Dynamic optimization model of energy related economic planning and development for the Navajo nation
Beladi, S.A.
1983-01-01
The Navajo reservation located in portions of Arizona, New Mexico and Utah is rich in low sulfur coal deposits, ideal for strip mining operation. The Navajo Nation has been leasing the mineral resources to non-Indian enterprises for purposes of extraction. Since the early 1950s the Navajo Nation has entered into extensive coal leases with several large companies and utilities. Contracts have committed huge quantities of Navajo coal for mining. This research was directed to evaluate the shadow prices of Navajo coal and identify optimal coal extraction. An economic model of coal resource extraction over time was structured within an optimal control theory framework. The control problem was formulated as a discrete dynamic optimization problem. A comparison of the shadow prices of coal deposits derived from the dynamic model with the royalty payments the tribe receives on the basis of the present long-term lease contracts indicates that, in most cases, the tribe is paid considerably less than the amount of royalty projected by the model. Part of these discrepancies may be explained in terms of the low coal demand condition at the time of leasing and due to greater uncertainties with respect to the geologic information and other risks associated with mining operations. However, changes in the demand for coal with rigidly fixed terms of royalty rates will lead to non-optimal extraction of coal. A corrective tax scheme is suggested on the basis of the results of this research. The proposed tax per unit of coal shipped from a site is the difference between the shadow price and the present royalty rate. The estimated tax rates over time are derived.
A dynamic model for the optimization of oscillatory low grade heat engines
Markides, Christos N.; Smith, Thomas C. B.
2015-01-22
The efficiency of a thermodynamic system is a key quantity on which its usefulness and wider application relies. This is especially true for a device that operates with marginal energy sources and close to ambient temperatures. Various definitions of efficiency are available, each of which reveals a certain performance characteristic of a device. Of these, some consider only the thermodynamic cycle undergone by the working fluid, whereas others contain additional information, including relevant internal components of the device that are not part of the thermodynamic cycle. Yet others attempt to factor out the conditions of the surroundings with which the device is interfacing thermally during operation. In this paper we present a simple approach for the modeling of complex oscillatory thermal-fluid systems capable of converting low grade heat into useful work. We apply the approach to the NIFTE, a novel low temperature difference heat utilization technology currently under development. We use the results from the model to calculate various efficiencies and comment on the usefulness of the different definitions in revealing performance characteristics. We show that the approach can be applied to make design optimization decisions, and suggest features for optimal efficiency of the NIFTE.
Development of a Dynamic DOE Calibration Model
Broader source: Energy.gov [DOE]
A dynamic heavy duty diesel engine model was developed. The model can be applied for calibration and control system optimization.
Application of optimal prediction to molecular dynamics
Barber IV, John Letherman
2004-12-01
Optimal prediction is a general system reduction technique for large sets of differential equations. In this method, which was devised by Chorin, Hald, Kast, Kupferman, and Levy, a projection operator formalism is used to construct a smaller system of equations governing the dynamics of a subset of the original degrees of freedom. This reduced system consists of an effective Hamiltonian dynamics, augmented by an integral memory term and a random noise term. Molecular dynamics is a method for simulating large systems of interacting fluid particles. In this thesis, I construct a formalism for applying optimal prediction to molecular dynamics, producing reduced systems from which the properties of the original system can be recovered. These reduced systems require significantly less computational time than the original system. I initially consider first-order optimal prediction, in which the memory and noise terms are neglected. I construct a pair approximation to the renormalized potential, and ignore three-particle and higher interactions. This produces a reduced system that correctly reproduces static properties of the original system, such as energy and pressure, at low-to-moderate densities. However, it fails to capture dynamical quantities, such as autocorrelation functions. I next derive a short-memory approximation, in which the memory term is represented as a linear frictional force with configuration-dependent coefficients. This allows the use of a Fokker-Planck equation to show that, in this regime, the noise is {delta}-correlated in time. This linear friction model reproduces not only the static properties of the original system, but also the autocorrelation functions of dynamical variables.
Optimal bolt preload for dynamic loading
Duffey, T.A.
1992-08-01
A simple spring-mass model is developed for closure bolting systems, including the effects of bolt prestress. An analytical solution is developed for the case of an initially peaked, exponentially decaying internal pressure pulse acting on the closure. The dependence of peak bolt stresses and deflections on bolt prestress level is investigated and an optimal prestress that minimizes peak bolt stress is found in certain cases. Vulnerability curves are developed for bolted-closure systems to provide rapid evaluation of the dynamic capacity of designs for a range in bolt prestress.
Optimal bolt preload for dynamic loading
Duffey, T.A.
1992-01-01
A simple spring-mass model is developed for closure bolting systems, including the effects of bolt prestress. An analytical solution is developed for the case of an initially peaked, exponentially decaying internal pressure pulse acting on the closure. The dependence of peak bolt stresses and deflections on bolt prestress level is investigated and an optimal prestress that minimizes peak bolt stress is found in certain cases. Vulnerability curves are developed for bolted-closure systems to provide rapid evaluation of the dynamic capacity of designs for a range in bolt prestress.
TRACKING CODE DEVELOPMENT FOR BEAM DYNAMICS OPTIMIZATION
Yang, L.
2011-03-28
Dynamic aperture (DA) optimization with direct particle tracking is a straight forward approach when the computing power is permitted. It can have various realistic errors included and is more close than theoretical estimations. In this approach, a fast and parallel tracking code could be very helpful. In this presentation, we describe an implementation of storage ring particle tracking code TESLA for beam dynamics optimization. It supports MPI based parallel computing and is robust as DA calculation engine. This code has been used in the NSLS-II dynamics optimizations and obtained promising performance.
Online optimization of storage ring nonlinear beam dynamics ...
Office of Scientific and Technical Information (OSTI)
Online optimization of storage ring nonlinear beam dynamics Citation Details In-Document Search Title: Online optimization of storage ring nonlinear beam dynamics Authors: Huang,...
Online optimization of storage ring nonlinear beam dynamics ...
Office of Scientific and Technical Information (OSTI)
Online optimization of storage ring nonlinear beam dynamics Citation Details In-Document Search Title: Online optimization of storage ring nonlinear beam dynamics You are...
Air Transport Optimization Model | NISAC
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
NISACAir Transport Optimization Model content top Network Optimization Models (RNAS and ATOM) Posted by Admin on Mar 1, 2012 in | Comments 0 comments Many critical infrastructures can be represented by a network of interconnected nodes and links. Mathematically sound nonlinear optimization techniques can then be applied to these networks to understand their behavior under normal and disrupted situations. Network optimization models are particularly useful for evaluating transportation system
An Optimization Framework for Dynamic Hybrid Energy Systems
Wenbo Du; Humberto E Garcia; Christiaan J.J. Paredis
2014-03-01
A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problem takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.
Pyomo : Python Optimization Modeling Objects.
Siirola, John; Laird, Carl Damon; Hart, William Eugene; Watson, Jean-Paul
2010-11-01
The Python Optimization Modeling Objects (Pyomo) package [1] is an open source tool for modeling optimization applications within Python. Pyomo provides an objected-oriented approach to optimization modeling, and it can be used to define symbolic problems, create concrete problem instances, and solve these instances with standard solvers. While Pyomo provides a capability that is commonly associated with algebraic modeling languages such as AMPL, AIMMS, and GAMS, Pyomo's modeling objects are embedded within a full-featured high-level programming language with a rich set of supporting libraries. Pyomo leverages the capabilities of the Coopr software library [2], which integrates Python packages (including Pyomo) for defining optimizers, modeling optimization applications, and managing computational experiments. A central design principle within Pyomo is extensibility. Pyomo is built upon a flexible component architecture [3] that allows users and developers to readily extend the core Pyomo functionality. Through these interface points, extensions and applications can have direct access to an optimization model's expression objects. This facilitates the rapid development and implementation of new modeling constructs and as well as high-level solution strategies (e.g. using decomposition- and reformulation-based techniques). In this presentation, we will give an overview of the Pyomo modeling environment and model syntax, and present several extensions to the core Pyomo environment, including support for Generalized Disjunctive Programming (Coopr GDP), Stochastic Programming (PySP), a generic Progressive Hedging solver [4], and a tailored implementation of Bender's Decomposition.
Palo, P.A.; Meggitt, D.J.; Nordell, W.J.
1983-05-01
This paper presents a summary of the development and validation of undersea cable dynamics computer models by the Naval Civil Engineering Laboratory (NCEL) under the sponsorship of the Naval Facilities Engineering Command. These models allow for the analysis of both small displacement (strumming) and large displacement (static and dynamic) deformations of arbitrarily configured cable structures. All of the large displacement models described in this paper are available to the public. This paper does not emphasize the theoretical development of the models (this information is available in other references) but emphasizes the various features of the models, the comparisons between model output and experimental data, and applications for which the models have been used.
Optimizing legacy molecular dynamics software with directive-based offload
Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; Thakkar, Foram M.; Plimpton, Steven J.
2015-05-14
The directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also result in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.
Optimizing legacy molecular dynamics software with directive-based offload
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Michael Brown, W.; Carrillo, Jan-Michael Y.; Gavhane, Nitin; Thakkar, Foram M.; Plimpton, Steven J.
2015-05-14
The directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also resultmore » in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.« less
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Dynamics Model content top Chemical Supply Chain Analysis Posted by Admin on Mar 1, 2012 in | Comments 0 comments Chemical Supply Chain Analysis NISAC has developed a range of...
HOMER: The Micropower Optimization Model
Not Available
2004-03-01
HOMER, the micropower optimization model, helps users to design micropower systems for off-grid and grid-connected power applications. HOMER models micropower systems with one or more power sources including wind turbines, photovoltaics, biomass power, hydropower, cogeneration, diesel engines, cogeneration, batteries, fuel cells, and electrolyzers. Users can explore a range of design questions such as which technologies are most effective, what size should components be, how project economics are affected by changes in loads or costs, and is the renewable resource adequate.
Network Optimization Models (RNAS and ATOM) | NISAC
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
been used to study policy options concerning the movement of toxic chemicals by rail. Air Transport Optimization Model (ATOM) The TOM is a network-optimization model designed to...
Biotrans: Cost Optimization Model | Open Energy Information
URI: cleanenergysolutions.orgcontentbiotrans-cost-optimization-model,http Language: English Policies: Deployment Programs DeploymentPrograms: Demonstration &...
Optimized Uncertainty Quantification Algorithm Within a Dynamic Event Tree Framework
J. W. Nielsen; Akira Tokuhiro; Robert Hiromoto
2014-06-01
Methods for developing Phenomenological Identification and Ranking Tables (PIRT) for nuclear power plants have been a useful tool in providing insight into modelling aspects that are important to safety. These methods have involved expert knowledge with regards to reactor plant transients and thermal-hydraulic codes to identify are of highest importance. Quantified PIRT provides for rigorous method for quantifying the phenomena that can have the greatest impact. The transients that are evaluated and the timing of those events are typically developed in collaboration with the Probabilistic Risk Analysis. Though quite effective in evaluating risk, traditional PRA methods lack the capability to evaluate complex dynamic systems where end states may vary as a function of transition time from physical state to physical state . Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. A limitation of DPRA is its potential for state or combinatorial explosion that grows as a function of the number of components; as well as, the sampling of transition times from state-to-state of the entire system. This paper presents a method for performing QPIRT within a dynamic event tree framework such that timing events which result in the highest probabilities of failure are captured and a QPIRT is performed simultaneously while performing a discrete dynamic event tree evaluation. The resulting simulation results in a formal QPIRT for each end state. The use of dynamic event trees results in state explosion as the number of possible component states increases. This paper utilizes a branch and bound algorithm to optimize the solution of the dynamic event trees. The paper summarizes the methods used to implement the branch-and-bound algorithm in solving the discrete dynamic event trees.
First principles molecular dynamics without self-consistent field optimization
Souvatzis, Petros; Niklasson, Anders M. N.
2014-01-28
We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations.
Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)
Energy Science and Technology Software Center (OSTI)
2012-05-31
The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.
Simple Dynamic Gasifier Model That Runs in Aspen Dynamics
Robinson, P.J.; Luyben, W.L.
2008-10-15
Gasification (or partial oxidation) is a vital component of 'clean coal' technology. Sulfur and nitrogen emissions can be reduced, overall energy efficiency is increased, and carbon dioxide recovery and sequestration are facilitated. Gasification units in an electric power generation plant produce a fuel for driving combustion turbines. Gasification units in a chemical plant generate gas, which can be used to produce a wide spectrum of chemical products. Future plants are predicted to be hybrid power/chemical plants with gasification as the key unit operation. The widely used process simulator Aspen Plus provides a library of models that can be used to develop an overall gasifier model that handles solids. So steady-state design and optimization studies of processes with gasifiers can be undertaken. This paper presents a simple approximate method for achieving the objective of having a gasifier model that can be exported into Aspen Dynamics. The basic idea is to use a high molecular weight hydrocarbon that is present in the Aspen library as a pseudofuel. This component should have the same 1:1 hydrogen-to-carbon ratio that is found in coal and biomass. For many plantwide dynamic studies, a rigorous high-fidelity dynamic model of the gasifier is not needed because its dynamics are very fast and the gasifier gas volume is a relatively small fraction of the total volume of the entire plant. The proposed approximate model captures the essential macroscale thermal, flow, composition, and pressure dynamics. This paper does not attempt to optimize the design or control of gasifiers but merely presents an idea of how to dynamically simulate coal gasification in an approximate way.
Pfeffer, A; Das, S; Lawless, D; Ng, B
2006-10-10
Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.
Model-Based Transient Calibration Optimization for Next Generation...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Based Transient Calibration Optimization for Next Generation Diesel Engines Model-Based Transient Calibration Optimization for Next Generation Diesel Engines 2005 Diesel Engine...
Regional Dynamics Model (REDYN) | Open Energy Information
use the REDYN model to estimate the effects of actions and policies on people and the economy. The REDYN model powers the unique Regional Dynamics Economic Service, an...
Optimization of the Dynamic Aperture for SPEAR3 Low-Emittance...
Office of Scientific and Technical Information (OSTI)
There is a smaller dynamic aperture for the lower emittance optics due to a stronger ... DAMPING; EFFICIENCY; GENETICS; LIFETIME; MAGNETS; OPTICS; OPTIMIZATION; RESONANCE
Optimal Initial Conditions for Coupling Ice Sheet Models to Earth...
Office of Scientific and Technical Information (OSTI)
Optimal Initial Conditions for Coupling Ice Sheet Models to Earth System Models. Citation ... Country of Publication: United States Language: English Word Cloud More Like This Full ...
optimal initial conditions for coupling ice sheet models to earth...
Office of Scientific and Technical Information (OSTI)
optimal initial conditions for coupling ice sheet models to earth system models Perego, Mauro Sandia National Laboratories Sandia National Laboratories; Price, Stephen F. Dr...
Model Identification for Optimal Diesel Emissions Control
Stevens, Andrew J.; Sun, Yannan; Song, Xiaobo; Parker, Gordon
2013-06-20
In this paper we develop a model based con- troller for diesel emission reduction using system identification methods. Specifically, our method minimizes the downstream readings from a production NOx sensor while injecting a minimal amount of urea upstream. Based on the linear quadratic estimator we derive the closed form solution to a cost function that accounts for the case some of the system inputs are not controllable. Our cost function can also be tuned to trade-off between input usage and output optimization. Our approach performs better than a production controller in simulation. Our NOx conversion efficiency was 92.7% while the production controller achieved 92.4%. For NH3 conversion, our efficiency was 98.7% compared to 88.5% for the production controller.
Photocathode Optimization for a Dynamic Transmission Electron Microscope: Final Report
Ellis, P; Flom, Z; Heinselman, K; Nguyen, T; Tung, S; Haskell, R; Reed, B W; LaGrange, T
2011-08-04
The Dynamic Transmission Electron Microscope (DTEM) team at Harvey Mudd College has been sponsored by LLNL to design and build a test setup for optimizing the performance of the DTEM's electron source. Unlike a traditional TEM, the DTEM achieves much faster exposure times by using photoemission from a photocathode to produce electrons for imaging. The DTEM team's work is motivated by the need to improve the coherence and current density of the electron cloud produced by the electron gun in order to increase the image resolution and contrast achievable by DTEM. The photoemission test setup is nearly complete and the team will soon complete baseline tests of electron gun performance. The photoemission laser and high voltage power supply have been repaired; the optics path for relaying the laser to the photocathode has been finalized, assembled, and aligned; the internal setup of the vacuum chamber has been finalized and mostly implemented; and system control, synchronization, and data acquisition has been implemented in LabVIEW. Immediate future work includes determining a consistent alignment procedure to place the laser waist on the photocathode, and taking baseline performance measurements of the tantalum photocathode. Future research will examine the performance of the electron gun as a function of the photoemission laser profile, the photocathode material, and the geometry and voltages of the accelerating and focusing components in the electron gun. This report presents the team's progress and outlines the work that remains.
Quantitative Modeling of High Temperature Magnetization Dynamics
Zhang, Shufeng
2009-03-01
Final Technical Report Project title: Quantitative Modeling of High Temperature Magnetization Dynamics DOE/Office of Science Program Manager Contact: Dr. James Davenport
Dynamical Arrest, Structural Disorder, and Optimization of Organic Photovoltaic Devices
Gould, Ian; Dmitry, Matyushov
2014-09-11
This project describes fundamental experimental and theoretical work that relates to charge separation and migration in the solid, heterogeneous or aggregated state. Marcus theory assumes a system in equilibrium with all possible solvent (dipolar) configurations, with rapid interconversion among these on the ET timescale. This project has addressed the more general situation where the medium is at least partially frozen on the ET timescale, i.e. under conditions of dynamical arrest. The approach combined theory and experiment and includes: (1) Computer simulations of model systems, (2) Development of analytical procedures consistent with computer experiment and (3) Experimental studies and testing of the formal theories on this data. Electron transfer processes are unique as a consequence of the close connection between kinetics, spectroscopy and theory, which is an essential component of this work.
Modeling and Multidimensional Optimization of a Tapered Free...
Office of Scientific and Technical Information (OSTI)
Journal Article: Modeling and Multidimensional Optimization of a Tapered Free Electron Laser Citation Details ... Publication Date: 2013-03-28 OSTI Identifier: 1074231 Report ...
The Challenges to Coupling Dynamic Geospatial Models
Goldstein, N
2006-06-23
Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanization and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.
Stochastic Robust Mathematical Programming Model for Power System Optimization
Liu, Cong; Changhyeok, Lee; Haoyong, Chen; Mehrotra, Sanjay
2016-01-01
This paper presents a stochastic robust framework for two-stage power system optimization problems with uncertainty. The model optimizes the probabilistic expectation of different worst-case scenarios with ifferent uncertainty sets. A case study of unit commitment shows the effectiveness of the proposed model and algorithms.
Very Large System Dynamics Models - Lessons Learned
Jacob J. Jacobson; Leonard Malczynski
2008-10-01
This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.
Dynamics Modelling of Biolistic Gene Guns
Zhang, M.; Tao, W.; Pianetta, P.A.
2009-06-04
The gene transfer process using biolistic gene guns is a highly dynamic process. To achieve good performance, the process needs to be well understood and controlled. Unfortunately, no dynamic model is available in the open literature for analysing and controlling the process. This paper proposes such a model. Relationships of the penetration depth with the helium pressure, the penetration depth with the acceleration distance, and the penetration depth with the micro-carrier radius are presented. Simulations have also been conducted. The results agree well with experimental results in the open literature. The contribution of this paper includes a dynamic model for improving and manipulating performance of the biolistic gene gun.
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P
2012-10-01
It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.
Optimization of a Two-Fluid Hydrodynamic Model of Churn-Turbulent Flow
Donna Post Guillen
2009-07-01
A hydrodynamic model of two-phase, churn-turbulent flows is being developed using the computational multiphase fluid dynamics (CMFD) code, NPHASE-CMFD. The numerical solutions obtained by this model are compared with experimental data obtained at the TOPFLOW facility of the Institute of Safety Research at the Forschungszentrum Dresden-Rossendorf. The TOPFLOW data is a high quality experimental database of upward, co-current air-water flows in a vertical pipe suitable for validation of computational fluid dynamics (CFD) codes. A five-field CMFD model was developed for the continuous liquid phase and four bubble size groups using mechanistic closure models for the ensemble-averaged Navier-Stokes equations. Mechanistic models for the drag and non-drag interfacial forces are implemented to include the governing physics to describe the hydrodynamic forces controlling the gas distribution. The closure models provide the functional form of the interfacial forces, with user defined coefficients to adjust the force magnitude. An optimization strategy was devised for these coefficients using commercial design optimization software. This paper demonstrates an approach to optimizing CMFD model parameters using a design optimization approach. Computed radial void fraction profiles predicted by the NPHASE-CMFD code are compared to experimental data for four bubble size groups.
Swarm Intelligence for Urban Dynamics Modelling
Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.
2009-04-16
In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.
Computational Fluid Dynamics Modeling of Diesel Engine Combustion...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Computational Fluid Dynamics Modeling of Diesel Engine Combustion and Emissions Computational Fluid Dynamics Modeling of Diesel Engine Combustion and Emissions 2005 Diesel Engine ...
Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A
2009-02-26
The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.
Model-Based Transient Calibration Optimization for Next Generation Diesel
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Engines | Department of Energy Model-Based Transient Calibration Optimization for Next Generation Diesel Engines Model-Based Transient Calibration Optimization for Next Generation Diesel Engines 2005 Diesel Engine Emissions Reduction (DEER) Conference Presentations and Posters 2005_deer_atkinson.pdf (585.55 KB) More Documents & Publications Future Diesel Engine Thermal Efficiency Improvement andn Emissions Control Technology Integrated Engine and Aftertreatment Technology Roadmap for EPA
Use Computational Model to Design and Optimize Welding Conditions to
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Suppress Helium Cracking during Welding | Department of Energy Use Computational Model to Design and Optimize Welding Conditions to Suppress Helium Cracking during Welding Use Computational Model to Design and Optimize Welding Conditions to Suppress Helium Cracking during Welding Today, welding is widely used for repair, maintenance and upgrade of nuclear reactor components. As a critical technology to extend the service life of nuclear power plants beyond 60 years, weld technology must be
Contingency contractor optimization. Phase 3, model description and formulation.
Gearhart, Jared Lee; Adair, Kristin Lynn; Jones, Katherine A.; Bandlow, Alisa; Durfee, Justin D.; Jones, Dean A.; Martin, Nathaniel; Detry, Richard Joseph; Nanco, Alan Stewart; Nozick, Linda Karen
2013-10-01
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
Contingency contractor optimization. phase 3, model description and formulation.
Gearhart, Jared Lee; Adair, Kristin Lynn; Jones, Katherine A.; Bandlow, Alisa; Detry, Richard Joseph; Durfee, Justin D.; Jones, Dean A.; Martin, Nathaniel; Nanco, Alan Stewart; Nozick, Linda Karen
2013-06-01
The goal of Phase 3 the OSD ATL Contingency Contractor Optimization (CCO) project is to create an engineering prototype of a tool for the contingency contractor element of total force planning during the Support for Strategic Analysis (SSA). An optimization model was developed to determine the optimal mix of military, Department of Defense (DoD) civilians, and contractors that accomplishes a set of user defined mission requirements at the lowest possible cost while honoring resource limitations and manpower use rules. An additional feature allows the model to understand the variability of the Total Force Mix when there is uncertainty in mission requirements.
Simulation and optimization of pressure swing adsorption systmes using reduced-order modeling
Agarwal, A.; Biegler, L.; Zitney, S.
2009-01-01
Over the past three decades, pressure swing adsorption (PSA) processes have been widely used as energyefficient gas separation techniques, especially for high purity hydrogen purification from refinery gases. Models for PSA processes are multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep fronts moving with time. As a result, the optimization of such systems represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. This study develops a reducedorder model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization and making the optimization problem computationally efficient. The method has been applied to the dynamic coupled PDE-based model of a twobed four-step PSA process for separation of hydrogen from methane. Separate ROMs have been developed for each operating step with different POD modes for each of them. A significant reduction in the order of the number of states has been achieved. The reduced-order model has been successfully used to maximize hydrogen recovery by manipulating operating pressures, step times and feed and regeneration velocities, while meeting product purity and tight bounds on these parameters. Current results indicate the proposed ROM methodology as a promising surrogate modeling technique for cost-effective optimization purposes.
Modeling of Reactor Kinetics and Dynamics
Matthew Johnson; Scott Lucas; Pavel Tsvetkov
2010-09-01
In order to model a full fuel cycle in a nuclear reactor, it is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by coupling fuel burnup equations with the kinetics equations. When the equations are solved simultaneously with a nonlinear equation solver, the end result is a code with the unique capability of modeling transients at any time during a fuel cycle.
Structural system identification: Structural dynamics model validation
Red-Horse, J.R.
1997-04-01
Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang
2015-04-01
The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at Tx ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (Tm ~ 900K), and the crossover temperature ismore » roughly twice of the glass-transition temperature (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less
DYNAMICAL MODELING OF GALAXY MERGERS USING IDENTIKIT
Privon, G. C.; Evans, A. S.; Barnes, J. E.; Hibbard, J. E.; Yun, M. S.; Mazzarella, J. M.; Armus, L.; Surace, J.
2013-07-10
We present dynamical models of four interacting systems: NGC 5257/8, The Mice, the Antennae, and NGC 2623. The parameter space of the encounters are constrained using the Identikit model-matching and visualization tool. Identikit utilizes hybrid N-body and test particle simulations to enable rapid exploration of the parameter space of galaxy mergers. The Identikit-derived matches of these systems are reproduced with self-consistent collisionless simulations which show very similar results. The models generally reproduce the observed morphology and H I kinematics of the tidal tails in these systems with reasonable properties inferred for the progenitor galaxies. The models presented here are the first to appear in the literature for NGC 5257/8 and NGC 2623, and The Mice and the Antennae are compared with previously published models. Based on the assumed mass model and our derived initial conditions, the models indicate that the four systems are currently being viewed 175-260 Myr after first passage and cover a wide range of merger stages. In some instances there are mismatches between the models and the data (e.g., in the length of a tail); these are likely due to our adoption of a single mass model for all galaxies. Despite the use of a single mass model, these results demonstrate the utility of Identikit in constraining the parameter space for galaxy mergers when applied to real data.
Determining Reduced Order Models for Optimal Stochastic Reduced Order Models
Bonney, Matthew S.; Brake, Matthew R.W.
2015-08-01
The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better represent the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.
Restoration of the Potosi Dynamic Model 2010
Adushita, Yasmin; Leetaru, Hannes
2014-09-30
In topical Report DOE/FE0002068-1 [2] technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In this Task the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. Also, it might have overestimated the injection capacity by enhancing too much the pressure relief due to the relatively close proximity between the injector and the infinite acting boundaries. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48 km by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. Potosi Dynamic Model 2013.a gives an average CO2 injection rate of 1.4 MTPA and cumulative injection of 43 Mt in 30 years, which corresponds to 45% of the injection target. This implies that according to this preliminary model, a minimum of three (3) wells could be required to achieve the injection target. The injectivity evaluation of the Potosi formation will be revisited in topical Report 15 during which more data will be integrated in the modeling exercise. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure (THP) and to investigate whether the corresponding well injection rate
Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors
Datta, Kaushik; Kamil, Shoaib; Williams, Samuel; Oliker, Leonid; Shalf, John; Yelick, Katherine
2007-06-01
Stencil-based kernels constitute the core of many important scientific applications on blockstructured grids. Unfortunately, these codes achieve a low fraction of peak performance, due primarily to the disparity between processor and main memory speeds. In this paper, we explore the impact of trends in memory subsystems on a variety of stencil optimization techniques and develop performance models to analytically guide our optimizations. Our work targets cache reuse methodologies across single and multiple stencil sweeps, examining cache-aware algorithms as well as cache-oblivious techniques on the Intel Itanium2, AMD Opteron, and IBM Power5. Additionally, we consider stencil computations on the heterogeneous multicore design of the Cell processor, a machine with an explicitly managed memory hierarchy. Overall our work represents one of the most extensive analyses of stencil optimizations and performance modeling to date. Results demonstrate that recent trends in memory system organization have reduced the efficacy of traditional cache-blocking optimizations. We also show that a cache-aware implementation is significantly faster than a cache-oblivious approach, while the explicitly managed memory on Cell enables the highest overall efficiency: Cell attains 88% of algorithmic peak while the best competing cache-based processor achieves only 54% of algorithmic peak performance.
Balasubramonian, Rajeev; Dwarkadas, Sandhya; Albonesi, David
2012-01-24
In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.
Pumping Optimization Model for Pump and Treat Systems - 15091
Baker, S.; Ivarson, Kristine A.; Karanovic, M.; Miller, Charles W.; Tonkin, M.
2015-01-15
Pump and Treat systems are being utilized to remediate contaminated groundwater in the Hanford 100 Areas adjacent to the Columbia River in Eastern Washington. Design of the systems was supported by a three-dimensional (3D) fate and transport model. This model provided sophisticated simulation capabilities but requires many hours to calculate results for each simulation considered. Many simulations are required to optimize system performance, so a two-dimensional (2D) model was created to reduce run time. The 2D model was developed as a equivalent-property version of the 3D model that derives boundary conditions and aquifer properties from the 3D model. It produces predictions that are very close to the 3D model predictions, allowing it to be used for comparative remedy analyses. Any potential system modifications identified by using the 2D version are verified for use by running the 3D model to confirm performance. The 2D model was incorporated into a comprehensive analysis system (the Pumping Optimization Model, POM) to simplify analysis of multiple simulations. It allows rapid turnaround by utilizing a graphical user interface that: 1 allows operators to create hypothetical scenarios for system operation, 2 feeds the input to the 2D fate and transport model, and 3 displays the scenario results to evaluate performance improvement. All of the above is accomplished within the user interface. Complex analyses can be completed within a few hours and multiple simulations can be compared side-by-side. The POM utilizes standard office computing equipment and established groundwater modeling software.
Reduced order model based on principal component analysis for process simulation and optimization
Lang, Y.; Malacina, A.; Biegler, L.; Munteanu, S.; Madsen, J.; Zitney, S.
2009-01-01
It is well-known that distributed parameter computational fluid dynamics (CFD) models provide more accurate results than conventional, lumped-parameter unit operation models used in process simulation. Consequently, the use of CFD models in process/equipment co-simulation offers the potential to optimize overall plant performance with respect to complex thermal and fluid flow phenomena. Because solving CFD models is time-consuming compared to the overall process simulation, we consider the development of fast reduced order models (ROMs) based on CFD results to closely approximate the high-fidelity equipment models in the co-simulation. By considering process equipment items with complicated geometries and detailed thermodynamic property models, this study proposes a strategy to develop ROMs based on principal component analysis (PCA). Taking advantage of commercial process simulation and CFD software (for example, Aspen Plus and FLUENT), we are able to develop systematic CFD-based ROMs for equipment models in an efficient manner. In particular, we show that the validity of the ROM is more robust within well-sampled input domain and the CPU time is significantly reduced. Typically, it takes at most several CPU seconds to evaluate the ROM compared to several CPU hours or more to solve the CFD model. Two case studies, involving two power plant equipment examples, are described and demonstrate the benefits of using our proposed ROM methodology for process simulation and optimization.
Modeling Microinverters and DC Power Optimizers in PVWatts
MacAlpine, S.; Deline, C.
2015-02-01
Module-level distributed power electronics including microinverters and DC power optimizers are increasingly popular in residential and commercial PV systems. Consumers are realizing their potential to increase design flexibility, monitor system performance, and improve energy capture. It is becoming increasingly important to accurately model PV systems employing these devices. This document summarizes existing published documents to provide uniform, impartial recommendations for how the performance of distributed power electronics can be reflected in NREL's PVWatts calculator (http://pvwatts.nrel.gov/).
Dynamical model for light composite fermions
Derman, E.
1981-04-01
A simple dynamical model for the internal structure of the three light lepton and quark generations (..nu../sub e/,e,u,d), (..nu../sub ..mu../,..mu..,c,s), and (..nu../sub tau/,tau,t,b) is proposed. Each generation is constructed of only one fundamental massive generation F=(L-italic/sup 0/,L/sup -/,U,D) with the same (SU/sub 3/)/sub c/ x SU/sub 2/ x U/sub 1/ quantum numbers as the light generations, bound to a core of one or more massive Higgs bosons H, where H is the single physical Higgs boson necessary for spontaneous symmetry breaking in the standard model. For example, e/sup -/=L/sup -/H), ..mu../sup -/=L/sup -/HH), tau/sup -/=L/sup -/HHH). It is shown that the known binding force due to H exchange is attractive and strong enough to produce light bound states. Dynamical calculations for the bound-state composite fermions using the Bethe-Salpeter equation, together with some phenomenological imput, suggest M/sub H/approx.16 TeV and M/sub F/approx.100 GeV. It is likely that such bound states can have properties compatible with the up to now apparently elementary appearance of known fermions, for example, their Dirac magnetic moments and absence of intergeneration radiative decays (such as ..mu -->..e..gamma..). Phenomenological consequences and tests of the model are discussed.
Particle model for skyrmions in metallic chiral magnets: Dynamics...
Office of Scientific and Technical Information (OSTI)
Particle model for skyrmions in metallic chiral magnets: Dynamics, pinning, and creep Citation Details In-Document Search Title: Particle model for skyrmions in metallic chiral ...
Computational social dynamic modeling of group recruitment.
Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken; Smrcka, Julianne D.; Ko, Teresa H.; Moy, Timothy David; Wu, Benjamin C.
2004-01-01
The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.
Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang
2015-04-01
The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu_{40}Zr_{51}Al_{9} using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at T_{x} ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (T_{m} ~ 900K), and the crossover temperature is roughly twice of the glass-transition temperature (T_{g}). Below T_{x}, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below T_{x} and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.
Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; Fleming, Paul A.; Ruben, S. D.; Marden, J. R.; Pao, L. Y.
2016-01-01
This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limited number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.
RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks
Balasundaram, Balabhaskar; Butenko, Sergiy; Boginski, Vladimir; Uryasev, Stan
2013-12-25
The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need
Optimal control of CPR procedure using hemodynamic circulation model
Lenhart, Suzanne M.; Protopopescu, Vladimir A.; Jung, Eunok
2007-12-25
A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.
LDRD final report : mesoscale modeling of dynamic loading of heterogeneous
Office of Scientific and Technical Information (OSTI)
materials. (Technical Report) | SciTech Connect LDRD final report : mesoscale modeling of dynamic loading of heterogeneous materials. Citation Details In-Document Search Title: LDRD final report : mesoscale modeling of dynamic loading of heterogeneous materials. Material response to dynamic loading is often dominated by microstructure (grain structure, porosity, inclusions, defects). An example critically important to Sandia's mission is dynamic strength of polycrystalline metals where
Progress on Optimization of the Nonlinear Beam Dynamics in the MEIC Collider Rings
Morozov, Vasiliy S.; Derbenev, Yaroslav S.; Lin, Fanglei; Pilat, Fulvia; Zhang, Yuhong; Cai, Y.; Nosochkov, Y. M.; Sullivan, Michael; Wang, M.-H.; Wienands, Uli
2015-09-01
One of the key design features of the Medium-energy Electron-Ion Collider (MEIC) proposed by Jefferson Lab is a small beta function at the interaction point (IP) allowing one to achieve a high luminosity of up to 1034 cm-2s-1. The required strong beam focusing unavoidably causes large chromatic effects such as chromatic tune spread and beam smear at the IP, which need to be compensated. This paper reports recent progress in our development of a chromaticity correction scheme for the ion ring including optimization of dynamic aperture and momentum acceptance.
Overview of the synergia 3-D multi-particle dynamics modeling framework
Spentzouris, P.; Amundson, J.F.; Dechow, D.R.; /Tech-X, Boulder
2005-05-01
High precision modeling of space-charge effects is essential for designing future accelerators as well as optimizing the performance of existing machines. Synergia is a high-fidelity parallel beam dynamics simulation package with fully three dimensional space-charge capabilities and a higher-order optics implementation. We describe the Synergia framework and model benchmarks we obtained by comparing to semi-analytic results and other codes. We also present Synergia simulations of the Fermilab Booster accelerator and comparisons with experiment.
Toward a mechanistic modeling of nitrogen limitation on vegetation dynamics
Xu, Chonggang [Los Alamos National Laboratory (LANL); Fisher, Rosie [National Center for Atmospheric Research (NCAR); Wullschleger, Stan D [ORNL; Wilson, Cathy [Los Alamos National Laboratory (LANL); Cai, Michael [Los Alamos National Laboratory (LANL); McDowell, Nathan [Los Alamos National Laboratory (LANL)
2012-01-01
Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO{sub 2} concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO{sub 2} concentration, temperature, and radiation when evaluated against published data of V{sub c,max} (maximum carboxylation rate) and J{sub max} (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO{sub 2} concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions
Lessons Learned from Alternative Transportation Fuels: Modeling Transition Dynamics
Welch, C.
2006-02-01
Report focuses on understanding how analytical system modeling and data from AFV experiences could improve our understanding of the dynamic forces governing the transition to a hydrogen future.
Davtyan, Aram; Dama, James F.; Voth, Gregory A.; Andersen, Hans C.
2015-04-21
Coarse-grained (CG) models of molecular systems, with fewer mechanical degrees of freedom than an all-atom model, are used extensively in chemical physics. It is generally accepted that a coarse-grained model that accurately describes equilibrium structural properties (as a result of having a well constructed CG potential energy function) does not necessarily exhibit appropriate dynamical behavior when simulated using conservative Hamiltonian dynamics for the CG degrees of freedom on the CG potential energy surface. Attempts to develop accurate CG dynamic models usually focus on replacing Hamiltonian motion by stochastic but Markovian dynamics on that surface, such as Langevin or Brownian dynamics. However, depending on the nature of the system and the extent of the coarse-graining, a Markovian dynamics for the CG degrees of freedom may not be appropriate. In this paper, we consider the problem of constructing dynamic CG models within the context of the Multi-Scale Coarse-graining (MS-CG) method of Voth and coworkers. We propose a method of converting a MS-CG model into a dynamic CG model by adding degrees of freedom to it in the form of a small number of fictitious particles that interact with the CG degrees of freedom in simple ways and that are subject to Langevin forces. The dynamic models are members of a class of nonlinear systems interacting with special heat baths that were studied by Zwanzig [J. Stat. Phys. 9, 215 (1973)]. The properties of the fictitious particles can be inferred from analysis of the dynamics of all-atom simulations of the system of interest. This is analogous to the fact that the MS-CG method generates the CG potential from analysis of equilibrium structures observed in all-atom simulation data. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics programs. We present tests of this method on a series of simple examples that demonstrate that
Computer model for characterizing, screening, and optimizing electrolyte systems
Gering, Kevin L.
2015-06-15
Electrolyte systems in contemporary batteries are tasked with operating under increasing performance requirements. All battery operation is in some way tied to the electrolyte and how it interacts with various regions within the cell environment. Seeing the electrolyte plays a crucial role in battery performance and longevity, it is imperative that accurate, physics-based models be developed that will characterize key electrolyte properties while keeping pace with the increasing complexity of these liquid systems. Advanced models are needed since laboratory measurements require significant resources to carry out for even a modest experimental matrix. The Advanced Electrolyte Model (AEM) developed at the INL is a proven capability designed to explore molecular-to-macroscale level aspects of electrolyte behavior, and can be used to drastically reduce the time required to characterize and optimize electrolytes. Although it is applied most frequently to lithium-ion battery systems, it is general in its theory and can be used toward numerous other targets and intended applications. This capability is unique, powerful, relevant to present and future electrolyte development, and without peer. It redefines electrolyte modeling for highly-complex contemporary systems, wherein significant steps have been taken to capture the reality of electrolyte behavior in the electrochemical cell environment. This capability can have a very positive impact on accelerating domestic battery development to support aggressive vehicle and energy goals in the 21st century.
Optimal Control of Distributed Energy Resources using Model Predictive Control
Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen
2012-07-22
In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.
Computer model for characterizing, screening, and optimizing electrolyte systems
Energy Science and Technology Software Center (OSTI)
2015-06-15
Electrolyte systems in contemporary batteries are tasked with operating under increasing performance requirements. All battery operation is in some way tied to the electrolyte and how it interacts with various regions within the cell environment. Seeing the electrolyte plays a crucial role in battery performance and longevity, it is imperative that accurate, physics-based models be developed that will characterize key electrolyte properties while keeping pace with the increasing complexity of these liquid systems. Advanced modelsmore » are needed since laboratory measurements require significant resources to carry out for even a modest experimental matrix. The Advanced Electrolyte Model (AEM) developed at the INL is a proven capability designed to explore molecular-to-macroscale level aspects of electrolyte behavior, and can be used to drastically reduce the time required to characterize and optimize electrolytes. Although it is applied most frequently to lithium-ion battery systems, it is general in its theory and can be used toward numerous other targets and intended applications. This capability is unique, powerful, relevant to present and future electrolyte development, and without peer. It redefines electrolyte modeling for highly-complex contemporary systems, wherein significant steps have been taken to capture the reality of electrolyte behavior in the electrochemical cell environment. This capability can have a very positive impact on accelerating domestic battery development to support aggressive vehicle and energy goals in the 21st century.« less
Dynamic Modeling of Adjustable-Speed Pumped Storage Hydropower Plant: Preprint
Muljadi, E.; Singh, M.; Gevorgian, V.; Mohanpurkar, M.; Havsapian, R.; Koritarov, V.
2015-04-06
Hydropower is the largest producer of renewable energy in the U.S. More than 60% of the total renewable generation comes from hydropower. There is also approximately 22 GW of pumped storage hydropower (PSH). Conventional PSH uses a synchronous generator, and thus the rotational speed is constant at synchronous speed. This work details a hydrodynamic model and generator/power converter dynamic model. The optimization of the hydrodynamic model is executed by the hydro-turbine controller, and the electrical output real/reactive power is controlled by the power converter. All essential controllers to perform grid-interface functions and provide ancillary services are included in the model.
Dynamic Model Validation with Governor Deadband on the Eastern Interconnection
Kou, Gefei; Hadley, Stanton W; Liu, Yilu
2014-04-01
This report documents the efforts to perform dynamic model validation on the Eastern Interconnection (EI) by modeling governor deadband. An on-peak EI dynamic model is modified to represent governor deadband characteristics. Simulation results are compared with synchrophasor measurements collected by the Frequency Monitoring Network (FNET/GridEye). The comparison shows that by modeling governor deadband the simulated frequency response can closely align with the actual system response.
OPF incorporating load models maximizing net revenue. [Optimal Power Flow
Dias, L.G.; El-Hawary, M.E. . Dept. of Electrical Engineering)
1993-02-01
Studies of effects of load modeling in optimal power flow studies using minimum cost and minimum loss objective reveal that a main disadvantage of cost minimization is the reduction of the objective via a reduction in the power demand. This inevitably results in lowering the total revenue and in most cases, reducing net revenue as well. An alternative approach for incorporating load models in security-constrained OPF (SCOPF) studies apparently avoids reducing the total power demand for the intact system, but reduces the voltages. A study of the behavior of conventional OPF solutions in the presence of loads not controlled by ULTC's shows that this result in a reducing the total power demand for the intact system. In this paper, the authors propose an objective that avoids the tendency to lower the total power demand, total revenue and net revenue, for OPF neglecting contingencies (normal OPF), as well as for security-constrained OPF. The minimum cost objective is modified by subtracting the total power demand from the total fuel cost. This is equivalent to maximizing the net revenue.
Optimizing a dynamical decoupling protocol for solid-state electronic spin ensembles in diamond
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.
2015-08-24
In this study, we demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through optimized dynamical decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T1 effects and DD microwave pulses are used to increase the transverse coherence time T2 from ~0.7ms up to ~30ms. Furthermore, we extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We also identify that the optimal controlmore » scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.« less
Optimizing a dynamical decoupling protocol for solid-state electronic spin ensembles in diamond
Farfurnik, D.; Jarmola, A.; Pham, L. M.; Wang, Z. H.; Dobrovitski, V. V.; Walsworth, R. L.; Budker, D.; Bar-Gill, N.
2015-08-24
In this study, we demonstrate significant improvements of the spin coherence time of a dense ensemble of nitrogen-vacancy (NV) centers in diamond through optimized dynamical decoupling (DD). Cooling the sample down to 77 K suppresses longitudinal spin relaxation T_{1} effects and DD microwave pulses are used to increase the transverse coherence time T_{2} from ~0.7ms up to ~30ms. Furthermore, we extend previous work of single-axis (Carr-Purcell-Meiboom-Gill) DD towards the preservation of arbitrary spin states. Following a theoretical and experimental characterization of pulse and detuning errors, we compare the performance of various DD protocols. We also identify that the optimal control scheme for preserving an arbitrary spin state is a recursive protocol, the concatenated version of the XY8 pulse sequence. The improved spin coherence might have an immediate impact on improvements of the sensitivities of ac magnetometry. Moreover, the protocol can be used on denser diamond samples to increase coherence times up to NV-NV interaction time scales, a major step towards the creation of quantum collective NV spin states.
Dynamic Modeling in Solid-Oxide Fuel Cells Controller Design
Lu, Ning; Li, Qinghe; Sun, Xin; Khaleel, Mohammad A.
2007-06-28
In this paper, a dynamic model of the solid-oxide fuel cell (SOFC) power unit is developed for the purpose of designing a controller to regulate fuel flow rate, fuel temperature, air flow rate, and air temperature to maintain the SOFC stack temperature, fuel utilization rate, and voltage within operation limits. A lumped model is used to consider the thermal dynamics and the electro-chemial dynamics inside an SOFC power unit. The fluid dynamics at the fuel and air inlets are considered by using the in-flow ramp-rates.
Developing a Dynamic Pharmacophore Model for HIV-1 Integrase
Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen; Bushman, Frederic; Jorgensen, William L.; Lins, Roberto; Briggs, James; Mccammon, Andy
2000-05-11
We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.
Dynamic model predicts well bore surge and swab pressures
Bing, Z.; Kaiji, Z.
1996-12-30
A dynamic well control model predicts surge and swab pressures more accurately than a steady-state model, thereby providing better estimates of pressure fluctuations when pipe is tripped. Pressure fluctuations from tripping pipe into a well can contribute to lost circulation, kicks,and well control problems. This dynamic method of predicting surge and swab pressures was verified in a full-scale test well in the Zhong Yuan oil field in China. Both the dynamic model and steady state model were verified through the test data. The test data showed the dynamic model can correctly predict downhole pressures from running or pulling pipe in a well; steady state models may result in relatively large prediction errors, especially in deeper wells.
Computational Fluid Dynamics Modeling of Diesel Engine Combustion and
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Emissions | Department of Energy Computational Fluid Dynamics Modeling of Diesel Engine Combustion and Emissions Computational Fluid Dynamics Modeling of Diesel Engine Combustion and Emissions 2005 Diesel Engine Emissions Reduction (DEER) Conference Presentations and Posters 2005_deer_reitz.pdf (682.47 KB) More Documents & Publications Experiments and Modeling of Two-Stage Combustion in Low-Emissions Diesel Engines Comparison of Conventional Diesel and Reactivity Controlled Compression
Model based control of dynamic atomic force microscope
Lee, Chibum; Salapaka, Srinivasa M.
2015-04-15
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Applying the Battery Ownership Model in Pursuit of Optimal Battery Use Strategies (Presentation)
Neubauer, J.; Ahmad, P.; Brooker, A.; Wood, E.; Smith, K.; Johnson, C.; Mendelsohn, M.
2012-05-01
This Annual Merit Review presentation describes the application of the Battery Ownership Model for strategies for optimal battery use in electric drive vehicles (PEVs, PHEVs, and BEVs).
Modeling microbial dynamics in heterogeneous environments: Growth on soil carbon sources
Resat, Haluk; Bailey, Vanessa L.; McCue, Lee Ann; Konopka, Allan
2012-01-01
We have developed a new hybrid model to study how microbial dynamics are affected by the heterogeneity in the physical structure of the environment. The modeling framework can represent porous media such as soil. The individual based biological model can explicitly simulate microbial diversity, and cell metabolism is regulated via optimal allocation of cellular resources to enzyme synthesis, control of growth rate by protein synthesis capacity, and shifts to dormancy. This model was developed to study how microbial community functioning is influenced by local environmental conditions and by the functional attributes of individual microbes. Different strategies for acquisition of carbon from polymeric cellulose were investigated. Bacteria that express membrane-associated hydrolase had different growth and survival dynamics in soil pores than bacteria that release extracellular hydrolases. The kinetic differences may suggest different functional roles for these two classes of microbes in cellulose utilization. Our model predicted an emergent behavior in which co-existence led to higher cellulose utilization efficiency and reduced stochasticity. Microbial community dynamics were simulated at two spatial scales: micro-pores that resemble 6-20 {micro}m size portions of the soil physical structure and in 111 {micro}m size soil aggregates with a random pore structure. Trends in dynamic properties were very similar at these two scales, implying that micro-scale studies can be useful approximations to aggregate scale studies when local effects on microbial dynamics are studied.
Optimal SCR Control Using Data-Driven Models
Stevens, Andrew J.; Sun, Yannan; Lian, Jianming; Devarakonda, Maruthi N.; Parker, Gordon
2013-04-16
We present an optimal control solution for the urea injection for a heavy-duty diesel (HDD) selective catalytic reduction (SCR). The approach taken here is useful beyond SCR and could be applied to any system where a control strategy is desired and input-output data is available. For example, the strategy could also be used for the diesel oxidation catalyst (DOC) system. In this paper, we identify and validate a one-step ahead Kalman state-space estimator for downstream NOx using the bench reactor data of an SCR core sample. The test data was acquired using a 2010 Cummins 6.7L ISB production engine with a 2010 Cummins production aftertreatment system. We used a surrogate HDD federal test procedure (FTP), developed at Michigan Technological University (MTU), which simulates the representative transients of the standard FTP cycle, but has less engine speed/load points. The identified state-space model is then used to develop a tunable cost function that simultaneously minimizes NOx emissions and urea usage. The cost function is quadratic and univariate, thus the minimum can be computed analytically. We show the performance of the closed-loop controller in using a reduced-order discrete SCR simulator developed at MTU. Our experiments with the surrogate HDD-FTP data show that the strategy developed in this paper can be used to identify performance bounds for urea dose controllers.
Generic solar photovoltaic system dynamic simulation model specification.
Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas
2013-10-01
This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intended to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.
Continuously Optimized Reliable Energy (CORE) Microgrid: Models & Tools (Fact Sheet)
Not Available
2013-07-01
This brochure describes Continuously Optimized Reliable Energy (CORE), a trademarked process NREL employs to produce conceptual microgrid designs. This systems-based process enables designs to be optimized for economic value, energy surety, and sustainability. Capabilities NREL offers in support of microgrid design are explained.
Dynamical Models of the Excitations of Nucleon Resonances
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
T. Sato; Lee, T.-S. H.
2009-05-01
The development of a dynamical model for investigating the nucleon resonances using the reactions of meson production frommore » $$\\pi N$$, $$\\gamma N$$, $N(e,e')$, and $$N(\
Developing Generic Dynamic Models for the 2030 Eastern Interconnection Grid
Kou, Gefei; Hadley, Stanton W; Markham, Penn N; Liu, Yilu
2013-12-01
The Eastern Interconnection Planning Collaborative (EIPC) has built three major power flow cases for the 2030 Eastern Interconnection (EI) based on various levels of energy/environmental policy conditions, technology advances, and load growth. Using the power flow cases, this report documents the process of developing the generic 2030 dynamic models using typical dynamic parameters. The constructed model was validated indirectly using the synchronized phasor measurements by removing the wind generation temporarily.
Dr. Chenn Zhou
2008-10-15
Pulverized coal injection (PCI) into the blast furnace (BF) has been recognized as an effective way to decrease the coke and total energy consumption along with minimization of environmental impacts. However, increasing the amount of coal injected into the BF is currently limited by the lack of knowledge of some issues related to the process. It is therefore important to understand the complex physical and chemical phenomena in the PCI process. Due to the difficulty in attaining trus BF measurements, Computational fluid dynamics (CFD) modeling has been identified as a useful technology to provide such knowledge. CFD simulation is powerful for providing detailed information on flow properties and performing parametric studies for process design and optimization. In this project, comprehensive 3-D CFD models have been developed to simulate the PCI process under actual furnace conditions. These models provide raceway size and flow property distributions. The results have provided guidance for optimizing the PCI process.
Dynamic model verification studies for the thermal response of the Fort St. Vrain HTGR Core
Ball, S J
1980-01-01
The safety research program for high-temperature gas-cooled reactors at ORNL is directed primarily at addressing licensing questions on the Fort St. Vrain reactor near Denver, CO. An important part of the program is to make use of experimental data from the reactor to at least partially verify the dynamic simulations that are used to predict the effects of postulated accident sequences. Comparisons were made of predictions with data from four different reactor scram (trip) events from operating power levels between 30 and 50%. An optimization program was used to rationalize the differences between predictions and measurements, and, in general, excellent agreement can be obtained by adjustment of models and parameters within their uncertainty ranges. Although the optimized models are not necessarily unique, results of the study have identified areas in which some of the models were deficient.
Oneida Tribe of Indians of Wisconsin Energy Optimization Model
Troge, Michael
2014-12-01
Oneida Nation is located in Northeast Wisconsin. The reservation is approximately 96 square miles (8 miles x 12 miles), or 65,000 acres. The greater Green Bay area is east and adjacent to the reservation. A county line roughly splits the reservation in half; the west half is in Outagamie County and the east half is in Brown County. Land use is predominantly agriculture on the west 2/3 and suburban on the east 1/3 of the reservation. Nearly 5,000 tribally enrolled members live in the reservation with a total population of about 21,000. Tribal ownership is scattered across the reservation and is about 23,000 acres. Currently, the Oneida Tribe of Indians of Wisconsin (OTIW) community members and facilities receive the vast majority of electrical and natural gas services from two of the largest investor-owned utilities in the state, WE Energies and Wisconsin Public Service. All urban and suburban buildings have access to natural gas. About 15% of the population and five Tribal facilities are in rural locations and therefore use propane as a primary heating fuel. Wood and oil are also used as primary or supplemental heat sources for a small percent of the population. Very few renewable energy systems, used to generate electricity and heat, have been installed on the Oneida Reservation. This project was an effort to develop a reasonable renewable energy portfolio that will help Oneida to provide a leadership role in developing a clean energy economy. The Energy Optimization Model (EOM) is an exploration of energy opportunities available to the Tribe and it is intended to provide a decision framework to allow the Tribe to make the wisest choices in energy investment with an organizational desire to establish a renewable portfolio standard (RPS).
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; Fleming, Paul A.; Ruben, S. D.; Marden, J. R.; Pao, L. Y.
2016-01-01
This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limitedmore » number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.« less
Approximate Bisimulation-Based Reduction of Power System Dynamic Models
Stankovic, AM; Dukic, SD; Saric, AT
2015-05-01
In this paper we propose approximate bisimulation relations and functions for reduction of power system dynamic models in differential- algebraic (descriptor) form. The full-size dynamic model is obtained by linearization of the nonlinear transient stability model. We generalize theoretical results on approximate bisimulation relations and bisimulation functions, originally derived for a class of constrained linear systems, to linear systems in descriptor form. An algorithm for transient stability assessment is proposed and used to determine whether the power system is able to maintain the synchronism after a large disturbance. Two benchmark power systems are used to illustrate the proposed algorithm and to evaluate the applicability of approximate bisimulation relations and bisimulation functions for reduction of the power system dynamic models.
Modeling and simulation of consumer response to dynamic pricing.
Valenzuela, J.; Thimmapuram, P.; Kim, J
2012-08-01
Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets. We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.
Modeling of Endothelial Glyccalyx via Dissipative Particle Dynamics |
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Argonne Leadership Computing Facility Modeling of Endothelial Glyccalyx via Dissipative Particle Dynamics Authors: Mingge, D., Haojun, L., Karniadakis, G We employ Dissipative Particle Dynamics (DPD) to simulate flow in small vessels with the endothelial glycocalyx attached to the wall. Of particular interest is the quantification of the slip velocity at the edge of glycocalyx and of the increased pressure drop at different crafting densities, stiffness and height of the glycocalyx. Results
High-throughput generation, optimization and analysis of genome-scale metabolic models.
Henry, C. S.; DeJongh, M.; Best, A. A.; Frybarger, P. M.; Linsay, B.; Stevens, R. L.
2010-09-01
Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Yet efforts to develop new models are failing to keep pace with genome sequencing. To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models. The Model SEED integrates existing methods and introduces techniques to automate nearly every step of this process, taking {approx}48 h to reconstruct a metabolic model from an assembled genome sequence. We apply this resource to generate 130 genome-scale metabolic models representing a taxonomically diverse set of bacteria. Twenty-two of the models were validated against available gene essentiality and Biolog data, with the average model accuracy determined to be 66% before optimization and 87% after optimization.
Building Restoration Operations Optimization Model Beta Version 1.0
Energy Science and Technology Software Center (OSTI)
2007-05-31
The Building Restoration Operations Optimization Model (BROOM), developed by Sandia National Laboratories, is a software product designed to aid in the restoration of large facilities contaminated by a biological material. BROOMs integrated data collection, data management, and visualization software improves the efficiency of cleanup operations, minimizes facility downtime, and provides a transparent basis for reopening the facility. Secure remote access to building floor plans Floor plan drawings and knowledge of the HVAC system are criticalmore » to the design and implementation of effective sampling plans. In large facilities, access to these data may be complicated by the sheer abundance and disorganized state they are often stored in. BROOM avoids potentially costly delays by providing a means of organizing and storing mechanical and floor plan drawings in a secure remote database that is easily accessed. Sampling design tools BROOM provides an array of tools to answer the question of where to sample and how many samples to take. In addition to simple judgmental and random sampling plans, the software includes two sophisticated methods of adaptively developing a sampling strategy. Both tools strive to choose sampling locations that best satisfy a specified objective (i.e. minimizing kriging variance) but use numerically different strategies to do so. Surface samples are collected early in the restoration process to characterize the extent of contamination and then again later to verify that the facility is safe to reenter. BROOM supports sample collection using a ruggedized PDA equipped with a barcode scanner and laser range finder. The PDA displays building floor drawings, sampling plans, and electronic forms for data entry. Barcodes are placed on sample containers for the purpose of tracking the specimen and linking acquisition data (i.e. location, surface type, texture) to laboratory results. Sample location is determined by activating the integrated
Lessons Learned from Alternative Transportation Fuels: Modeling Transition Dynamics
Lessons Learned from Alternative Transportation Fuels: Modeling Transition Dynamics C. Welch Technical Report NREL/TP-540-39446 February 2006 Lessons Learned from Alternative Transportation Fuels: Modeling Transition Dynamics C. Welch Prepared under Task Nos. HS04.2000 and HS06.1002 Technical Report NREL/TP-540-39446 February 2006 National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov Operated for the U.S. Department of Energy Office of
Dynamic crack initiation toughness : experiments and peridynamic modeling.
Foster, John T.
2009-10-01
This is a dissertation on research conducted studying the dynamic crack initiation toughness of a 4340 steel. Researchers have been conducting experimental testing of dynamic crack initiation toughness, K{sub Ic}, for many years, using many experimental techniques with vastly different trends in the results when reporting K{sub Ic} as a function of loading rate. The dissertation describes a novel experimental technique for measuring K{sub Ic} in metals using the Kolsky bar. The method borrows from improvements made in recent years in traditional Kolsky bar testing by using pulse shaping techniques to ensure a constant loading rate applied to the sample before crack initiation. Dynamic crack initiation measurements were reported on a 4340 steel at two different loading rates. The steel was shown to exhibit a rate dependence, with the recorded values of K{sub Ic} being much higher at the higher loading rate. Using the knowledge of this rate dependence as a motivation in attempting to model the fracture events, a viscoplastic constitutive model was implemented into a peridynamic computational mechanics code. Peridynamics is a newly developed theory in solid mechanics that replaces the classical partial differential equations of motion with integral-differential equations which do not require the existence of spatial derivatives in the displacement field. This allows for the straightforward modeling of unguided crack initiation and growth. To date, peridynamic implementations have used severely restricted constitutive models. This research represents the first implementation of a complex material model and its validation. After showing results comparing deformations to experimental Taylor anvil impact for the viscoplastic material model, a novel failure criterion is introduced to model the dynamic crack initiation toughness experiments. The failure model is based on an energy criterion and uses the K{sub Ic} values recorded experimentally as an input. The failure model
Zarea, M.F.; Toumbas, D.N.; Philibert, C.E.; Deo, I.
1996-12-31
Gas transmission pipe resistance to external damage is a subject of great attention at Gaz de France and in Europe. Existing results cover part of the necessary criteria for the residual life of damaged pipelines, but more knowledge is needed on defect creation. The authors propose to complement existing experimental work which is limited to the explored range of parameters by validated numerical models. The first, simple static denting model aims at optimizing the conditions for calculating the residual stress distribution needed to assess the fatigue life of dents and dents and gouges. The second, more complex dynamic puncture model calculates both the puncture force and the puncture energy for a given pipe, excavator and tooth geometry. These models can contribute to enhance the external damage prevention policies of transmission pipeline operators.
Computational fluid dynamics modeling of coal gasification in a pressurized spout-fluid bed
Zhongyi Deng; Rui Xiao; Baosheng Jin; He Huang; Laihong Shen; Qilei Song; Qianjun Li
2008-05-15
Computational fluid dynamics (CFD) modeling, which has recently proven to be an effective means of analysis and optimization of energy-conversion processes, has been extended to coal gasification in this paper. A 3D mathematical model has been developed to simulate the coal gasification process in a pressurized spout-fluid bed. This CFD model is composed of gas-solid hydrodynamics, coal pyrolysis, char gasification, and gas phase reaction submodels. The rates of heterogeneous reactions are determined by combining Arrhenius rate and diffusion rate. The homogeneous reactions of gas phase can be treated as secondary reactions. A comparison of the calculated and experimental data shows that most gasification performance parameters can be predicted accurately. This good agreement indicates that CFD modeling can be used for complex fluidized beds coal gasification processes. 37 refs., 7 figs., 5 tabs.
An Optimization Model for Plug-In Hybrid Electric Vehicles
Malikopoulos, Andreas; Smith, David E
2011-01-01
The necessity for environmentally conscious vehicle designs in conjunction with increasing concerns regarding U.S. dependency on foreign oil and climate change have induced significant investment towards enhancing the propulsion portfolio with new technologies. More recently, plug-in hybrid electric vehicles (PHEVs) have held great intuitive appeal and have attracted considerable attention. PHEVs have the potential to reduce petroleum consumption and greenhouse gas (GHG) emissions in the commercial transportation sector. They are especially appealing in situations where daily commuting is within a small amount of miles with excessive stop-and-go driving. The research effort outlined in this paper aims to investigate the implications of motor/generator and battery size on fuel economy and GHG emissions in a medium-duty PHEV. An optimization framework is developed and applied to two different parallel powertrain configurations, e.g., pre-transmission and post-transmission, to derive the optimal design with respect to motor/generator and battery size. A comparison between the conventional and PHEV configurations with equivalent size and performance under the same driving conditions is conducted, thus allowing an assessment of the fuel economy and GHG emissions potential improvement. The post-transmission parallel configuration yields higher fuel economy and less GHG emissions compared to pre-transmission configuration partly attributable to the enhanced regenerative braking efficiency.
Optimization of Depletion Modeling and Simulation for the High...
Office of Scientific and Technical Information (OSTI)
for the high-fidelity modeling and simulation of the ... Mathematics and Computation (M&C), Supercomputing in Nuclear Applications (SNA) and the Monte Carlo (MC) Method, ...
Integrated dynamic modeling and management system mission analysis
Lee, A.K.
1994-12-28
This document summarizes the mission analysis performed on the Integrated Dynamic Modeling and Management System (IDMMS). The IDMMS will be developed to provide the modeling and analysis capability required to understand the TWRS system behavior in terms of the identified TWRS performance measures. The IDMMS will be used to demonstrate in a verified and validated manner the satisfactory performance of the TWRS system configuration and assurance that the requirements have been satisfied.
Dynamic Metabolic Modeling of Denitrifying Bacterial Growth: The Cybernetic Approach
Song, Hyun-Seob; Liu, Chongxuan
2015-06-29
Denitrification is a multistage reduction process converting nitrate ultimately to nitrogen gas, carried out mostly by facultative bacteria. Modeling of the denitrification process is challenging due to the complex metabolic regulation that modulates sequential formation and consumption of a series of nitrogen oxide intermediates, which serve as the final electron acceptors for denitrifying bacteria. In this work, we examined the effectiveness and accuracy of the cybernetic modeling framework in simulating the growth dynamics of denitrifying bacteria in comparison with kinetic models. In four different case studies using the literature data, we successfully simulated diauxic and triauxic growth patterns observed in anoxic and aerobic conditions, only by tuning two or three parameters. In order to understand the regulatory structure of the cybernetic model, we systematically analyzed the effect of cybernetic control variables on simulation accuracy. The results showed that the consideration of both enzyme synthesis and activity control through u- and v-variables is necessary and relevant and that uvariables are of greater importance in comparison to v-variables. In contrast, simple kinetic models were unable to accurately capture dynamic metabolic shifts across alternative electron acceptors, unless an inhibition term was additionally incorporated. Therefore, the denitrification process represents a reasonable example highlighting the criticality of considering dynamic regulation for successful metabolic modeling.
Gauge turbulence, topological defect dynamics, and condensation in Higgs models
Gasenzer, Thomas; McLerran, Larry; Pawlowski, Jan M.; Sexty, Dénes
2014-07-28
The real-time dynamics of topological defects and turbulent configurations of gauge fields for electric and magnetic confinement are studied numerically within a 2+1D Abelian Higgs model. It is shown that confinement is appearing in such systems equilibrating after a strong initial quench such as the overpopulation of the infrared modes. While the final equilibrium state does not support confinement, metastable vortex defect configurations appearing in the gauge field are found to be closely related to the appearance of physically observable confined electric and magnetic charges. These phenomena are seen to be intimately related to the approach of a non-thermal fixed point of the far-from-equilibrium dynamical evolution, signaled by universal scaling in the gauge-invariant correlation function of the Higgs field. Even when the parameters of the Higgs action do not support condensate formation in the vacuum, during this approach, transient Higgs condensation is observed. We discuss implications of these results for the far-from-equilibrium dynamics of Yang–Mills fields and potential mechanisms of how confinement and condensation in non-Abelian gauge fields can be understood in terms of the dynamics of Higgs models. These suggest that there is an interesting new class of dynamics of strong coherent turbulent gauge fields with condensates.
Gauge turbulence, topological defect dynamics, and condensation in Higgs models
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Gasenzer, Thomas; McLerran, Larry; Pawlowski, Jan M.; Sexty, Dénes
2014-07-28
The real-time dynamics of topological defects and turbulent configurations of gauge fields for electric and magnetic confinement are studied numerically within a 2+1D Abelian Higgs model. It is shown that confinement is appearing in such systems equilibrating after a strong initial quench such as the overpopulation of the infrared modes. While the final equilibrium state does not support confinement, metastable vortex defect configurations appearing in the gauge field are found to be closely related to the appearance of physically observable confined electric and magnetic charges. These phenomena are seen to be intimately related to the approach of a non-thermal fixedmore » point of the far-from-equilibrium dynamical evolution, signaled by universal scaling in the gauge-invariant correlation function of the Higgs field. Even when the parameters of the Higgs action do not support condensate formation in the vacuum, during this approach, transient Higgs condensation is observed. We discuss implications of these results for the far-from-equilibrium dynamics of Yang–Mills fields and potential mechanisms of how confinement and condensation in non-Abelian gauge fields can be understood in terms of the dynamics of Higgs models. These suggest that there is an interesting new class of dynamics of strong coherent turbulent gauge fields with condensates.« less
Optimal bispectrum constraints on single-field models of inflation
Anderson, Gemma J.; Regan, Donough; Seery, David E-mail: D.Regan@sussex.ac.uk
2014-07-01
We use WMAP 9-year bispectrum data to constrain the free parameters of an 'effective field theory' describing fluctuations in single-field inflation. The Lagrangian of the theory contains a finite number of operators associated with unknown mass scales. Each operator produces a fixed bispectrum shape, which we decompose into partial waves in order to construct a likelihood function. Based on this likelihood we are able to constrain four linearly independent combinations of the mass scales. As an example of our framework we specialize our results to the case of 'Dirac-Born-Infeld' and 'ghost' inflation and obtain the posterior probability for each model, which in Bayesian schemes is a useful tool for model comparison. Our results suggest that DBI-like models with two or more free parameters are disfavoured by the data by comparison with single-parameter models in the same class.
Dynamic simulation models and performance of an OTEC power plant
Wormley, D.N.; Carmichael, D.A.; Umans, S.
1983-08-01
In this study, the aspects of plant performance which influence the potential for integration of an OTEC plant into a utility grid are considered. A set of simulation models have been developed for the evaluation of OTEC dynamic plant performance. A detailed nonlinear dynamic model has been forumlated which is useful for the assessment of component performance including heat exchangers, turbines, pumps and control systems. A reduced order linear model has been developed which is useful for studies of plant stability, control system development and transient performance of the plant connected to a utility grid. This model is particularly suitable for transient dynamic studies of an OTEC plant as a unit in a utility grid. A quasi-steady power availability model has also been developed which is useful to determine plant ouput power as a function of ocean thermal gradients so that the influence of daily and seasonal temperature variations may be easily computed. The study has found no fundamental technical barriers which would prohibit the interconnection of an OTEC plant into a utility grid. It has also shown that detailed consideration of turbine nozzle angle control is merited and such a control has the potential to provide superior performance in comparison to turbine bypass valve control.
Mathematical Modeling of Microbial Community Dynamics: A Methodological Review
Song, Hyun-Seob; Cannon, William R.; Beliaev, Alex S.; Konopka, Allan
2014-10-17
Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can be potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.
Melintescu, A.; Galeriu, D.; Diabate, S.; Strack, S.
2015-03-15
The processes involved in tritium transfer in crops are complex and regulated by many feedback mechanisms. A full mechanistic model is difficult to develop due to the complexity of the processes involved in tritium transfer and environmental conditions. First, a review of existing models (ORYZA2000, CROPTRIT and WOFOST) presenting their features and limits, is made. Secondly, the preparatory steps for a robust model are discussed, considering the role of dry matter and photosynthesis contribution to the OBT (Organically Bound Tritium) dynamics in crops.
Modeling the influence of polls on elections: a population dynamics approach
Hyman, James M; Restrepo, Juan M; Rael, Rosalyn C
2009-01-01
We propose a population dynamics model for quantifying the effects of polling data on the outcome of multi-party elections decided by a majority-rule voting process. We divide the population into two groups: committed voters impervious to polling data, and susceptible voters whose decision to vote is influenced by data, depending on its reliability. This population-based approach to modeling the process sidesteps the problem of upscaling models based upon the choices made by individuals. We find releasing poll data is not advantageous to leading candidates, but it can be exploited by those closely trailing. The analysis identifies the particular type of voting impetus at play in different stages of an election and could help strategists optimize their influence on susceptible voters.
Office Of Nuclear Energy Annual Review Meeting Dynamic Simulation Modeling Tool
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Annual Review Meeting Dynamic Simulation Modeling Tool Lou Qualls ORNL September 16-18, 2014 2 Work Package SR-14OR130108 - Modeling Tools for Dynamic Behavior Simulations of SMRs 2 ü FY14 molten salt cooled model deliverable due. n FY15 web application deliverable due. n FY15 model repository establishment due. n FY15 working collaboration with University partners. n Simplified Dynamic Modeling for Advanced SMRs - Numerous dynamic models are needed to simulate plant behavior
A system-level cost-of-energy wind farm layout optimization with landowner modeling
Chen, Le [Ames Laboratory; MacDonald, Erin [Ames Laboratory
2013-10-01
This work applies an enhanced levelized wind farm cost model, including landowner remittance fees, to determine optimal turbine placements under three landowner participation scenarios and two land-plot shapes. Instead of assuming a continuous piece of land is available for the wind farm construction, as in most layout optimizations, the problem formulation represents landowner participation scenarios as a binary string variable, along with the number of turbines. The cost parameters and model are a combination of models from the National Renewable Energy Laboratory (NREL), Lawrence Berkeley National Laboratory, and Windustiy. The system-level cost-of-energy (COE) optimization model is also tested under two land-plot shapes: equally-sized square land plots and unequal rectangle land plots. The optimal COEs results are compared to actual COE data and found to be realistic. The results show that landowner remittances account for approximately 10% of farm operating costs across all cases. Irregular land-plot shapes are easily handled by the model. We find that larger land plots do not necessarily receive higher remittance fees. The model can help site developers identify the most crucial land plots for project success and the optimal positions of turbines, with realistic estimates of costs and profitability. (C) 2013 Elsevier Ltd. All rights reserved.
THE APPLICATION OF AN EVOLUTIONARY ALGORITHM TO THE OPTIMIZATION OF A MESOSCALE METEOROLOGICAL MODEL
Werth, D.; O'Steen, L.
2008-02-11
We show that a simple evolutionary algorithm can optimize a set of mesoscale atmospheric model parameters with respect to agreement between the mesoscale simulation and a limited set of synthetic observations. This is illustrated using the Regional Atmospheric Modeling System (RAMS). A set of 23 RAMS parameters is optimized by minimizing a cost function based on the root mean square (rms) error between the RAMS simulation and synthetic data (observations derived from a separate RAMS simulation). We find that the optimization can be efficient with relatively modest computer resources, thus operational implementation is possible. The optimization efficiency, however, is found to depend strongly on the procedure used to perturb the 'child' parameters relative to their 'parents' within the evolutionary algorithm. In addition, the meteorological variables included in the rms error and their weighting are found to be an important factor with respect to finding the global optimum.
Model of a deterministic detector and dynamical decoherence
Lee, Jae Weon; Shepelyansky, Dima L. [Laboratoire de Physique Theorique, UMR 5152 du CNRS, Univ. P. Sabatier, 31062 Toulouse Cedex 4 (France); Averin, Dmitri V. [Department of Physics, University of Stony Brook, SUNY, Stony Brook, New York 11794 (United States); Benenti, Giuliano [Center for Nonlinear and Complex Systems, Universita degli Studi dell'Insubria and Istituto Nazionale per la Fisica della Materia, Unita di Como, Via Valleggio 11, 22100 Como (Italy)
2005-07-15
We discuss a deterministic model of detector coupled to a two-level system (a qubit). The detector is a quasiclassical object whose dynamics is described by the kicked rotator Hamiltonian. We show that in the regime of quantum chaos the detector acts as a chaotic bath and induces decoherence of the qubit. We discuss the dephasing and relaxation rates and demonstrate that the main features of single-qubit decoherence due to a heat bath can be reproduced by our fully deterministic dynamical model. Moreover, we show that, for strong enough qubit-detector coupling, the dephasing rate is given by the rate of exponential instability of the detector's dynamics, that is, by the Lyapunov exponent of classical motion. Finally, we discuss the measurement in the regimes of strong and weak qubit-detector coupling. For the case of strong coupling the detector performs a measurement of the up/down state of the qubit. In the case of weak coupling, due to chaos, the dynamical evolution of the detector is strongly sensitive to the state of the qubit. However, in this case it is unclear how to extract a signal from any measurement with a coarse-graining in the phase space on a size much larger than the Planck cell.
A MILP-Based Distribution Optimal Power Flow Model for Microgrid Operation
Liu, Guodong; Starke, Michael R; Zhang, Xiaohu; Tomsovic, Kevin
2016-01-01
This paper proposes a distribution optimal power flow (D-OPF) model for the operation of microgrids. The proposed model minimizes not only the operating cost, including fuel cost, purchasing cost and demand charge, but also several performance indices, including voltage deviation, network power loss and power factor. It co-optimizes the real and reactive power form distributed generators (DGs) and batteries considering their capacity and power factor limits. The D-OPF is formulated as a mixed-integer linear programming (MILP). Numerical simulation results show the effectiveness of the proposed model.
Modeling Crabbing Dynamics in an Electron-Ion Collider
Castilla, Alejandro; Morozov, Vasiliy S.; Satogata, Todd J.; Delayen, Jean R.
2015-09-01
A local crabbing scheme requires ?/2 (mod ?) horizontal betatron phase advances from an interaction point (IP) to the crab cavities on each side of it. However, realistic phase advances generated by sets of quadrupoles, or Final Focusing Blocks (FFB), between the crab cavities located in the expanded beam regions and the IP differ slightly from ?/2. To understand the effect of crabbing on the beam dynamics in this case, a simple model of the optics of the Medium Energy Electron-Ion Collider (MEIC) including local crabbing was developed using linear matrices and then studied numerically over multiple turns (1000 passes) of both electron and proton bunches. The same model was applied to both local and global crabbing schemes to determine the linear-order dynamical effects of the synchro-betatron coupling induced by crabbing.
Optimization of large-scale heterogeneous system-of-systems models.
Parekh, Ojas; Watson, Jean-Paul; Phillips, Cynthia Ann; Siirola, John; Swiler, Laura Painton; Hough, Patricia Diane; Lee, Herbert K. H.; Hart, William Eugene; Gray, Genetha Anne; Woodruff, David L.
2012-01-01
Decision makers increasingly rely on large-scale computational models to simulate and analyze complex man-made systems. For example, computational models of national infrastructures are being used to inform government policy, assess economic and national security risks, evaluate infrastructure interdependencies, and plan for the growth and evolution of infrastructure capabilities. A major challenge for decision makers is the analysis of national-scale models that are composed of interacting systems: effective integration of system models is difficult, there are many parameters to analyze in these systems, and fundamental modeling uncertainties complicate analysis. This project is developing optimization methods to effectively represent and analyze large-scale heterogeneous system of systems (HSoS) models, which have emerged as a promising approach for describing such complex man-made systems. These optimization methods enable decision makers to predict future system behavior, manage system risk, assess tradeoffs between system criteria, and identify critical modeling uncertainties.
Modeling the dynamic crush of impact mitigating materials
Logan, R.W.; McMichael, L.D.
1995-05-12
Crushable materials are commonly utilized in the design of structural components to absorb energy and mitigate shock during the dynamic impact of a complex structure, such as an automobile chassis or drum-type shipping container. The development and application of several finite-element material models which have been developed at various times at LLNL for DYNA3D will be discussed. Between the models, they are able to account for several of the predominant mechanisms which typically influence the dynamic mechanical behavior of crushable materials. One issue we addressed was that no single existing model would account for the entire gambit of constitutive features which are important for crushable materials. Thus, we describe the implementation and use of an additional material model which attempts to provide a more comprehensive model of the mechanics of crushable material behavior. This model combines features of the pre-existing DYNA models and incorporates some new features as well in an invariant large-strain formulation. In addition to examining the behavior of a unit cell in uniaxial compression, two cases were chosen to evaluate the capabilities and accuracy of the various material models in DYNA. In the first case, a model for foam filled box beams was developed and compared to test data from a 4-point bend test. The model was subsequently used to study its effectiveness in energy absorption in an aluminum extrusion, spaceframe, vehicle chassis. The second case examined the response of the AT-400A shipping container and the performance of the overpack material during accident environments selected from 10CFR71 and IAEA regulations.
Suthar, B; Northrop, PWC; Braatz, RD; Subramanian, VR
2014-07-30
This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery by restricting the intercalation-induced stresses to a pre-determined limit estimated using a pseudo 2-dimensional (P2D). model. This paper focuses on the problem of maximizing the charge stored in a given time while restricting capacity fade due to intercalation-induced stresses. Conventional charging profiles for lithium-ion batteries (e.g., constant current followed by constant voltage or CC-CV) are not derived by considering capacity fade mechanisms, which are not only inefficient in terms of life-time usage of the batteries but are also slower by not taking into account the changing dynamics of the system. (C) The Author(s) 2014. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: oa@electrochem.org. All rights reserved.
Nuclear Hybrid Energy System Modeling: RELAP5 Dynamic Coupling Capabilities
Piyush Sabharwall; Nolan Anderson; Haihua Zhao; Shannon Bragg-Sitton; George Mesina
2012-09-01
The nuclear hybrid energy systems (NHES) research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation.
An opinion-driven behavioral dynamics model for addictive behaviors
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.
2015-04-08
We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less
Options of system integrated environment modelling in the predicated dynamic cyberspace
Janková, Martina; Dvořák, Jiří
2015-03-10
In this article there are briefly mentioned some selected options of contemporary conception of cybernetic system models in the corresponding and possible integratable environment with modern system dynamics thinking and all this in the cyberspace of possible projecting of predicted system characteristics. The key to new capabilities of system integration modelling in the considered cyberspace is mainly the ability to improve the environment and the system integration options, all this with the aim of modern control in the hierarchically arranged dynamic cyberspace, e.g. in the currently desired electronic business with information. The aim of this article is to assess generally the trends in the use of modern modelling methods considering the cybernetics applications verified in practice, modern concept of project management and also the potential integration of artificial intelligence in the new projecting and project management of integratable and intelligent models, e.g. with the optimal structures and adaptable behaviour.The article results from the solution of a specific research partial task at the faculty; especially the moments proving that the new economics will be based more and more on information, knowledge system defined cyberspace of modern management, are stressed in the text.
Use dynamic simulation to model HPU reactor depressuring
Ernest, J.B.; Depew, C.A. )
1995-01-01
Dynamic simulation is the best available method for the analysis of hydroprocessing unit (HPU) depressuring. Depressuring is crucial for the safe operation of hydrocracking and other HPUs with catalysts that have hydrocracking activity. Effective design for depressuring is valuable for all types of HPUs, both grass-roots and revamps. Reactor loop depressuring can set design temperatures and pressures for the reactor effluent cooling train and other equipment and piping in an HPU. Unfortunately, usual methods for determining equipment and piping design conditions during depressuring leave much room for improvement because they poorly account for time-dependent temperature and pressure changes. Dynamic simulation makes it practical to more accurately estimate these transient conditions. The paper discusses depressuring design, including the nature of depressuring, the impact of depressuring on design, and depressuring calculation methods. The author then describes modeling of hydroprocessing unit depressuring by discussing the general and particular correspondence of simulation modules to physical equipment using the base case of total electrical power failure. The special data that is required for dynamic simulation is described and typical simulation results are given. Lastly, the advantages of dynamic simulation are summarized.
Parameter Estimation and Model Validation of Nonlinear Dynamical Networks
Abarbanel, Henry; Gill, Philip
2015-03-31
In the performance period of this work under a DOE contract, the co-PIs, Philip Gill and Henry Abarbanel, developed new methods for statistical data assimilation for problems of DOE interest, including geophysical and biological problems. This included numerical optimization algorithms for variational principles, new parallel processing Monte Carlo routines for performing the path integrals of statistical data assimilation. These results have been summarized in the monograph: “Predicting the Future: Completing Models of Observed Complex Systems” by Henry Abarbanel, published by Spring-Verlag in June 2013. Additional results and details have appeared in the peer reviewed literature.
Eulerian hydrocode modeling of a dynamic tensile extrusion experiment (u)
Burkett, Michael W; Clancy, Sean P
2009-01-01
Eulerian hydrocode simulations utilizing the Mechanical Threshold Stress flow stress model were performed to provide insight into a dynamic extrusion experiment. The dynamic extrusion response of copper (three different grain sizes) and tantalum spheres were simulated with MESA, an explicit, 2-D Eulerian continuum mechanics hydrocode and compared with experimental data. The experimental data consisted of high-speed images of the extrusion process, recovered extruded samples, and post test metallography. The hydrocode was developed to predict large-strain and high-strain-rate loading problems. Some of the features of the features of MESA include a high-order advection algorithm, a material interface tracking scheme and a van Leer monotonic advection-limiting. The Mechanical Threshold Stress (MTS) model was utilized to evolve the flow stress as a function of strain, strain rate and temperature for copper and tantalum. Plastic strains exceeding 300% were predicted in the extrusion of copper at 400 m/s, while plastic strains exceeding 800% were predicted for Ta. Quantitative comparisons between the predicted and measured deformation topologies and extrusion rate were made. Additionally, predictions of the texture evolution (based upon the deformation rate history and the rigid body rotations experienced by the copper during the extrusion process) were compared with the orientation imaging microscopy measurements. Finally, comparisons between the calculated and measured influence of the initial texture on the dynamic extrusion response of tantalum was performed.
Dynamic mesoscale model of dipolar fluids via fluctuating hydrodynamics
Persson, Rasmus A. X.; Chu, Jhih-Wei, E-mail: jwchu@nctu.edu.tw [Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu 30068, Taiwan (China); Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 30068, Taiwan (China); Voulgarakis, Nikolaos K. [Department of Mathematics, Washington State University, Richland, Washington 99372 (United States)
2014-11-07
Fluctuating hydrodynamics (FHD) is a general framework of mesoscopic modeling and simulation based on conservational laws and constitutive equations of linear and nonlinear responses. However, explicit representation of electrical forces in FHD has yet to appear. In this work, we devised an Ansatz for the dynamics of dipole moment densities that is linked with the Poisson equation of the electrical potential ? in coupling to the other equations of FHD. The resulting ?-FHD equations then serve as a platform for integrating the essential forces, including electrostatics in addition to hydrodynamics, pressure-volume equation of state, surface tension, and solvent-particle interactions that govern the emergent behaviors of molecular systems at an intermediate scale. This unique merit of ?-FHD is illustrated by showing that the water dielectric function and ion hydration free energies in homogeneous and heterogenous systems can be captured accurately via the mesoscopic simulation. Furthermore, we show that the field variables of ?-FHD can be mapped from the trajectory of an all-atom molecular dynamics simulation such that model development and parametrization can be based on the information obtained at a finer-grained scale. With the aforementioned multiscale capabilities and a spatial resolution as high as 5 , the ?-FHD equations represent a useful semi-explicit solvent model for the modeling and simulation of complex systems, such as biomolecular machines and nanofluidics.
Computational fluid dynamic modeling of fluidized-bed polymerization reactors
Rokkam, Ram
2012-01-01
Polyethylene is one of the most widely used plastics, and over 60 million tons are produced worldwide every year. Polyethylene is obtained by the catalytic polymerization of ethylene in gas and liquid phase reactors. The gas phase processes are more advantageous, and use fluidized-bed reactors for production of polyethylene. Since they operate so close to the melting point of the polymer, agglomeration is an operational concern in all slurry and gas polymerization processes. Electrostatics and hot spot formation are the main factors that contribute to agglomeration in gas-phase processes. Electrostatic charges in gas phase polymerization fluidized bed reactors are known to influence the bed hydrodynamics, particle elutriation, bubble size, bubble shape etc. Accumulation of electrostatic charges in the fluidized-bed can lead to operational issues. In this work a first-principles electrostatic model is developed and coupled with a multi-fluid computational fluid dynamic (CFD) model to understand the effect of electrostatics on the dynamics of a fluidized-bed. The multi-fluid CFD model for gas-particle flow is based on the kinetic theory of granular flows closures. The electrostatic model is developed based on a fixed, size-dependent charge for each type of particle (catalyst, polymer, polymer fines) phase. The combined CFD model is first verified using simple test cases, validated with experiments and applied to a pilot-scale polymerization fluidized-bed reactor. The CFD model reproduced qualitative trends in particle segregation and entrainment due to electrostatic charges observed in experiments. For the scale up of fluidized bed reactor, filtered models are developed and implemented on pilot scale reactor.
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
Felice, Maria V.; Velichko, Alexander Wilcox, Paul D.; Barden, Tim; Dunhill, Tony
2015-03-31
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Best practices for system dynamics model design and construction with powersim studio.
Malczynski, Leonard A.
2011-06-01
This guide addresses software quality in the construction of Powersim{reg_sign} Studio 8 system dynamics simulation models. It is the result of almost ten years of experience with the Powersim suite of system dynamics modeling tools (Constructor and earlier Studio versions). It is a guide that proposes a common look and feel for the construction of Powersim Studio system dynamics models.
Model for Aggregated Water Heater Load Using Dynamic Bayesian Networks
Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai; Kalsi, Karanjit
2012-07-19
The transition to the new generation power grid, or smart grid, requires novel ways of using and analyzing data collected from the grid infrastructure. Fundamental functionalities like demand response (DR), that the smart grid needs, rely heavily on the ability of the energy providers and distributors to forecast the load behavior of appliances under different DR strategies. This paper presents a new model of aggregated water heater load, based on dynamic Bayesian networks (DBNs). The model has been validated against simulated data from an open source distribution simulation software (GridLAB-D). The results presented in this paper demonstrate that the DBN model accurately tracks the load profile curves of aggregated water heaters under different testing scenarios.
Modeling nanoscale hydrodynamics by smoothed dissipative particle dynamics
Lei, Huan; Mundy, Christopher J.; Schenter, Gregory K.; Voulgarakis, Nikolaos
2015-05-21
Thermal fluctuation and hydrophobicity are two hallmarks of fluid hydrodynamics on the nano-scale. It is a challenge to consistently couple the small length and time scale phenomena associated with molecular interaction with larger scale phenomena. The development of this consistency is the essence of mesoscale science. In this study, we develop a nanoscale fluid model based on smoothed dissipative particle dynamics that accounts for the phenomena of associated with density fluctuations and hydrophobicity. We show consistency in the fluctuation spectrum across scales. In doing so, it is necessary to account for finite fluid particle size. Furthermore, we demonstrate that the present model can capture of the void probability and solvation free energy of apolar particles of different sizes. The present fluid model is well suited for a understanding emergent phenomena in nano-scale fluid systems.
Aggregated Residential Load Modeling Using Dynamic Bayesian Networks
Vlachopoulou, Maria; Chin, George; Fuller, Jason C.; Lu, Shuai
2014-09-28
AbstractIt is already obvious that the future power grid will have to address higher demand for power and energy, and to incorporate renewable resources of different energy generation patterns. Demand response (DR) schemes could successfully be used to manage and balance power supply and demand under operating conditions of the future power grid. To achieve that, more advanced tools for DR management of operations and planning are necessary that can estimate the available capacity from DR resources. In this research, a Dynamic Bayesian Network (DBN) is derived, trained, and tested that can model aggregated load of Heating, Ventilation, and Air Conditioning (HVAC) systems. DBNs can provide flexible and powerful tools for both operations and planing, due to their unique analytical capabilities. The DBN model accuracy and flexibility of use is demonstrated by testing the model under different operational scenarios.
Critical dynamics of cluster algorithms in the dilute Ising model
Hennecke, M. Universitaet Karlsruhe ); Heyken, U. )
1993-08-01
Autocorrelation times for thermodynamic quantities at [Tc] are calculated from Monte Carlo simulations of the site-diluted simple cubic Ising model, using the Swendsen-Wand and Wolff cluster algorithms. The results show that for these algorithms the autocorrelation times decrease when reducing the concentration of magnetic sites from 100% down to 40%. This is of crucial importance when estimating static properties of the model, since the variances of these estimators increase with autocorrelation time. The dynamical critical exponents are calculated for both algorithms, observing pronounced finite-size effects in the energy autocorrelation data for the algorithm of Wolff. It is concluded that, when applied to the dilute Ising model, cluster algorithms become even more effective than local algorithms, for which increasing autocorrelation times are expected. 33 refs., 5 figs., 2 tabs.
A Dynamic Approach to Modeling Dependence Between Human Failure Events
Boring, Ronald Laurids
2015-09-01
In practice, most HRA methods use direct dependence from THERP—the notion that error be- gets error, and one human failure event (HFE) may increase the likelihood of subsequent HFEs. In this paper, we approach dependence from a simulation perspective in which the effects of human errors are dynamically modeled. There are three key concepts that play into this modeling: (1) Errors are driven by performance shaping factors (PSFs). In this context, the error propagation is not a result of the presence of an HFE yielding overall increases in subsequent HFEs. Rather, it is shared PSFs that cause dependence. (2) PSFs have qualities of lag and latency. These two qualities are not currently considered in HRA methods that use PSFs. Yet, to model the effects of PSFs, it is not simply a matter of identifying the discrete effects of a particular PSF on performance. The effects of PSFs must be considered temporally, as the PSFs will have a range of effects across the event sequence. (3) Finally, there is the concept of error spilling. When PSFs are activated, they not only have temporal effects but also lateral effects on other PSFs, leading to emergent errors. This paper presents the framework for tying together these dynamic dependence concepts.
User Guide for PV Dynamic Model Simulation Written on PSCAD Platform
Muljadi, E.; Singh, M.; Gevorgian, V.
2014-11-01
This document describes the dynamic photovoltaic model developed by the National Renewable Energy Laboratory and is intended as a guide for users of these models.
Sun, Yipeng; /SLAC
2012-05-11
A storage ring with tunable momentum compaction has the advantage in achieving different RMS bunch length with similar RF capacity, which is potentially useful for many applications, such as linear collider damping ring and pre-damping ring where injected beam has a large energy spread and a large transverse emittance. A tunable bunch length also makes the commissioning and fine tuning easier in manipulating the single bunch instabilities. In this paper, a compact ring design based on a supercell is presented, which achieves a tunable momentum compaction while maintaining a large dynamic aperture.
Reference Model MHK Turbine Array Optimization Study within a Generic River System.
Johnson, Erick; Barco Mugg, Janet; James, Scott; Roberts, Jesse D.
2011-12-01
Increasing interest in marine hydrokinetic (MHK) energy has spurred to significant research on optimal placement of emerging technologies to maximize energy conversion and minimize potential effects on the environment. However, these devices will be deployed as an array in order to reduce the cost of energy and little work has been done to understand the impact these arrays will have on the flow dynamics, sediment-bed transport and benthic habitats and how best to optimize these arrays for both performance and environmental considerations. An %22MHK-friendly%22 routine has been developed and implemented by Sandia National Laboratories (SNL) into the flow, sediment dynamics and water-quality code, SNL-EFDC. This routine has been verified and validated against three separate sets of experimental data. With SNL-EFDC, water quality and array optimization studies can be carried out to optimize an MHK array in a resource and study its effects on the environment. The present study examines the effect streamwise and spanwise spacing has on the array performance. Various hypothetical MHK array configurations are simulated within a trapezoidal river channel. Results show a non-linear increase in array-power efficiency as turbine spacing is increased in each direction, which matches the trends seen experimentally. While the sediment transport routines were not used in these simulations, the flow acceleration seen around the MHK arrays has the potential to significantly affect the sediment transport characteristics and benthic habitat of a resource. Evaluation Only. Created with Aspose.Pdf.Kit. Copyright 2002-2011 Aspose Pty Ltd Evaluation Only. Created with Aspose.Pdf.Kit. Copyright 2002-2011 Aspose Pty Ltd
Equation-based languages – A new paradigm for building energy modeling, simulation and optimization
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wetter, Michael; Bonvini, Marco; Nouidui, Thierry S.
2016-04-01
Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization. We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller thatmore » adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. As a result, exploiting the equation-based language led to 2, 200 times faster solution« less
Model Studies of the Dynamics of Bacterial Flagellar Motors
Bai, F; Lo, C; Berry, R; Xing, J
2009-03-19
The Bacterial Flagellar Motor is a rotary molecular machine that rotates the helical filaments which propel swimming bacteria. Extensive experimental and theoretical studies exist on the structure, assembly, energy input, power generation and switching mechanism of the motor. In our previous paper, we explained the general physics underneath the observed torque-speed curves with a simple two-state Fokker-Planck model. Here we further analyze this model. In this paper we show (1) the model predicts that the two components of the ion motive force can affect the motor dynamics differently, in agreement with the latest experiment by Lo et al.; (2) with explicit consideration of the stator spring, the model also explains the lack of dependence of the zero-load speed on stator number in the proton motor, recently observed by Yuan and Berg; (3) the model reproduces the stepping behavior of the motor even with the existence of the stator springs and predicts the dwelling time distribution. Predicted stepping behavior of motors with two stators is discussed, and we suggest future experimental verification.
Optimization of dynamic aperture for hadron lattices in eRHIC
Jing, Yichao; Litvinenko, Vladimir; Trbojevic, Dejan
2015-05-03
The potential upgrade of the Relativistic Heavy Ion Collider (RHIC) to an electron ion collider (eRHIC) involves numerous extensive changes to the existing collider complex. The expected very high luminosity is planned to be achieved at eRHIC with the help of squeezing the beta function of the hadron ring at the IP to a few cm, causing a large rise of the natural chromaticities and thus bringing with it challenges for the beam long term stability (Dynamic aperture). We present our effort to expand the DA by carefully tuning the nonlinear magnets thus controlling the size of the footprints in tune space and all lower order resonance driving terms. We show a reasonably large DA through particle tracking over millions of turns of beam revolution.
Model Predictive Control-based Optimal Coordination of Distributed Energy Resources
Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.
2013-01-07
Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.
Model Predictive Control-based Optimal Coordination of Distributed Energy Resources
Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.
2013-04-03
Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.
Intelligent Object-Oriented GIS Engine W/dynamic Coupling to Modeled Objects
Energy Science and Technology Software Center (OSTI)
1997-02-12
The GEOVIEWER is an intelligent object-oriented Geographic Information System (GIS) engine that provides not only a spatially-optimized object representation, but also direct linkage to the underlying object, its data and behaviors. Tools are incorporated to perform tasks involving typical GIS functionality, data ingestion, linkage to external models, and integration with other application frameworks. The GOEVIEWER module was designed to provide GIS functionality to create, query, view, and manipulate software objects within a selected area undermore » investigation in a simulation system. Many of these objects are not stored in a format conductive to efficient GIS usage. Their dynamic nature, complexity, and the sheer number of possible entity classes preclude effective integration with traditional GIS technologies due to the loosely coupled nature of their data representations. The primary difference between GEOVIEWER and standard GIS packages is that standard GIS packages offer static views of geospatial data while GEOVIEWER can be dynamically coupled to models and/or applications producing data and, therefore, display changes in geometry, attributes or behavior as they occur in the simulation.« less
Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model
Rossi, R; Gallagher, B; Neville, J; Henderson, K
2011-11-11
Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied our model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.
VISION -- A Dynamic Model of the Nuclear Fuel Cycle
J. J. Jacobson; A. M. Yacout; S. J. Piet; D. E. Shropshire; G. E. Matthern
2006-02-01
The Advanced Fuel Cycle Initiative’s (AFCI) fundamental objective is to provide technology options that – if implemented – would enable long-term growth of nuclear power while improving sustainability and energy security. The AFCI organization structure consists of four areas; Systems Analysis, Fuels, Separations and Transmutations. The Systems Analysis Working Group is tasked with bridging the program technical areas and providing the models, tools, and analyses required to assess the feasibility of design and deploy¬ment options and inform key decision makers. An integral part of the Systems Analysis tool set is the development of a system level model that can be used to examine the implications of the different mixes of reactors, implications of fuel reprocessing, impact of deployment technologies, as well as potential “exit” or “off ramp” approaches to phase out technologies, waste management issues and long-term repository needs. The Verifiable Fuel Cycle Simulation Model (VISION) is a computer-based simulation model that allows performing dynamic simulations of fuel cycles to quantify infrastructure requirements and identify key trade-offs between alternatives. VISION is intended to serve as a broad systems analysis and study tool applicable to work conducted as part of the AFCI (including costs estimates) and Generation IV reactor development studies.
Computational fluid dynamics modeling of proton exchange membrane fuel cells
UM,SUKKEE; WANG,C.Y.; CHEN,KEN S.
2000-02-11
A transient, multi-dimensional model has been developed to simulate proton exchange membrane (PEM) fuel cells. The model accounts simultaneously for electrochemical kinetics, current distribution, hydrodynamics and multi-component transport. A single set of conservation equations valid for flow channels, gas-diffusion electrodes, catalyst layers and the membrane region are developed and numerically solved using a finite-volume-based computational fluid dynamics (CFD) technique. The numerical model is validated against published experimental data with good agreement. Subsequently, the model is applied to explore hydrogen dilution effects in the anode feed. The predicted polarization cubes under hydrogen dilution conditions are found to be in qualitative agreement with recent experiments reported in the literature. The detailed two-dimensional electrochemical and flow/transport simulations further reveal that in the presence of hydrogen dilution in the fuel stream, hydrogen is depleted at the reaction surface resulting in substantial kinetic polarization and hence a lower current density that is limited by hydrogen transport from the fuel stream to the reaction site.
EXTENDING THE REALM OF OPTIMIZATION FOR COMPLEX SYSTEMS: UNCERTAINTY, COMPETITION, AND DYNAMICS
Shanbhag, Uday V; Basar, Tamer; Meyn, Sean; Mehta, Prashant
2013-10-08
Research reported addressed these topics: the development of analytical and algorithmic tools for distributed computation of Nash equilibria; synchronization in mean-field oscillator games, with an emphasis on learning and efficiency analysis; questions that combine learning and computation; questions including stochastic and mean-field games; modeling and control in the context of power markets.
ARRAY OPTIMIZATION FOR TIDAL ENERGY EXTRACTION IN A TIDAL CHANNEL A NUMERICAL MODELING ANALYSIS
Yang, Zhaoqing; Wang, Taiping; Copping, Andrea
2014-04-18
This paper presents an application of a hydrodynamic model to simulate tidal energy extraction in a tidal dominated estuary in the Pacific Northwest coast. A series of numerical experiments were carried out to simulate tidal energy extraction with different turbine array configurations, including location, spacing and array size. Preliminary model results suggest that array optimization for tidal energy extraction in a real-world site is a very complex process that requires consideration of multiple factors. Numerical models can be used effectively to assist turbine siting and array arrangement in a tidal turbine farm for tidal energy extraction.
Observations on the Optimality Tolerance in the CAISO 33% RPS Model
Yao, Y; Meyers, C; Schmidt, A; Smith, S; Streitz, F
2011-09-22
In 2008 Governor Schwarzenegger of California issued an executive order requiring that 33 percent of all electricity in the state in the year 2020 should come from renewable resources such as wind, solar, geothermal, biomass, and small hydroelectric facilities. This 33% renewable portfolio standard (RPS) was further codified and signed into law by Governor Brown in 2011. To assess the market impacts of such a requirement, the California Public Utilities Commission (CPUC) initiated a study to quantify the cost, risk, and timing of achieving a 33% RPS by 2020. The California Independent System Operator (CAISO) was contracted to manage this study. The production simulation model used in this study was developed using the PLEXOS software package, which allows energy planners to optimize long-term system planning decisions under a wide variety of system constraints. In this note we describe our observations on varying the optimality tolerance in the CAISO 33% RPS model. In particular, we observe that changing the optimality tolerance from .05% to .5% leads to solutions over 5 times faster, on average, producing very similar solutions with a negligible difference in overall distance from optimality.
Vrugt, Jasper A; Wohling, Thomas
2008-01-01
Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.
Gutowski, William J.; Prusa, Joseph M.; Smolarkiewicz, Piotr K.
2012-05-08
This project had goals of advancing the performance capabilities of the numerical general circulation model EULAG and using it to produce a fully operational atmospheric global climate model (AGCM) that can employ either static or dynamic grid stretching for targeted phenomena. The resulting AGCM combined EULAG's advanced dynamics core with the "physics" of the NCAR Community Atmospheric Model (CAM). Effort discussed below shows how we improved model performance and tested both EULAG and the coupled CAM-EULAG in several ways to demonstrate the grid stretching and ability to simulate very well a wide range of scales, that is, multi-scale capability. We leveraged our effort through interaction with an international EULAG community that has collectively developed new features and applications of EULAG, which we exploited for our own work summarized here. Overall, the work contributed to over 40 peer-reviewed publications and over 70 conference/workshop/seminar presentations, many of them invited. 3a. EULAG Advances EULAG is a non-hydrostatic, parallel computational model for all-scale geophysical flows. EULAG's name derives from its two computational options: EULerian (flux form) or semi-LAGrangian (advective form). The model combines nonoscillatory forward-in-time (NFT) numerical algorithms with a robust elliptic Krylov solver. A signature feature of EULAG is that it is formulated in generalized time-dependent curvilinear coordinates. In particular, this enables grid adaptivity. In total, these features give EULAG novel advantages over many existing dynamical cores. For EULAG itself, numerical advances included refining boundary conditions and filters for optimizing model performance in polar regions. We also added flexibility to the model's underlying formulation, allowing it to work with the pseudo-compressible equation set of Durran in addition to EULAG's standard anelastic formulation. Work in collaboration with others also extended the demonstrated range of
Cady, C.M.; Chen, S.R.; Gray, G.T. III
1996-08-23
The objective of this study was to characterize the dynamic mechanical properties of four different structural sheet steels used in automobile manufacture. The analysis of a drawing quality, special killed (DQSK) mild steel; high strength, low alloy (HSLA) steel; interstitial free (IF); and a high strength steel (M-190) have been completed. In addition to the true stress-true strain data, coefficients for the Johnson-Cook, Zerilli-Armstrong, and Mechanical Threshold Stress constitutive models have been determined from the mechanical test results at various strain rates and temperatures and are summarized. Compression, tensile, and biaxial bulge tests and low (below 0.1/s) strain rate tests were completed for all four steels. From these test results it was determined to proceed with the material modeling optimization using the through thickness compression results. Compression tests at higher strain rates and temperatures were also conducted and analyzed for all the steels. Constitutive model fits were generated from the experimental data. This report provides a compilation of information generated from mechanical tests, the fitting parameters for each of the constitutive models, and an index and description of data files.
Fluid dynamic modeling of nano-thermite reactions
Martirosyan, Karen S.; Zyskin, Maxim; Jenkins, Charles M.; Horie, Yasuyuki
2014-03-14
This paper presents a direct numerical method based on gas dynamic equations to predict pressure evolution during the discharge of nanoenergetic materials. The direct numerical method provides for modeling reflections of the shock waves from the reactor walls that generates pressure-time fluctuations. The results of gas pressure prediction are consistent with the experimental evidence and estimates based on the self-similar solution. Artificial viscosity provides sufficient smoothing of shock wave discontinuity for the numerical procedure. The direct numerical method is more computationally demanding and flexible than self-similar solution, in particular it allows study of a shock wave in its early stage of reaction and allows the investigation of “slower” reactions, which may produce weaker shock waves. Moreover, numerical results indicate that peak pressure is not very sensitive to initial density and reaction time, providing that all the material reacts well before the shock wave arrives at the end of the reactor.
Description of waste pretreatment and interfacing systems dynamic simulation model
Garbrick, D.J.; Zimmerman, B.D.
1995-05-01
The Waste Pretreatment and Interfacing Systems Dynamic Simulation Model was created to investigate the required pretreatment facility processing rates for both high level and low level waste so that the vitrification of tank waste can be completed according to the milestones defined in the Tri-Party Agreement (TPA). In order to achieve this objective, the processes upstream and downstream of the pretreatment facilities must also be included. The simulation model starts with retrieval of tank waste and ends with vitrification for both low level and high level wastes. This report describes the results of three simulation cases: one based on suggested average facility processing rates, one with facility rates determined so that approximately 6 new DSTs are required, and one with facility rates determined so that approximately no new DSTs are required. It appears, based on the simulation results, that reasonable facility processing rates can be selected so that no new DSTs are required by the TWRS program. However, this conclusion must be viewed with respect to the modeling assumptions, described in detail in the report. Also included in the report, in an appendix, are results of two sensitivity cases: one with glass plant water recycle steams recycled versus not recycled, and one employing the TPA SST retrieval schedule versus a more uniform SST retrieval schedule. Both recycling and retrieval schedule appear to have a significant impact on overall tank usage.
Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Genevieve Saur (PI), Chris Ainscough (Presenter), Kevin Harrison, Todd Ramsden National Renewable Energy Laboratory January 17 th , 2013 This presentation does not contain any proprietary, confidential, or otherwise restricted information 2 Acknowledgements * This work was made possible by support from the U.S. Department of Energy's Fuel Cell Technologies Office within the Office of Energy Efficiency and
2015-09-01
The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art dynamic model of the domestic biofuels supply chain which explicitly focuses on policy issues, their feasibility, and potential side effects. It integrates resource availability, physical/technological/economic constraints, behavior, and policy. The model uses a system dynamics simulation (not optimization) to model dynamic interactions across the supply chain.
Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant
Kumar, Rajeeva; Kumar, Aditya; Dai, Dan; Seenumani, Gayathri; Down, John; Lopez, Rodrigo
2012-12-31
This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve
Creating dynamic equivalent PV circuit models with impedance spectroscopy for arc-fault modeling.
Johnson, Jay Dean; Kuszmaul, Scott S.; Strauch, Jason E.; Schoenwald, David Alan
2011-06-01
Article 690.11 in the 2011 National Electrical Code{reg_sign} (NEC{reg_sign}) requires new photovoltaic (PV) systems on or penetrating a building to include a listed arc fault protection device. Currently there is little experimental or empirical research into the behavior of the arcing frequencies through PV components despite the potential for modules and other PV components to filter or attenuate arcing signatures that could render the arc detector ineffective. To model AC arcing signal propagation along PV strings, the well-studied DC diode models were found to inadequately capture the behavior of high frequency arcing signals. Instead dynamic equivalent circuit models of PV modules were required to describe the impedance for alternating currents in modules. The nonlinearities present in PV cells resulting from irradiance, temperature, frequency, and bias voltage variations make modeling these systems challenging. Linearized dynamic equivalent circuits were created for multiple PV module manufacturers and module technologies. The equivalent resistances and capacitances for the modules were determined using impedance spectroscopy with no bias voltage and no irradiance. The equivalent circuit model was employed to evaluate modules having irradiance conditions that could not be measured directly with the instrumentation. Although there was a wide range of circuit component values, the complex impedance model does not predict filtering of arc fault frequencies in PV strings for any irradiance level. Experimental results with no irradiance agree with the model and show nearly no attenuation for 1 Hz to 100 kHz input frequencies.
The challenges of modelling antibody repertoire dynamics in HIV infection
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Luo, Shishi; Perelson, Alan S.
2015-07-20
Antibody affinity maturation by somatic hypermutation of B-cell immunoglobulin variable region genes has been studied for decades in various model systems using well-defined antigens. While much is known about the molecular details of the process, our understanding of the selective forces that generate affinity maturation are less well developed, particularly in the case of a co-evolving pathogen such as HIV. Despite this gap in understanding, high-throughput antibody sequence data are increasingly being collected to investigate the evolutionary trajectories of antibody lineages in HIV-infected individuals. Here, we review what is known in controlled experimental systems about the mechanisms underlying antibody selectionmore » and compare this to the observed temporal patterns of antibody evolution in HIV infection. In addition, we describe how our current understanding of antibody selection mechanisms leaves questions about antibody dynamics in HIV infection unanswered. Without a mechanistic understanding of antibody selection in the context of a co-evolving viral population, modelling and analysis of antibody sequences in HIV-infected individuals will be limited in their interpretation and predictive ability.« less
Ultrafast Structural Dynamics in Combustion Relevant Model Systems
Weber, Peter M.
2014-03-31
The research project explored the time resolved structural dynamics of important model reaction system using an array of novel methods that were developed specifically for this purpose. They include time resolved electron diffraction, time resolved relativistic electron diffraction, and time resolved Rydberg fingerprint spectroscopy. Toward the end of the funding period, we also developed time-resolved x-ray diffraction, which uses ultrafast x-ray pulses at LCLS. Those experiments are just now blossoming, as the funding period expired. In the following, the time resolved Rydberg Fingerprint Spectroscopy is discussed in some detail, as it has been a very productive method. The binding energy of an electron in a Rydberg state, that is, the energy difference between the Rydberg level and the ground state of the molecular ion, has been found to be a uniquely powerful tool to characterize the molecular structure. To rationalize the structure sensitivity we invoke a picture from electron diffraction: when it passes the molecular ion core, the Rydberg electron experiences a phase shift compared to an electron in a hydrogen atom. This phase shift requires an adjustment of the binding energy of the electron, which is measurable. As in electron diffraction, the phase shift depends on the molecular, geometrical structure, so that a measurement of the electron binding energy can be interpreted as a measurement of the molecules structure. Building on this insight, we have developed a structurally sensitive spectroscopy: the molecule is first elevated to the Rydberg state, and the binding energy is then measured using photoelectron spectroscopy. The molecules structure is read out as the binding energy spectrum. Since the photoionization can be done with ultrafast laser pulses, the technique is inherently capable of a time resolution in the femtosecond regime. For the purpose of identifying the structures of molecules during chemical reactions, and for the analysis of
Wu, H. L.; Tian, W. D.; Ma, Y. G.; Cai, X. Z.; Chen, J. G.; Fang, D. Q.; Guo, W.; Wang, H. W.
2010-04-15
Dynamical dipole gamma-ray emission in heavy-ion collisions is explored in the framework of the quantum molecular dynamics model. The studies are focused on systems of {sup 40}Ca bombarding {sup 48}Ca and its isotopes at different incident energies and impact parameters. Yields of gamma rays are calculated and the centroid energy and dynamical dipole emission width of the gamma spectra are extracted to investigate the properties of gamma emission. In addition, sensitivities of dynamical dipole gamma-ray emission to the isospin and the symmetry energy coefficient of the equation of state are studied. The results show that detailed study of dynamical dipole gamma radiation can provide information on the equation of state and the symmetry energy around the normal nuclear density.
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Zhang, Yongfeng; Bai, Xian-Ming; Yu, Jianguo; Tonks, Michael R.; Noordhoek, Mark J.; Phillpot, Simon R.
2016-06-01
A formation path for homogeneous γ hydride formation in hcp α-Zr, from solid solution to the ζ and then the γ hydride, was demonstrated using molecular static calculations and molecular dynamic simulations with the charge-optimized many-body (COMB) potential. Hydrogen has limited solubility in α-Zr. Once the solubility limit is exceeded, the stability of solid solution gives way to that of coherent hydride phases such as the ζ hydride by planar precipitation of hydrogen. At finite temperatures, the ζ hydride goes through a partial hcp-fcc transformation via 1/3 <1¯100> slip on the basal plane, and transforms into a mixture of γmore » hydride and α-Zr. In the ζ hydride, slip on the basal plane is favored thermodynamically with negligible barrier, and is therefore feasible at finite temperatures without mechanical loading. The transformation process involves slips of three equivalent shear partials, in contrast to that proposed in the literature where only a single shear partial was involved. The adoption of multiple slip partials minimizes the macroscopic shape change of embedded hydride clusters and the shear strain accumulation in the matrix, and thus reduces the overall barrier needed for homogeneous γ hydride formation. In conclusion, this formation path requires finite temperatures for hydrogen diffusion without mechanical loading. Therefore, it should be effective at the cladding operating conditions.« less
Dynamics Modeling and Loads Analysis of an Offshore Floating Wind Turbine
Jonkman, J. M.
2007-12-01
This report describes the development, verification, and application of a comprehensive simulation tool for modeling coupled dynamic responses of offshore floating wind turbines.
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Optimization Hyperparameter Optimization In machine learning, parameters are the values that describe a machine learning model and are usually chosen by a learning algorithm. Hyperparameters, on the other hand, are parameters for the learning algorithm. The process of looking for the most optimal hyperparameters for a machine learning algorithm is called hyperparameter optimization. We support a few pieces of software for hyperparameter optimzation. Single Node Scikit-Learn Grid Search Random
Optimizing the transverse thermal conductivity of 2D-SiCf/SiC composites, I. Modeling
Youngblood, Gerald E.; Senor, David J.; Jones, Russell H.
2002-12-31
For potential fusion applications, considerable fabrication efforts have been directed to obtaining transverse thermal conductivity (Keff) values in excess of 30 W/mK (unirradiated) in the 800-1000°C temperature range for 2D-SiCf/SiC composites. To gain insight into the factors affecting Keff, at PNNL we have tested three different analytic models for predicting Keff in terms of constituent (fiber, matrix and interphase) properties. The tested models were: the Hasselman-Johnson (H-J) “2-Cylinder” model, which examines the effects of fiber-matrix (f/m) thermal barriers; the Markworth “3-Cylinder” model, which specifically examines the effects of interphase thickness and thermal conductivity; and a newly-developed Anisotropic “3-Square” model, which examines the potential effect of introducing a fiber coating with anisotropic properties to enhance (or diminish) f/m thermal coupling. The first two models are effective medium models, while the third model is a simple combination of parallel and series conductances. Model predictions suggest specific designs and/or development efforts directed to optimize the overall thermal transport performance of 2D-SiCf/SiC.
From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Blazewicz, Marek; Hinder, Ian; Koppelman, David M.; Brandt, Steven R.; Ciznicki, Milosz; Kierzynka, Michal; Löffler, Frank; Schnetter, Erik; Tao, Jian
2013-01-01
Starting from a high-level problem description in terms of partial differential equations using abstract tensor notation, the Chemora framework discretizes, optimizes, and generates complete high performance codes for a wide range of compute architectures. Chemora extends the capabilities of Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient manner for complex applications, without low-level code tuning. Chemora achieves parallelism through MPI and multi-threading, combining OpenMP and CUDA. Optimizations include high-level code transformations, efficient loop traversal strategies, dynamically selected data and instruction cache usage strategies, and JIT compilation of GPU code tailored to the problem characteristics. The discretizationmore » is based on higher-order finite differences on multi-block domains. Chemora's capabilities are demonstrated by simulations of black hole collisions. This problem provides an acid test of the framework, as the Einstein equations contain hundreds of variables and thousands of terms.« less
From the Building to the Grid: An Energy Revolution and Modeling...
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
important. * If we model a whole country, no need for detailed response, but need to know dynamic response. Sophisticated models are not required. * Models should be optimized for...
MATHEMATICAL MODELS OF HYSTERESIS (DYNAMIC PROBLEMS IN HYSTERESIS)
Professor Isaak Mayergoyz
2006-08-21
This research has further advanced the current state of the art in the areas of dynamic aspects of hysteresis and nonlinear large scale magnetization dynamics. The results of this research will find important engineering applications in the areas of magnetic data storage technology and the emerging technology of “spintronics”. Our research efforts have been focused on the following tasks: • Study of fast (pulse) precessional switching of magnetization in magnetic materials. • Analysis of critical fields and critical angles for precessional switching of magnetization. • Development of inverse problem approach to the design of magnetic field pulses for precessional switching of magnetization. • Study of magnetization dynamics induced by spin polarized current injection. • Construction of complete stability diagrams for spin polarized current induced magnetization dynamics. • Development of the averaging technique for the analysis of the slow time scale magnetization dynamics. • Study of thermal effects on magnetization dynamics by using the theory of stochastic processes on graphs.
Development of an entrained flow gasifier model for process optimization study
Biagini, E.; Bardi, A.; Pannocchia, G.; Tognotti, L.
2009-10-15
Coal gasification is a versatile process to convert a solid fuel in syngas, which can be further converted and separated in hydrogen, which is a valuable and environmentally acceptable energy carrier. Different technologies (fixed beds, fluidized beds, entrained flow reactors) are used, operating under different conditions of temperature, pressure, and residence time. Process studies should be performed for defining the best plant configurations and operating conditions. Although 'gasification models' can be found in the literature simulating equilibrium reactors, a more detailed approach is required for process analysis and optimization procedures. In this work, a gasifier model is developed by using AspenPlus as a tool to be implemented in a comprehensive process model for the production of hydrogen via coal gasification. It is developed as a multizonal model by interconnecting each step of gasification (preheating, devolatilization, combustion, gasification, quench) according to the reactor configuration, that is in entrained flow reactor. The model removes the hypothesis of equilibrium by introducing the kinetics of all steps and solves the heat balance by relating the gasification temperature to the operating conditions. The model allows to predict the syngas composition as well as quantity the heat recovery (for calculating the plant efficiency), 'byproducts', and residual char. Finally, in view of future works, the development of a 'gasifier model' instead of a 'gasification model' will allow different reactor configurations to be compared.
Optimization of Advanced Diesel Engine Combustion Strategies...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
More Documents & Publications Optimization of Advanced Diesel Engine Combustion Strategies Optimization of Advanced Diesel Engine Combustion Strategies Computational Fluid Dynamics ...
Integrated dynamic landscape analysis and modeling system (IDLAMS) : installation manual.
Li, Z.; Majerus, K. A.; Sundell, R. C.; Sydelko, P. J.; Vogt, M. C.
1999-02-24
The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) is a prototype, integrated land management technology developed through a joint effort between Argonne National Laboratory (ANL) and the US Army Corps of Engineers Construction Engineering Research Laboratories (USACERL). Dr. Ronald C. Sundell, Ms. Pamela J. Sydelko, and Ms. Kimberly A. Majerus were the principal investigators (PIs) for this project. Dr. Zhian Li was the primary software developer. Dr. Jeffrey M. Keisler, Mr. Christopher M. Klaus, and Mr. Michael C. Vogt developed the decision analysis component of this project. It was developed with funding support from the Strategic Environmental Research and Development Program (SERDP), a land/environmental stewardship research program with participation from the US Department of Defense (DoD), the US Department of Energy (DOE), and the US Environmental Protection Agency (EPA). IDLAMS predicts land conditions (e.g., vegetation, wildlife habitats, and erosion status) by simulating changes in military land ecosystems for given training intensities and land management practices. It can be used by military land managers to help predict the future ecological condition for a given land use based on land management scenarios of various levels of training intensity. It also can be used as a tool to help land managers compare different land management practices and further determine a set of land management activities and prescriptions that best suit the needs of a specific military installation.
Tessier, Tracey E.; Caves, Carlton M.; Deutsch, Ivan H.; Eastin, Bryan; Bacon, Dave
2005-09-15
We present a model, motivated by the criterion of reality put forward by Einstein, Podolsky, and Rosen and supplemented by classical communication, which correctly reproduces the quantum-mechanical predictions for measurements of all products of Pauli operators on an n-qubit GHZ state (or 'cat state'). The n-2 bits employed by our model are shown to be optimal for the allowed set of measurements, demonstrating that the required communication overhead scales linearly with n. We formulate a connection between the generation of the local values utilized by our model and the stabilizer formalism, which leads us to conjecture that a generalization of this method will shed light on the content of the Gottesman-Knill theorem.
A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
De Pillis, L. G.; Radunskaya, A.
2001-01-01
We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less
A Technical Review on Biomass Processing: Densification, Preprocessing, Modeling and Optimization
Jaya Shankar Tumuluru; Christopher T. Wright
2010-06-01
It is now a well-acclaimed fact that burning fossil fuels and deforestation are major contributors to climate change. Biomass from plants can serve as an alternative renewable and carbon-neutral raw material for the production of bioenergy. Low densities of 40–60 kg/m3 for lignocellulosic and 200–400 kg/m3 for woody biomass limits their application for energy purposes. Prior to use in energy applications these materials need to be densified. The densified biomass can have bulk densities over 10 times the raw material helping to significantly reduce technical limitations associated with storage, loading and transportation. Pelleting, briquetting, or extrusion processing are commonly used methods for densification. The aim of the present research is to develop a comprehensive review of biomass processing that includes densification, preprocessing, modeling and optimization. The specific objective include carrying out a technical review on (a) mechanisms of particle bonding during densification; (b) methods of densification including extrusion, briquetting, pelleting, and agglomeration; (c) effects of process and feedstock variables and biomass biochemical composition on the densification (d) effects of preprocessing such as grinding, preheating, steam explosion, and torrefaction on biomass quality and binding characteristics; (e) models for understanding the compression characteristics; and (f) procedures for response surface modeling and optimization.
Meyer, Arne [University of Hamburg, c/o DESY, Building 22a, Notkestrasse 85, 22603 Hamburg (Germany); Dierks, Karsten [University of Hamburg, c/o DESY, Building 22a, Notkestrasse 85, 22603 Hamburg (Germany); XtalConcepts, Marlowring 19, 22525 Hamburg (Germany); Hussein, Rana [University of Hamburg, c/o DESY, Building 22a, Notkestrasse 85, 22603 Hamburg (Germany); Brillet, Karl [ESBS, Ple API, 300 Boulevard Sbastien Brant, CS10413, 67412 Illkirch CEDEX (France); Brognaro, Hevila [So Paulo State University, UNESP/IBILCE, Caixa Postal 136, So Jos do Rio Preto-SP, 15054 (Brazil); Betzel, Christian, E-mail: christian.betzel@uni-hamburg.de [University of Hamburg, c/o DESY, Building 22a, Notkestrasse 85, 22603 Hamburg (Germany)
2015-01-01
Application of in situ dynamic light scattering to solutions of proteindetergent complexes permits characterization of these complexes in samples as small as 2 l in volume. Detergents are widely used for the isolation and solubilization of membrane proteins to support crystallization and structure determination. Detergents are amphiphilic molecules that form micelles once the characteristic critical micelle concentration (CMC) is achieved and can solubilize membrane proteins by the formation of micelles around them. The results are presented of a study of micelle formation observed by in situ dynamic light-scattering (DLS) analyses performed on selected detergent solutions using a newly designed advanced hardware device. DLS was initially applied in situ to detergent samples with a total volume of approximately 2 l. When measured with DLS, pure detergents show a monodisperse radial distribution in water at concentrations exceeding the CMC. A series of all-transn-alkyl-?-d-maltopyranosides, from n-hexyl to n-tetradecyl, were used in the investigations. The results obtained verify that the application of DLS in situ is capable of distinguishing differences in the hydrodynamic radii of micelles formed by detergents differing in length by only a single CH{sub 2} group in their aliphatic tails. Subsequently, DLS was applied to investigate the distribution of hydrodynamic radii of membrane proteins and selected water-insoluble proteins in presence of detergent micelles. The results confirm that stable proteindetergent complexes were prepared for (i) bacteriorhodopsin and (ii) FetA in complex with a ligand as examples of transmembrane proteins. A fusion of maltose-binding protein and the Duck hepatitis B virus X protein was added to this investigation as an example of a non-membrane-associated protein with low water solubility. The increased solubility of this protein in the presence of detergent could be monitored, as well as the progress of proteolytic cleavage to
Vandersall, Jennifer A.; Gardner, Shea N.; Clague, David S.
2010-05-04
A computational method and computer-based system of modeling DNA synthesis for the design and interpretation of PCR amplification, parallel DNA synthesis, and microarray chip analysis. The method and system include modules that address the bioinformatics, kinetics, and thermodynamics of DNA amplification and synthesis. Specifically, the steps of DNA selection, as well as the kinetics and thermodynamics of DNA hybridization and extensions, are addressed, which enable the optimization of the processing and the prediction of the products as a function of DNA sequence, mixing protocol, time, temperature and concentration of species.
OneidaTribe of Indians Energy Optimization Model Development and Energy Audits
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Energy Optimization Model Development & Energy Audits U.S. DOE - Tribal Energy Program - 11/14/12 2 12/13/2012 where is it? Overview ► Reservation size of 65,430 acres (roughly 8 x 12 miles) with Oneida ownership of approximately 24,173 acres ► Membership of 16,877 with 7,360 members living on the Reservation or in immediate area ► Repurchase and restoration of lands a priority since casino started in 1993 ► Surburban sprawl from Green Bay and rising land prices Energy Team ►
Bond-Lamberty, Benjamin; Calvin, Katherine V.; Jones, Andrew D.; Mao, Jiafu; Patel, Pralit L.; Shi, Xiaoying; Thomson, Allison M.; Thornton, Peter E.; Zhou, Yuyu
2014-01-01
Human activities are significantly altering biogeochemical cycles at the global scale, posing a significant problem for earth system models (ESMs), which may incorporate static land-use change inputs but do not actively simulate policy or economic forces. One option to address this problem is a to couple an ESM with an economically oriented integrated assessment model. Here we have implemented and tested a coupling mechanism between the carbon cycles of an ESM (CLM) and an integrated assessment (GCAM) model, examining the best proxy variables to share between the models, and quantifying our ability to distinguish climate- and land-use-driven flux changes. CLMs net primary production and heterotrophic respiration outputs were found to be the most robust proxy variables by which to manipulate GCAMs assumptions of long-term ecosystem steady state carbon, with short-term forest production strongly correlated with long-term biomass changes in climate-change model runs. By leveraging the fact that carbon-cycle effects of anthropogenic land-use change are short-term and spatially limited relative to widely distributed climate effects, we were able to distinguish these effects successfully in the model coupling, passing only the latter to GCAM. By allowing climate effects from a full earth system model to dynamically modulate the economic and policy decisions of an integrated assessment model, this work provides a foundation for linking these models in a robust and flexible framework capable of examining two-way interactions between human and earth system processes.
Schwedock, M.J.; Windes, L.C.; Ray, W.H.
1985-01-01
Heterogeneous and pseudohomogeneous models are compared to experimental data from a packed bed reactor for the partical oxidation of methanol to formaldehyde over an iron oxide-molybdenum oxide catalyst. Heat transfer parameters which were successful in matching data from experiments without reaction were not successful in matching temperature data from experiments with reaction. This made it necessary to decrease the fluid radial heat transfer to obtain good fit. A good fit was obtained for steady state composition profiles by optimizing selected frequency factors and the activation energy for methanol. A redox rate expression for the oxidation of formaldehyde to carbon monoxide was proposed since a simple first-order rate expression did not fit the data. The pseudohomogeneous model gave results similar to the heterogeneous model for both steady state and dynamic experiments and has been recommended for future experimental state estimation and control studies. 21 refs., 31 figs., 6 tabs.
Modeling and optimizing of the random atomic spin gyroscope drift based on the atomic spin gyroscope
Quan, Wei; Lv, Lin Liu, Baiqi
2014-11-15
In order to improve the atom spin gyroscope's operational accuracy and compensate the random error caused by the nonlinear and weak-stability characteristic of the random atomic spin gyroscope (ASG) drift, the hybrid random drift error model based on autoregressive (AR) and genetic programming (GP) + genetic algorithm (GA) technique is established. The time series of random ASG drift is taken as the study object. The time series of random ASG drift is acquired by analyzing and preprocessing the measured data of ASG. The linear section model is established based on AR technique. After that, the nonlinear section model is built based on GP technique and GA is used to optimize the coefficients of the mathematic expression acquired by GP in order to obtain a more accurate model. The simulation result indicates that this hybrid model can effectively reflect the characteristics of the ASG's random drift. The square error of the ASG's random drift is reduced by 92.40%. Comparing with the AR technique and the GP + GA technique, the random drift is reduced by 9.34% and 5.06%, respectively. The hybrid modeling method can effectively compensate the ASG's random drift and improve the stability of the system.
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Schryver, Jack; Nutaro, James; Shankar, Mallikarjun
2015-10-30
An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less
Gneiding, N.; Zhuromskyy, O.; Peschel, U.; Shamonina, E.
2014-10-28
Metamaterials are comprised of metallic structures with a strong response to incident electromagnetic radiation, like, for example, split ring resonators. The interaction of resonator ensembles with electromagnetic waves can be simulated with finite difference or finite elements algorithms, however, above a certain ensemble size simulations become inadmissibly time or memory consuming. Alternatively a circuit description of metamaterials, a well developed modelling tool at radio and microwave frequencies, allows to significantly increase the simulated ensemble size. This approach can be extended to the IR spectral range with an appropriate set of circuit element parameters accounting for physical effects such as electron inertia and finite conductivity. The model is verified by comparing the coupling coefficients with the ones obtained from the full wave numerical simulations, and used to optimize the nano-antenna design with improved radiation characteristics.
He, Yi; Scheraga, Harold A.; Liwo, Adam
2015-12-28
Coarse-grained models are useful tools to investigate the structural and thermodynamic properties of biomolecules. They are obtained by merging several atoms into one interaction site. Such simplified models try to capture as much as possible information of the original biomolecular system in all-atom representation but the resulting parameters of these coarse-grained force fields still need further optimization. In this paper, a force field optimization method, which is based on maximum-likelihood fitting of the simulated to the experimental conformational ensembles and least-squares fitting of the simulated to the experimental heat-capacity curves, is applied to optimize the Nucleic Acid united-RESidue 2-point (NARES-2P) model for coarse-grained simulations of nucleic acids recently developed in our laboratory. The optimized NARES-2P force field reproduces the structural and thermodynamic data of small DNA molecules much better than the original force field.
JACKSON VL
2011-08-31
The primary purpose of the tank mixing and sampling demonstration program is to mitigate the technical risks associated with the ability of the Hanford tank farm delivery and celtification systems to measure and deliver a uniformly mixed high-level waste (HLW) feed to the Waste Treatment and Immobilization Plant (WTP) Uniform feed to the WTP is a requirement of 24590-WTP-ICD-MG-01-019, ICD-19 - Interface Control Document for Waste Feed, although the exact definition of uniform is evolving in this context. Computational Fluid Dynamics (CFD) modeling has been used to assist in evaluating scaleup issues, study operational parameters, and predict mixing performance at full-scale.
Stamp, Jason E.; Eddy, John P.; Jensen, Richard P.; Munoz-Ramos, Karina
2016-01-01
Microgrids are a focus of localized energy production that support resiliency, security, local con- trol, and increased access to renewable resources (among other potential benefits). The Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS) Joint Capa- bility Technology Demonstration (JCTD) program between the Department of Defense (DOD), Department of Energy (DOE), and Department of Homeland Security (DHS) resulted in the pre- liminary design and deployment of three microgrids at military installations. This paper is focused on the analysis process and supporting software used to determine optimal designs for energy surety microgrids (ESMs) in the SPIDERS project. There are two key pieces of software, an ex- isting software application developed by Sandia National Laboratories (SNL) called Technology Management Optimization (TMO) and a new simulation developed for SPIDERS called the per- formance reliability model (PRM). TMO is a decision support tool that performs multi-objective optimization over a mixed discrete/continuous search space for which the performance measures are unrestricted in form. The PRM is able to statistically quantify the performance and reliability of a microgrid operating in islanded mode (disconnected from any utility power source). Together, these two software applications were used as part of the ESM process to generate the preliminary designs presented by SNL-led DOE team to the DOD. Acknowledgements Sandia National Laboratories and the SPIDERS technical team would like to acknowledge the following for help in the project: * Mike Hightower, who has been the key driving force for Energy Surety Microgrids * Juan Torres and Abbas Akhil, who developed the concept of microgrids for military instal- lations * Merrill Smith, U.S. Department of Energy SPIDERS Program Manager * Ross Roley and Rich Trundy from U.S. Pacific Command * Bill Waugaman and Bill Beary from U.S. Northern Command * Tarek Abdallah, Melanie
Dynamic Models for Wind Turbines and Wind Power Plants
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
... Each of these models includes representations of general turbine aerodynamics, the ... 9 1.1.2 Wind power integration and wind turbine modeling ......
Dynamic modelling of a double-pendulum gantry crane system incorporating payload
Ismail, R. M. T. Raja; Ahmad, M. A.; Ramli, M. S.; Ishak, R.; Zawawi, M. A.
2011-06-20
The natural sway of crane payloads is detrimental to safe and efficient operation. Under certain conditions, the problem is complicated when the payloads create a double pendulum effect. This paper presents dynamic modelling of a double-pendulum gantry crane system based on closed-form equations of motion. The Lagrangian method is used to derive the dynamic model of the system. A dynamic model of the system incorporating payload is developed and the effects of payload on the response of the system are discussed. Extensive results that validate the theoretical derivation are presented in the time and frequency domains.
Urniezius, Renaldas
2011-03-14
The principle of Maximum relative Entropy optimization was analyzed for dead reckoning localization of a rigid body when observation data of two attached accelerometers was collected. Model constraints were derived from the relationships between the sensors. The experiment's results confirmed that accelerometers each axis' noise can be successfully filtered utilizing dependency between channels and the dependency between time series data. Dependency between channels was used for a priori calculation, and a posteriori distribution was derived utilizing dependency between time series data. There was revisited data of autocalibration experiment by removing the initial assumption that instantaneous rotation axis of a rigid body was known. Performance results confirmed that such an approach could be used for online dead reckoning localization.
Lenhart, S. |; Protopopescu, V.
1994-09-01
The last years have witnessed a dramatic shift of the world`s military, political, and economic paradigm from a bi-polar competitive gridlock to a more fluid, multi-player environment. This change has necessarily been followed by a re-evaluation of the strategic thinking and by a reassessment of mutual positions, options, and decisions. The essential attributes of the new situation are modeled by a system of nonlinear evolution equations with competitive/cooperative interactions. The mathematical setting is quite general to accommodate models related to military confrontation, arms control, economic competition, political negotiations, etc. Irrespective of the specific details, all these situations share a common denominator, namely the presence of various players with different and often changing interests and goals. The interests, ranging from conflicting to consensual, are defined in a context of interactions between the players that vary from competitive to cooperative. Players with converging interests tend to build up cooperative coalitions while coalitions with diverging interests usually compete among themselves, but this is not an absolute requirement (namely, one may have groups with converging interests and competitive interactions, and vice-versa). Appurtenance to a coalition may change in time according to the shift in one`s perceptions, interests, or obligations. During the time evolution, the players try to modify their strategies as to best achieve their respective goals. An objective functional quantifying the rate of success (payoff) vs. effort (cost) measures the degree of goal attainment for all players involved, thus selecting an optimal strategy based on optimal controls. While the technical details may vary from problem to problem, the general approach described here establishes a standard framework for a host of concrete situations that may arise from tomorrow`s {open_quotes}next competition{close_quotes}.
A dynamic model for underbalanced drilling with coiled tubing
Rommetveit, R.; Vefring, E.H.; Wang, Z.; Bieseman, T.; Faure, A.M.
1995-11-01
A model for underbalanced drilling with coiled tubing has been developed which takes into account all important factors contributing to the process. This model is a unique tool to plan and execute underbalanced or near balance drilling operations. It is a transient, one-dimensional multi-phase flow model with the following components: Lift gas system model, multiphase hydraulics model, reservoir-wellbore interaction model, drilling model, models for multiphase fluids (lift gas, produced gas, mud, foam, produced gas, oil, water and cuttings). Various alternative geometries for gas injection are modeled as well as all important operations during underbalanced drilling with coiled tubing. The model as well as some simulation results for its use are presented in this paper.
A Full Demand Response Model in Co-Optimized Energy and
Liu, Guodong; Tomsovic, Kevin
2014-01-01
It has been widely accepted that demand response will play an important role in reliable and economic operation of future power systems and electricity markets. Demand response can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demand response in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demand response model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.
A mathematical liver model and its application to system optimization and texture analysis
Cargill, E.B.
1989-01-01
This dissertation presents realistic mathematical models of normal and diseased livers and a nuclear medicine camera. The mathematical model of a normal liver is developed by creating a data set of points on the surface of the liver and fitting it to a truncated set of spherical harmonics. We model the depth-dependent MTF of a scintillation camera taking into account the effects of Compton scatter, linear attenuation, intrinsic detector resolution, collimator resolution, and Poisson noise. The differential diagnosis on a liver scan includes normal, focal disease, and diffuse disease. Object classes of normal livers are created by randomly perturbing the spherical harmonic coefficients. Object classes of livers with focal disease are created by introducing cold ellipsoids within the liver volume. Cirrhotic livers are created by modelling the gross morphological changes, heterogenous uptake, and decreased overall uptake. Simulated nuclear medicine images are made by projecting livers through nuclear imaging systems. The combination of object classes of simulated livers and models of different imaging systems is applied to imaging-system design optimization in a psycho-physical study. Human observer performance on simulated liver images made on nine different systems is compared to the Hotelling trace criterion (HTC). The system with the best observer performance is judged to be the best system. The correlation between the human performance metric d{sub a} and the HTC for this study was 0.829, suggesting that the HTC may have value as a predictor of observer performance. Texture in a liver scan is related to the three-dimensional distribution of functional acini, which changes with disease. One measure of texture is the fractal dimension, related to the Fourier power spectrum. We measured the average radial power spectra of 70 liver scans.
Office of Legacy Management (LM)
Dynamic , and Static , Res.ponse of the Government Oil Shale Mine at ' , . , Rifle, ... AND STATIC RESPONSE 'OF THE GOVERNMENT OIL SHALE MINE A T RIFLE, COLORADO, T O THE, ...
Modelling vegetation dynamics at global scale due to climate changes: Comparison of two approaches
Belotelov, N.V.; Bogatyrev, B.G.; Lobanov, A.I.
1996-12-31
Climate changes will influence vegetation dynamics. One of the ways of forecasting these changes is the creation of mathematical models describing vegetation dynamics. Computer experiments can then be conducted under climate change scenarios. Two main approaches are used to create such models. The first approach is based on a bioclimatic dynamic approach. The second approach is based on modelling the main eco-physiological processes. The bioclimatic dynamic approach consists of hypotheses about vegetation types or biomes, and their interrelationships with climate. In the eco-physiological approach, a detailed description of the processes, such as production, mortality, plants migration and their competition is presented. A number of computer experiments has been conducted for several climatic scenario for Russia and the whole world. A qualitative comparison of the results with the results of an earlier bioclimatic model has been done.
A Mechanical Fluid-Dynamical Model For Ground Movements At Campi...
Mechanical Fluid-Dynamical Model For Ground Movements At Campi Flegrei Caldera Jump to: navigation, search OpenEI Reference LibraryAdd to library Journal Article: A Mechanical...
Dynamical Model for Meson Production off Nucleon and Application to Neutrino-Nucleus Reactions
Nakamura, Satoshi X.
2011-11-23
I explain the Sato-Lee (SL) model and its extension to the neutrino-induced pion production off the nucleon. Then I discuss applications of the SL model to incoherent and coherent pion productions in the neutrino-nucleus scattering. I mention a further extension of this approach with a dynamical coupled-channels model developed in Excited Baryon Analysis Center of JLab.
Optimization of the parameters of plasma liners with zero-dimensional models
Oreshkin, V. I.
2013-11-15
The efficiency of conversion of the energy stored in the capacitor bank of a high-current pulse generator into the kinetic energy of an imploding plasma liner is analyzed. The analysis is performed by using a model consisting of LC circuit equations and equations of motion of a cylindrical shell. It is shown that efficient energy conversion can be attained only with a low-inductance generator. The mode of an 'ideal' load is considered where the load current at the final stage of implosion is close to zero. The advantages of this mode are, first, high efficiency of energy conversion (80%) and, second, improved stability of the shell implosion. In addition, for inertial confinement fusion realized by the scheme of a Z pinch dynamic hohlraum, not one but several fusion targets can be placed in the cavity on the pinch axis due to the large length of the liner.
Optimization of Depletion Modeling and Simulation for the High Flux Isotope Reactor
Betzler, Benjamin R; Ade, Brian J; Chandler, David; Ilas, Germina; Sunny, Eva E
2015-01-01
Monte Carlo based depletion tools used for the high-fidelity modeling and simulation of the High Flux Isotope Reactor (HFIR) come at a great computational cost; finding sufficient approximations is necessary to make the use of these tools feasible. The optimization of the neutronics and depletion model for the HFIR is based on two factors: (i) the explicit representation of the involute fuel plates with sets of polyhedra and (ii) the treatment of depletion mixtures and control element position during depletion calculations. A very fine representation (i.e., more polyhedra in the involute plate approximation) does not significantly improve simulation accuracy. The recommended representation closely represents the physical plates and ensures sufficient fidelity in regions with high flux gradients. Including the fissile targets in the central flux trap of the reactor as depletion mixtures has the greatest effect on the calculated cycle length, while localized effects (e.g., the burnup of specific isotopes or the power distribution evolution over the cycle) are more noticeable consequences of including a critical control element search or depleting burnable absorbers outside the fuel region.
Wang, Shaobu; Lu, Shuai; Zhou, Ning; Lin, Guang; Elizondo, Marcelo A.; Pai, M. A.
2014-09-04
In interconnected power systems, dynamic model reduction can be applied on generators outside the area of interest to mitigate the computational cost with transient stability studies. This paper presents an approach of deriving the reduced dynamic model of the external area based on dynamic response measurements, which comprises of three steps, dynamic-feature extraction, attribution and reconstruction (DEAR). In the DEAR approach, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highest similarity, forming a suboptimal basis of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original external system. Network model is un-changed in the DEAR method. Tests on several IEEE standard systems show that the proposed method gets better reduction ratio and response errors than the traditional coherency aggregation methods.
Chapter 18: Understanding the Developing Cellulosic Biofuels Industry through Dynamic Modeling
Newes, E.; Inman, D.; Bush, B.
2011-01-01
The purpose of this chapter is to discuss a system dynamics model called the Biomass Scenario Model (BSM), which is being developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the burgeoning cellulosic biofuels industry in the United States. The model has also recently been expanded to include advanced conversion technologies and biofuels (i.e., conversion pathways that yield biomass-based gasoline, diesel, jet fuel, and butanol), but we focus on cellulosic ethanol conversion pathways here. The BSM uses a system dynamics modeling approach (Bush et al., 2008) built on the STELLA software platform.
Representation of Dormant and Active Microbial Dynamics for Ecosystem Modeling
Wang, Gangsheng; Mayes, Melanie; Gu, Lianhong; Schadt, Christopher Warren
2014-01-01
Dormancy is an essential strategy for microorganisms to cope with environmental stress. However, global ecosystem models typically ignore microbial dormancy, resulting in notable model uncertainties. To facilitate the consideration of dormancy in these large-scale models, we propose a new microbial physiology component that works for a wide range of substrate availabilities. This new model is based on microbial physiological states and the major parameters are the maximum specific growth and maintenance rates of active microbes and the ratio of dormant to active maintenance rates. A major improvement of our model over extant models is that it can explain the low active microbial fractions commonly observed in undisturbed soils. Our new model shows that the exponentially-increasing respiration from substrate-induced respiration experiments can only be used to determine the maximum specific growth rate and initial active microbial biomass, while the respiration data representing both exponentially-increasing and non-exponentially-increasing phases can robustly determine a range of key parameters including the initial total live biomass, initial active fraction, the maximum specific growth and maintenance rates, and the half-saturation constant. Our new model can be incorporated into existing ecosystem models to account for dormancy in microbially-driven processes and to provide improved estimates of microbial activities.
Applied Dynamic Analysis of the Global Economy (ADAGE) Model...
model capable of examining many types of economic, energy, environmental, climate change mitigation, and trade policies at the international, national, U.S. regional, and U.S....
Modeling icesheets dynamics: forward and inverse problems. (Conference...
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for Modeling and Scientific Computing MOX Seminar held September 9, 2013 in Milano, Italy. ... Country of Publication: United States Language: English Word Cloud More Like This Full ...
Dynamic Models for Wind Turbines and Wind Power Plants
Singh, M.; Santoso, S.
2011-10-01
The primary objective of this report was to develop universal manufacturer-independent wind turbine and wind power plant models that can be shared, used, and improved without any restrictions by project developers, manufacturers, and engineers. Manufacturer-specific models of wind turbines are favored for use in wind power interconnection studies. While they are detailed and accurate, their usages are limited to the terms of the non-disclosure agreement, thus stifling model sharing. The primary objective of the work proposed is to develop universal manufacturer-independent wind power plant models that can be shared, used, and improved without any restrictions by project developers, manufacturers, and engineers. Each of these models includes representations of general turbine aerodynamics, the mechanical drive-train, and the electrical characteristics of the generator and converter, as well as the control systems typically used. To determine how realistic model performance is, the performance of one of the models (doubly-fed induction generator model) has been validated using real-world wind power plant data. This work also documents selected applications of these models.
Dynamic Model Validation of PV Inverters Under Short-Circuit Conditions: Preprint
Muljadi, E.; Singh, M.; Bravo, R.; Gevorgian, V.
2013-03-01
Photovoltaic (PV) modules have dramatically decreased in price in the past few years, spurring the expansion of photovoltaic deployment. Residential and commercial rooftop installations are connected to the distribution network; large-scale installation PV power plants (PVPs) have benefited from tax incentives and the low cost of PV modules. As the level penetration of PV generation increases, the impact on power system reliability will also be greater. Utility power system planners must consider the role of PV generation in power systems more realistically by representing PV generation in dynamic stability analyses. Dynamic models of PV inverters have been developed in the positive sequence representation. NREL has developed a PV inverter dynamic model in PSCAD/EMTDC. This paper validates the dynamic model with an actual hardware bench test conducted by Southern California Edison's Distributed Energy Resources laboratory. All the fault combinations -- symmetrical and unsymmetrical -- were performed in the laboratory. We compare the simulation results with the bench test results.
Dynamics of pentaquarks in constituent quark models: recent developments
Stancu, Fl.
2005-06-14
Some recent developments in the study of light and heavy pentaquarks are reviewed, mainly within constituent quark models. Emphasis is made on results obtained in the flavor-spin model where a nearly ideal octet-antidecuplet mixing is obtained. The charmed antisextet is reviewed in the context of an SU(4) classification.
Liese, Eric; Zitney, Stephen E.
2013-01-01
Research in dynamic process simulation for integrated gasification combined cycles (IGCC) with carbon capture has been ongoing at the National Energy Technology Laboratory (NETL), culminating in a full operator training simulator (OTS) and immersive training simulator (ITS) for use in both operator training and research. A derivative work of the IGCC dynamic simulator has been a modification of the combined cycle section to more closely represent a typical natural gas fired combined cycle (NGCC). This paper describes the NGCC dynamic process model and highlights some of the simulator’s current capabilities through a particular startup and shutdown scenario.
Human Performance Modeling for Dynamic Human Reliability Analysis
Boring, Ronald Laurids; Joe, Jeffrey Clark; Mandelli, Diego
2015-08-01
Part of the U.S. Department of Energy’s (DOE’s) Light Water Reac- tor Sustainability (LWRS) Program, the Risk-Informed Safety Margin Charac- terization (RISMC) Pathway develops approaches to estimating and managing safety margins. RISMC simulations pair deterministic plant physics models with probabilistic risk models. As human interactions are an essential element of plant risk, it is necessary to integrate human actions into the RISMC risk framework. In this paper, we review simulation based and non simulation based human reliability analysis (HRA) methods. This paper summarizes the founda- tional information needed to develop a feasible approach to modeling human in- teractions in RISMC simulations.
Advanced Modeling of Renewable Energy Market Dynamics: May 2006
Evans, M.; Little, R.; Lloyd, K.; Malikov, G.; Passolt, G.; Arent, D.; Swezey, B.; Mosey, G.
2007-08-01
This report documents a year-long academic project, presenting selected techniques for analysis of market growth, penetration, and forecasting applicable to renewable energy technologies. Existing mathematical models were modified to incorporate the effects of fiscal policies and were evaluated using available data. The modifications were made based on research and classification of current mathematical models used for predicting market penetration. An analysis of the results was carried out, based on available data. MATLAB versions of existing and new models were developed for research and policy analysis.
Coupled Dynamic Modeling of Floating Wind Turbine Systems: Preprint
Wayman, E. N.; Sclavounos, P. D.; Butterfield, S.; Jonkman, J.; Musial, W.
2006-03-01
This article presents a collaborative research program that the Massachusetts Institute of Technology (MIT) and the National Renewable Energy Laboratory (NREL) have undertaken to develop innovative and cost-effective floating and mooring systems for offshore wind turbines in water depths of 10-200 m. Methods for the coupled structural, hydrodynamic, and aerodynamic analysis of floating wind turbine systems are presented in the frequency domain. This analysis was conducted by coupling the aerodynamics and structural dynamics code FAST [4] developed at NREL with the wave load and response simulation code WAMIT (Wave Analysis at MIT) [15] developed at MIT. Analysis tools were developed to consider coupled interactions between the wind turbine and the floating system. These include the gyroscopic loads of the wind turbine rotor on the tower and floater, the aerodynamic damping introduced by the wind turbine rotor, the hydrodynamic damping introduced by wave-body interactions, and the hydrodynamic forces caused by wave excitation. Analyses were conducted for two floater concepts coupled with the NREL 5-MW Offshore Baseline wind turbine in water depths of 10-200 m: the MIT/NREL Shallow Drafted Barge (SDB) and the MIT/NREL Tension Leg Platform (TLP). These concepts were chosen to represent two different methods of achieving stability to identify differences in performance and cost of the different stability methods. The static and dynamic analyses of these structures evaluate the systems' responses to wave excitation at a range of frequencies, the systems' natural frequencies, and the standard deviations of the systems' motions in each degree of freedom in various wind and wave environments. This article in various wind and wave environments. This article explores the effects of coupling the wind turbine with the floating platform, the effects of water depth, and the effects of wind speed on the systems' performance. An economic feasibility analysis of the two concepts
Modeling Dynamic Ductility: An Equation of State for Porous Metals...
Office of Scientific and Technical Information (OSTI)
with material elastic-plastic response in a 2D hydrocode, and then discuss the modeling of ... Country of Publication: United States Language: English Subject: 36 MATERIALS SCIENCE; 75 ...
Dynamics of holographic vacuum energy in the DGP model
Wu Xing; Zhu Zonghong; Cai Ronggen
2008-02-15
We consider the evolution of the vacuum energy in the Dvali-Gabadadze-Porrati (DGP) model according to the holographic principle under the assumption that the relation linking the IR and UV cutoffs still holds in this scenario. The model is studied when the IR cutoff is chosen to be the Hubble scale H{sup -1}, the particle horizon R{sub ph}, and the future event horizon R{sub eh}, respectively. The two branches of the DGP model are also taken into account. Through numerical analysis, we find that in the cases of H{sup -1} in the (+) branch and R{sub eh} in both branches, the vacuum energy can play the role of dark energy. Moreover, when considering the combination of the vacuum energy and the 5D gravity effect in both branches, the equation of state of the effective dark energy may cross -1, which may lead to the big rip singularity. Besides, we constrain the model with the Type Ia supernovae and baryon oscillation data and find that our model is consistent with current data within 1{sigma}, and that the observations prefer either a pure holographic dark energy or a pure DGP model.
Link, S.O.; Kickert, R.N.; Fayer, M.J.; Gee, G.W.
1993-06-01
This report describes the results of simulation models used to predict soil water storage dynamics at the Field Lysimeter Test Facility (FLTF) weighing lysimeters. The objectives of this research is to develop the capability to predict soil water storage dynamics with plants in support of water infiltration control studies for the Hanford Permanent Isolation Barrier Development Program. It is important to gain confidence in one`s ability to simulate soil water dynamics over long time periods to assess the barrier`s ability to prevent drainage. Two models were compared for their ability to simulate soil water storage dynamics with and without plants in weighing lysimeters, the soil water infiltration and movement (SWIM) and the simulation of production and utilization of rangelands (SPUR-91) models. These models adequately simulated soil water storage dynamics for the weighing lysimeters. The range of root mean square error values for the two models was 7.0 to 19.8. This compares well with the range reported by Fayer et al. (1992) for the bare soil data sets of 8.1 to 22.1. Future research will test the predictive capability of these models for longer term lysimeter data sets and for historical data sets collected in various plant community types.
Jackson, Bret; Nattino, Francesco; Kroes, Geert-Jan
2014-08-07
The dissociative chemisorption of methane on metal surfaces is of great practical and fundamental importance. Not only is it the rate-limiting step in the steam reforming of natural gas, the reaction exhibits interesting mode-selective behavior and a strong dependence on the temperature of the metal. We present a quantum model for this reaction on Ni(100) and Ni(111) surfaces based on the reaction path Hamiltonian. The dissociative sticking probabilities computed using this model agree well with available experimental data with regard to variation with incident energy, substrate temperature, and the vibrational state of the incident molecule. We significantly expand the vibrational basis set relative to earlier studies, which allows reaction probabilities to be calculated for doubly excited initial vibrational states, though it does not lead to appreciable changes in the reaction probabilities for singly excited initial states. Sudden models used to treat the center of mass motion parallel to the surface are compared with results from ab initio molecular dynamics and found to be reasonable. Similar comparisons for molecular rotation suggest that our rotationally adiabatic model is incorrect, and that sudden behavior is closer to reality. Such a model is proposed and tested. A model for predicting mode-selective behavior is tested, with mixed results, though we find it is consistent with experimental studies of normal vs. total (kinetic) energy scaling. Models for energy transfer into lattice vibrations are also examined.
Data Driven Approach for High Resolution Population Distribution and Dynamics Models
Bhaduri, Budhendra L; Bright, Eddie A; Rose, Amy N; Liu, Cheng; Urban, Marie L; Stewart, Robert N
2014-01-01
High resolution population distribution data are vital for successfully addressing critical issues ranging from energy and socio-environmental research to public health to human security. Commonly available population data from Census is constrained both in space and time and does not capture population dynamics as functions of space and time. This imposes a significant limitation on the fidelity of event-based simulation models with sensitive space-time resolution. This paper describes ongoing development of high-resolution population distribution and dynamics models, at Oak Ridge National Laboratory, through spatial data integration and modeling with behavioral or activity-based mobility datasets for representing temporal dynamics of population. The model is resolved at 1 km resolution globally and describes the U.S. population for nighttime and daytime at 90m. Integration of such population data provides the opportunity to develop simulations and applications in critical infrastructure management from local to global scales.
Dynamic (G2) Model Design Document, 24590-WTP-MDD-PR-01-002, Rev. 12
Deng, Yueying; Kruger, Albert A.
2013-12-16
The Hanford Tank Waste Treatment and Immobilization Plant (WTP) Statement of Work (Department of Energy Contract DE-AC27-01RV14136, Section C) requires the contractor to develop and use process models for flowsheet analyses and pre-operational planning assessments. The Dynamic (G2) Flowsheet is a discrete-time process model that enables the project to evaluate impacts to throughput from eventdriven activities such as pumping, sampling, storage, recycle, separation, and chemical reactions. The model is developed by the Process Engineering (PE) department, and is based on the Flowsheet Bases, Assumptions, and Requirements Document (24590-WTP-RPT-PT-02-005), commonly called the BARD. The terminologies of Dynamic (G2) Flowsheet and Dynamic (G2) Model are interchangeable in this document. The foundation of this model is a dynamic material balance governed by prescribed initial conditions, boundary conditions, and operating logic. The dynamic material balance is achieved by tracking the storage and material flows within the plant as time increments. The initial conditions include a feed vector that represents the waste compositions and delivery sequence of the Tank Farm batches, and volumes and concentrations of solutions in process equipment before startup. The boundary conditions are the physical limits of the flowsheet design, such as piping, volumes, flowrates, operation efficiencies, and physical and chemical environments that impact separations, phase equilibriums, and reaction extents. The operating logic represents the rules and strategies of running the plant.
Modal test optimization using VETO (Virtual Environment for Test Optimization)
Klenke, S.E.; Reese, G.M.; Schoof, L.A.; Shierling, C.
1996-01-01
We present a software environment integrating analysis and test-based models to support optimal modal test design through a Virtual Environment for Test Optimization (VETO). A goal in developing this software tool is to provide test and analysis organizations with a capability of mathematically simulating the complete test environment in software. Derived models of test equipment, instrumentation and hardware can be combined within the VETO to provide the user with a unique analysis and visualization capability to evaluate new and existing test methods. The VETO assists analysis and test engineers in maximizing the value of each modal test. It is particularly advantageous for structural dynamics model reconciliation applications. The VETO enables an engineer to interact with a finite element model of a test object to optimally place sensors and exciters and to investigate the selection of data acquisition parameters needed to conduct a complete modal survey. Additionally, the user can evaluate the use of different types of instrumentation such as filters, amplifiers and transducers for which models are available in the VETO. The dynamic response of most of the virtual instruments (including the device under test) is modeled in the state space domain. Design of modal excitation levels and appropriate test instrumentation are facilitated by the VETO`s ability to simulate such features as unmeasured external inputs, A/D quantization effects, and electronic noise. Measures of the quality of the experimental design, including the Modal Assurance Criterion, and the Normal Mode Indicator Function are available.
Wang, Gangsheng; Post, Wilfred M; Mayes, Melanie
2013-01-01
We developed a Microbial-ENzyme-mediated Decomposition (MEND) model, based on the Michaelis-Menten kinetics, that describes the dynamics of physically defined pools of soil organic matter (SOC). These include particulate, mineral-associated, dissolved organic matter (POC, MOC, and DOC, respectively), microbial biomass, and associated exoenzymes. The ranges and/or distributions of parameters were determined by both analytical steady-state and dynamic analyses with SOC data from the literature. We used an improved multi-objective parameter sensitivity analysis (MOPSA) to identify the most important parameters for the full model: maintenance of microbial biomass, turnover and synthesis of enzymes, and carbon use efficiency (CUE). The model predicted an increase of 2 C (baseline temperature =12 C) caused the pools of POC-Cellulose, MOC, and total SOC to increase with dynamic CUE and decrease with constant CUE, as indicated by the 50% confidence intervals. Regardless of dynamic or constant CUE, the pool sizes of POC, MOC, and total SOC varied from 8% to 8% under +2 C. The scenario analysis using a single parameter set indicates that higher temperature with dynamic CUE might result in greater net increases in both POC-Cellulose and MOC pools. Different dynamics of various SOC pools reflected the catalytic functions of specific enzymes targeting specific substrates and the interactions between microbes, enzymes, and SOC. With the feasible parameter values estimated in this study, models incorporating fundamental principles of microbial-enzyme dynamics can lead to simulation results qualitatively different from traditional models with fast/slow/passive pools.
Ramamurthy, Byravamurthy
2014-05-05
In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published several conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.
Numerical research of the optimal control problem in the semi-Markov inventory model
Gorshenin, Andrey K.
2015-03-10
This paper is devoted to the numerical simulation of stochastic system for inventory management products using controlled semi-Markov process. The results of a special software for the systems research and finding the optimal control are presented.
Multiple dynamical resonances in a discrete neuronal model
Jiang Yu
2005-05-01
The conditions for the occurrence of different multiple resonances in an excitable neuron model are analyzed numerically. It is shown that the excitable system may display both stochastic and coherence resonance, in response to periodic stimuli in the presence of different intensities of additive and parametric noises. It is found that double coherence resonances may take place in the low-amplitude oscillation regimes, and coherence resonance may persists even in the weak oscillatory regimes for control parameters slightly larger than the Hopf bifurcation point, where the system is in the incipient stage of large-amplitude excitation regime.
Modeling aspects of the dynamic response of heterogeneous materials
Ionita, Axinte; Clements, Brad; Mas, Eric
2009-01-01
In numerical simulations of engineering applications involving heterogeneous materials capturing the local response coming from a distribution of heterogeneities can lead to a very large model thus making simulations difficult. The use of homogenization techniques can reduce the size of the problem but will miss the local effects. Homogenization can also be difficult if the constituents obey different types of constitutive laws. Additional complications arise if inelastic deformation. In such cases a two-scale approach is prefened and tills work addresses these issues in the context of a two-scale Finite Element Method (FEM). Examples of using two-scale FEM approaches are presented.
Advanced Neutron Source Dynamic Model (ANSDM) code description and user guide
March-Leuba, J.
1995-08-01
A mathematical model is designed that simulates the dynamic behavior of the Advanced Neutron Source (ANS) reactor. Its main objective is to model important characteristics of the ANS systems as they are being designed, updated, and employed; its primary design goal, to aid in the development of safety and control features. During the simulations the model is also found to aid in making design decisions for thermal-hydraulic systems. Model components, empirical correlations, and model parameters are discussed; sample procedures are also given. Modifications are cited, and significant development and application efforts are noted focusing on examination of instrumentation required during and after accidents to ensure adequate monitoring during transient conditions.
Update on Small Modular Reactors Dynamics System Modeling Tool -- Molten Salt Cooled Architecture
Hale, Richard Edward; Cetiner, Sacit M.; Fugate, David L.; Qualls, A L.; Borum, Robert C.; Chaleff, Ethan S.; Rogerson, Doug W.; Batteh, John J.; Tiller, Michael M.
2014-08-01
The Small Modular Reactor (SMR) Dynamic System Modeling Tool project is in the third year of development. The project is designed to support collaborative modeling and study of various advanced SMR (non-light water cooled) concepts, including the use of multiple coupled reactors at a single site. The objective of the project is to provide a common simulation environment and baseline modeling resources to facilitate rapid development of dynamic advanced reactor SMR models, ensure consistency among research products within the Instrumentation, Controls, and Human-Machine Interface (ICHMI) technical area, and leverage cross-cutting capabilities while minimizing duplication of effort. The combined simulation environment and suite of models are identified as the Modular Dynamic SIMulation (MoDSIM) tool. The critical elements of this effort include (1) defining a standardized, common simulation environment that can be applied throughout the program, (2) developing a library of baseline component modules that can be assembled into full plant models using existing geometry and thermal-hydraulic data, (3) defining modeling conventions for interconnecting component models, and (4) establishing user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.
Smith, Kyle K. G.; Poulsen, Jens Aage Nyman, Gunnar; Rossky, Peter J.
2015-06-28
We develop two classes of quasi-classical dynamics that are shown to conserve the initial quantum ensemble when used in combination with the Feynman-Kleinert approximation of the density operator. These dynamics are used to improve the Feynman-Kleinert implementation of the classical Wigner approximation for the evaluation of quantum time correlation functions known as Feynman-Kleinert linearized path-integral. As shown, both classes of dynamics are able to recover the exact classical and high temperature limits of the quantum time correlation function, while a subset is able to recover the exact harmonic limit. A comparison of the approximate quantum time correlation functions obtained from both classes of dynamics is made with the exact results for the challenging model problems of the quartic and double-well potentials. It is found that these dynamics provide a great improvement over the classical Wigner approximation, in which purely classical dynamics are used. In a special case, our first method becomes identical to centroid molecular dynamics.
Melin, Alexander M.; Kisner, Roger A.; Fugate, David L.
2013-10-01
This report documents the current status of the modeling, control design, and embedded control research for the magnetic bearing canned rotor pump being used as a demonstration platform for deeply integrating instrumentation and controls (I{\\&}C) into nuclear power plant components. This pump is a highly inter-connected thermo/electro/mechanical system that requires an active control system to operate. Magnetic bearings are inherently unstable system and without active, moment by moment control, the rotor would contact fixed surfaces in the pump causing physical damage. This report details the modeling of the pump rotordynamics, fluid forces, electromagnetic properties of the protective cans, active magnetic bearings, power electronics, and interactions between different dynamical models. The system stability of the unforced and controlled rotor are investigated analytically. Additionally, controllers are designed using proportional derivative (PD) control, proportional integral derivative (PID) control, voltage control, and linear quadratic regulator (LQR) control. Finally, a design optimization problem that joins the electrical, mechanical, magnetic, and control system design into one problem to balance the opposing needs of various design criteria using the embedded system approach is presented.
Modeling ramp compression experiments using large-scale molecular dynamics simulation.
Mattsson, Thomas Kjell Rene; Desjarlais, Michael Paul; Grest, Gary Stephen; Templeton, Jeremy Alan; Thompson, Aidan Patrick; Jones, Reese E.; Zimmerman, Jonathan A.; Baskes, Michael I.; Winey, J. Michael; Gupta, Yogendra Mohan; Lane, J. Matthew D.; Ditmire, Todd; Quevedo, Hernan J.
2011-10-01
Molecular dynamics simulation (MD) is an invaluable tool for studying problems sensitive to atomscale physics such as structural transitions, discontinuous interfaces, non-equilibrium dynamics, and elastic-plastic deformation. In order to apply this method to modeling of ramp-compression experiments, several challenges must be overcome: accuracy of interatomic potentials, length- and time-scales, and extraction of continuum quantities. We have completed a 3 year LDRD project with the goal of developing molecular dynamics simulation capabilities for modeling the response of materials to ramp compression. The techniques we have developed fall in to three categories (i) molecular dynamics methods (ii) interatomic potentials (iii) calculation of continuum variables. Highlights include the development of an accurate interatomic potential describing shock-melting of Beryllium, a scaling technique for modeling slow ramp compression experiments using fast ramp MD simulations, and a technique for extracting plastic strain from MD simulations. All of these methods have been implemented in Sandia's LAMMPS MD code, ensuring their widespread availability to dynamic materials research at Sandia and elsewhere.
Optimal Compensation with Hidden Action and Lump-Sum Payment in a Continuous-Time Model
Cvitanic, Jaksa Wan, Xuhu Zhang Jianfeng
2009-02-15
We consider a problem of finding optimal contracts in continuous time, when the agent's actions are unobservable by the principal, who pays the agent with a one-time payoff at the end of the contract. We fully solve the case of quadratic cost and separable utility, for general utility functions. The optimal contract is, in general, a nonlinear function of the final outcome only, while in the previously solved cases, for exponential and linear utility functions, the optimal contract is linear in the final output value. In a specific example we compute, the first-best principal's utility is infinite, while it becomes finite with hidden action, which is increasing in value of the output. In the second part of the paper we formulate a general mathematical theory for the problem. We apply the stochastic maximum principle to give necessary conditions for optimal contracts. Sufficient conditions are hard to establish, but we suggest a way to check sufficiency using non-convex optimization.
Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)
Optimizing Performance Optimizing Performance Storage Optimization Optimizing the sizes of the files you store in HPSS and minimizing the number of tapes they are on will lead to...
Corradini, D.; Rovere, M.; Gallo, P.
2015-09-21
In a previous study [Gallo et al., Nat. Commun. 5, 5806 (2014)], we have shown an important connection between thermodynamic and dynamical properties of water in the supercritical region. In particular, by analyzing the experimental viscosity and the diffusion coefficient obtained in simulations performed using the TIP4P/2005 model, we have found that the line of response function maxima in the one phase region, the Widom line, is connected to a crossover from a liquid-like to a gas-like behavior of the transport coefficients. This is in agreement with recent experiments concerning the dynamics of supercritical simple fluids. We here show how different popular water models (TIP4P/2005, TIP4P, SPC/E, TIP5P, and TIP3P) perform in reproducing thermodynamic and dynamic experimental properties in the supercritical region. In particular, the comparison with experiments shows that all the analyzed models are able to qualitatively predict the dynamical crossover from a liquid-like to a gas-like behavior upon crossing the Widom line. Some of the models perform better in reproducing the pressure-temperature slope of the Widom line of supercritical water once a rigid shift of the phase diagram is applied to bring the critical points to coincide with the experimental ones.
Dynamical Coupled-Channel Model of Meson Production Reactions in the Nucleon Resonance Region
T.-S. H. Lee; A. Matsuyama; T. Sato
2006-11-15
A dynamical coupled-channel model is presented for investigating the nucleon resonances (N*) in the meson production reactions induced by pions and photons. Our objective is to extract the N* parameters and to investigate the meson production reaction mechanisms for mapping out the quark-gluon substructure of N* from the data. The model is based on an energy-independent Hamiltonian which is derived from a set of Lagrangians by using a unitary transformation method.
Tan, Sirui; Huang, Lianjie
2014-11-01
For modeling scalar-wave propagation in geophysical problems using finite-difference schemes, optimizing the coefficients of the finite-difference operators can reduce numerical dispersion. Most optimized finite-difference schemes for modeling seismic-wave propagation suppress only spatial but not temporal dispersion errors. We develop a novel optimized finite-difference scheme for numerical scalar-wave modeling to control dispersion errors not only in space but also in time. Our optimized scheme is based on a new stencil that contains a few more grid points than the standard stencil. We design an objective function for minimizing relative errors of phase velocities of waves propagating in all directions within a given range of wavenumbers. Dispersion analysis and numerical examples demonstrate that our optimized finite-difference scheme is computationally up to 2.5 times faster than the optimized schemes using the standard stencil to achieve the similar modeling accuracy for a given 2D or 3D problem. Compared with the high-order finite-difference scheme using the same new stencil, our optimized scheme reduces 50 percent of the computational cost to achieve the similar modeling accuracy. This new optimized finite-difference scheme is particularly useful for large-scale 3D scalar-wave modeling and inversion.
Hart, W.E.; Istrail, S. [Sandia National Labs., Albuquerque, NM (United States). Algorithms and Discrete Mathematics Dept.
1996-08-09
This paper considers the protein structure prediction problem for lattice and off-lattice protein folding models that explicitly represent side chains. Lattice models of proteins have proven extremely useful tools for reasoning about protein folding in unrestricted continuous space through analogy. This paper provides the first illustration of how rigorous algorithmic analyses of lattice models can lead to rigorous algorithmic analyses of off-lattice models. The authors consider two side chain models: a lattice model that generalizes the HP model (Dill 85) to explicitly represent side chains on the cubic lattice, and a new off-lattice model, the HP Tangent Spheres Side Chain model (HP-TSSC), that generalizes this model further by representing the backbone and side chains of proteins with tangent spheres. They describe algorithms for both of these models with mathematically guaranteed error bounds. In particular, the authors describe a linear time performance guaranteed approximation algorithm for the HP side chain model that constructs conformations whose energy is better than 865 of optimal in a face centered cubic lattice, and they demonstrate how this provides a 70% performance guarantee for the HP-TSSC model. This is the first algorithm in the literature for off-lattice protein structure prediction that has a rigorous performance guarantee. The analysis of the HP-TSSC model builds off of the work of Dancik and Hannenhalli who have developed a 16/30 approximation algorithm for the HP model on the hexagonal close packed lattice. Further, the analysis provides a mathematical methodology for transferring performance guarantees on lattices to off-lattice models. These results partially answer the open question of Karplus et al. concerning the complexity of protein folding models that include side chains.
Experimental estimation of dynamic plastic bending moments by plastic hinge models
Sogo, T.; Ujihashi, S.; Matsumoto, H.; Adachi, T.
1995-12-31
In the present paper, the experimental estimation of dynamic plastic bending moments for metallic materials is investigated. The three-point bending, test under impact and static loads is applied to aluminum alloy (JIS A6063S) and mild steel (JIS SS400). It is confirmed that tile dynamic bending deformations in three-point bending test can be modeled as a plastic hinge, tile experimental results show that the consumed energies of the specimens are proportional to the bending angles. The ratio of the consumed energy to the bending angle is approximately equal to the plastic bending moment. In the case of aluminum alloy, the dynamic plastic bending moments for the different average bending angular velocities coincide with the static plastic bending moments. On the other hand, in the case of mild steel, the dynamic plastic bending moments are proportional to the average bending angular velocities. As a result, we confirm that the present method based on the plastic hinge model and the consumed energy is efficient for determining tile dynamic plastic bending moment.
Technical Review of the CENWP Computational Fluid Dynamics Model of the John Day Dam Forebay
Rakowski, Cynthia L.; Serkowski, John A.; Richmond, Marshall C.
2010-12-01
The US Army Corps of Engineers Portland District (CENWP) has developed a computational fluid dynamics (CFD) model of the John Day forebay on the Columbia River to aid in the development and design of alternatives to improve juvenile salmon passage at the John Day Project. At the request of CENWP, Pacific Northwest National Laboratory (PNNL) Hydrology Group has conducted a technical review of CENWP's CFD model run in CFD solver software, STAR-CD. PNNL has extensive experience developing and applying 3D CFD models run in STAR-CD for Columbia River hydroelectric projects. The John Day forebay model developed by CENWP is adequately configured and validated. The model is ready for use simulating forebay hydraulics for structural and operational alternatives. The approach and method are sound, however CENWP has identified some improvements that need to be made for future models and for modifications to this existing model.
DYNAMIC MODELING STRATEGY FOR FLOW REGIME TRANSITION IN GAS-LIQUID TWO-PHASE FLOWS
X. Wang; X. Sun; H. Zhao
2011-09-01
In modeling gas-liquid two-phase flows, the concept of flow regime has been used to characterize the global interfacial structure of the flows. Nearly all constitutive relations that provide closures to the interfacial transfers in two-phase flow models, such as the two-fluid model, are often flow regime dependent. Currently, the determination of the flow regimes is primarily based on flow regime maps or transition criteria, which are developed for steady-state, fully-developed flows and widely applied in nuclear reactor system safety analysis codes, such as RELAP5. As two-phase flows are observed to be dynamic in nature (fully-developed two-phase flows generally do not exist in real applications), it is of importance to model the flow regime transition dynamically for more accurate predictions of two-phase flows. The present work aims to develop a dynamic modeling strategy for determining flow regimes in gas-liquid two-phase flows through the introduction of interfacial area transport equations (IATEs) within the framework of a two-fluid model. The IATE is a transport equation that models the interfacial area concentration by considering the creation and destruction of the interfacial area, such as the fluid particle (bubble or liquid droplet) disintegration, boiling and evaporation; and fluid particle coalescence and condensation, respectively. For the flow regimes beyond bubbly flows, a two-group IATE has been proposed, in which bubbles are divided into two groups based on their size and shape (which are correlated), namely small bubbles and large bubbles. A preliminary approach to dynamically identifying the flow regimes is provided, in which discriminators are based on the predicted information, such as the void fraction and interfacial area concentration of small bubble and large bubble groups. This method is expected to be applied to computer codes to improve their predictive capabilities of gas-liquid two-phase flows, in particular for the applications in
Dynamic Modeling Strategy for Flow Regime Transition in Gas-Liquid Two-Phase Flows
Xia Wang; Xiaodong Sun; Benjamin Doup; Haihua Zhao
2012-12-01
In modeling gas-liquid two-phase flows, the concept of flow regimes has been widely used to characterize the global interfacial structure of the flows. Nearly all constitutive relations that provide closures to the interfacial transfers in two-phase flow models, such as the two-fluid model, are flow regime dependent. Current nuclear reactor safety analysis codes, such as RELAP5, classify flow regimes using flow regime maps or transition criteria that were developed for steady-state, fully-developed flows. As twophase flows are dynamic in nature, it is important to model the flow regime transitions dynamically to more accurately predict the two-phase flows. The present work aims to develop a dynamic modeling strategy to determine flow regimes in gas-liquid two-phase flows through introduction of interfacial area transport equations (IATEs) within the framework of a two-fluid model. The IATE is a transport equation that models the interfacial area concentration by considering the creation of the interfacial area, fluid particle (bubble or liquid droplet) disintegration, boiling and evaporation, and the destruction of the interfacial area, fluid particle coalescence and condensation. For flow regimes beyond bubbly flows, a two-group IATE has been proposed, in which bubbles are divided into two groups based on their size and shapes, namely group-1 and group-2 bubbles. A preliminary approach to dynamically identify the flow regimes is discussed, in which discriminator s are based on the predicted information, such as the void fraction and interfacial area concentration. The flow regime predicted with this method shows good agreement with the experimental observations.
Environmental patterns from free trade: Implications from dynamic NAFTA models of Mexico
Gale, L.R.
1994-12-31
Studies of the economic impact on Mexico from joining the North American Free Trade Agreement (NAFTA) point to significant dynamic gains from trade. Few studies, however, have effectively related these changes in economic variables to changes in environmental variables. Using sector-share relationships and projections of income growth from dynamic computable general equilibrium models of Mexico, several possible time paths for carbon dioxide emissions are derived. Various scenarios of trade and investment liberalization and increased fuel efficiency under NAFTA result in simulated pollution paths of carbon dioxide that show a reduction in not only the amount of emissions but also in rate of growth of emissions.
On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Zhang, S.; Wang, M.; Ghan, S. J.; Ding, A.; Wang, H.; Zhang, K.; Neubauer, D.; Lohmann, U.; Ferrachat, S.; Takeamura, T.; et al
2015-09-02
Aerosol-cloud interactions continue to constitute a major source of uncertainty for the estimate of climate radiative forcing. The variation of aerosol indirect effects (AIE) in climate models is investigated across different dynamical regimes, determined by monthly mean 500 hPa vertical pressure velocity (?500), lower-tropospheric stability (LTS) and large-scale surface precipitation rate derived from several global climate models (GCMs), with a focus on liquid water path (LWP) response to cloud condensation nuclei (CCN) concentrations. The LWP sensitivity to aerosol perturbation within dynamic regimes is found to exhibit a large spread among these GCMs. It is in regimes of strong large-scale ascendmore(?500 ?1) and low clouds (stratocumulus and trade wind cumulus) where the models differ most. Shortwave aerosol indirect forcing is also found to differ significantly among different regimes. Shortwave aerosol indirect forcing in ascending regimes is as large as that in stratocumulus regimes, which indicates that regimes with strong large-scale ascend are as important as stratocumulus regimes in studying AIE. It is further shown that shortwave aerosol indirect forcing over regions with high monthly large-scale surface precipitation rate (> 0.1 mm d?1) contributes the most to the total aerosol indirect forcing (from 64 to nearly 100 %). Results show that the uncertainty in AIE is even larger within specific dynamical regimes than that globally, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.less
Computational fluid dynamics modeling of two-phase flow in a BWR fuel assembly. Final CRADA Report.
Tentner, A.; Nuclear Engineering Division
2009-10-13
A direct numerical simulation capability for two-phase flows with heat transfer in complex geometries can considerably reduce the hardware development cycle, facilitate the optimization and reduce the costs of testing of various industrial facilities, such as nuclear power plants, steam generators, steam condensers, liquid cooling systems, heat exchangers, distillers, and boilers. Specifically, the phenomena occurring in a two-phase coolant flow in a BWR (Boiling Water Reactor) fuel assembly include coolant phase changes and multiple flow regimes which directly influence the coolant interaction with fuel assembly and, ultimately, the reactor performance. Traditionally, the best analysis tools for this purpose of two-phase flow phenomena inside the BWR fuel assembly have been the sub-channel codes. However, the resolution of these codes is too coarse for analyzing the detailed intra-assembly flow patterns, such as flow around a spacer element. Advanced CFD (Computational Fluid Dynamics) codes provide a potential for detailed 3D simulations of coolant flow inside a fuel assembly, including flow around a spacer element using more fundamental physical models of flow regimes and phase interactions than sub-channel codes. Such models can extend the code applicability to a wider range of situations, which is highly important for increasing the efficiency and to prevent accidents.
Comparison of bifurcation dynamics of turbulent transport models for the L-H transition
Weymiens, W. Blank, H. J. de; Hogeweij, G. M. D.; Paquay, S.
2014-05-15
In more than three decades, a large amount of models and mechanisms have been proposed to describe a very beneficial feature of magnetically confined fusion plasmas: the L-H transition. Bifurcation theory can be used to compare these different models based on their dynamical transition structure. In this paper, we employ bifurcation theory to distinguish two fundamentally different descriptions of the interaction between turbulence levels and sheared flows. The analytic bifurcation analysis characterises the parameter space structure of the transition dynamics. Herewith, in these models three dynamically different types of transitions are characterised, sharp transitions, oscillatory transitions, and smooth transitions. One of the two models has a very robust transition structure and is therefore likely to be more accurate for such a robust phenomenon as the L-H transition. The other model needs more fine-tuning to get non-oscillatory transitions. These conclusions from the analytic bifurcation analysis are confirmed by dedicated numerical simulations, with the newly developed code Bifurcator.
Using a dynamic point-source percolation model to simulate bubble growth.
Zimmerman, Jonathan A.; Zeigler, David A.; Cowgill, Donald F.
2004-05-01
Accurate modeling of nucleation, growth and clustering of helium bubbles within metal tritide alloys is of high scientific and technological importance. Of interest is the ability to predict both the distribution of these bubbles and the manner in which these bubbles interact at a critical concentration of helium-to-metal atoms to produce an accelerated release of helium gas. One technique that has been used in the past to model these materials, and again revisited in this research, is percolation theory. Previous efforts have used classical percolation theory to qualitatively and quantitatively model the behavior of interstitial helium atoms in a metal tritide lattice; however, higher fidelity models are needed to predict the distribution of helium bubbles and include features that capture the underlying physical mechanisms present in these materials. In this work, we enhance classical percolation theory by developing the dynamic point-source percolation model. This model alters the traditionally binary character of site occupation probabilities by enabling them to vary depending on proximity to existing occupied sites, i.e. nucleated bubbles. This revised model produces characteristics for one and two dimensional systems that are extremely comparable with measurements from three dimensional physical samples. Future directions for continued development of the dynamic model are also outlined.
MULTI-SCALE MODELING AND APPROXIMATION ASSISTED OPTIMIZATION OF BARE TUBE HEAT EXCHANGERS
Bacellar, Daniel; Ling, Jiazhen; Aute, Vikrant; Radermacher, Reinhard; Abdelaziz, Omar
2014-01-01
Air-to-refrigerant heat exchangers are very common in air-conditioning, heat pump and refrigeration applications. In these heat exchangers, there is a great benefit in terms of size, weight, refrigerant charge and heat transfer coefficient, by moving from conventional channel sizes (~ 9mm) to smaller channel sizes (< 5mm). This work investigates new designs for air-to-refrigerant heat exchangers with tube outer diameter ranging from 0.5 to 2.0mm. The goal of this research is to develop and optimize the design of these heat exchangers and compare their performance with existing state of the art designs. The air-side performance of various tube bundle configurations are analyzed using a Parallel Parameterized CFD (PPCFD) technique. PPCFD allows for fast-parametric CFD analyses of various geometries with topology change. Approximation techniques drastically reduce the number of CFD evaluations required during optimization. Maximum Entropy Design method is used for sampling and Kriging method is used for metamodeling. Metamodels are developed for the air-side heat transfer coefficients and pressure drop as a function of tube-bundle dimensions and air velocity. The metamodels are then integrated with an air-to-refrigerant heat exchanger design code. This integration allows a multi-scale analysis of air-side performance heat exchangers including air-to-refrigerant heat transfer and phase change. Overall optimization is carried out using a multi-objective genetic algorithm. The optimal designs found can exhibit 50 percent size reduction, 75 percent decrease in air side pressure drop and doubled air heat transfer coefficients compared to a high performance compact micro channel heat exchanger with same capacity and flow rates.
Li, Ben; He, Feng; Ouyang, Jiting; Duan, Xiaoxi
2015-12-15
Simulation work is very important for understanding the formation of self-organized discharge patterns. Previous works have witnessed different models derived from other systems for simulation of discharge pattern, but most of these models are complicated and time-consuming. In this paper, we introduce a convenient phenomenological dynamic model based on the basic dynamic process of glow discharge and the voltage transfer curve (VTC) to study the dielectric barrier glow discharge (DBGD) pattern. VTC is an important characteristic of DBGD, which plots the change of wall voltage after a discharge as a function of the initial total gap voltage. In the modeling, the combined effect of the discharge conditions is included in VTC, and the activation-inhibition effect is expressed by a spatial interaction term. Besides, the model reduces the dimensionality of the system by just considering the integration effect of current flow. All these greatly facilitate the construction of this model. Numerical simulations turn out to be in good accordance with our previous fluid modeling and experimental result.