellent examples of hybrid
Model Predictive Control of a Kaibel Distillation Column
Skogestad, Sigurd
Model Predictive Control of a Kaibel Distillation Column Martin Kvernland Ivar Halvorsen Sigurd (e-mail: skoge@ntnu.no) Abstract: This is a simulation study on controlling a Kaibel distillation column with model predictive control (MPC). A Kaibel distillation column has several advantages compared
Nonlinear Model Predictive Control of an Omnidirectional Mobile Robot
Zell, Andreas
, University of TÃ¼bingen, Sand 1, 72076 TÃ¼bingen, Germany Abstract. This paper focuses on motion controlNonlinear Model Predictive Control of an Omnidirectional Mobile Robot Xiang LI a,1 , Kiattisin problems of an omnidirectional robot based on the Nonlinear Model Predictive Control (NMPC) method
Plug-and-Play Decentralized Model Predictive Control Stefano Riverso
Ferrari-Trecate, Giancarlo
Plug-and-Play Decentralized Model Predictive Control Stefano Riverso , Marcello Farina. When this is possible, we show how to automatize the design of local controllers so that it can information with neighboring subsystems. In particular, local controllers exploit tube-based Model Predictive
Model Predictive Control based Real Time Power System Protection Schemes
Kumar, Ratnesh
1 Model Predictive Control based Real Time Power System Protection Schemes Licheng Jin, Member by controlling the production, absorption as well as flow of reactive power at various locations in the system predictive control, trajectory sensitivity, voltage stabilization, switching control, power system I
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
2012-07-22T23:59:59.000Z
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
2000-01-01T23:59:59.000Z
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 engineers, and for anyone...
Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants
Van den Hof, Paul
Nonlinear Model Predictive Control of Municipal Solid Waste Combustion Plants M. Leskens , R.h.Bosgra@tudelft.nl, p.m.j.vandenhof@tudelft.nl Keywords : nonlinear model predictive control, municipal solid waste combus- tion Abstract : Combustion of municipal solid waste (MSW; = household waste) is used to reduce
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
control logic for building energy systems. Most moderncontrol actuators. Modern digital building automation systemssystem in the lab. The lab is equipped with a modern digital control
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
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
Duong, Thien Chi
2011-02-22T23:59:59.000Z
. The reason for choosing these applications is that they introduce more control challenges than non-real-time services. One promising flow control strategy was proposed by Bhattacharya and it was based on Model Predictive Control (MPC). The controller...
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
Model Predictive Control with Prioritised Actuators
Gallieri, Marco; Maciejowski, Jan M.
2015-05-26T23:59:59.000Z
makes use of multi-parametric programming and the theory of exact penalty functions (Theorem 14.3.1 of [5]). *Research supported by the EPSRC grant “Control for Energy and Sustainability”, EP/G066477/1. 1 Marco Gallieri is with McLaren Racing Limited...
Tuning Methods for Model Predictive Controllers
methods for tuning of a Gas-Oil Furnace, a Wood-Berry Distillation Column and a Cement Mill Circuit. #12 to develop a tuning toolbox for SISO systems, which visualizes the performance of control designs. A study systemer, som kan visualisere ydelsen af regulator designs. Der er undersøgt, hvorledes ydelsesm
Model Predictive Control of Residential Energy Systems Using
Knobloch,Jürgen
, a local energy storage element, and solar photovoltaic panels. Each RES is connected to the widerModel Predictive Control of Residential Energy Systems Using Energy Storage & Controllable Loads energy storage and smart energy scheduling can be used to flatten energy profiles with undesirable peaks
Incorporating Control Performance Tuning into Economic Model Predictive Control
Olanrewaju, Olumuyiwa I.; Maciejowski, Jan M.
2015-01-01T23:59:59.000Z
[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...
Axis control using model predictive control: identification and friction effect reduction
Boyer, Edmond
Axis control using model predictive control: identification and friction effect reduction Pedro this numerical model is used to synthetize a predictive GPC controller reducing the impact of the friction Rodriguez-Ayerbe, Didier Dumur, Sylvain Lavernhe** * SUPELEC- E3S, Automatic Control, 3 rue Joliot Curie
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
Terminal Spacecraft Rendezvous and Capture with LASSO Model Predictive Control
Hartley, Edward N.; Gallieri, Marco; Maciejowski, Jan M.
2013-08-20T23:59:59.000Z
.S., and How, J.P. (2006), “Safe Trajectories for Autonomous Rendezvous of Space- craft,” in Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Keystone, CO, Aug. 21–24. Breger, L., and How, J.P. (2005), “J2-Modified GVE-based MPC... for deeply pipelined FPGA implementation: Algorithms and Circuitry,” IET Control Theory & Applica- tions, (Under review). Joelianto, E., and Hernawan, F.M. (2009), “Multiplexed Model Predictive Control Weighting Selection using Genetic Algorithm,” in Proc...
Fast Nonconvex Model Predictive Control for Commercial Refrigeration
Fast Nonconvex Model Predictive Control for Commercial Refrigeration Tobias Gybel Hovgard , Lars F multi-zone refrigeration system, consisting of several cooling units that share a common compressor. This corresponds roughly to 2% of the entire electricity consumption in the country. Refrigerated goods constitute
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)
1997-01-01T23:59:59.000Z
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.
1997-08-19T23:59:59.000Z
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
2010-08-31T23:59:59.000Z
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.
Duong, Thien Chi
2011-02-22T23:59:59.000Z
FLOW CONTROL OF REAL TIME MULTIMEDIA APPLICATIONS USING MODEL PREDICTIVE CONTROL WITH A FEED FORWARD TERM A Thesis by THIEN CHI DUONG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2010 Major Subject: Mechanical Engineering Flow Control of Real Time Multimedia Applications Using Model Predictive Control with Feed Forward Term...
Johansen, Tor Arne
Model predictive control of power plant superheater comparison of multi model and nonlinear Norway Tor.Arne.Johansen@itk.ntnu.no Abstract -- Model predictive control of a three stage power plant superheater is investigated in this paper. This power plant subsystem consists of three heat exchangers
Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong
Paris-Sud XI, Université de
Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong of the dynamics of the robot and propose a new Linear Model Predictive Control scheme which is an improvement are unfortunately severely limited. Model Predictive Control, also known as Receding Horizon Control, is a general
Lapp, Tiffany Rae, 1979-
2004-01-01T23:59:59.000Z
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. ...
Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil], [3], the Airborne Wind Energy (AWE) paradigm shift proposes to get rid of the structural elements
Flood control of rivers with nonlinear model predictive control and moving horizon estimation
Flood 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 into account, it uses the buffer capacity of the available flood basins in a more optimal way. Simulation
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
-based predictive controllers (MPC) are becoming very popular in petrochemical refineries, as they simultaneously control ayd optimize large sections of a petrochemical process;yqng a predictive model. However, current
Distributed state estimation and model predictive control of linear interconnected system
Boyer, Edmond
requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive
Plug-and-play decentralized model predictive control for linear systems
Ferrari-Trecate, Giancarlo
1 Plug-and-play decentralized model predictive control for linear systems Stefano Riverso, Graduate to automatize the design of local controllers so that it can be carried out in parallel by smart actuators. In particular, local controllers exploit tube-based Model Predictive Control (MPC) in order to guarantee
Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive
Paris-Sud XI, Université de
Model Predictive Tracking Control for a Head-Positioning in a Hard-Disk-Drive M. Taktak-Meziou, A generated from Model Predictive Control (MPC). The first approach consists of a classical linear MPC without/Write (R/W) head of a Hard-Disk-Drive (HDD) servo-system, which is resolved with two control algorithms
Distributed event-based Model Predictive Control for Multi-Agent systems under disturbances
Dimarogonas, Dimos
Distributed event-based Model Predictive Control for Multi-Agent systems under disturbances an aperiodic formulation of Distributed Model Predictive Control for the cooperation of multi-agent systems loads under critical resource constraints in networked control systems, such as limited communication
Fault-tolerant model predictive control of a wind turbine benchmark
Cambridge, University of
Fault-tolerant model predictive control of a wind turbine benchmark X. Yang J.M. Maciejowski tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre component of the wind turbine. The global MPC is used to schedule the operation of the components
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 success in the petrochemical industry, they have introduced new challenges for the operators and engineers
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
DECENTRALIZED ROBUST NONLINEAR MODEL PREDICTIVE CONTROLLER FOR UNMANNED AERIAL SYSTEMS
Garcia, Gonzalo Andres
2013-05-31T23:59:59.000Z
that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2 A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3 An artificial neural network...
Energy Savings Through Application of Model Predictive Control to an Air Separation Facility
Hanson, T. C.; Scharf, P. F.
Energy Savings Through Application of Model Predictive Control to an Air Separation Facility Thomas C. Hanson PauiF. Scharf Manager Senior Engineering Associate Process Development Process Control Technology Praxair, Inc., Tonawanda, New York...
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
2012-01-01T23:59:59.000Z
optimization and control for intentionally transient processpredictive control and optimization of processes : enablingoperation. Within process control, the economic optimization
Interactive software for model predictive control with simultaneous identification
Echeverria Del Rio, Pablo
2000-01-01T23:59:59.000Z
and Internal Model Control (IMC) by Garcia and Morari (Garcia and Morari, 1982); the other one was about the stability of constrained MPC by Rawlings and Muske (Rawlings and Muske, 1993). Among the research papers and thesis that have been written about MPC... making process (Garcia, Prett and Morari, 1989). In order to obtain the maximum benefit from a process, several performance objectives should be specified and attained in the design and actual implementation of the plant. However, this condition...
Economic and Distributed Model Predictive Control of Nonlinear Systems
Heidarinejad, Mohsen
2012-01-01T23:59:59.000Z
hybrid systems. IEEE Transactions on Automatic Control, [6]nonlinear systems. IEEE Transactions on Automatic Control,of switched systems. IEEE Transactions on Automatic Control,
Economic Model Predictive Control of Nonlinear Process Systems Using Empirical Models
ALANQAR, ANAS WAEL
2015-01-01T23:59:59.000Z
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/
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
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
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01T23:59:59.000Z
storage in building cooling systems. Technical report,storage in building cooling systems. Decision and Control,for the Operation of Building Cooling Systems Yudong Ma ? ,
Embedded Online Optimization for Model Predictive Control at ...
2013-03-05T23:59:59.000Z
optimization-based control systems on low cost embedded platforms. ..... Modern computing platforms must allow for a wide range of applications that operate on.
Unit Commitment and Economic Model Predictive Control for
-controllable farms of wind turbines. The results of the simulations successfully show that the novel control strategy system operations. We demonstrate significant savings in imbalance cost and potential reduction and the input param- eterization for the UC have a cost impact on the solution. Solving the UC problem with high
Coordinated Dynamic Voltage Stabilization based on Model Predictive Control
Kumar, Ratnesh
devices, generator reactive power control, transformer tap changer control and load shedding. As shown to reduce power loss and to improve voltage profiles during a day. [12] presents an artificial neural response of a power system. [13] presents a method of coordination of load shedding, capacitor switchi
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
2012-07-03T23:59:59.000Z
. . . . . . . . . . . . . . . . . . . . . . . . . . . 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
2009-05-15T23:59:59.000Z
separate body of water, referred to as a cooling zone. The two evaporators are connected to a single condenser and variable speed compressor, and feature variable water flow and electronic expansion valves. The control problem lies in development of a...
Decentralized model predictive control of a multiple evaporator HVAC system
Elliott, Matthew Stuart
2009-05-15T23:59:59.000Z
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 ...
A Tutorial on Model Predictive Control for Spacecraft Rendezvous
Hartley, Edward N.
2015-05-26T23:59:59.000Z
sensors can be highly directional. However, unlike translation control, this can also be performed using reaction wheels, which expend only solar-generated electrical power, and therefore does not limit the lifetime of the mission. In Section II we... computation latency between measurement and control application, whilst maintaining relatively low clock rates required for robustness to effects such as solar radiation. Variable horizons are implemented by enumerating a sequence of optimisation problems...
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01T23:59:59.000Z
of the cooling towers while consuming less energy. Duringtowers, the thermal storage tank and the electricity energytowers, the thermal storage tank, the campus model and the electricity energy
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
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
Supervisory hybrid model predictive control for voltage stability of power networks
Paris-Sud XI, Université de
Supervisory hybrid model predictive control for voltage stability of power networks R.R. Negenborn voltage control problems in electric power networks have stimulated the interest for the imple- mentation dynamics to restore power consumption beyond the capability of the transmission and generation system
Model predictive adaptive control of process systems using recurrent neural networks
Parthasarathy, Sanjay
1993-01-01T23:59:59.000Z
) 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
Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa
2013-04-09T23:59:59.000Z
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.
2014-02-01T23:59:59.000Z
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.
Subsurface Flow Management and Real-Time Production Optimization using Model Predictive Control
Lopez, Thomas Jai
2012-02-14T23:59:59.000Z
research will focus on System Identification (System-ID) (Jansen, 2009) and Model Predictive Control (MPC) (Gildin, 2008) to serve this purpose. A mathematical treatment of System-ID and MPC as applied to reservoir simulation will be presented. Linear MPC...
Economic Nonlinear Model Predictive Control for the Optimization of Gas Pipeline Networks
Grossmann, Ignacio E.
/ 24 #12;Natural Gas Industry Motivation Natural Gas Industry Globally increasing demand & production of natural gas. Demand distribution (as of 2008) 21 % residential, 13 % Commercial, 34 % Industrial, 29 - Regulated, Deregulated markets Applying Economic Model Predictive Control to gas transportation. 1Zheng et
Model Predictive Control for Starvation Prevention in a Hybrid Fuel Cell System1
Stefanopoulou, Anna
of reactants across the membrane. The design and optimization of the fuel cell auxiliary sys- tem is complexModel 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
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
A Simulation Study on Model Predictive Control and Extremum Seeking Control for
Braslavsky, Julio H.
. Recently, it has been proposed to use feedback control to improve the rate of mineral extraction Control (ESC), to improve copper extraction in a heap bioleaching process. Simplified linear models of the process show that similar copper extraction rates can be obtained using either strategy. While better
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Buceta, D.; Tojo, C.; Vukmirovic, M.; Deepak, F. L.; Arturo Lopez-Quintela, M.
2015-07-14T23:59:59.000Z
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.
Evaluation of Transport and Dispersion Models: A Controlled Comparison of HPAC and NARAC Predictions
Warner, S; Heagy, J F; Platt, N; Larson, D; Sugiyama, G; Nasstrom, J S; Foster, K T; Bradley, S; Bieberbach, G
2001-05-01T23:59:59.000Z
During fiscal year 2000, a series of studies in support of the Defense Threat Reduction Agency (DTRA) was begun. The goal of these studies is to improve the verification, validation, and accreditation (VV&A) of hazard prediction and assessment models and capabilities. These studies are part of a larger joint VV&A collaborative effort that DTRA and the Department of Energy (DOE), via the Lawrence Livermore National Laboratory (LLNL), are conducting. This joint effort includes comparisons of the LLNL and DTRA transport and dispersion (T&D) modeling systems, NARAC and HPAC, respectively. The purpose of this work is to compare, in a systematic way, HPAC and NARAC model predictions for a set of controlled hypothetical release scenarios. Only ''model-versus-model'' comparisons are addressed in this work. Model-to-field trial comparisons for HPAC and NARAC have been addressed in a recent companion study, in support of the same joint VV&A effort.
Goodrich, Michael A.
Logic Control Michael A. Goodrich, Wynn C. Stirling, and Richard L. Frost Abstract-- Model constrained and nonlinear control problems. However, even when a good model is available, it may be necessary employs a fuzzy description of system consequences via model predictions. This controller considers
Kohler, Christian
2012-08-01T23:59:59.000Z
Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.
Nazarathy, Yoni
2013-01-01T23:59:59.000Z
al., 1996). The more recent works on traffic control systems have adopted results of modern control responsibility of Delft University of Technology Keywords: Model Predictive Control, Intelligent Transport System, Congestion Control 1. Introduction Increasing population and economic activities in modern societies have led
Haves, Phillip
2010-01-01T23:59:59.000Z
heat exchangers, the models calibrated using the manufacturer performance curves predicted power consumption within 10%. The data
Joshi, Praveen Sudhakar
1999-01-01T23:59:59.000Z
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...
Joshi, Praveen Sudhakar
1999-01-01T23:59:59.000Z
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...
Haves, Phillip; Hencey, Brandon; Borrell, Francesco; Elliot, John; Ma, Yudong; Coffey, Brian; Bengea, Sorin; Wetter, Michael
2010-06-29T23:59:59.000Z
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
Pappas, George J.
regulating the fraction of induction of a colony of Escherichia coli. We use the abstract model to designHybrid model predictive control of induction of Escherichia coli A. Agung Julius, M. Selman Sakar a feedback controller based on model predictive control strategy. Upon simulation, we show that the model
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
2015-01-01T23:59:59.000Z
4 Application to a Chemical Process Example 5 Conclusionsnonlinear processes. Chemical Engineering Science 2003, 58,based on Wiener models. Chemical Engineering Science 1998,
MULTIPLE ARX MODEL-BASED AIR-FUEL RATIO PREDICTIVE CONTROL FOR SI
Johansen, Tor Arne
strategy for combustion engines. The mix- ture quality is essential for efficiency of a three- way control problems. One of the most popular approaches to combustion engine modeling is based on neural where the amount of the fuel is a function of the control action. It was demonstrated by simulation
Distributed Model Predictive Control of Nonlinear and Two-Time-Scale Process Networks
Chen, Xianzhong
2012-01-01T23:59:59.000Z
the economic optimization and process control layer. Inoptimization and control for intentionally transient processpredictive control and optimization of processes : Enabling
Distributed Model Predictive Control of Nonlinear and Two-Time-Scale Process Networks
Chen, Xianzhong
2012-01-01T23:59:59.000Z
process . . . . . . . . . . . . Process and control problem147 Process description and control systemof benzene pro- cess Process and control problem description
Distributed Model Predictive Control of Nonlinear and Two-Time-Scale Process Networks
Chen, Xianzhong
2012-01-01T23:59:59.000Z
layer) employs automatic feedback control systems to forcenonlinear systems. IEEE Transactions on Automatic Control,dynamical systems. IEEE Transactions on Automatic Control,
Mittelmann, Hans D.
is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demandingOptimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model
Haves, Phillip
2010-01-01T23:59:59.000Z
13] Wetter, M.. 2009. “Modelica?based Modeling and 14] Wetter, M.. 2009. “Modelica?based Modeling and modeling language Modelica. Steady state models of
A distributed accelerated gradient algorithm for distributed model predictive
Como, Giacomo
power control, Distributed optimization, Accelerated gradient algorithm, Model predictive control, Distributed model predictive control 1. Introduction Hydro power plants generate electricity from potential. By sig- nificantly increasing the power efficiency of hydro power valley (HPV) systems, real-time control
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.
2014-05-01T23:59:59.000Z
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.
Fatemi, Ali
Application of bi-linear loglog SN model to strain-controlled fatigue data of aluminum alloyslog model is applied to stress amplitude versus fatigue life data of 14 aluminum alloys. It is shown-life curves are discussed. Life predictions of aluminum alloys based on linear and bi-linear models are also
Johansson, Karl Henrik
energy requirements, there is a need for improving the energetic efficiency of existing buildings, Smart Buildings, Sustainable Control Systems, Copulas, Learning Abstract Heating, Ventilation and Air Conditioning (HVAC) sys- tems play a fundamental role in maintaining acceptable ther- mal comfort and Indoor
Haves, Phillip
2010-01-01T23:59:59.000Z
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.
Design of Predictive Control Strategies for Active BITIES Systems Using Frequency Domain Models
Chen, Y.; Athienitis, A. K.; Gala, K. E.
2013-01-01T23:59:59.000Z
. Source Layer Temperature and Thermal Energy Injection Using discrete frequency response modeling for an assembly consisting of ? layers of material (Figure 3), the oscillatory responses of heat flux ???? ?,? and temperature ???? ?,? at surface 0... top surface 1 2 N 0 l Layer index for the assembly Surface index for each layer 0 l 0 l boundary (e.g. the concrete underneath the source layer). The responses ???? ? and ???? ? at time interval ? at source layer can be calculated...
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
Chen, .Dake
Pacific; whereas the total linearized nonlinear advection brings a cooling effect controlling the negative Introduction ENSO is the strongest interannual variability in the global climate system. It happens impacts. Significant progress has been made in understanding and predicting ENSO over the past few decades
Intelligent Predictive Control Methods for Synchronous Power System
Rizvi, Syed Z.
Intelligent Predictive Control Methods for Synchronous Power System Muhammad S. Yousuf Electrical with the control of the system in case of perturbations. Optimal control theory for stabilizing SMIB power systems@kfupm.edu.sa Abstract--In this paper, an intelligent Model Predictive Con- troller (MPC) for a Synchronous Power Machine
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
Tu, TungSheng
2013-01-01T23:59:59.000Z
optimization and control for intentionally transient processeconomic optimization and process control is economic modelpredictive control and optimization of processes: enabling
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
Tu, TungSheng
2013-01-01T23:59:59.000Z
operation. Journal of Process Control, [10] C. E. Garcia, D.sys- tems. Journal of Process Control, 23:404–414, 2013. [processes. Journal of Process Control, 21:501–509, 2011. [
Tu, TungSheng
2013-01-01T23:59:59.000Z
monomer process design. Chemical Engineering Communications,design/control study for the vinyl acetate monomer process. Computers & Chemical Engineering,
ghMulti-Level Approach for Model-Based Predictive Control (MPC) in Buildings: A Preliminary Overview
Candanedo, J. A.; Dehkordi, V. R.
2013-01-01T23:59:59.000Z
to building modelling have been followed in MPC studies: (i) detailed building simulation (Corbin et al., 2013) and (ii) low-order models (Candanedo et al., 2013b). A building simulation model (e.g., EnergyPlus) consists of detailed models of indoor... METHODOLOGY Case Study Building This investigation makes use of a small, case- study commercial building. The simulation model was created in EnergyPlus (Figure 2). Figure 2. EnergyPlus model. This building was conceived in the context of a project...
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
Tang, Youmin
brings a cooling effect controlling the negative perturbation growth in the central Pacific. Keywords variability in the global climate system. It happens in the tropical Pacific Ocean with a period of 27 years and has world-wide climatic, ecological, and social impacts. Significant progress has been made
Claridge,D.; Chen,W.J
2014-01-01T23:59:59.000Z
-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
2005-10-18T23:59:59.000Z
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.
Predicting Improved Chiller Performance Through Thermodynamic Modeling
Figueroa, I. E.; Cathey, M.; Medina, M. A.; Nutter, D. W.
1998-01-01T23:59:59.000Z
This paper presents two case studies in which thermodynamic modeling was used to predict improved chiller performance. The model predicted the performance (COP and total energy consumption) of water-cooled centrifugal chillers as a function...
Productivity prediction model based on Bayesian analysis and productivity console
Yun, Seok Jun
2005-08-29T23:59:59.000Z
in poor planning and defies effective control of time and budgets in project management. In this research, we have built a productivity prediction model which uses productivity data from an ongoing project to reevaluate the initial productivity estimate...
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
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces
Golbeck, Jennifer
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces Ben that are comprehensible, predictable and controllable. Direct manipulation interfaces are seen as more likely candidates Research University of Maryland, College Park, MD 20742 Abstract: Direct manipulation user interfaces have
R.W. Carpick; M.E. Plesha
2007-03-03T23:59:59.000Z
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.
Accepted for Publication Simulation modeling combined with decision control can
Accepted for Publication ABSTRACT Simulation modeling combined with decision control can offer) with Model Predictive Control (MPC) paradigms using a Knowledge Interchange Broker (KIB). This environment uses the KIB to compose discrete event simulation and model predictive control models. This approach
Applying new optimization algorithms to more predictive control
Wright, S.J.
1996-03-01T23:59:59.000Z
The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.
PreHeat: Controlling Home Heating Using Occupancy Prediction
Krumm, John
PreHeat: Controlling Home Heating Using Occupancy Prediction James Scott1 , A.J. Bernheim Brush2 efficiently heat homes by using occupancy sensing and occupancy prediction to automatically control home heating. We deployed PreHeat in five homes, three in the US and two in the UK. In UK homes, we controlled
Predict-prevent control method for perturbed excitable systems
Marzena Ciszak; Claudio R. Mirasso; Raul Toral; Oscar Calvo
2008-07-15T23:59:59.000Z
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.
Hot blast stove process model and model-based controller
Muske, K.R. [Villanova Univ., PA (United States). Dept. of Chemical Engineering; Howse, J.W.; Hansen, G.A.; Cagliostro, D.J. [Los Alamos National Lab., NM (United States). Computational Science Methods Group; Chaubal, P.C. [Inland Steel Industries, Inc., East Chicago, IN (United States). Research Labs.
1998-12-31T23:59:59.000Z
This paper describes the process model and model-based control techniques implemented on the hot blast stoves for the No. 7 Blast Furnace at the Inland Steel facility in East Chicago, Indiana. A detailed heat transfer model of the stoves is developed and verified using plant data. This model is used as part of a predictive control scheme to determine the minimum amount of fuel necessary to achieve the blast air requirements. The model is also used to predict maximum and minimum temperature constraint violations within the stove so that the controller can take corrective actions while still achieving the required stove performance.
Predictive wavefront control for Adaptive Optics with arbitrary control loop delays
Poyneer, L A; Veran, J
2007-10-30T23:59:59.000Z
We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.
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
Model Reference Adaptive Control Framework for Real Time Traffic
Minnesota, University of
Adaptive Control #12;12 Prescriptive Dynamic Traffic Assignment A Prediction Model and the Reference ModelModel Reference Adaptive Control Framework for Real Time Traffic Management Under Emergency Movement Volume Adaptive Controller Model Reference Adaptive Control (MRAC) Assumptions Super Zone Concept
THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED
Bailey-Kellogg, Chris
THE SPATIAL AGGREGATION LANGUAGE FOR MODELING AND CONTROLLING DISTRIBUTED PHYSICAL SYSTEMS study novel approaches to decentralized control de- sign, in the context of thermal regulation important science and engineering applications, such as predicting weather patterns, controlling
Voltage control in pulsed system by predict-ahead control
Payne, A.N.; Watson, J.A.; Sampayan, S.E.
1994-09-13T23:59:59.000Z
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
Design and Certification of Industrial Predictive Controllers
Dutta, Abhishek
2014-09-24T23:59:59.000Z
-line optimization part of MPC led to its adoption in mechanical and mechatronic systems from process control and petrochemical applications. However, the massive strides made by the academic community in guaranteeing stability through state-space MPC have...
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
Project Profile: Predictive Physico-Chemical Modeling of Intrinsic...
Predictive Physico-Chemical Modeling of Intrinsic Degradation Mechanisms for Advanced Reflector Materials Project Profile: Predictive Physico-Chemical Modeling of Intrinsic...
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces
Shneiderman, Ben
Direct Manipulation for Comprehensible, Predictable and Controllable User Interfaces Ben Direct manipulation user interfaces have proven their worth over two decades, but they are still in their youth. Dramatic opportunities exist to develop direct manipulation pro- gramming to create end
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
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
Schaltz, Erik
2011-01-01T23:59:59.000Z
for Model Predictive Direct Current Control in High Power PMSM Drive Systems 555 Fig. 1 Block diagram Predictive Direct Current Control in High Power PMSM Drive Systems M. Preindl1, 2 and E. Schaltz2 1. Power that they play a minor role in operation. Keywords: Drive systems, model predictive control (MPC), current
BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS
Ray, Asok
BEHAVIOR PREDICTION FOR DECISION AND CONTROL IN COGNITIVE AUTONOMOUS SYSTEMS ASOK RAY*, SHASHI for decision and control in cognitive autonomous systems. The objective is to coordinate human. 1. Introduction Modern human-engineered systems (e.g. power grid, communication, transportation
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
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
Model Based Control Refrigeration Systems
Model Based Control of Refrigeration Systems Ph.D. Thesis Lars Finn Sloth Larsen Central R & D University, Denmark. The work has been carried out at the Central R&D - Refrigeration and Air Conditioning The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers
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.
2014-03-19T23:59:59.000Z
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.
QMC Simulations DataBase for Predictive Theory and Modeling ...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
One application of the QMC Simulations Database for the Predictive Modeling and Theory project is to model this important surface reaction which is poorly modeled by methods...
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
Gamma-Ray Pulsars: Models and Predictions
Alice K. Harding
2000-12-12T23:59:59.000Z
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.
Predictable SCR co-benefits for mercury control
Pritchard, S. [Cormtech Inc. (USA)
2009-01-15T23:59:59.000Z
A test program, performed in cooperation with Dominion Power and the Babcock and Wilcox Co., was executed at Dominion Power's Mount Storm power plant in Grant County, W. Va. The program was focused on both the selective catalytic reduction (SCR) catalyst capability to oxide mercury as well as the scrubber's capability to capture and retain the oxidized mercury. This article focuses on the SCR catalyst performance aspects. The Mount Storm site consists of three units totaling approximately 1,660 MW. All units are equipped with SCR systems for NOx control. A full-scale test to evaluate the effect of the SCR was performed on Unit 2, a 550 MWT-fired boiler firing a medium sulfur bituminous coal. This test program demonstrated that the presence of an SCR catalyst can significantly affect the mercury speciation profile. Observation showed that in the absence of an SCR catalyst, the extent of oxidation of element a mercury at the inlet of the flue gas desulfurization system was about 64%. The presence of a Cornertech SCR catalyst improved this oxidation to levels greater than 95% almost all of which was captured by the downstream wet FGD system. Cornertech's proprietary SCR Hg oxidation model was used to accurately predict the field results. 1 ref., 2 figs., 1 tab.
Numerical and analytical modeling of sanding onset prediction
Yi, Xianjie
2004-09-30T23:59:59.000Z
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...
A Predictive power control of Doubly Fed Induction Generator for Wave Energy Converter
Brest, Université de
A Predictive power control of Doubly Fed Induction Generator for Wave Energy Converter in Irregular there are several wave energy converters to harness this energy. Some of them, as in tidal applications, use based Wave Energy Converter under irregular wave climate which is modeled as time series elevation from
Performance-driven control theory and applications
Riggs, Daniel J.
2012-01-01T23:59:59.000Z
Non-Linear Predictive Control: Theory and Practice. IET, UK,M. Morari. Model predictive control: Theory and practice – aModel Predictive Control: Theory and Algorithms. Springer-
Predicting the past: archaeological predictive modeling in Central Texas
Werner, Corey M
2002-01-01T23:59:59.000Z
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...
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
chillers/cooling towers for energy conversion, an electricalconsuming energy are chillers, cooling towers, and pumps. Atconsuming energy are chillers, cooling towers, and pumps. It
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
more sophisticated building automation systems and buildingthrough the building automation system “Automated Logic Websystem. ALC is a building automation system, offering a user
Predictive control with Gaussian process models
Kocijan, J.; Murray-Smith, R.
Kocijan,J. Murray-Smith,R. Rasmussen,C.E. Likar,B. IEEE Eurocon 2003: The International Conference on Computer as a Tool, September, Ljubljana, Slovenia, IEEE
Model Predictive Control for Energy Efficient Buildings
Ma, Yudong
2012-01-01T23:59:59.000Z
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
2012-01-01T23:59:59.000Z
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
2012-01-01T23:59:59.000Z
ALC) system. ALC is a building automation system, offering aModern digital building automation systems satisfy thesemore sophisticated building automation systems and building
Modeling And Control Of Articulated Vehicles
Chen, Chieh; Tomizuka, Masayoshi
1997-01-01T23:59:59.000Z
Modeling, Advanced Vehicle Control Systems, Lateral control, SteeringSteering and Braking Control of Heavy Duty Vehicles. Under this project, dynamic modeling
Hybrid Model for Building Performance Diagnosis and Optimal Control
Wang, S.; Xu, X.
2003-01-01T23:59:59.000Z
Modern buildings require continuous performance monitoring, automatic diagnostics and optimal supervisory control. For these applications, simplified dynamic building models are needed to predict the cooling and heating requirement viewing...
Colliding cascades model for earthquake prediction
2000-10-12T23:59:59.000Z
3 International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russia. 4 Department of Earth ...
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
is proposed for the control of switching systems characterized by linear system dynamics with a time delay that will take the system closest to the desired future state. The resulting control action is sub-optimal by linear dynamics with a time-delayed input. A switching control system (as defined herein) is one
MODELING HORMONAL CONTROL MENSTRUAL CYCLE
MODELING HORMONAL CONTROL OF THE MENSTRUAL CYCLE James F. Selgrade Department of Mathematics of five hormones important for regulation and maintenance of the menstrual cycle. Models which correctly@math.ncsu.edu Abstract This study presents a strategy for developing a mathematical model describing the concentrations
The myth of science-based predictive modeling.
Hemez, F. M. (François M.)
2004-01-01T23:59:59.000Z
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
Hospital Readmission in General Medicine Patients: A Prediction Model
2010-01-01T23:59:59.000Z
to the department of medicine as a screening tool forquality of care problems. Medicine. 2008;87:294–300. 3.Readmission in General Medicine Patients: A Prediction Model
Martin, A; Venkatesan, Dr V Prasanna
2011-01-01T23:59:59.000Z
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.
Predictive modeling of reactive wetting and metal joining.
van Swol, Frank B.
2013-09-01T23:59:59.000Z
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.
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 ...
Tippett, Michael K. [Columbia University
2014-04-09T23:59:59.000Z
This report is a progress report of the accomplishments of the research grant “Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observa- tions” during the period 1 May 2011- 31 August 2013. This project is a collaborative one between Columbia University and George Mason University. George Mason University will submit a final technical report at the conclusion of their no-cost extension. The purpose of the proposed research is to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. Components of unforced decadal predictability will be isolated by maximizing the Average Predictability Time (APT) in long, multimodel control runs from state-of-the-art climate models. Components with decadal predictability have large APT, so maximizing APT ensures that components with decadal predictability will be detected. Optimal fingerprinting techniques, as used in detection and attribution analysis, will be used to separate variations due to natural and anthropogenic forcing from those due to unforced decadal predictability. This methodology will be applied to the decadal hindcasts generated by the CMIP5 project to assess the reliability of model projections. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be investigated.
State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence-based control frameworks, such as model predictive control (MPC), use the expected dynamics to generate that requires active balance control in the presence of modeling error. Primus humanoid shown in Figure 1
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. ...
Predictability of extreme events in a branching diffusion model Abstract
2010-01-15T23:59:59.000Z
We have found a single control parameter that governs multiple spatio-temporal ... and provide a natural framework for their theoretical and empirical study. ... The present study is focused on predicting individual extreme events. ... (Kalman-
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
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 in India 3 -200 -100 0 100 200 300 W/m2 Latent Sensible Radiative Convergence A NCEP/NCAR 2 4 6 8 10 12
CFD Modeling for Mercury Control Technology
Madsen, J.I.
2006-12-01T23:59:59.000Z
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.
Summary & Implications Internal models adapt rapidly: Predictions
Kreiter, Andreas K.
Subjects Error-Bars: Standard Error * p motor control. · Heavytaileddistance distributions are con- sistent with removal of random trends to lower mean errors at the cost functionsmayinducediffer- ent control strategies and resulting dynam- ics 1-D Balancing with Highscore Distributions on Day
Modeling probability distributions with predictive state representations
Wiewiora, Eric Walter
2008-01-01T23:59:59.000Z
Discovery is the process of choosing the core tests, whose success probabilities will become the state of the learned model.
A probabilistic particle-control approximation of chance-constrained stochastic predictive control
Blackmore, Lars
Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation, disturbances, and modeling errors, as well ...
LLNL-TR-411072 A Predictive Model
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:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports(Journal Article)41clothThe Bonneville PowerTariff Pages default Sign In AboutIsrelocates I UCRLr90790 RAtomic,impacts |? 4072 A Predictive
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
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
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 for constraining climate predictions based on observations of past climate change. The first uses large ensembles
Conformal Higgs model: predicted dark energy density
R. K. Nesbet
2014-11-03T23:59:59.000Z
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-
2004-01-01T23:59:59.000Z
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 ...
On the predictive capability and stability of rubber material models
Zheng, Haining
2008-01-01T23:59:59.000Z
Due to the high non-linearity and incompressibility constraint of rubber materials, the predictive capability and stability of rubber material models require specific attention for practical engineering analysis. In this ...
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
2013-06-01T23:59:59.000Z
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.
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
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
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
Observer-Controllers for Output Regulation: the Internal Model Principle Revisited
Pao, Lucy Y.
Observer-Controllers for Output Regulation: the Internal Model Principle Revisited Jason H. Laks rejection;tracking;model predictive control;output feedback control 1 Introduction Output regulation, the design of an output regulating observer-controller is less clear. This latter approach is based
Hamiltonian control systems From modeling to analysis and control
Knobloch,Jürgen
Hamiltonian control systems From modeling to analysis and control Arjan van der Schaft Johann-based modeling 3 Definition of port-Hamiltonian systems 4 Scattering: from power variables to wave variables 5, University of Groningen, the Netherlands DiHamiltonian control systems Elgersburg School, March, 2012 1 / 108
Towards Prediction-Based Prosthetic Control Pilarski PM1
Sutton, Richard S.
an approach to one of the principal open problems in multi-function myoelectric control--robust, ongoing-time machine learning, adaptive control, myoelectric control, prosthetics, assistive medical devices. Introduction Simultaneous myoelectric control of multiple joints remains a challenging unsolved problem [1
Predictive models of circulating fluidized bed combustors
Gidaspow, D.
1992-07-01T23:59:59.000Z
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.
Multi-step-ahead prediction of MPEG-coded video source traffic using empirical modeling techniques
Gupta, Deepanker
2006-04-12T23:59:59.000Z
-VOPs . . . . . . . . . . . . . . . . . . 61 a. SSP Using ARX Models . . . . . . . . . . . . . . 61 b. SSP Using ESN Models . . . . . . . . . . . . . . 64 2. Prediction of Moving Average of VOPs . . . . . . . . 64 a. SSP Using AR Models . . . . . . . . . . . . . . . 67 b. SSP Using ARX Models...-step-ahead Prediction Using ESN Models . . 76 2. Prediction of Moving Average of VOPs . . . . . . . . 82 a. Two-step-ahead Prediction Using AR Models . . 82 b. Two-step-ahead Prediction Using ARX Models . . 84 ix CHAPTER Page c. Two-step-ahead Prediction Using FMLP...
New trends in vehicle dynamics: from modelling to control. Olivier SENAME
Paris-Sud XI, Université de
New trends in vehicle dynamics: from modelling to control. Olivier SENAME GIPSA-lab - Department approaches such as H approach for Linear Parameter Varying systems and Model predictive control have shown methods for modelling and control of subsystems and of the vehicle. The session will be organized
Classical Cepheid Pulsation Models. III. The Predictable Scenario
G. Bono; V. Castellani; M. Marconi
1999-08-02T23:59:59.000Z
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.
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
Predictive Power Control of Doubly-Fed Induction Generator for Wave Energy Converters
Paris-Sud XI, Université de
Predictive Power Control of Doubly-Fed Induction Generator for Wave Energy Converters M.S. Lagoun1. There are several wave energy converters to harness this energy. Some of them, as in tidal applications, use of a DFIG-based Wave Energy Converter (WEC). In the proposed control approach, the predicted output power
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
OPTIMAL CONTROL WITH ADAPTIVE INTERNAL DYNAMICS MODELS
Vijayakumar, Sethu
. The optimal feedback control law for systems with non-linear dynamics and non-quadratic costs can be foundOPTIMAL CONTROL WITH ADAPTIVE INTERNAL DYNAMICS MODELS Djordje Mitrovic, Stefan Klanke, and Sethu, optimal control, adaptive control, robot simulation Abstract: Optimal feedback control has been proposed
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)
2013-01-01T23:59:59.000Z
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 ...
Risk prediction models for melanoma: A systematic review
Usher-Smith, Juliet A.; Emery, Jon; Kassianos, Angelos P.; Walter, Fiona M.
2014-06-03T23:59:59.000Z
Published OnlineFirst June 3, 2014.Cancer Epidemiol Biomarkers Prev Juliet A. Usher-Smith, Jon Emery, Angelos P. Kassianos, et al. Risk prediction models for melanoma: A systematic review Updated version 10.1158/1055-9965.EPI-14... .1158/1055-9965.EPI-14-0295 © 1 Risk prediction models for melanoma: A systematic review Juliet A Usher-Smith1, Jon Emery1,2,3, Angelos P. Kassianos1, Fiona M Walter1,2,3 1 The Primary Care Unit, Department of Public Health and Primary Care, University...
Lepton Flavor Violation in Predictive SUSY-GUT Models
Albright, Carl H.; /Northern Illinois U. /Fermilab; Chen, Mu-Chun; /UC, Irvine
2008-02-01T23:59:59.000Z
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.
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
Predictive modeling of thermoelastic energy dissipation in tunable MEMS mirrors
Yi, Yun-Bo
is of significant importance in many microelectromechanical sys- tem MEMS applications. Thermoelastic damping can; published online Apr. 29, 2008. 1 Introduction Microelectromechanical systems MEMS mirrors are widely usedPredictive modeling of thermoelastic energy dissipation in tunable MEMS mirrors Houwen Tang
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
2008-03-20T23:59:59.000Z
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.
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
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
Predicting solar cycle 24 with a solar dynamo model
Arnab Rai Choudhuri; Piyali Chatterjee; Jie Jiang
2007-01-18T23:59:59.000Z
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.
Design and Predictive Control of a Net Zero Energy Home
Morelli, F.; Abbarno, N.; Boese, E.; Bullock, J.; Carter, B.; Edwards, R.; Lapite, O.; Mann, D.; Mulvihill, C.; Purcell, E.; Stein, M. IV; Rasmussen, B. P.
2013-01-01T23:59:59.000Z
This paper analyzes two methods to reduce residential energy consumption for a Net Zero home in Austin, Texas. The first method seeks to develop a control algorithm that actively engages environmental conditioning. The home must preserve user...
Predictive Control of Hot Water Heaters - Energy Innovation Portal
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:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5(Million Cubic Feet) Oregon (Including Vehicle Fuel) (Million Cubic Feet)sets safety recordPotentialfewPredicting Hurricanes
TRES predicts transcription control in embryonic stem cells.
Pooley, Christopher; Ruau, David; Lombard, Patrick; Gottgens, Berthold; Joshi, Anagha
2014-06-23T23:59:59.000Z
have developed a web tool called ‘Transcription Regulation in Embyonic Stem Cells’, or TRES for short, to link gene sets to likely upstream regulators in ES cells. *To whom correspondence should be addressed. 2 THE TRES PIPELINE Figure 1A... our understanding of normal development as well as disease. To facili- tate this, we have developed a novel web tool called ‘TRES’ that predicts the likely upstream regulators for a given gene list. This is achieved by integrating transcription...
Model Predictability Depends on Model Fidelity: Challenges in...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
and climate, and projections of climate change, show that current climate and Earth-system models continue to have stubborn irreducible errors. It is unlikely that the...
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
Kewlani, Gaurav
2009-01-01T23:59:59.000Z
The ability of autonomous or semi-autonomous unmanned ground vehicles (UGVs) to rapidly and accurately predict terrain negotiability, generate efficient paths online and have effective motion control is a critical requirement ...
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
AUTOMATIC GENERATION OF OPTIMAL CONTROLLERS THROUGH MODEL CHECKING TECHNIQUES
Tronci, Enrico
AUTOMATIC GENERATION OF OPTIMAL CONTROLLERS THROUGH MODEL CHECKING TECHNIQUES Giuseppe Della Penna Keywords: Controller Synthesis, Controller Optimization, Model Checking, Nonlinear Systems Abstract: We INTRODUCTION Control systems (or, shortly, controllers) are small hardware/software components that control
A prediction of energy savings resulting from building infiltration control
McWatters, Kenneth Rob
1995-01-01T23:59:59.000Z
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...
A Prediction of Energy Savings Resulting from Building Infiltration Control
McWatters, K.; Claridge, D. E.; Liu, M.
1996-01-01T23:59:59.000Z
/roof. This alteration of the heat flow across the building envelope can be termed the "interaction effect" For purposes of this study, a simplified heat transfer model of a building is used to calculate the heat balance across a building envelope, according to a... standard equation and an equation accounting for the interaction effect and others where air flow patterns through building walls/roof are varied. A computer simulation program written for this study applies the heat transfer models through iterative...
A prediction of energy savings resulting from building infiltration control
McWatters, Kenneth Rob
1995-01-01T23:59:59.000Z
. . . . . . . . . . . . . . . , . . . . . . . . . . . . . . . . . . . . . . . Page 29 55 2. 1 BASIS OF THIS ANALYSIS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2. 2 CALCULATION OF HEAT TRANSFER THROUGH A WALL. 29 2. 2. 1. Classical wall heat transfer model... IN THE THESIS. . . . . . . . . APPENDIX E HARDCOPY PRINTOUT OF BUILDING HEAT TRANSFER MODELING PROGRAMS TEST. FOR AND HOUSE. FOR. . . . 239 246 VITA. . . . . . 277 LIST OF TABLES TABLE Page 4. 1 Annual program-calculated results in Houston, TX...
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
Stochastic Models Predict User Behavior in Social Media
Hogg, Tad; Smith, Laura M
2013-01-01T23:59:59.000Z
User response to contributed content in online social media depends on many factors. These include how the site lays out new content, how frequently the user visits the site, how many friends the user follows, how active these friends are, as well as how interesting or useful the content is to the user. We present a stochastic modeling framework that relates a user's behavior to details of the site's user interface and user activity and describe a procedure for estimating model parameters from available data. We apply the model to study discussions of controversial topics on Twitter, specifically, to predict how followers of an advocate for a topic respond to the advocate's posts. We show that a model of user behavior that explicitly accounts for a user transitioning through a series of states before responding to an advocate's post better predicts response than models that fail to take these states into account. We demonstrate other benefits of stochastic models, such as their ability to identify users who a...
On the Predictiveness of Single-Field Inflationary Models
C. P. Burgess; Subodh P. Patil; Michael Trott
2015-07-20T23:59:59.000Z
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.
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)
2014-06-19T23:59:59.000Z
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.
Quantum Internal Model Principle: Decoherence Control
Narayan Ganesan; Tzyh-Jong Tarn
2010-12-10T23:59:59.000Z
In this article, we study the problem of designing a Decoherence Control for quantum systems with the help of a scalable ancillary quantum control and techniques from geometric control theory, in order to successfully and completely decouple an open quantum system from its environment. We re-formulate the problem of decoherence control as a disturbance rejection scheme which also leads us to the idea of Internal Model Principle for quantum control systems which is first of its kind in the literature. It is shown that decoupling a quantum disturbance from an open quantum system, is possible only with the help of a quantum controller which takes into account the model of the environmental interaction. This is demonstrated for a simple 2-qubit system wherein the effects of decoherence are completely eliminated. The theory provides conditions to be imposed on the controller to ensure perfect decoupling. Hence the problem of decoherence control naturally gives rise to the quantum internal model principle which relates the disturbance rejecting control to the model of the environmental interaction. Classical internal model principle and disturbance decoupling focus on different aspects viz. perfect output tracking and complete decoupling of output from external disturbances respectively. However for quantum systems, the two problems come together and merge in order to produce an effective platform for decoherence control. In this article we introduce a seminal connection between disturbance decoupling and the corresponding analog for internal model principle for quantum systems.
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)
2005-10-01T23:59:59.000Z
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
Carbon-cycle models for better long-term predictions | EMSL
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Carbon-cycle models for better long-term predictions Carbon-cycle models for better long-term predictions Released: November 04, 2014 Reduced variation among models should improve...
Evaluation of a mathematical model in predicting intake of growing and finishing cattle
Bourg, Brandi Marie
2009-05-15T23:59:59.000Z
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...
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
Towards feasible and effective predictive wavefront control for adaptive
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:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports to3,1,50022,3,,0,,6,1,SeparationConnect1.08]Te[subscriptM-PACEResponses to aConnect Towards an explicit model of D-braneoptics
Towards feasible and effective predictive wavefront control for adaptive
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:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports to3,1,50022,3,,0,,6,1,SeparationConnect1.08]Te[subscriptM-PACEResponses to aConnect Towards an explicit model of
Cardiovascular & Respiratory Modeling, Analysis & Control
Batzel, Jerry
Problem . . . . . . . . . . . . . 23 1.5 The Bicycle Ergometer Test eter identification problem . . . . . . . . . . . . . . 30 1.7 Numerical Results . . . . . . . . . . . . 47 2.1.2 The chemical control system for ventilation . . . . . 48 2.1.3 Structural features
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
Cardiovascular & Respiratory Modeling, Analysis & Control
Batzel, Jerry
of Grodins' system . . . . . 21 1.4 The Linear-quadratic Regulator Problem . . . . . . . . . . . . . 23 1-least-squares formulation of the param- eter identification problem . . . . . . . . . . . . . . 30 1.7 Numerical Results . . . . . . . . . . . . 47 2.1.2 The chemical control system for ventilation . . . . . 48 2.1.3 Structural features
Almassalkhi, MR; Hiskens, IA
2015-01-01T23:59:59.000Z
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
2013-09-01T23:59:59.000Z
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.
Modeling and control of genetic regulatory networks
Pal, Ranadip
2009-05-15T23:59:59.000Z
MODELING AND CONTROL OF GENETIC REGULATORY NETWORKS A Dissertation by RANADIP PAL Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2007 Major... Subject: Electrical Engineering MODELING AND CONTROL OF GENETIC REGULATORY NETWORKS A Dissertation by RANADIP PAL Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR...
Modelling artificial pheromone strategies for SPB control
Isakson, Kyle George
1981-01-01T23:59:59.000Z
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...
Subramanian, Venkat
in optimal control and nonlinear model predictive control incorporating a Single Particle Model (SPM
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
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
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
Nonlinear adaptive internal model control using neural networks
Gandhi, Amit Krushnavadan
2001-01-01T23:59:59.000Z
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...
Modeling, Analysis, and Control of Demand Response Resources
Mathieu, Johanna L.
2013-01-01T23:59:59.000Z
Modeling and control of aggregated heterogeneous thermostatically controlled loads for ancillary services”. In: Proceedings of the Power SystemsModeling and control of thermostatically controlled loads”. In: Pro- ceedings of 17 th Power Systems
Modeling, Analysis, and Control of Demand Response Resources
Mathieu, Johanna L.
2012-01-01T23:59:59.000Z
Modeling and control of aggregated heterogeneous thermostatically controlled loads for ancillary services”. In: Proceedings of the Power SystemsModeling and control of thermostatically controlled loads”. In: Pro- ceedings of 17 th Power Systems
Modelling Monsoons: Understanding and Predicting Current and Future Behaviour
Turner, A; Sperber, K R; Slingo, J M; Meehl, G A; Mechoso, C R; Kimoto, M; Giannini, A
2008-09-16T23:59:59.000Z
The global monsoon system is so varied and complex that understanding and predicting its diverse behaviour remains a challenge that will occupy modellers for many years to come. Despite the difficult task ahead, an improved monsoon modelling capability has been realized through the inclusion of more detailed physics of the climate system and higher resolution in our numerical models. Perhaps the most crucial improvement to date has been the development of coupled ocean-atmosphere models. From subseasonal to interdecadal timescales, only through the inclusion of air-sea interaction can the proper phasing and teleconnections of convection be attained with respect to sea surface temperature variations. Even then, the response to slow variations in remote forcings (e.g., El Nino-Southern Oscillation) does not result in a robust solution, as there are a host of competing modes of variability that must be represented, including those that appear to be chaotic. Understanding the links between monsoons and land surface processes is not as mature as that explored regarding air-sea interactions. A land surface forcing signal appears to dominate the onset of wet season rainfall over the North American monsoon region, though the relative role of ocean versus land forcing remains a topic of investigation in all the monsoon systems. Also, improved forecasts have been made during periods in which additional sounding observations are available for data assimilation. Thus, there is untapped predictability that can only be attained through the development of a more comprehensive observing system for all monsoon regions. Additionally, improved parameterizations - for example, of convection, cloud, radiation, and boundary layer schemes as well as land surface processes - are essential to realize the full potential of monsoon predictability. Dynamical considerations require ever increased horizontal resolution (probably to 0.5 degree or higher) in order to resolve many monsoon features including, but not limited to, the Mei-Yu/Baiu sudden onset and withdrawal, low-level jet orientation and variability, and orographic forced rainfall. Under anthropogenic climate change many competing factors complicate making robust projections of monsoon changes. Without aerosol effects, increased land-sea temperature contrast suggests strengthened monsoon circulation due to climate change. However, increased aerosol emissions will reflect more solar radiation back to space, which may temper or even reduce the strength of monsoon circulations compared to the present day. A more comprehensive assessment is needed of the impact of black carbon aerosols, which may modulate that of other anthropogenic greenhouse gases. Precipitation may behave independently from the circulation under warming conditions in which an increased atmospheric moisture loading, based purely on thermodynamic considerations, could result in increased monsoon rainfall under climate change. The challenge to improve model parameterizations and include more complex processes and feedbacks pushes computing resources to their limit, thus requiring continuous upgrades of computational infrastructure to ensure progress in understanding and predicting the current and future behavior of monsoons.
Use of Linear Predictive Control for a Solar Electric Generating System
Wisconsin at Madison, University of
behavior can be used to design and operate plants. The solar power plant is characterized by significant1 Use of Linear Predictive Control for a Solar Electric Generating System Thorsten Stuetzle, Nathan Blair, William A. Beckman, John W. Mitchell Solar Energy Laboratory University of Wisconsin-Madison 1500
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 approach. A central part of this system is statistical models for short-term predictions of the wind power Modelling (IMM) as the modelling team and all the Danish utilities as partners and users. The new models
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
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
Chaos control in traffic flow models
Elman Mohammed Shahverdiev; Shin-ichi Tadaki
1998-11-30T23:59:59.000Z
Chaos control in some of the one- and two-dimensional traffic flow dynamical models in the mean field theory is studied.One dimensional model is investigated taking into account the effect of random delay. Two dimensional model takes into account the effects of overpasses, symmetric distribution of cars and blockages of cars moving in the same direction. Chaos synchronization is performed within both replica and nonreplica approaches, and using parameter perturbation method.
Surussavadee, Chinnawat
2007-01-01T23:59:59.000Z
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 ...
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.
2015-08-05T23:59:59.000Z
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.
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...
Reference Model for Control and Automation Systems in Electrical...
Office of Environmental Management (EM)
Model for Control and Automation Systems in Electrical Power (October 2005) Reference Model for Control and Automation Systems in Electrical Power (October 2005) Modern...
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,...
Demonstrating and Validating a Next Generation Model-Based Controller...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
and Validating a Next Generation Model-Based Controller for Fuel Efficient, Low Emissions Diesel Engines Demonstrating and Validating a Next Generation Model-Based Controller for...
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
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
1997-12-31T23:59:59.000Z
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.
Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)] [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)
2012-05-01T23:59:59.000Z
Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ? We characterize a new in silico model to predict mutagenicity of drug impurities. ? The model predicts Salmonella mutagenicity and will be useful for safety assessment. ? We examine toxicity fingerprints and toxicophores of this Ames assay model. ? We compare these attributes to those found in drug impurities known to FDA/CDER. ? We validate the model and find it has a desired predictive performance.
Toward understanding predictability of climate: a linear stochastic modeling approach
Wang, Faming
2004-11-15T23:59:59.000Z
skill; and we also look for the oceanic processes that contribute to the climate predictability via interaction with the atmosphere. First, we develop a framework for assessing the predictability of a linear stochastic system. Based on the information...
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
Predictability and reduced order modeling in stochastic reaction networks.
Najm, Habib N.; Debusschere, Bert J.; Sargsyan, Khachik
2008-10-01T23:59:59.000Z
Many systems involving chemical reactions between small numbers of molecules exhibit inherent stochastic variability. Such stochastic reaction networks are at the heart of processes such as gene transcription, cell signaling or surface catalytic reactions, which are critical to bioenergy, biomedical, and electrical storage applications. The underlying molecular reactions are commonly modeled with chemical master equations (CMEs), representing jump Markov processes, or stochastic differential equations (SDEs), rather than ordinary differential equations (ODEs). As such reaction networks are often inferred from noisy experimental data, it is not uncommon to encounter large parametric uncertainties in these systems. Further, a wide range of time scales introduces the need for reduced order representations. Despite the availability of mature tools for uncertainty/sensitivity analysis and reduced order modeling in deterministic systems, there is a lack of robust algorithms for such analyses in stochastic systems. In this talk, we present advances in algorithms for predictability and reduced order representations for stochastic reaction networks and apply them to bistable systems of biochemical interest. To study the predictability of a stochastic reaction network in the presence of both parametric uncertainty and intrinsic variability, an algorithm was developed to represent the system state with a spectral polynomial chaos (PC) expansion in the stochastic space representing parametric uncertainty and intrinsic variability. Rather than relying on a non-intrusive collocation-based Galerkin projection [1], this PC expansion is obtained using Bayesian inference, which is ideally suited to handle noisy systems through its probabilistic formulation. To accommodate state variables with multimodal distributions, an adaptive multiresolution representation is used [2]. As the PC expansion directly relates the state variables to the uncertain parameters, the formulation lends itself readily to sensitivity analysis. Reduced order modeling in the time dimension is accomplished using a Karhunen-Loeve (KL) decomposition of the stochastic process in terms of the eigenmodes of its covariance matrix. Subsequently, a Rosenblatt transformation relates the random variables in the KL decomposition to a set of independent random variables, allowing the representation of the system state with a PC expansion in those independent random variables. An adaptive clustering method is used to handle multimodal distributions efficiently, and is well suited for high-dimensional spaces. The spectral representation of the stochastic reaction networks makes these systems more amenable to analysis, enabling a detailed understanding of their functionality, and robustness under experimental data uncertainty and inherent variability.
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
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
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 ...
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 ...
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 ...
Air Leakage of U.S. Homes: Model Prediction
Sherman, Max H.; McWilliams, Jennifer A.
2007-01-01T23:59:59.000Z
Air tightness is an important property of building envelopes. It is a key factor in determining infiltration and related wall-performance properties such as indoor air quality, maintainability and moisture balance. Air leakage in U.S. houses consumes roughly 1/3 of the HVAC energy but provides most of the ventilation used to control IAQ. The Lawrence Berkeley National Laboratory has been gathering residential air leakage data from many sources and now has a database of more than 100,000 raw measurements. This paper uses a model developed from that database in conjunction with US Census Bureau data for estimating air leakage as a function of location throughout the US.
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20T23:59:59.000Z
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.
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)
2014-08-25T23:59:59.000Z
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.
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...
Model predictive control for energy efficient cooling and dehumidification
Zakula, Tea
2013-01-01T23:59:59.000Z
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 Wind Aleksander Gosk
-3192 #12;Summary In the era of growing interest in limiting CO2 emission and our dependence on fossil fuels are aiming for maximizing the produced electric power for some range of wind speeds and keeping it constant
Model Predictive Control of a Wind Lars Christian Henriksen
.imm.dtu.dk #12;Summary The increase in size, prize and power production of modern wind turbines con- tinue wind turbines is on the sea as their is a more stable wind. These water based wind farms are confined speed vr [m/s] - Relative wind speed Pw [W] - Wind power in the absence of a rotor disc Pr [W] - Power
Model Predictive Control for the Operation of Building Cooling Systems
Ma, Yudong
2010-01-01T23:59:59.000Z
and passive building thermal storage. International Journalcooling towers, the thermal storage tank and the electricityand passive building thermal storage inventory: Part 1.
Model Predictive Control of Residential Energy Systems Using
Knobloch,Jürgen
generation technologies such as solar photovoltaics and wind turbines are leading to undesirable voltage network infrastructure and can lead to a degradation of power quality and even outages. In response, a local energy storage element, and solar photovoltaic panels. Each RES is connected to the wider
An invisible axion model with controlled FCNCs at tree level
Alejandro Celis; Javier Fuentes-Martin; Hugo Serodio
2015-01-04T23:59:59.000Z
We derive the necessary conditions to build a class of invisible axion models with Flavor Changing Neutral Currents at tree-level controlled by the fermion mixing matrices and present an explicit model implementation. A horizontal Peccei-Quinn symmetry provides a solution to the strong CP problem via the Peccei-Quinn mechanism and predicts a cold dark mater candidate, the invisible axion or familon. The smallness of active neutrino masses can be explained via a type I seesaw mechanism, providing a dynamical origin for the heavy seesaw scale. The possibility to avoid the domain wall problem stands as one of the most interesting features of the type of models considered. Experimental limits relying on the axion-photon coupling, astrophysical considerations and familon searches in rare kaon and muon decays are discussed.
Model for the prediction of 3D surface topography in 5-axis milling
Paris-Sud XI, Université de
1 Model for the prediction of 3D surface topography in 5-axis milling Sylvain Lavernhe LURPA - ENS surface topography obtained in 5-axis milling in function of the machining conditions. For this purpose to a feed rate prediction model. Thanks to the simulation model of 3D surface topography, the influence
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
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
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
Modeling Metal Fatigue As a Key Step in PV Module Life Time Prediction (Presentation)
Bosco, N.
2012-02-01T23:59:59.000Z
This presentation covers modeling metal fatigue as a key step in photovoltaic (PV) module lifetime predictions. Described are time-dependent and time-independent case studies.
USING PARAMETERIZED UML TO SPECIFY AND COMPOSE ACCESS CONTROL MODELS
Ray, Indrakshi
USING PARAMETERIZED UML TO SPECIFY AND COMPOSE ACCESS CONTROL MODELS Indrakshi Ray, Na Li, Dae is to model the access control frameworks, compose the models, and analyze the resulting model to identify problems. In this pa- per we outline a technique for modeling and composing access control policy
Hindi, Haitham; Prabhakar, Shyam; Fox, John D.; Linscott, Ivan; Teytelman, Dmitri; /SLAC
2011-08-31T23:59:59.000Z
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.
Burlatsky, S F; O'Neill, J; Atrazhev, V V; Varyukhin, A N; Dmitriev, D V; Erikhman, N S
2013-01-01T23:59:59.000Z
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...
MODELING AND VERIFICATION OF AN ATM PORT CONTROLLER IN VIS
Tahar, SofiÃ¨ne
MODELING AND VERIFICATION OF AN ATM PORT CONTROLLER IN VIS Jianping Lu and SofiÃ¨ne Tahar Dept port controller using model checking. The ATM port controller is part of the Cambridge Fairisle ATM on the model checking of the ATM port controller using the VIS tool from UC Berkeley. To this end, we
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...
Paris-Sud XI, Université de
the second one on force [4][5]. In order to synthesize a controller for the manipulation force, a model is necessary. However, it is known that the model linking this manipulation force and the input controlRobust control for a class of interval model: application to the force control of piezoelectric
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
Uncertainty, Performance, and Model Dependency in Approximate Adaptive Nonlinear Control
Szepesvari, Csaba
Uncertainty, Performance, and Model Dependency in Approximate Adaptive Nonlinear Control M. French, and the performance of a class of approximate model based adaptive controllers is studied. An upper performance bound uncertainty model; control effort bounds require both L 2 and L 1 uncertainty models), and various structural
Predicting regeneration establishment with the prognosis model. Forest Service research paper
Ferguson, D.E.; Carlson, C.E.
1993-08-01T23:59:59.000Z
The conifer establishment following regeneration timber harvests is predicted by version 2 of the Regeneration Establishment Model, a submodel of the Prognosis Model. The regeneration model covers 10 species for forests in Montana, central Idaho, and northern Idaho. Most harvest and site preparation methods can be simulated so that alternative treatments can be evaluated. Also included in the model is the influence of western spruce budworm (Choristoneura occidentalis) on regeneration success. The model predicts the probability of stocking, seedling density, species composition, and seedling heights 2 to 20 years after harvest. The paper describes the study design, equation development, model formulation, and model behavior for the Regeneration Establishment Model.
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
Smith, Alice E.
A Predictive Model for Slip Resistance Using Artificial Neural Networks Janet M. Twomey, IIE Artificial Neural Networks Why This Paper is Important Slips and falls are a serious ergonomic problem a slip resistance testing device were used to develop an artificial neural network model which predicts
Understanding, Modeling and Predicting Hidden Solder Joint Shape Using Active Thermography
Giron Palomares, Jose
2012-07-16T23:59:59.000Z
i UNDERSTANDING, MODELING AND PREDICTING HIDDEN SOLDER JOINT SHAPE USING ACTIVE THERMOGRAPHY A Dissertation by JOSE BENJAMIN DOLORES GIRON PALOMARES Submitted to the Office of Graduate Studies of Texas A&M University... Using Active Thermography Copyright 2012 Jose Benjamin Dolores Giron Palomares iii UNDERSTANDING, MODELING AND PREDICTING HIDDEN SOLDER JOINT SHAPE USING ACTIVE THERMOGRAPHY A Dissertation by JOSE BENJAMIN DOLORES GIRON PALOMARES...
Statistical prediction of aircraft trajectory: regression methods vs point-mass model
Paris-Sud XI, Université de
the altitude of climbing aircraft. In addition to the standard linear regression model, two common non-linear, BADA, linear regression, neural networks, Loess. INTRODUCTION Predicting aircraft trajectoriesStatistical prediction of aircraft trajectory: regression methods vs point-mass model M. Ghasemi
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
A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings
Chen, Qingyan "Yan"
A New Empirical Model for Predicting Single-Sided, Wind-Driven Natural Ventilation in Buildings-sided natural ventilation is difficult due to the bi-directional flow at the opening and the complex flow around buildings. A new empirical model was developed that can predict the mean ventilation rate and fluctuating
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
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
A graphical model approach for predicting free energies of association for protein-protein
Langmead, Christopher James
A graphical model approach for predicting free energies of association for protein University, Pittsburgh, PA 1 Corresponding Author: cjl@cs.cmu.edu #12;Keywords: Graphical Models, Free Energy in free energy, and the ability to predict binding free energies provides both better understanding
Almassalkhi, MR; Hiskens, IA
2015-01-01T23:59:59.000Z
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.
Overview of Neutrino Mixing Models and Their Mixing Angle Predictions
Albright, Carl H.
2009-11-01T23:59:59.000Z
An overview of neutrino-mixing models is presented with emphasis on the types of horizontal flavor and vertical family symmetries that have been invoked. Distributions for the mixing angles of many models are displayed. Ways to differentiate among the models and to narrow the list of viable models are discussed.
Watney, W.L.
1992-01-01T23:59:59.000Z
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.
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE
Neumaier, Arnold
called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This socalled protein folding problem is one of the most challenging problems in current bio chemistry
MOLECULAR MODELING OF PROTEINS AND MATHEMATICAL PREDICTION OF PROTEIN STRUCTURE
Neumaier, Arnold
-called protein folding problem. The static aspect is concerned with how to predict the folded (native, tertiary at solutions to the protein folding problem. Key words. protein folding, molecular mechanics, transition states. This so-called protein folding problem is one of the most challenging problems in current bio- chemistry
Numerical and analytical modeling of sanding onset prediction
Yi, Xianjie
2004-09-30T23:59:59.000Z
results vary with the selection of one or another rock strength criterion. In this work, we present four commonly used rock strength criteria in sanding onset prediction and wellbore stability studies: Mohr-Coulomb, Hoek-Brown, Drucker-Prager, and Modified...
Predicting Solar Flares by Data Assimilation in Avalanche Models. I. Model Design and Validation
Eric Bélanger; Alain Vincent; Paul Charbonneau
2007-08-14T23:59:59.000Z
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.
The Operating Regime Approach to Nonlinear Modelling and Control
Johansen, T.A.; Murray-Smith, R.
Johansen,T.A. Murray-Smith,R. Multiple Model Approaches to Modelling and Control pp 3-72 Taylor and Francis
Sleep Dynamics and Seizure Control in a Mesoscale Cortical Model
Lopour, Beth Ann
2009-01-01T23:59:59.000Z
Contributions . . . . . . . . . 2 Mesoscale Cortical Modelstates in h e from the mesoscale cortical model, here- afterand Seizure Control in a Mesoscale Cortical Model by Beth
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
Parametric Urban Regulation Models for Predicting Development Performances
Kim, Jong Bum
2014-12-23T23:59:59.000Z
This research developed and evaluated the Parametric Urban Regulation Model (PURM) to represent urban regulations in parametric Building Information Modeling (BIM) and assess the development performances of urban regulations ...
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, ...
On the Predictive Uncertainty of a Distributed Hydrologic Model
Cho, Huidae
2009-05-15T23:59:59.000Z
.2.2. Sampling strategy for high diversity . . . . . . . . . . 34 3.2.3. Isolated speciation . . . . . . . . . . . . . . . . . . . 36 3.2.4. Fitness assimilation . . . . . . . . . . . . . . . . . . . 39 3.2.5. Nesting criteria for global and local optima... unique optimal solution Beven (2006a). There may exist even mathematically inferior solutions, often referred to as local optima, that provide more realistic predictions. However, it is not straight- forward to find local optima using global optimization...
Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model
Leow, Wee Kheng
Predictive Simulation of Bidirectional Glenn Shunt Using a Hybrid Blood Vessel Model Hao Li1 to model the deformation of blood vessels. The hybrid blood vessel model consists of a reference Cosserat rod and a surface mesh. The reference Cosserat rod models the blood vessel's global bending
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
Abdelgawad, Marwa
2012-07-16T23:59:59.000Z
are based on a linear model, therefore, the nonlinear model is linearized using the perturbation method. The linear model is validated by comparing its performance with the nonlinear model about a suitable operating point. The control of ignition timing can...
Automatic Model Complexity Control Using Marginalized Discriminative Growth Functions
Hain, Thomas
Automatic model complexity control . Most LVCSR systems are trained on large amounts of data. . ManyAutomatic Model Complexity Control Using Marginalized Discriminative Growth Functions X. Liu & M. J. J. F. Gales: Automatic Model Complexity Control Using Marginalized Discriminative Growth Functions
Analyzing and Developing Role-Based Access Control Models
Sheldon, Nathan D.
Analyzing and Developing Role-Based Access Control Models by Liang Chen A thesis submitted-based access control (RBAC) has become today's dominant access control model, and many of its theoretical and practical aspects are well understood. However, certain aspects of more advanced RBAC models
Preprint submitted to SAE Optimal Control Based Modeling of
Stryk, Oskar von
Preprint submitted to SAE Optimal Control Based Modeling of Vehicle Driver Properties Torsten Butz. On the stabilization level, a nonlinear position controller guides the full vehicle dynamics model along the prescribed operation and at the driving limits. In the following, we investigate an optimal control based model
A Provenance-based Access Control Model Jaehong Park
Sandhu, Ravi
A Provenance-based Access Control Model Jaehong Park Institute for Cyber Security University of protecting provenance data. In this paper, we propose a novel provenance-based access control model additional capabilities beyond those available in traditional access control models. We utilize a notion
Modeling and Analysis of Multi-Hop Control Networks
Alur, Rajeev
Modeling and Analysis of Multi-Hop Control Networks Rajeev Alur1 , Alessandro D'Innocenzo1,2 , Karl on control performance is needed. In this paper, we propose a formal model for analyzing the joint dynamics of the system, we define a switched system that models the dynamics of the composed multi-hop control network
Using Model Checking for Analyzing Distributed Power Control Problems
Paris-Sud XI, Université de
1 Using Model Checking for Analyzing Distributed Power Control Problems Thomas Brihaye, Marc. Realizing that the distributed power control (PC) problem can be modeled by a timed game between a given Distributed power control, game theory, interference channel, model checking, timed games, verification
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
A Hybrid Model and MIMO Control for Intelligent Buildings Temperature
Boyer, Edmond
A Hybrid Model and MIMO Control for Intelligent Buildings Temperature Regulation over WSN Emmanuel is to propose a model-based feedback control strategy for indoor temperature regulation in buildings equipped. In order to set a model-based Fig. 1. UFAD ventilation control approach, we first investigate
Nguyen, Ba Nghiep; Kunc, Vlastimil; Jin, Xiaoshi; Tucker III, Charles L.; Costa, Franco
2013-12-18T23:59:59.000Z
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.
Gray, Jeffrey G.
Model Comparison: A Key Challenge for Transformation Testing and Version Control in Model Driven practices associated with model transformation testing and version control of models. 1. Introduction target model). #12;Â· Version Control Tools do not Match the Structural Nature of Models An essential
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, decreased cerebral blood flow, and diminished cerebral blood flow regula- tion, are among the first signs that can predict blood flow and pressure during posture change from sitting to standing. The mathematical
THE EFFECT OF UNCERTAINTY IN MODELING COEFFICIENTS USED TO PREDICT...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
a worst case scenario because the analysis assumes all the variation in the module database represents random variation about the true coefficient. Physics based models...
Reduced model prediction of electron temperature profiles in...
Office of Scientific and Technical Information (OSTI)
electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as e, *e, the MHD parameter, and the...
Predicting hurricane regional landfall rates: comparing local and basin-wide track model approaches
Hall, T; Hall, Tim; Jewson, Stephen
2006-01-01T23:59:59.000Z
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.
Predictive Models of Li-ion Battery Lifetime (Presentation) (Conference) |
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:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5(Million Cubic Feet) Oregon (Including Vehicle Fuel) (Million Cubic Feet)sets safety recordPotentialfewPredicting HurricanesSciTech Connect
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
Model Formulation and Predictions for a Pyrotechnically Actuated Pin Puller*
) actuated pin puller. The conservation principles are written as a set of ordinary differential equations-stirred reactor is simulated. These assumptions generally restrict the validity of the model to regimes near a formulation of the model in terms of the mass, momentum, and energy principles supplemented by appropriate
On modeling and controlling intelligent systems
Dress, W.B.
1993-11-01T23:59:59.000Z
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.
`TVLSI-00029-2003.R1 An Analytical Model for Predicting the Remaining Battery
Pedram, Massoud
. Reference [7] studied the battery discharge efficiency under different loading conditions and approximated`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
Paris-Sud XI, Université de
Non-asymptotic Adaptive Prediction in Functional Linear Models ´Elodie Brunel, Andr´e Mas, and Angelina Roche I3M, Universit´e Montpellier II Abstract Functional linear regression has recently attracted. Functional linear regression, functional principal components analysis, mean squared prediction error
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
USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS,
Paris-Sud XI, UniversitÃ© de
USING LEARNING MACHINES TO CREATE SOLAR RADIATION MAPS FROM NUMERICAL WEATHER PREDICTION MODELS to develop a methodology to generate solar radiation maps using information from different sources. First with conclusions and next works in the last section. Keywords: Solar Radiation maps, Numerical Weather Predictions
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
Scientific Programming 11 (2003) 159176 159 A performance-prediction model for PIC
Vlad, Gregorio
2003-01-01T23:59:59.000Z
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
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
Corani, Giorgio
2005-01-01T23:59:59.000Z
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
A Method for Predicting Egg Diapause Initiation and its Use in Control of Dark Ricefield Mosquitoes.
Delorme, D.R.; Meola, R.W.; Olson, J.K.
1986-01-01T23:59:59.000Z
.1592 1.1564 1.1550 1.1523 1.1509 8/29 8/30 8/31 9/1 9/2 9/3 9/4 60.00 0.7780 0.7751 0.7722 0.7708 0.7679 0.7664 0.7635 61.00 0.7903 0.7874 0.7846 0.7831 0.7802 0.7788 0.7759 62.00 0.8027 0.7998 0.7969 0.7955 0.7926 0.7911 0.7883 63.00 0.8150 0.8121 0...TDoe Z TA245.7 B873 NO.1538 / (Blank Pa,ge ~iD, 0 ..... BuDetiBJ ' ,. 1,. "t .. ' .\\ . ', :,.;-{ r " .,. . .... .; ;. , .' ; '.: , :,' ,', '.'" ; , ' ':0. Method for Predicting Egg Diapause Initiation and Its Use in Control of Dark...
CONTROL-ORIENTED PLANAR MOTION MODELING OF UNMANNED SURFACE VEHICLES
Virginia Tech
CONTROL-ORIENTED PLANAR MOTION MODELING OF UNMANNED SURFACE VEHICLES C. Sonnenburg, A. Gadre, D effective model-based control design, (2) sufficiently simple to allow straight forward parameter. A first order steering model relates steering angle to turn rate. A second order steering model relates
Transformer Thermal Modeling: Improving Reliability Using Data Quality Control
data. Models obtained from measured data give more accurate results than models based on transformer1 Transformer Thermal Modeling: Improving Reliability Using Data Quality Control Daniel J. Tylavsky as possible. In this work, we use data-quality control and data-set screening to show that model reliability
Wenzel, Mike
2013-10-14T23:59:59.000Z
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.
Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.
2009-07-15T23:59:59.000Z
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.
Evaluation of SWAT model - subdaily runoff prediction in Texas watersheds
Palanisamy, Bakkiyalakshmi
2007-09-17T23:59:59.000Z
Spatial variability of rainfall is a significant factor in hydrologic and water quality modeling. In recent years, characterizing and analyzing the effect of spatial variability of rainfall in hydrologic applications has become vital with the advent...
Dispersion modeling for prediction of emission factors for cattle feedyards
Parnell, Sarah Elizabeth
1994-01-01T23:59:59.000Z
of state air pollution regulatory agencies will require accurate EPA AP-42 emission factors. A protocol was developed so that accurate emission factors can be determined using both source sampling data and dispersion modeling. In this study, an emission...
Predictive models for power dissipation in optical transceivers
Butler, Katherine, 1981-
2004-01-01T23:59:59.000Z
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 ...
How predictable : modeling rates of change in individuals and populations
Krumme, Katherine
2013-01-01T23:59:59.000Z
This thesis develops methodologies to measure rates of change in individual human behavior, and to capture statistical regularities in change at the population level, in three pieces: i) a model of individual rate of change ...
Application of the cumulative risk model in predicting school readiness in Head Start children
Rodriguez-Escobar, Olga Lydia
2009-05-15T23:59:59.000Z
outcomes. This study built on this literature by investigating how child, parent, and family risk factors predicted school readiness in Head Start children using two statistical models. Specific aims of this study included identifying 1) to what degree...
How GIS and fire indices can be used in developing a fire prediction model for Scotland
MacKinnon, Frances
2008-12-05T23:59:59.000Z
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, ...
Tang, William C
, atomic MEMS, compact thermal model. INTRODUCTION We present a two-step process for predicting and the VCSEL, active heating and cooling was included in the presented prototype through an external heater
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 ...
Validity of the WEPP model for predicting infiltration on irrigated lands
Ngang, Fidelis Ndemah
1995-01-01T23:59:59.000Z
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...
Temperature Prediction Model for Horizontal Well with Multiple Fractures in Shale Reservoir
Yoshida, Nozomu
2013-04-12T23:59:59.000Z
reliability on the results. In this work, we show an application of a temperature prediction model for a horizontal well with multiple hydraulic fractures in order to investigate the possibility of evaluating reservoir and hydraulic fracture parameters using...
S. F. Burlatsky; M. Gummalla; J. O'Neill; V. V. Atrazhev; A. N. Varyukhin; D. V. Dmitriev; N. S. Erikhman
2013-06-19T23:59:59.000Z
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.
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
1 Artificial Neural Networks and Hidden Markov Models for Predicting the Protein Structures advice on the development of this project #12;2 Artificial Neural Networks and Hidden Markov Models learning methods: artificial neural networks (ANN) and hidden Markov models (HMM) (Rost 2002; Karplus et al
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
Power law decay in model predictability skill Peter C. Chu,1
Chu, Peter C.
Power law decay in model predictability skill Peter C. Chu,1 Leonid M. Ivanov,1,2 Lakshmi H. Kantha a Gulf of Mexico nowcast/forecast model. Power law scaling is found in the mean square error of displacement between drifting buoy and model trajectories (both at 50 m depth). The probability density
Huang, C.; Song, Y.; Luo, X.
2006-01-01T23:59:59.000Z
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...
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
Property Verification for Access Control Models via Model Checking1 Vincent C. Hu1
Young, R. Michael
Property Verification for Access Control Models via Model Checking1 Vincent C. Hu1 , D. Richard. In this paper, we propose a new general approach for property verification for access control models via model checking. The approach defines a standardized structure for access control models, providing for both
Rothe, Jeanne Marie
1983-01-01T23:59:59.000Z
A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF . EMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Submitted to the Graduate College of Texas ASM University in Partial fulfillment... of the requirement for the degree of MASTER OF SCIENCE DECEMBER 1983 Major Subject: Bioengineering A COMPUTER SIMULATION MODEL FOR THE PREDICTION OF TEMPERATURE DISTRIBUTIONS IN RADIOFREQUENCY HYPERTHERMIA TREATMENT A Thesis by JEANNE MARIE ROTHE Approved...
A new, efficient computational model for the prediction of fluid seal flowfields
Hibbs, Robert Irwin
1988-01-01T23:59:59.000Z
A NEW) EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Submitted to the Office of Graduate Studies of Texas ASM University in partial fulfillment of the requirement for the degree... of MASTER OF SCIENCE December 1988 Major Subject: Mechanical Engineering A NEW, EFFICIENT COMPUTATIONAL MODEL FOR THE PREDICTION OF FLUID SEAL FLOWFIELDS A Thesis by ROBERT IRWIN HIBBS, JR. Approved as to style and content by: David L. Rhode...
Evaluation of a mathematical model in predicting intake of growing and finishing cattle
Bourg, Brandi Marie
2009-05-15T23:59:59.000Z
EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...
Evaluation of a mathematical model in predicting intake of growing and finishing cattle
Bourg, Brandi Marie
2008-10-10T23:59:59.000Z
EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... of the requirements for the degree of MASTER OF SCIENCE December 2007 Major Subject: Animal Science EVALUATIONS OF A MATHEMATICAL MODEL IN PREDICTING INTAKE OF GROWING AND FINISHING CATTLE A Thesis by BRANDI MARIE BOURG Submitted...
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:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports(Journal Article) |govInstrumentsmfrirtA Journey Inside the Complex andFOUR Los Phase 1Miller winsMission and| Department ofModelModel
On the Predictive Uncertainty of a Distributed Hydrologic Model
Cho, Huidae
2009-05-15T23:59:59.000Z
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...
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)
2013-10-15T23:59:59.000Z
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.
Title of dissertation: MODELING, SIMULATING, AND CONTROLLING THE FLUID DYNAMICS
Shapiro, Benjamin
ABSTRACT Title of dissertation: MODELING, SIMULATING, AND CONTROLLING THE FLUID DYNAMICS OF ELECTRO an algorithm to steer indi- vidual particles inside the EWOD system by control of actuators already present number of actuators available in the EWOD system. #12;MODELING, SIMULATING, AND CONTROLLING THE FLUID
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
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
2012-01-01T23:59:59.000Z
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.
3D Rigid Body Impact Burial Prediction Model
Chu, Peter C.
-fixed coordinate (E-coordinate) · cylinder's main-axis following coordinate (M-coordinate) · hydrodynamic force-Coordiante Hydrodynamic forces (drag and lift) are easily calculated. #12;Moment of Momentum Equations #12;Interfacial;Experiment · Hydrodynamic Model Development · Behavior of Falling Cylinder in Water Column (Chaotic
Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition
Paris-Sud XI, UniversitÃ© de
by comparing the center lines of the road's lanes to a local curvilinear model of the path of the vehicle. The overall approach was tested on prerecorded human real driving data and results show that the Maneuver. INTRODUCTION Active safety systems and self-driving cars are a promising solution to reduce the number
A NEW MODEL FOR PERFORMANCE PREDICTION OF HARD ROCK TBMS.
TBMs. The model uses information on the rock properties and cutting geometry to calculate TBM rate on data collected in the field and is merely a regression between machine parameters, rock properties is introduced to provide an estimate of disc cutting forces as a function of rock properties and the cutting
Prediction under uncertainty in reservoir modeling S. Subbeya,*, M. Christiea
Sambridge, Malcolm
a Institute of Petroleum Engineering, Heriot-Watt University, Edinburgh EH14 4AS, UK b Research School to production data, is obtained. The model is then used to forecast future production profiles. Because the history match is non-unique, the forecast production profiles are therefore uncertain, although
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
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
Rychard J. Bouwens; Laura Cayon; Joseph Silk
1997-09-13T23:59:59.000Z
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).
Gravdahl, Jan Tommy
with the required background. Reprinted, with permission, from IEEE Control Systems Mag- azine, Vol. 24, No. 5, 2004 Norwegian Society of Automatic Controldoi:10.4173/mic.2007.2.2 #12;Modeling, Identification and Control Year in Industrial Systems 3rd Linear System Theory, Modeling and Simulation, Optimization and Control, Real
In-situ prediction on sensor networks using distributed multiple linear regression models
Basha, Elizabeth (Elizabeth Ann)
2010-01-01T23:59:59.000Z
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 ...
Autothermal reforming of gasoline for fuel cell applications : a control-oriented dynamic model.
Hu, Y.; Chmielewski, D. J.; Papadias, D.; Chemical Sciences and Engineering Division; Illinois Inst. of Tech.
2008-11-05T23:59:59.000Z
In this work, we develop a control-oriented, reduced order dynamic model of an autothermal reforming (ATR) reactor. The targeted application is within the on-board fuel-processing unit of a fuel cell vehicle. A previous effort has illustrated that a predictive-type controller may be required to achieve desired performance within this application. The objective of the current effort is to determine the existence of a reduced order model with enough speed and accuracy to meet the online computational demands of a predictive controller. Central to the model development is an approximation of reaction rates that achieve reasonable accuracy near the inlet while preserving the overall energy balance. The resulting scheme converts a partial differential equation model into a set of ordinary differential/algebraic equations and achieves nearly a 4 orders of magnitude improvement in computational speed while preserving most of the nonlinear characteristics of the original system. Such results give clear indication that the hurdle of computational viability can be overcome and opens the door for further development of a predictive controller for the ATR application.
Model Transformation with Hierarchical Discrete-Event Control
Model Transformation with Hierarchical Discrete- Event Control Thomas Huining Feng Electrical permission. #12;Model Transformation with Hierarchical Discrete-Event Control by Huining Feng B.S. (Nanjing Date Date University of California, Berkeley Spring 2009 #12;Model Transformation with Hierarchical
A soil moisture availability model for crop stress prediction
Gay, Roger Franklin
1983-01-01T23:59:59.000Z
wet so11 profile [Ritch1e et al. , 1972] . . . . . . . . . . . . . . 12 Relationships between the ratio of actual evaporation (Ea) to pan evaporat1on (E an) as a function of the available soil water in Rule and Bragg soybean [Burch et al. , 1978...] F1gure Interact1ons between soil-moisture status and other components of a general crop yield model . . . . . . . . . . . . . . . 16 Figure Root densit1es for ra1nfed Ruse and Bragg soybean, 98 days after planting [Burch et al. , 1978...
Optimal control with adaptive internal dynamics models
Mitrovic, Djordje; Klanke, Stefan; Vijayakumar, Sethu
2008-01-01T23:59:59.000Z
Optimal feedback control has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. The optimal feedback control law for systems with non-linear dynamics ...
On Dynamic Models of Robot Force Control
Eppinger, Steven D.
1986-07-01T23:59:59.000Z
For precise robot control, endpoint compliance strategies utilize feedback from a force sensor located near the tool/workpiece interface. Such endpoint force control systems have been observed in the laboratory to be ...
Modelling and control of satellite formations
Vaddi, Veera Venkata Sesha Sai
2004-09-30T23:59:59.000Z
®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...
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
Modeling and Control of Advanced Technology Engines
Stefanopoulou, Anna
in powertrain control systems, largely driven by government regulations aimed at improving fuel economy, and apply classical and modern control techniques to improve engine performance. Moreover, we study control systems. #12;c Anna Stefanopoulou 1996 All Rights Reserved #12;Dedicated to George, Kaite
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
Use of artificial intelligence for process modeling and control
You, Yong
1991-01-01T23:59:59.000Z
. Artificial intelligence has been widely used in process modeling and control. In this thesis, applications of two sub-areas of artificial intelligencc, neural networks and fuzzy logic, to process modeling and control are studied. A methocl of nonlinear... 60 71 77 SO 82 INTRODUCTION Artificial intelligcncc (AI) has been widely used in process modeling and control. Active research areas inclucle, among others, expert systems, qualitative simulations, fuzzy logic, ansi artificial neural networks...
Lall, Pradeep; Wei, Junchao; Davis, J Lynn
2014-06-24T23:59:59.000Z
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.
Reference Model for Control and Automation Systems in Electrical...
Broader source: Energy.gov (indexed) [DOE]
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...
Asset-Liability Management Modelling with Risk Control by ...
Xi Yang
2009-01-15T23:59:59.000Z
Jan 15, 2009 ... Asset-Liability Management Modelling with Risk Control by Stochastic Dominance. Xi Yang (X.Yang ***at*** ed.ac.uk) Jacek Gondzio ...
On the modeling and control of delamination processes
Michal Kocvara
2004-01-20T23:59:59.000Z
Jan 20, 2004 ... On the modeling and control of delamination processes. Michal Kocvara (kocvara ***at*** utia.cas.cz) Jiri V. Outrata (outrata ***at*** utia.cas.cz).
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
Chaubey, Indrajeet
considerable interest in developing methods for uncertainty analysis of artificial neural network (ANN) models and parametric uncertainty in artificial neural network hydrologic models, Water Resour. Res., 43, W10407, doi:10A simplified approach to quantifying predictive and parametric uncertainty in artificial neural
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
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
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
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
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
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
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
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
The 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire
Paris-Sud XI, Université de
manuscript, published in "6. International Seminar on Fire and Explosion Hazards (FEH), Leeds : UnitedThe 1D Iterative Model for Predicting Thermal Radiation from a Jet Fire Leroy, G.* and Duplantier of the current jet fire models used in the accidental fire risks department are semi- empirical. They depend
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
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
PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES
Boyer, Edmond
PAVEMENT PREDICTION PERFORMANCE MODELS AND RELATION WITH TRAFFIC FATALITIES AND INJURIES V. CEREZO.gothie@developpement-durable.gouv.fr ABSTRACT This paper presents some results of a study, which aimed at modelling pavement evolution, pavement characteristics and age. In a second part, non-linear regressions were used in view of obtaining
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.
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
World Wind Energy Conference, Berlin (2002) REGIONAL WIND POWER PREDICTION WITH RISK CONTROL
Heinemann, Detlev
2002-01-01T23:59:59.000Z
World Wind Energy Conference, Berlin (2002) PREVIENTO REGIONAL WIND POWER PREDICTION WITH RISK prediction systems provide the expected power output of single wind farms up to three days in advance of our investigations were included in the development of the wind power prediction system Previento
Langton, C.; Kosson, D.
2009-11-30T23:59:59.000Z
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.
Aditya Kumar
2010-12-30T23:59:59.000Z
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.
Modeling control room crews for accident sequence analysis
Huang, Y. (Yuhao)
1991-01-01T23:59:59.000Z
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 ...
Nonlinear adaptive internal model control using neural networks
Gandhi, Amit Krushnavadan
2001-01-01T23:59:59.000Z
(NIMC) strategy based on neural network models is presented for SISO processes. The nonlinearities of the dynamical system are modelled by neural network architectures. Recurrent neural networks can be used for both the identification and control of nonlinear...
Ritchie, L.T.; Brown, W.D.; Wayland, J.R.
1980-05-01T23:59:59.000Z
A general temperate latitude cyclonic rainstorm model is presented which describes the effects of washout and runoff on consequences of atmospheric releases of radioactive material from potential nuclear reactor accidents. The model treats the temporal and spatial variability of precipitation processes. Predicted air and ground concentrations of radioactive material and resultant health consequences for the new model are compared to those of the original WASH-1400 model under invariant meteorological conditions and for realistic weather events using observed meteorological sequences. For a specific accident under a particular set of meteorological conditions, the new model can give significantly different results from those predicted by the WASH-1400 model, but the aggregate consequences produced for a large number of meteorological conditions are similar.
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
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 of California at Berkeley Berkeley, CA 94720 Abstract. The study of hierarchical, hybrid control systems by today's Air Traffic Control (ATC), a groundbased system which routes aircraft along predefined jet ways
Generic Average Modeling and Simulation of Discrete Controllers
modeling of discrete controllers for PWM power conversion systems. The method applies a section be advantageous to have the capability of running AC analysis of digitally controlled power systems on a general the simulation of digitally controlled power conversion systems on general-purpose circuit simulators
Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab (Massachusetts Institute of Technology, Cambridge, MA); Armstrong, Robert C.; Vanderveen, Keith
2008-09-01T23:59:59.000Z
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.
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
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
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
Controlling Social Dynamics with a Parametrized Model of Floor Regulation
Das, Suman
Controlling Social Dynamics with a Parametrized Model of Floor Regulation Crystal Chao, Andrea L is to build autonomous robot controllers for successfully engaging in human-like turn-taking interactions. Towards this end, we present CADENCE, a novel computational model and architecture that explicitly reasons
NEWS AND VIEWS Modeling gene expression control using Omes Law
Nguyen, Dat H.
NEWS AND VIEWS Modeling gene expression control using Omes Law Harmen J Bussemaker Department class of methods that fit simple mathematical models of transcription regulation to DNA microarray data factors (TFs) to specific sites in the genome is a crucial step in the molecular process controlling gene
Model-Free Control of Shape Memory Alloys Antagonistic Actuators
Paris-Sud XI, Université de
Model-Free Control of Shape Memory Alloys Antagonistic Actuators Pierre-Antoine G´edouin , C with a first application of the new framework of model-free control to the promising technology of shape memory alloys actuators. In particular antagonistic shape memory alloys actuator. These devices are known
MATHEMATICAL PROGRAMMING MODELS FOR ENVIRONMENTAL QUALITY CONTROL
Greenberg, Harvey J.
was a linear programming model for wastewater treatment plant design. Mathematical pro- gramming models an equivalent mathematical program or use mathematical programming to compute a fixed point. A primary goal
Stochastic optimal control with learned dynamics models
Mitrovic, Djordje
2011-01-01T23:59:59.000Z
The motor control of anthropomorphic robotic systems is a challenging computational task mainly because of the high levels of redundancies such systems exhibit. Optimality principles provide a general strategy to resolve ...
Unified Modeling of Complex Real-Time Control Systems
Hai, He; Chi-Lan, Cai
2011-01-01T23:59:59.000Z
Complex real-time control system is a software dense and algorithms dense system, which needs modern software engineering techniques to design. UML is an object-oriented industrial standard modeling language, used more and more in real-time domain. This paper first analyses the advantages and problems of using UML for real-time control systems design. Then, it proposes an extension of UML-RT to support time-continuous subsystems modeling. So we can unify modeling of complex real-time control systems on UML-RT platform, from requirement analysis, model design, simulation, until generation code.
Park, Joo-Yang
1994-01-01T23:59:59.000Z
. . . . . . . . . . . . . . . . . ?. .. , . . . . . . . . . . . . 55 10 Prediction of porewater pH . 11 Effects of pH on predictions of various species . . . 12 Prediction of Al concentration 13 Prediction of Fe concentration 14 Prediction of SO4 concentration . 15 Prediction of Ca concentration . 16...A hydration (16). However, Reardon (9) indicated that equilibrium models using current K, ?values of these minerals tend to predict the thermodynamic stability of ettringite over monosulfate. Because the hydration of C4AF is analogous to that of CsA, C4AF...
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
Predicting System Performance with Uncertainty
Yan, B.; Malkawi, A.
2012-01-01T23:59:59.000Z
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...
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.
2015-09-02T23:59:59.000Z
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
Lovley, Derek R.
2012-10-31T23:59:59.000Z
This project successfully accomplished its goal of coupling genome-scale metabolic models with hydrological and geochemical models to predict the activity of subsurface microorganisms during uranium bioremediation. Furthermore, it was demonstrated how this modeling approach can be used to develop new strategies to optimize bioremediation. The approach of coupling genome-scale metabolic models with reactive transport modeling is now well enough established that it has been adopted by other DOE investigators studying uranium bioremediation. Furthermore, the basic principles developed during our studies will be applicable to much broader investigations of microbial activities, not only for other types of bioremediation, but microbial metabolism in diversity of environments. This approach has the potential to make an important contribution to predicting the impact of environmental perturbations on the cycling of carbon and other biogeochemical cycles.
Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling
Jaroslav Solc
2009-06-01T23:59:59.000Z
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.
Dynamics of Cell Shape and Forces on Micropatterned Substrates Predicted by a Cellular Potts Model
Philipp J. Albert; Ulrich S. Schwarz
2014-05-19T23:59:59.000Z
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.
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
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 exploration using a powerful data mining ap- proach, which considers almost the entire Great Artesian Basin-f). By combining these data sets as layers enabling spatio-temporal data mining using the GPlates PaleoGIS software
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
Blood Glucose Level Prediction using Physiological Models and Support Vector Regression
Bunescu, Razvan C.
Blood Glucose Level Prediction using Physiological Models and Support Vector Regression Razvan continually monitor their blood glucose levels and adjust insulin doses, striving to keep blood glucose levels as close to normal as possible. Blood glucose levels that deviate from the normal range can lead to serious
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
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
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
Paul Smolen; Douglas A. Baxter; John H. Byrne
2012-08-03T23:59:59.000Z
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.
Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column
Chu, Peter C.
1 1 Three-Dimensional Hydrodynamic Model for Prediction of Falling Cylinder Through Water Column-coordinate), cylinder's main-axis following coordinate (M-coordinate), and hydrodynamic force following coordinate (F-coordinate system. The hydrodynamic forces (such as the drag and lift forces) and their moments are easily computed
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
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
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
Predicting Protein Folds with Structural Repeats Using a Chain Graph Model
Xing, Eric P.
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
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
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
Nonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials
Xie, Jun
Introduction In most clinical trials, there is much heterogeneity among individual outcomes and the treat- mentNonparametric Variable Selection for Predictive Models and Subpopulations in Clinical Trials Jingyi, IN 47907 Abstract Most clinical trials have heterogeneous treatment effect among patient individuals
A Prediction Model for Adiabatic and Diabatic Capillary Tubes with Alternative Refrigerants
Zhang, Yupeng
2014-12-05T23:59:59.000Z
line) that exits the evaporator, which creates the so called capillary tube/suction line heat exchanger. Models to predict the mass flow in both adiabatic capillary tubes and capillary tube/suction line heat exchangers are developed in this thesis...
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-induced internal wave energy in the world's oceans, J. Geophys. Res., 113, C09034, doi:10.1029/2008JC004768. 1
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
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
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
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
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
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
Prediction Intervals for NAR Model Structures Using a Bootstrap De Brabanter J.,
Prediction Intervals for NAR Model Structures Using a Bootstrap Method De Brabanter J structure. Our approach relies on the external bootstrap procedure [1]. This method is contrasted. In this paper, an external bootstrap method will be proposed for this purpose. The bootstrap is a computer
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
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
The Dirac Form Factor Predicts the Pauli Form Factor in the Endpoint Model
Sumeet Dagaonkar; Pankaj Jain; John P. Ralston
2015-03-24T23:59:59.000Z
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. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia and Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Singh, S. S. K.; Alebrahim, R.; Azizi, M. A. [Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); K, Elwaleed A. [Institute of Space Science (ANGKASA), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (Malaysia); Noorani, M. S. M. [School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (Malaysia)
2014-06-19T23:59:59.000Z
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.
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
2009-01-01T23:59:59.000Z
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 ...
A predictive robust cascade position-torque control strategy for Pneumatic Artificial Muscles
Paris-Sud XI, Université de
. By specifying the pressure average between the two muscles, it is possible to control the torque by controlling the pressure in each muscle. A constrained LMI based H controller is synthesized for the pressure inner loop as a nonlinear feedback using sliding modes by [3] for a planar 2 DOF manipulator. In [4], authors explored
.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
Predictions and measurements of isothermal airflow in a model once-through steam generator
Carter, H R; Promey, G J; Rush, G C
1982-11-01T23:59:59.000Z
Once-Through Steam Generators (OTSGs) are used in the Nuclear Steam Supply Systems marketed by The Babcock and Wilcox Company (B and W). To analytically predict the three-dimensional, steady-state thermohydraulic conditions in the OTSG, B and W has developed a proprietary code THEDA-1 and is working in cooperation with EPRI to develop an improved version, THEDA-2. Confident application of THEDA requires experimental verification to demonstrate that the code can accurately describe the thermohydraulic conditions in geometries characteristic of the OTSG. The first step in the THEDA verification process is the subject of this report. A full-scale, partial-section model of two OTSG spans was constructed and tested using isothermal air as the working fluid. Model local velocities and pressure profiles were measured and compared to THEDA prediction for five model configurations. Over 3000 velocity measurements were taken and the results were compared to THEDA predictions. Agreement between measured and predicted velocity data was generally better than +-12.5%.
Van Blackwood; Travis Koenig; Saleem Drera; Brajenda Mishra; Davis Olson; Doug Porter; Robert Mariani
2012-03-01T23:59:59.000Z
Traditional alloy theory models, specifically Darken-Gurry and Miedema’s analyses, that characterize solutes in solid solvents relative to physical properties of the elements have been used to assist in predicting alloy behavior. These models will be applied relative to the three solid phases of uranium: alpha (orthorhombic), beta (tetragonal), and gamma (bcc). These phases have different solubilities for specific alloy additions as a function of temperature. The Darken-Gurry and Miedema models, with modifications based on concepts of Waber, Gschneider, and Brewer will be used to predict the behavior of four types of solutes: 1) Transition metals that are used for various purposes associated with the containment as alloy additions in the uranium fuel 2) Transuranic elements in the uranium 3) Rare earth fission products (lanthanides) 4) Transition metals and other fission products Using these solute map criteria, elemental behavior will be predicted as highly soluble, marginally soluble, or immiscible (compound formers) and will be used to compare solute effects during uranium phase transformations. The overlapping of these solute maps are convenient first approximation tools for predicting alloy behavior.
Neural Modeling and Control of Diesel Engine with Pollution Constraints
Ouladsine, Mustapha; Dovifaaz, Xavier; 10.1007/s10846-005-3806-y
2009-01-01T23:59:59.000Z
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...
M. K. Parida; Sudhanwa Patra
2013-01-14T23:59:59.000Z
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.
Predicting Land-Ice Retreat and Sea-Level Rise with the Community Earth System Model
Lipscomb, William [Los Alamos National Laboratory
2012-06-19T23:59:59.000Z
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.
Bittle, Joshua A. [Texas A& M University] [Texas A& M University; Gao, Zhiming [ORNL] [ORNL; Jacobs, Timothy J. [Texas A& M University] [Texas A& M University
2013-01-01T23:59:59.000Z
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.
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)
2013-12-15T23:59:59.000Z
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.
Model Specification for Networked Outdoor Lighting Control Systems
Broader source: Energy.gov [DOE]
The DOE Municipal Solid-State Street Lighting Consortium's Model Specification for Networked Outdoor Lighting Control Systems is a tool designed to help cities, utilities, and other local agencies...
2.003 Modeling Dynamics and Control I, Spring 2002
Trumper, David L.
First of two-term sequence on modeling, analysis and control of dynamic systems. Mechanical translation, uniaxial rotation, electrical circuits and their coupling via levers, gears and electro-mechanical devices. Analytical ...
GENI: A graphical environment for model-based control
Kleban, S.; Lee, M.; Zambre, Y.
1989-10-01T23:59:59.000Z
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.
A model for predicting the costs of research and development in the Post Office Department
Watts, David Eli
1970-01-01T23:59:59.000Z
coefficients relating Y and 4. e is an n x 1 vector of the random errors c which are 2 normally distributed with mean 0 and variance a The least squares solution to this model is I ] I B ~ (K X) X Y Linear Cost Models The general philosophy behind linear... of Committee) ~ g QAr4 (Member) (Head of Department) ( er) January 1970 ABSTRACT A Model for Predicting the Costs of Research and Development in the Post Office Department. (January 1970) David E. Vatts, B. S. , Texas A&M University; Directed by: Dr...
Integrated modeling of the electric grid, communications, and control
Nutaro, James J [ORNL; Miller, Laurie E [ORNL; Shankar, Mallikarjun [ORNL; Kuruganti, Phani Teja [ORNL
2006-01-01T23:59:59.000Z
We present a central concern in modeling and simulating electric grids and the information infrastructure that monitors and controls them: hybrid modeling and simulation. We argue that imminent modernizations and new technologies will require a joint (hybrid) modeling of the continuous world of power systems and the discrete world of events sparked by external contingencies, and by communication, computation, and control operations. The power systems community requires methods to model and simulate hybrid scenarios for systems as large and complex as the electric grid. We discuss an approach based on DEVS and present a scenario in which the integrated information and electric grid infrastructures address a frequency maintenance problem.
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