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
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
U.S. Department of Energy (DOE) all 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
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
U.S. Department of Energy (DOE) all 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
U.S. Department of Energy (DOE) all 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
Open Energy Information (Open El) [EERE & EIA]
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
Open Energy Information (Open El) [EERE & EIA]
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.
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
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
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).
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 |
U.S. Department of Energy (DOE) all 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
Alternative Fuels and Advanced Vehicles Data Center
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
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
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
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
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.
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.
U.S. Department of Energy (DOE) all 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
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...
U.S. Department of Energy (DOE) all 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
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.
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
U.S. Department of Energy (DOE) all 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...
Open Energy Information (Open El) [EERE & EIA]
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...
Open Energy Information (Open El) [EERE & EIA]
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...
Office of Scientific and Technical Information (OSTI)
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.
U.S. Department of Energy (DOE) all 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
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.
Modeling dynamic stall on wind turbine blades under rotationally augmented flow fields
Guntur, S.; Schreck, S.; Sorensen, N. N.; Bergami, L.
2015-04-22
It is well known that airfoils under unsteady flow conditions with a periodically varying angle of attack exhibit aerodynamic characteristics different from those under steady flow conditions, a phenomenon commonly known as dynamic stall. It is also well known that the steady aerodynamic characteristics of airfoils in the inboard region of a rotating blade differ from those under steady two-dimensional (2D) flow conditions, a phenomenon commonly known as rotational augmentation. This paper presents an investigation of these two phenomena together in the inboard parts of wind turbine blades. This analysis is carried out using data from three sources: (1) the National Renewable Energy Laboratory’s Unsteady Aerodynamics Experiment Phase VI experimental data, including constant as well as continuously pitching blade conditions during axial operation, (2) data from unsteady Delayed Detached Eddy Simulations (DDES) carried out using the Technical University of Denmark’s in-house flow solver Ellipsys3D, and (3) data from a simplified model based on the blade element momentum method with a dynamic stall subroutine that uses rotationally augmented steady-state polars obtained from steady Phase VI experimental sequences, instead of the traditional 2D nonrotating data. The aim of this work is twofold. First, the blade loads estimated by the DDES simulations are compared to three select cases of the N sequence experimental data, which serves as a validation of the DDES method. Results show reasonable agreement between the two data in two out of three cases studied. Second, the dynamic time series of the lift and the moment polars obtained from the experiments are compared to those from the dynamic stall subroutine that uses the rotationally augmented steady polars. This allowed the differences between the stall phenomenon on the inboard parts of harmonically pitching blades on a rotating wind turbine and the classic dynamic stall representation in 2D flow to be
Elizondo, Marcelo A.; Tuffner, Francis K.; Schneider, Kevin P.
2016-01-01
Unlike transmission systems, distribution feeders in North America operate under unbalanced conditions at all times, and generally have a single strong voltage source. When a distribution feeder is connected to a strong substation source, the system is dynamically very stable, even for large transients. However if a distribution feeder, or part of the feeder, is separated from the substation and begins to operate as an islanded microgrid, transient dynamics become more of an issue. To assess the impact of transient dynamics at the distribution level, it is not appropriate to use traditional transmission solvers, which generally assume transposed lines and balanced loads. Full electromagnetic solvers capture a high level of detail, but it is difficult to model large systems because of the required detail. This paper proposes an electromechanical transient model of synchronous machine for distribution-level modeling and microgrids. This approach includes not only the machine model, but also its interface with an unbalanced network solver, and a powerflow method to solve unbalanced conditions without a strong reference bus. The presented method is validated against a full electromagnetic transient simulation.
Joubert-Doriol, Loc; Ryabinkin, Ilya G.; Izmaylov, Artur F.; Chemical Physics Theory Group, Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6
2013-12-21
In molecular systems containing conical intersections (CIs), a nontrivial geometric phase (GP) appears in the nuclear and electronic wave functions in the adiabatic representation. We study GP effects in nuclear dynamics of an N-dimensional linear vibronic coupling (LVC) model. The main impact of GP on low-energy nuclear dynamics is reduction of population transfer between the local minima of the LVC lower energy surface. For the LVC model, we proposed an isometric coordinate transformation that confines non-adiabatic effects within a two-dimensional subsystem interacting with an N ? 2 dimensional environment. Since environmental modes do not couple electronic states, all GP effects originate from nuclear dynamics within the subsystem. We explored when the GP affects nuclear dynamics of the isolated subsystem, and how the subsystem-environment interaction can interfere with GP effects. Comparing quantum dynamics with and without GP allowed us to devise simple rules to determine significance of the GP for nuclear dynamics in this model.
A moist aquaplanet variant of the HeldSuarez test for atmospheric model dynamical cores
Thatcher, D. R.; Jablonowski, C.
2015-09-29
A moist idealized test case (MITC) for atmospheric model dynamical cores is presented. The MITC is based on the HeldSuarez (HS) test that was developed for dry simulations on a flat Earth and replaces the full physical parameterization package with a Newtonian temperature relaxation and Rayleigh damping of the low-level winds. This new variant of the HS test includes moisture and thereby sheds light on the non-linear dynamics-physics moisture feedbacks without the complexity of full physics parameterization packages. In particular, it adds simplified moist processes to the HS forcing to model large-scale condensation, boundary layer mixing, and the exchange ofmorelatent and sensible heat between the atmospheric surface and an ocean-covered planet. Using a variety of dynamical cores of NCAR's Community Atmosphere Model (CAM), this paper demonstrates that the inclusion of the moist idealized physics package leads to climatic states that closely resemble aquaplanet simulations with complex physical parameterizations. This establishes that the MITC approach generates reasonable atmospheric circulations and can be used for a broad range of scientific investigations. This paper provides examples of two application areas. First, the test case reveals the characteristics of the physics-dynamics coupling technique and reproduces coupling issues seen in full-physics simulations. In particular, it is shown that sudden adjustments of the prognostic fields due to moist physics tendencies can trigger undesirable large-scale gravity waves, which can be remedied by a more gradual application of the physical forcing. Second, the moist idealized test case can be used to intercompare dynamical cores. These examples demonstrate the versatility of the MITC approach and suggestions are made for further application areas. The new moist variant of the HS test can be considered a test case of intermediate complexity.less
A dynamical model for condition monitoring and fault diagnostics of spur gears
Paya, B.; Esat, I.; Badi, M.N.M.
1996-12-31
The symptoms of condition monitoring and fault diagnostics of machinery based on the dynamic modelling of spur gears are discussed in this paper. The mathematical model presented in the earlier work, assumes two degree of freedom for each gear and the rotor, and also incorporates a varying gear tooth stiffness. This system is assumed to be in good condition (i.e. no fault present). The results obtained from this analytical model are compared with the ones obtained from an experimental model gearbox. This experimental gearbox consists of two meshing spur gears driven by an electric motor. The comparison of the results are encouraging as fundamental (dominant) frequencies of the analytical results correlates very closely to the experimental ones. It is shown that certain vibration frequency of a real gearbox such as the tooth meshing frequencies can be achieved from its mathematical model.
Control method and system for hydraulic machines employing a dynamic joint motion model
Danko, George
2011-11-22
A control method and system for controlling a hydraulically actuated mechanical arm to perform a task, the mechanical arm optionally being a hydraulically actuated excavator arm. The method can include determining a dynamic model of the motion of the hydraulic arm for each hydraulic arm link by relating the input signal vector for each respective link to the output signal vector for the same link. Also the method can include determining an error signal for each link as the weighted sum of the differences between a measured position and a reference position and between the time derivatives of the measured position and the time derivatives of the reference position for each respective link. The weights used in the determination of the error signal can be determined from the constant coefficients of the dynamic model. The error signal can be applied in a closed negative feedback control loop to diminish or eliminate the error signal for each respective link.
LDRD final report : mesoscale modeling of dynamic loading of heterogeneous materials.
Robbins, Joshua; Dingreville, Remi Philippe Michel; Voth, Thomas Eugene; Furnish, Michael David
2013-12-01
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 heterogeneities lead to localization of deformation and loss of shear strength. Microstructural effects are of broad importance to the scientific community and several institutions within DoD and DOE; however, current models rely on inaccurate assumptions about mechanisms at the sub-continuum or mesoscale. Consequently, there is a critical need for accurate and robust methods for modeling heterogeneous material response at this lower length scale. This report summarizes work performed as part of an LDRD effort (FY11 to FY13; project number 151364) to meet these needs.
Bradonjic, Milan
2009-01-01
In this paper we study reputation mechanisms, and show how the notion of reputation can help us in building truthful online auction mechanisms. From the mechanism design prospective, we derive the conditions on and design a truthful online auction mechanism. Moreover, in the case when some agents may lay or cannot have the real knowledge about the other agents reputations, we derive the resolution of the auction, such that the mechanism is truthful. Consequently, we move forward to the optimal one-gambler/one-seller problem, and explain how that problem is refinement of the previously discussed online auction design in the presence of reputation mechanism. In the setting of the optimal one-gambler problem, we naturally rise and solve the specific question: What is an agent's optimal strategy, in order to maximize his revenue? We would like to stress that our analysis goes beyond the scope, which game theory usually discusses under the notion of reputation. We model one-player games, by introducing a new parameter (reputation), which helps us in predicting the agent's behavior, in real-world situations, such as, behavior of a gambler, real-estate dealer, etc.
A model of lipid-free Apolipoprotein A-I revealed by iterative molecular dynamics simulation
Zhang, Xing; Lei, Dongsheng; Zhang, Lei; Rames, Matthew; Zhang, Shengli
2015-03-20
Apolipoprotein A-I (apo A-I), the major protein component of high-density lipoprotein, has been proven inversely correlated to cardiovascular risk in past decades. The lipid-free state of apo A-I is the initial stage which binds to lipids forming high-density lipoprotein. Molecular models of lipid-free apo A-I have been reported by methods like X-ray crystallography and chemical cross-linking/mass spectrometry (CCL/MS). Through structural analysis we found that those current models had limited consistency with other experimental results, such as those from hydrogen exchange with mass spectrometry. Through molecular dynamics simulations, we also found those models could not reach a stable equilibrium state. Therefore, by integrating various experimental results, we proposed a new structural model for lipidfree apo A-I, which contains a bundled four-helix N-terminal domain (1–192) that forms a variable hydrophobic groove and a mobile short hairpin C-terminal domain (193–243). This model exhibits an equilibrium state through molecular dynamics simulation and is consistent with most of the experimental results known from CCL/MS on lysine pairs, fluorescence resonance energy transfer and hydrogen exchange. This solution-state lipid-free apo A-I model may elucidate the possible conformational transitions of apo A-I binding with lipids in high-density lipoprotein formation.
A model of lipid-free Apolipoprotein A-I revealed by iterative molecular dynamics simulation
Zhang, Xing; Lei, Dongsheng; Zhang, Lei; Rames, Matthew; Zhang, Shengli
2015-03-20
Apolipoprotein A-I (apo A-I), the major protein component of high-density lipoprotein, has been proven inversely correlated to cardiovascular risk in past decades. The lipid-free state of apo A-I is the initial stage which binds to lipids forming high-density lipoprotein. Molecular models of lipid-free apo A-I have been reported by methods like X-ray crystallography and chemical cross-linking/mass spectrometry (CCL/MS). Through structural analysis we found that those current models had limited consistency with other experimental results, such as those from hydrogen exchange with mass spectrometry. Through molecular dynamics simulations, we also found those models could not reach a stable equilibrium state. Therefore,more » by integrating various experimental results, we proposed a new structural model for lipidfree apo A-I, which contains a bundled four-helix N-terminal domain (1–192) that forms a variable hydrophobic groove and a mobile short hairpin C-terminal domain (193–243). This model exhibits an equilibrium state through molecular dynamics simulation and is consistent with most of the experimental results known from CCL/MS on lysine pairs, fluorescence resonance energy transfer and hydrogen exchange. This solution-state lipid-free apo A-I model may elucidate the possible conformational transitions of apo A-I binding with lipids in high-density lipoprotein formation.« less
Bossard, J.A.; Peck, R.E.; Schmidt, D.K.
1993-03-01
The development of an advanced dynamic model for aeroelastic hypersonic vehicles powered by air breathing engines requires an adequate engine model. This report provides a discussion of some of the more important features of supersonic combustion and their relevance to the analysis and design of supersonic ramjet engines. Of particular interest are those aspects of combustion that impact the control of the process. Furthermore, the report summarizes efforts to enhance the aeropropulsive/aeroelastic dynamic model developed at the Aerospace Research Center of Arizona State University by focusing on combustion and improved modeling of this flow. The expanded supersonic combustor model described here has the capability to model the effects of friction, area change, and mass addition, in addition to the heat addition process. A comparison is made of the results from four cases: (1) heat addition only; (2) heat addition plus friction; (3) heat addition, friction, and area reduction, and (4) heat addition, friction, area reduction, and mass addition. The relative impact of these effects on the Mach number, static temperature, and static pressure distributions within the combustor are then shown. Finally, the effects of frozen versus equilibrium flow conditions within the exhaust plume is discussed.
A Nonlocal Peridynamic Plasticity Model for the Dynamic Flow and Fracture of Concrete.
Vogler, Tracy; Lammi, Christopher James
2014-10-01
A nonlocal, ordinary peridynamic constitutive model is formulated to numerically simulate the pressure-dependent flow and fracture of heterogeneous, quasi-brittle ma- terials, such as concrete. Classical mechanics and traditional computational modeling methods do not accurately model the distributed fracture observed within this family of materials. The peridynamic horizon, or range of influence, provides a characteristic length to the continuum and limits localization of fracture. Scaling laws are derived to relate the parameters of peridynamic constitutive model to the parameters of the classical Drucker-Prager plasticity model. Thermodynamic analysis of associated and non-associated plastic flow is performed. An implicit integration algorithm is formu- lated to calculate the accumulated plastic bond extension and force state. The gov- erning equations are linearized and the simulation of the quasi-static compression of a cylinder is compared to the classical theory. A dissipation-based peridynamic bond failure criteria is implemented to model fracture and the splitting of a concrete cylinder is numerically simulated. Finally, calculation of the impact and spallation of a con- crete structure is performed to assess the suitability of the material and failure models for simulating concrete during dynamic loadings. The peridynamic model is found to accurately simulate the inelastic deformation and fracture behavior of concrete during compression, splitting, and dynamically induced spall. The work expands the types of materials that can be modeled using peridynamics. A multi-scale methodology for simulating concrete to be used in conjunction with the plasticity model is presented. The work was funded by LDRD 158806.
First report on non-thermal plasma reactor scaling criteria and optimization models
Rosocha, L.A.; Korzekwa, R.A.
1998-01-13
The purpose of SERDP project CP-1038 is to evaluate and develop non-thermal plasma (NTP) reactor technology for Department of Defense (DoD) air emissions control applications. The primary focus is on oxides of nitrogen (NO{sub x}) and a secondary focus on hazardous air pollutants (HAPs), especially volatile organic compounds (VOCs). Example NO{sub x} sources are jet engine test cells (JETCs) and diesel engine powered electrical generators. Example VOCs are organic solvents used in painting, paint stripping, and parts cleaning. To design and build NTP reactors that are optimized for particular DoD applications, one must understand the basic decomposition chemistry of the target compound(s) and how the decomposition of a particular chemical species depends on the air emissions stream parameters and the reactor operating parameters. This report is intended to serve as an overview of the subject of reactor scaling and optimization and will discuss the basic decomposition chemistry of nitric oxide (NO) and two representative VOCs, trichloroethylene and carbon tetrachloride, and the connection between the basic plasma chemistry, the target species properties, and the reactor operating parameters (in particular, the operating plasma energy density). System architecture, that is how NTP reactors can be combined or ganged to achieve higher capacity, will also be briefly discussed.
Dynamic and impact contact mechanics of geologic materials: Grain-scale experiments and modeling
Cole, David M.; Hopkins, Mark A.; Ketcham, Stephen A.
2013-06-18
High fidelity treatments of the generation and propagation of seismic waves in naturally occurring granular materials is becoming more practical given recent advancements in our ability to model complex particle shapes and their mechanical interaction. Of particular interest are the grain-scale processes that are activated by impact events and the characteristics of force transmission through grain contacts. To address this issue, we have developed a physics based approach that involves laboratory experiments to quantify the dynamic contact and impact behavior of granular materials and incorporation of the observed behavior indiscrete element models. The dynamic experiments do not involve particle damage and emphasis is placed on measured values of contact stiffness and frictional loss. The normal stiffness observed in dynamic contact experiments at low frequencies (e.g., 10 Hz) are shown to be in good agreement with quasistatic experiments on quartz sand. The results of impact experiments - which involve moderate to extensive levels of particle damage - are presented for several types of naturally occurring granular materials (several quartz sands, magnesite and calcium carbonate ooids). Implementation of the experimental findings in discrete element models is discussed and the results of impact simulations involving up to 5 Multiplication-Sign 105 grains are presented.
Development of a plant-wide dynamic model of an integrated gasification combined cycle (IGCC) plant
Bhattacharyya, D.; Turton, R.; Zitney, S.
2009-01-01
In this presentation, development of a plant-wide dynamic model of an advanced Integrated Gasification Combined Cycle (IGCC) plant with CO2 capture will be discussed. The IGCC reference plant generates 640 MWe of net power using Illinois No.6 coal as the feed. The plant includes an entrained, downflow, General Electric Energy (GEE) gasifier with a radiant syngas cooler (RSC), a two-stage water gas shift (WGS) conversion process, and two advanced 'F' class combustion turbines partially integrated with an elevated-pressure air separation unit (ASU). A subcritical steam cycle is considered for heat recovery steam generation. Syngas is selectively cleaned by a SELEXOL acid gas removal (AGR) process. Sulfur is recovered using a two-train Claus unit with tail gas recycle to the AGR. A multistage intercooled compressor is used for compressing CO2 to the pressure required for sequestration. Using Illinois No.6 coal, the reference plant generates 640 MWe of net power. The plant-wide steady-state and dynamic IGCC simulations have been generated using the Aspen Plus{reg_sign} and Aspen Plus Dynamics{reg_sign} process simulators, respectively. The model is generated based on the Case 2 IGCC configuration detailed in the study available in the NETL website1. The GEE gasifier is represented with a restricted equilibrium reactor model where the temperature approach to equilibrium for individual reactions can be modified based on the experimental data. In this radiant-only configuration, the syngas from the Radiant Syngas Cooler (RSC) is quenched in a scrubber. The blackwater from the scrubber bottom is further cleaned in the blackwater treatment plant. The cleaned water is returned back to the scrubber and also used for slurry preparation. The acid gas from the sour water stripper (SWS) is sent to the Claus plant. The syngas from the scrubber passes through a sour shift process. The WGS reactors are modeled as adiabatic plug flow reactors with rigorous kinetics based on the mid
A spectral transform dynamical core option within the Community Atmosphere Model (CAM4)
Evans, Katherine J; Mahajan, Salil; Branstetter, Marcia L; McClean, Julie L.; Caron, Julie M.; Maltrud, Matthew E.; Hack, James J; Bader, David C; Neale, Rich
2014-01-01
A spectral transform dynamical core with an 85 spectral truncation resolution (T85) within the Community Atmosphere Model (CAM), version 4, is evaluated within the recently released Community Earth System Model, version 1.0 (CESM) global climate model. The spectral dynamical core option provides a well-known base within the climate model community from which to assess climate behavior and statistics, and its relative computational efficiency for smaller computing platforms allows it to be extended to perform climate length simulations using high-resolution configurations in the near term. To establish the characteristics of the CAM4 T85, an ensemble of simulations covering the present day observational period using forced sea surface temperatures and prescribed sea-ice extent are evaluated. Overall, the T85 ensemble attributes and biases are similar to a companion ensemble of simulations using the one degree finite volume (FV1) dynamical core, relative to observed and model derived datasets. Notable improvements with T85 compared to FV1 include the representation of wintertime Arctic sea level pressure and summer precipitation over the Western Indian subcontinent. The mean and spatial patterns of the land surface temperature trends over the AMIP period are generally well simulated with the T85 ensemble relative to observations, however the model is not able to capture the extent nor magnitude of changes in temperature extremes over the boreal summer, where the changes are most dramatic. Biases in the wintertime Arctic surface temperature and annual mean surface stress fields persist with T85 as with the CAM3 version of T85.
Advanced High-Temperature Reactor Dynamic System Model Development: April 2012 Status
Qualls, A L; Cetiner, M S; Wilson, Jr, T L
2012-04-30
The Advanced High-Temperature Reactor (AHTR) is a large-output fluoride-salt-cooled high-temperature reactor (FHR). An early-phase preconceptual design of a 1500 MW(e) power plant was developed in 2011 [Refs. 1 and 2]. An updated version of this plant is shown as Fig. 1. FHRs feature low-pressure liquid fluoride salt cooling, coated-particle fuel, a high-temperature power cycle, and fully passive decay heat rejection. The AHTR is designed to be a “walk away” reactor that requires no action to prevent large off-site releases following even severe reactor accidents. This report describes the development of dynamic system models used to further the AHTR design toward that goal. These models predict system response during warmup, startup, normal operation, and limited off-normal operating conditions. Severe accidents that include a loss-of-fluid inventory are not currently modeled. The scope of the models is limited to the plant power system, including the reactor, the primary and intermediate heat transport systems, the power conversion system, and safety-related or auxiliary heat removal systems. The primary coolant system, the intermediate heat transport system and the reactor building structure surrounding them are shown in Fig. 2. These systems are modeled in the most detail because the passive interaction of the primary system with the surrounding structure and heat removal systems, and ultimately the environment, protects the reactor fuel and the vessel from damage during severe reactor transients. The reactor silo also plays an important role during system warmup. The dynamic system modeling tools predict system performance and response. The goal is to accurately predict temperatures and pressures within the primary, intermediate, and power conversion systems and to study the impacts of design changes on those responses. The models are design tools and are not intended to be used in reactor qualification. The important details to capture in the primary
A graphical interface based model for wind turbine drive train dynamics
Manwell, J.F.; McGowan, J.G.; Abdulwahid, U.; Rogers, A.; McNiff, B.
1996-12-31
This paper presents a summary of a wind turbine drive train dynamics code that has been under development at the University of Massachusetts, under National Renewable Energy Laboratory (NREL) support. The code is intended to be used to assist in the proper design and selection of drive train components. This work summarizes the development of the equations of motion for the model, and discusses the method of solution. In addition, a number of comparisons with analytical solutions and experimental field data are given. The summary includes conclusions and suggestions for future work on the model. 13 refs., 10 figs.
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
Users of the VEMAP Portal can access input files of numerical data that include monthly and daily files of geographic data, soil and site files, scenario files, etc. Model results from Phase I, the Equilibrium Response datasets, are available through the NCAR anonymous FTP site at http://www.cgd.ucar.edu/vemap/vresults.html. Phase II, Transient Dynamics, include climate datasets, models results, and analysis tools. Many supplemental files are also available from the main data page at http://www.cgd.ucar.edu/vemap/datasets.html.
Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production
Presentation slides from the US DOE Fuel Cell Technologies Office webinar, Wind-to-Hydrogen Cost Modeling and Project Findings, on held January 17, 2013.
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
The Vegetation-Ecosystem Modeling and Analysis Project (VEMAP) was a large, collaborative, multi-agency program to simulate and understand ecosystem dynamics for the continental U.S. The project involved the development of common data sets for model input including a high-resolution topographically-adjusted climate history of the U.S. from 1895-1993 on a 0.5? grid, with soils and vegetation cover. The vegetation cover data set includes a detailed agricultural data base based on USDA statistics and remote sensing, as well as natural vegetation (also derived from satellite imagery). Two principal model experiments were run. First, a series of ecosystem models were run from 1895 to 1993 to simulate current ecosystem biogeochemistry. Second, these same models were integrated forward using the output from two climate system models (CCC (Canadian Climate Centre) and Hadley Centre models) using climate results translated into the VEMAP grid and re-adjusted for high-resolution topography for the simulated period 1994-2100.[Quoted from http://www.cgd.ucar.edu/vemap/findings.html] The VEMAP Data Portal is a central collection of files maintained and serviced by the NCAR Data Group. These files (the VEMAP Community Datasets) represent a complete and current collection of VEMAP data files. All data files available through the Data Portal have undergone extensive quality assurance.[Taken from http://www.cgd.ucar.edu/vemap/datasets.html] Users of the VEMAP Portal can access input files of numerical data that include monthly and daily files of geographic data, soil and site files, scenario files, etc. Model results from Phase I, the Equilibrium Response datasets, are available through the NCAR anonymous FTP site at http://www.cgd.ucar.edu/vemap/vresults.html. Phase II, Transient Dynamics, include climate datasets, models results, and analysis tools. Many supplemental files are also available from the main data page at http://www.cgd.ucar.edu/vemap/datasets.html.
Modeling void formation dynamics in fibrous porous media with the lattice Boltzmann method
Spaid, M.A.A.; Phelan, F.R. Jr.
1997-12-31
A novel technique for simulating multiphase fluid flow in the microstructure of a fiber preform is developed, which has the capability of capturing the dynamics of void formation. The model is based on the lattice Boltzmann (LB) method -- a relatively new numerical technique which has rapidly emerged as a powerful tool for simulating multiphase fluid mechanics. The primary benefit of the lattice Boltzmann method is the ability to robustly model the interface between two immiscible fluids without the need for a complex interface tracking algorithm. In a previous paper, it was demonstrated that the lattice Boltzmann method may be modified to solve the Stokes/Brinkman formulation for flow in heterogeneous porous media. Multiphase infiltration of the fiber microstructure is modeled by combining the Stokes/Brinkman LB method, with the multiphase LB algorithm described by Shan and Chen. Numerical results are presented which compare void formation dynamics as a function of the nominal porosity for a model fiber microstructure. In addition, unsaturated permeabilities obtained from the numerical simulations are compared to saturated results for flow in the model porous microstructure.
On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models
Zhang, Shipeng; Wang, Minghuai; Ghan, Steven J.; Ding, Aijun; Wang, Hailong; Zhang, Kai; Neubauer, David; Lohmann, Ulrike; Ferrachat, Sylvaine; Takeamura, Toshihiko; et al
2016-03-04
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 (ω500), 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 ascentmore » (ω500 < −25 hPa day−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 close to that in subsidence regimes, which indicates that regimes with strong large-scale ascent 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 day−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 compared to the uncertainty in its global mean values, pointing to the need to reduce the uncertainty in AIE in different dynamical regimes.« less
A moist aquaplanet variant of the Held–Suarez test for atmospheric model dynamical cores
Thatcher, Diana R.; Jablonowski, Christiane
2016-04-04
A moist idealized test case (MITC) for atmospheric model dynamical cores is presented. The MITC is based on the Held–Suarez (HS) test that was developed for dry simulations on “a flat Earth” and replaces the full physical parameterization package with a Newtonian temperature relaxation and Rayleigh damping of the low-level winds. This new variant of the HS test includes moisture and thereby sheds light on the nonlinear dynamics–physics moisture feedbacks without the complexity of full-physics parameterization packages. In particular, it adds simplified moist processes to the HS forcing to model large-scale condensation, boundary-layer mixing, and the exchange of latent and sensible heat betweenmore » the atmospheric surface and an ocean-covered planet. Using a variety of dynamical cores of the National Center for Atmospheric Research (NCAR)'s Community Atmosphere Model (CAM), this paper demonstrates that the inclusion of the moist idealized physics package leads to climatic states that closely resemble aquaplanet simulations with complex physical parameterizations. This establishes that the MITC approach generates reasonable atmospheric circulations and can be used for a broad range of scientific investigations. This paper provides examples of two application areas. First, the test case reveals the characteristics of the physics–dynamics coupling technique and reproduces coupling issues seen in full-physics simulations. In particular, it is shown that sudden adjustments of the prognostic fields due to moist physics tendencies can trigger undesirable large-scale gravity waves, which can be remedied by a more gradual application of the physical forcing. Second, the moist idealized test case can be used to intercompare dynamical cores. These examples demonstrate the versatility of the MITC approach and suggestions are made for further application areas. The new moist variant of the HS test can be considered a test case of intermediate complexity.« less
Erdmann, Thorsten; Albert, Philipp J.; Schwarz, Ulrich S.
2013-11-07
Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors in equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.
A moist aquaplanet variant of the Held–Suarez test for atmospheric model dynamical cores
Thatcher, Diana R.; Jablonowski, Christiane
2016-04-04
A moist idealized test case (MITC) for atmospheric model dynamical cores is presented. The MITC is based on the Held–Suarez (HS) test that was developed for dry simulations on “a flat Earth” and replaces the full physical parameterization package with a Newtonian temperature relaxation and Rayleigh damping of the low-level winds. This new variant of the HS test includes moisture and thereby sheds light on the nonlinear dynamics–physics moisture feedbacks without the complexity of full-physics parameterization packages. In particular, it adds simplified moist processes to the HS forcing to model large-scale condensation, boundary-layer mixing, and the exchange of latent and sensible heat betweenmore » the atmospheric surface and an ocean-covered planet. Using a variety of dynamical cores of the National Center for Atmospheric Research (NCAR)'s Community Atmosphere Model (CAM), this paper demonstrates that the inclusion of the moist idealized physics package leads to climatic states that closely resemble aquaplanet simulations with complex physical parameterizations. This establishes that the MITC approach generates reasonable atmospheric circulations and can be used for a broad range of scientific investigations. This paper provides examples of two application areas. First, the test case reveals the characteristics of the physics–dynamics coupling technique and reproduces coupling issues seen in full-physics simulations. In particular, it is shown that sudden adjustments of the prognostic fields due to moist physics tendencies can trigger undesirable large-scale gravity waves, which can be remedied by a more gradual application of the physical forcing. Second, the moist idealized test case can be used to intercompare dynamical cores. These examples demonstrate the versatility of the MITC approach and suggestions are made for further application areas. Furthermore, the new moist variant of the HS test can be considered a test case of intermediate
Dynamic nuclear renography kinetic analysis: Four-compartment model for assessing kidney function
Raswan, T. R. Haryanto, F.
2014-09-30
Dynamic nuclear renography method produces TACs of kidneys and bladder. Multiple TACs data can be further analyzed to obtain the overview of urinary system's condition. Tracer kinetic analysis was performed using four-compartment models. The system's model consist of four irreversible compartment with four transport constants (k1, k2, k3 and k4). The mathematical expressions of tracer's distributions is fitted to experimental data (TACs) resulting in model constants. This transport constants represent the urinary system behavior, and later can be used for analyzing system's condition. Different intervals of kinetics parameter are clearly shown by abnormal system with respect to the normal one. Furthermore, the system with delayed uptake has 82% lower uptake parameters (k1 and k2) than normal one. Meanwhile, the system with prolonged clearance time has its kinetics parameters k3 or k4 lower than the others. This model is promising for quantitatively describe urinary system's function especially if supplied with more data.
NREL: Energy Analysis - BSM: Biomass Scenario Model
U.S. Department of Energy (DOE) all webpages (Extended Search)
BSM - Biomass Scenario Model Energy Analysis The Biomass Scenario Model (BSM) is a unique, carefully validated, state-of-the-art, dynamic model of the domestic biofuels supply chain. BSM explicitly focuses on policy issues, their feasibility, and potential side effects. It integrates resource availability, physical/technological/economic constraints, behavior, and policy. BSM uses a system dynamics simulation (not optimization) to model dynamic interactions across the supply chain. The model
Prusa, Joseph
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 EULAGâ??s advanced dynamics core with the â??physicsâ? 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.
An Integrated Approach to Coal Gasifier Testing, Modeling, and Process Optimization
Sundaram, S. K.; Johnson, Kenneth I.; Matyas, Josef; Williford, Ralph E.; Pilli, Siva Prasad; Korolev, Vladimir N.
2009-10-01
Gasification is an important method of converting coal into clean burning fuels and high-value industrial chemicals. However, gasifier reliability can be severely limited by rapid degradation of the refractory lining in hot-wall gasifiers. The Pacific Northwest National Laboratory (PNNL) is performing multidisciplinary research to provide the experimental data and the engineering models needed to control gasifier operation for extended refractory life. Our experimental program includes prediction of slag viscosity using empirical viscosity models encompassing US coals, characterization of selected slag-refractory interaction including transport of slag/refractory components at the slag-refractory interface, and measurement of slag penetration into refractories as a function of time and temperature. The experimental data is used in slag flow, slag penetration, and refractory damage models to predict the operating temperature limits for increased refractory life. A simplified entrained flow gasifier model is also being developed to simulate one-dimensional axial flow with average axial velocity, coal devolatilization, and combustion kinetics. Combining the slag flow, refractory degradation, and gasifier models will provide a powerful tool to predict the coal and oxidant feed rates and control the gasifier operation to balance coal conversion efficiency with increased refractory life. A research scale gasifier has also been constructed at PNNL to provide syngas for coal conversion and carbon sequestration research, and also valuable datasets on operating conditions for validating the modeling results.
The ArcSDE GIS Dynamic Population Model Tool for Savannah River Site Emergency Response
MCLANE, TRACY; JONES, DWIGHT
2005-10-03
The Savannah River Site (SRS) is a 310-square-mile Department of Energy site located near Aiken, South Carolina. With a workforce of over 10,000 employees and subcontractors, SRS emergency personnel must be able to respond to an emergency event in a timely and effective manner, in order to ensure the safety and security of the Site. Geographic Information Systems (GIS) provides the technology needed to give managers and emergency personnel the information they need to make quick and effective decisions. In the event of a site evacuation, knowing the number of on-site personnel to evacuate from a given area is an essential piece of information for emergency staff. SRS has developed a GIS Dynamic Population Model Tool to quickly communicate real-time information that summarizes employee populations by facility area and building and then generates dynamic maps that illustrate output statistics.
Smoothed particle hydrodynamics Non-Newtonian model for ice-sheet and ice-shelf dynamics
Pan, Wenxiao; Tartakovsky, Alexandre M.; Monaghan, Joseph J.
2013-06-01
Mathematical modeling of ice sheets is complicated by the non-linearity of the governing equations and boundary conditions. Standard grid-based methods require complex front tracking techniques and have limited capability to handle large material deformations and abrupt changes in bottom topography. As a consequence, numerical methods are usually restricted to shallow ice sheet and ice shelf approximations. We propose a new smoothed particle hydrodynamics (SPH) non-Newtonian model for coupled ice sheet and ice shelf dynamics. SPH, a fully Lagrangian particle method, is highly scalable and its Lagrangian nature and meshless discretization are well suited to the simulation of free surface ?ows, large material deformation, and material fragmentation. In this paper, SPH is used to study 3D ice sheet/ice shelf behavior, and the dynamics of the grounding line. The steady state position of the grounding line obtained from SPH simulations is in good agreement with laboratory observations for a wide range of simulated bedrock slopes, and density ratios, similar to those of ice and sea water. The numerical accuracy of the SPH algorithm is veri?ed by simulating Poiseuille ?ow, plane shear ?ow with free surface and the propagation of a blob of ice along a horizontal surface. In the laboratory experiment, the ice was represented with a viscous Newtonian ?uid. In the present work, however, the ice is modeled as both viscous Newtonian ?uid and non-Newtonian ?uid, such that the e?ect of non-Newtonian rheology on the dynamics of grounding line was examined. The non-Newtonian constitutive relation is prescribed to be Glens law for the creep of polycrystalline ice. A V-shaped bedrock ramp is further introduced to model the real geometry of bedrock slope.
Thermodynamic model of a thermal storage air conditioning system with dynamic behavior
Fleming, E; Wen, SY; Shi, L; da Silva, AK
2013-12-01
A thermodynamic model was developed to predict transient behavior of a thermal storage system, using phase change materials (PCMs), for a novel electric vehicle climate conditioning application. The main objectives of the paper are to consider the system's dynamic behavior, such as a dynamic air flow rate into the vehicle's cabin, and to characterize the transient heat transfer process between the thermal storage unit and the vehicle's cabin, while still maintaining accurate solution to the complex phase change heat transfer. The system studied consists of a heat transfer fluid circulating between either of the on-board hot and cold thermal storage units, which we refer to as thermal batteries, and a liquid-air heat exchanger that provides heat exchange with the incoming air to the vehicle cabin. Each thermal battery is a shell-and-tube configuration where a heat transfer fluid flows through parallel tubes, which are surrounded by PCM within a larger shell. The system model incorporates computationally inexpensive semianalytic solution to the conjugated laminar forced convection and phase change problem within the battery and accounts for airside heat exchange using the Number of Transfer Units (NTUs) method for the liquid-air heat exchanger. Using this approach, we are able to obtain an accurate solution to the complex heat transfer problem within the battery while also incorporating the impact of the airside heat transfer on the overall system performance. The implemented model was benchmarked against a numerical study for a melting process and against full system experimental data for solidification using paraffin wax as the PCM. Through modeling, we demonstrate the importance of capturing the airside heat exchange impact on system performance, and we investigate system response to dynamic operating conditions, e.g., air recirculation. (C) 2013 Elsevier Ltd. All rights reserved.
Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.
2015-03-27
Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health
Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.
2015-03-27
Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use formore » the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of
Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.
2015-03-27
Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health
Ron Moon
2011-06-30
This final scientific report documents the Industrial Technology Program (ITP) Stage 2 Concept Development effort on Data Center Energy Reduction and Management Through Real-Time Optimal Control (RTOC). Society is becoming increasingly dependent on information technology systems, driving exponential growth in demand for data center processing and an insatiable appetite for energy. David Raths noted, 'A 50,000-square-foot data center uses approximately 4 megawatts of power, or the equivalent of 57 barrels of oil a day1.' The problem has become so severe that in some cases, users are giving up raw performance for a better balance between performance and energy efficiency. Historically, power systems for data centers were crudely sized to meet maximum demand. Since many servers operate at 60%-90% of maximum power while only utilizing an average of 5% to 15% of their capability, there are huge inefficiencies in the consumption and delivery of power in these data centers. The goal of the 'Recovery Act: Decreasing Data Center Energy Use through Network and Infrastructure Control' is to develop a state of the art approach for autonomously and intelligently reducing and managing data center power through real-time optimal control. Advances in microelectronics and software are enabling the opportunity to realize significant data center power savings through the implementation of autonomous power management control algorithms. The first step to realizing these savings was addressed in this study through the successful creation of a flexible and scalable mathematical model (equation) for data center behavior and the formulation of an acceptable low technical risk market introduction strategy leveraging commercial hardware and software familiar to the data center market. Follow-on Stage 3 Concept Development efforts include predictive modeling and simulation of algorithm performance, prototype demonstrations with representative data center equipment to verify requisite
Lehoucq, Richard B.; Segalman, Daniel Joseph; Hetmaniuk, Ulrich L.; Dohrmann, Clark R.
2009-10-01
Advanced computing hardware and software written to exploit massively parallel architectures greatly facilitate the computation of extremely large problems. On the other hand, these tools, though enabling higher fidelity models, have often resulted in much longer run-times and turn-around-times in providing answers to engineering problems. The impediments include smaller elements and consequently smaller time steps, much larger systems of equations to solve, and the inclusion of nonlinearities that had been ignored in days when lower fidelity models were the norm. The research effort reported focuses on the accelerating the analysis process for structural dynamics though combinations of model reduction and mitigation of some factors that lead to over-meshing.
Double and single pion photoproduction within a dynamical coupled-channels model
Hiroyuki Kamano; Julia-Diaz, Bruno; Lee, T. -S. H.; Matsuyama, Akihiko; Sato, Toru
2009-12-16
Within a dynamical coupled-channels model which has already been fixed from analyzing the data of the πN → πN and γN → πN reactions, we present the predicted double pion photoproduction cross sections up to the second resonance region, W < 1.7 GeV. The roles played by the different mechanisms within our model in determining both the single and double pion photoproduction reactions are analyzed, focusing on the effects due to the direct γN → ππN mechanism, the interplay between the resonant and non-resonant amplitudes, and the coupled-channels effects. As a result, the model parameters which can be determined mostmore » effectively in the combined studies of both the single and double pion photoproduction data are identified for future studies.« less
Modeling the infrastructure dynamics of China -- Water, agriculture, energy, and greenhouse gases
Conrad, S.H.; Drennen, T.E.; Engi, D.; Harris, D.L.; Jeppesen, D.M.; Thomas, R.P.
1998-08-01
A comprehensive critical infrastructure analysis of the People`s Republic of China was performed to address questions about China`s ability to meet its long-term grain requirements and energy needs and to estimate greenhouse gas emissions in China likely to result from increased agricultural production and energy use. Four dynamic computer simulation models of China`s infrastructures--water, agriculture, energy and greenhouse gas--were developed to simulate, respectively, the hydrologic budgetary processes, grain production and consumption, energy demand, and greenhouse gas emissions in China through 2025. The four models were integrated into a state-of-the-art comprehensive critical infrastructure model for all of China. This integrated model simulates diverse flows of commodities, such as water and greenhouse gas, between the separate models to capture the overall dynamics of the integrated system. The model was used to generate projections of China`s available water resources and expected water use for 10 river drainage regions representing 100% of China`s mean annual runoff and comprising 37 major river basins. These projections were used to develop estimates of the water surpluses and/or deficits in the three end-use sectors--urban, industrial, and agricultural--through the year 2025. Projections of the all-China demand for the three major grains (corn, wheat, and rice), meat, and other (other grains and fruits and vegetables) were also generated. Each geographic region`s share of the all-China grain demand (allocated on the basis of each region`s share of historic grain production) was calculated in order to assess the land and water resources in each region required to meet that demand. Growth in energy use in six historically significant sectors and growth in greenhouse gas loading were projected for all of China.
A Smoothed Particle Hydrodynamics Model for Ice Sheet and Ice Shelf Dynamics
Pan, Wenxiao; Tartakovsky, Alexandre M.; Monaghan, Joseph J.
2012-02-08
Mathematical modeling of ice sheets is complicated by the non-linearity of the governing equations and boundary conditions. Standard grid-based methods require complex front tracking techniques and have limited capability to handle large material deformations and abrupt changes in bottom topography. As a consequence, numerical methods are usually restricted to shallow ice sheet and ice shelf approximations. We propose a new smoothed particle hydrodynamics (SPH) model for coupled ice sheet and ice shelf dynamics. SPH is a fully Lagrangian particle method. It is highly scalable and its Lagrangian nature and meshless discretization are well suited to the simulation of free surface flows, large material deformation, and material fragmentation. In this paper SPH is used to study ice sheet/ice shelf behavior, and the dynamics of the grounding line. The steady state position of the grounding line obtained from the SPH simulations is in good agreement with laboratory observations for a wide range of simulated bedrock slopes, and density ratios similar to those of ice and sea water. The numerical accuracy of the SPH algorithm is further verified by simulating the plane shear flow of two immiscible fluids and the propagation of a highly viscous blob of fluid along a horizontal surface. In the experiment, the ice was represented with a viscous newtonian fluid. For consistency, in the described SPH model the ice is also modeled as a viscous newtonian fluid. Typically, ice sheets are modeled as a non-Newtonian fluid, accounting for the changes in the mechanical properties of ice. Implementation of a non-Newtonian rheology in the SPH model is the subject of our ongoing research.
An integrated approach to coal gasifier testing, modeling, and process optimization
S.K. Sundaram; K.I. Johnson; J. Matyas; R.E. Williford; S.P. Pilli; V.N. Korolev
2009-09-15
Gasification is an important method of converting coal into clean-burning fuels and high-value industrial chemicals. However, gasifier reliability can be severely limited by rapid degradation of the refractory lining in hot-wall gasifiers. This paper describes an integrated approach to provide the experimental data and engineering models needed to better understand how to control gasifier operation for extended refractory life. The experimental program includes slag viscosity testing and measurement of slag penetration into refractories as a function of time and temperature. The experimental data is used in slag flow, slag penetration, and refractory damage models to predict the limits on operating temperature for increased refractory life. A simplified entrained flow gasifier model is also described to simulate one-dimensional axial flow with average axial velocity, coal devolatilization, and combustion kinetics. The goal of this experimental and model program is to predict coal and oxidant feed rates and to control the gasifier operation to balance coal conversion efficiency with increased refractory life. 26 refs., 7 figs., 3 tabs.
Optimizing Blast Furnace Operation to Increase Efficiency and Lower Costs
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Optimizing Blast Furnace Operation to Increase Efficiency and Lower Costs State-of-the-Art Computational Fluid Dynamics Model Optimizes Fuel Rate in Blast Furnaces The blast furnace (BF) is the most widely used ironmaking process in the U.S. A major advance in BF ironmaking has been the use of pulverized coal which partially replaces metallurgi- cal coke. This results in substantial improvement in furnace effciency and thus the reductions of energy consumption and greenhouse gas emissions.
Rafique, Rashid; Kumar, Sandeep; Luo, Yiqi; Kiely, Gerard; Asrar, Ghassem R.
2015-02-01
he accurate calibration of complex biogeochemical models is essential for the robust estimation of soil greenhouse gases (GHG) as well as other environmental conditions and parameters that are used in research and policy decisions. DayCent is a popular biogeochemical model used both nationally and internationally for this purpose. Despite DayCent’s popularity, its complex parameter estimation is often based on experts’ knowledge which is somewhat subjective. In this study we used the inverse modelling parameter estimation software (PEST), to calibrate the DayCent model based on sensitivity and identifi- ability analysis. Using previously published N2 O and crop yield data as a basis of our calibration approach, we found that half of the 140 parameters used in this study were the primary drivers of calibration dif- ferences (i.e. the most sensitive) and the remaining parameters could not be identified given the data set and parameter ranges we used in this study. The post calibration results showed improvement over the pre-calibration parameter set based on, a decrease in residual differences 79% for N2O fluxes and 84% for crop yield, and an increase in coefficient of determination 63% for N2O fluxes and 72% for corn yield. The results of our study suggest that future studies need to better characterize germination tem- perature, number of degree-days and temperature dependency of plant growth; these processes were highly sensitive and could not be adequately constrained by the data used in our study. Furthermore, the sensitivity and identifiability analysis was helpful in providing deeper insight for important processes and associated parameters that can lead to further improvement in calibration of DayCent model.
Doinikov, Alexander A. Bouakaz, Ayache; Sheeran, Paul S.; Dayton, Paul A.
2014-10-15
Purpose: Perfluorocarbon (PFC) microdroplets, called phase-change contrast agents (PCCAs), are a promising tool in ultrasound imaging and therapy. Interest in PCCAs is motivated by the fact that they can be triggered to transition from the liquid state to the gas state by an externally applied acoustic pulse. This property opens up new approaches to applications in ultrasound medicine. Insight into the physics of vaporization of PFC droplets is vital for effective use of PCCAs and for anticipating bioeffects. PCCAs composed of volatile PFCs (with low boiling point) exhibit complex dynamic behavior: after vaporization by a short acoustic pulse, a PFC droplet turns into a vapor bubble which undergoes overexpansion and damped radial oscillation until settling to a final diameter. This behavior has not been well described theoretically so far. The purpose of our study is to develop an improved theoretical model that describes the vaporization dynamics of volatile PFC droplets and to validate this model by comparison with in vitro experimental data. Methods: The derivation of the model is based on applying the mathematical methods of fluid dynamics and thermodynamics to the process of the acoustic vaporization of PFC droplets. The used approach corrects shortcomings of the existing models. The validation of the model is carried out by comparing simulated results with in vitro experimental data acquired by ultrahigh speed video microscopy for octafluoropropane (OFP) and decafluorobutane (DFB) microdroplets of different sizes. Results: The developed theory allows one to simulate the growth of a vapor bubble inside a PFC droplet until the liquid PFC is completely converted into vapor, and the subsequent overexpansion and damped oscillations of the vapor bubble, including the influence of an externally applied acoustic pulse. To evaluate quantitatively the difference between simulated and experimental results, the L2-norm errors were calculated for all cases where the
Documentation of INL’s In Situ Oil Shale Retorting Water Usage System Dynamics Model
Earl D Mattson; Larry Hull
2012-12-01
A system dynamic model was construction to evaluate the water balance for in-situ oil shale conversion. The model is based on a systems dynamics approach and uses the Powersim Studio 9™ software package. Three phases of an in situ retort were consider; a construction phase primarily accounts for water needed for drilling and water produced during dewatering, an operation phase includes the production of water from the retorting process, and a remediation phase water to remove heat and solutes from the subsurface as well as return the ground surface to its natural state. Throughout these three phases, the water is consumed and produced. Consumption is account for through the drill process, dust control, returning the ground water to its initial level and make up water losses during the remedial flushing of the retort zone. Production of water is through the dewatering of the retort zone, and during chemical pyrolysis reaction of the kerogen conversion. The document discusses each of the three phases used in the model.
Use of a dynamic simulation model to understand nitrogen cycling in the middle Rio Grande, NM.
Meixner, Tom; Tidwell, Vincent Carroll; Oelsner, Gretchen; Brooks, Paul; Roach, Jesse D.
2008-08-01
Water quality often limits the potential uses of scarce water resources in semiarid and arid regions. To best manage water quality one must understand the sources and sinks of both solutes and water to the river system. Nutrient concentration patterns can identify source and sink locations, but cannot always determine biotic processes that affect nutrient concentrations. Modeling tools can provide insight into these large-scale processes. To address questions about large-scale nitrogen removal in the Middle Rio Grande, NM, we created a system dynamics nitrate model using an existing integrated surface water--groundwater model of the region to evaluate our conceptual models of uptake and denitrification as potential nitrate removal mechanisms. We modeled denitrification in groundwater as a first-order process dependent only on concentration and used a 5% denitrification rate. Uptake was assumed to be proportional to transpiration and was modeled as a percentage of the evapotranspiration calculated within the model multiplied by the nitrate concentration in the water being transpired. We modeled riparian uptake as 90% and agricultural uptake as 50% of the respective evapotranspiration rates. Using these removal rates, our model results suggest that riparian uptake, agricultural uptake and denitrification in groundwater are all needed to produce the observed nitrate concentrations in the groundwater, conveyance channels, and river as well as the seasonal concentration patterns. The model results indicate that a total of 497 metric tons of nitrate-N are removed from the Middle Rio Grande annually. Where river nitrate concentrations are low and there are no large nitrate sources, nitrate behaves nearly conservatively and riparian and agricultural uptake are the most important removal mechanisms. Downstream of a large wastewater nitrate source, denitrification and agricultural uptake were responsible for approximately 90% of the nitrogen removal.
Multichannel Pseudogap Kondo Model: Large-N Solution and Quantum-Critical Dynamics
Vojta, Matthias
2001-08-27
We discuss a multichannel SU(N) Kondo model which displays nontrivial zero-temperature phase transitions due to a conduction electron density of states vanishing with a power law at the Fermi level. In a particular large-N limit, the system is described by coupled integral equations corresponding to a dynamic saddle point. We exactly determine the universal low-energy behavior of spectral densities at the scale-invariant fixed points, obtain anomalous exponents, and compute scaling functions describing the crossover near the quantum-critical points. We argue that our findings are relevant to recent experiments on impurity-doped d -wave superconductors.
Cohesive Modeling of Dynamic Crack Growth in Homogeneous and Functionally Graded Materials
Zhang Zhengyu; Paulino, Glaucio H.; Celes, Waldemar
2008-02-15
This paper presents a Cohesive Zone Model (CZM) approach for investigating dynamic crack propagation in homogeneous and Functionally Graded Materials (FGMs). The failure criterion is incorporated in the CZM using both a finite cohesive strength and work to fracture in the material description. A novel CZM for FGMs is explored and incorporated into a finite element framework. The material gradation is approximated at the element level using a graded element formulation. A numerical example is provided to demonstrate the efficacy of the CZM approach, in which the influence of the material gradation on the crack growth pattern is studied.
Ely, James H.; Siciliano, Edward R.; Swinhoe, Martyn T.; Lintereur, Azaree T.
2013-01-01
This report details the results of the modeling and simulation work accomplished for the ‘Neutron Detection without Helium-3’ project during the 2011 and 2012 fiscal years. The primary focus of the project is to investigate commercially available technologies that might be used in safeguards applications in the relatively near term. Other technologies that are being developed may be more applicable in the future, but are outside the scope of this study.
AFDM: An advanced fluid-dynamics model. Volume 6: EOS-AFDM interface
Henneges, G.; Kleinheins, S.
1994-01-01
This volume of the Advanced Fluid-Dynamics Model (AFDM) documents the modeling of the equation of state (EOS) in the code. The authors present an overview of the basic concepts underlying the thermodynamics modeling and resulting EOS, which is a set of relations between the thermodynamic properties of materials. The AFDM code allows for multiphase-multimaterial systems, which they explore in three phase models: two-material solid, two-material liquid, and three-material vapor. They describe and compare two ways of specifying the EOS of materials: (1) as simplified analytic expressions, or (2) as tables that precisely describe the properties of materials and their interactions for mechanical equilibrium. Either of the two EOS models implemented in AFDM can be selected by specifying the option when preprocessing the source code for compilation. Last, the authors determine thermophysical properties such as surface tension, thermal conductivities, and viscosities in the model for the intracell exchanges of AFDM. Specific notations, routines, EOS data, plots, test results, and corrections to the code are available in the appendices.
Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila
2011-08-15
Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.
J. Vernon Cole; Abhra Roy; Ashok Damle; Hari Dahr; Sanjiv Kumar; Kunal Jain; Ned Djilai
2012-10-02
Water management in Proton Exchange Membrane, PEM, Fuel Cells is challenging because of the inherent conflicts between the requirements for efficient low and high power operation. Particularly at low powers, adequate water must be supplied to sufficiently humidify the membrane or protons will not move through it adequately and resistance losses will decrease the cell efficiency. At high power density operation, more water is produced at the cathode than is necessary for membrane hydration. This excess water must be removed effectively or it will accumulate in the Gas Diffusion Layers, GDLs, between the gas channels and catalysts, blocking diffusion paths for reactants to reach the catalysts and potentially flooding the electrode. As power density of the cells is increased, the challenges arising from water management are expected to become more difficult to overcome simply due to the increased rate of liquid water generation relative to fuel cell volume. Thus, effectively addressing water management based issues is a key challenge in successful application of PEMFC systems. In this project, CFDRC and our partners used a combination of experimental characterization, controlled experimental studies of important processes governing how water moves through the fuel cell materials, and detailed models and simulations to improve understanding of water management in operating hydrogen PEM fuel cells. The characterization studies provided key data that is used as inputs to all state-of-the-art models for commercially important GDL materials. Experimental studies and microscopic scale models of how water moves through the GDLs showed that the water follows preferential paths, not branching like a river, as it moves toward the surface of the material. Experimental studies and detailed models of water and airflow in fuel cells channels demonstrated that such models can be used as an effective design tool to reduce operating pressure drop in the channels and the associated
Centralized Stochastic Optimal Control of Complex Systems
Malikopoulos, Andreas
2015-01-01
In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.
SU-E-T-583: Optimizing the MLC Model Parameters for IMRT in the RayStation Treatment Planning System
Chen, S; Yi, B; Xu, H; Yang, X; Prado, K; D'Souza, W
2014-06-01
Purpose: To optimize the MLC model parameters for IMRT in the RayStation v.4.0 planning system and for a Varian C-series Linac with a 120-leaf Millennium MLC. Methods: The RayStation treatment planning system models rounded leaf-end MLC with the following parameters: average transmission, leaf-tip width, tongue-and-groove, and position offset. The position offset was provided by Varian. The leaf-tip width was iteratively evaluated by comparing computed and measured transverse dose profiles of MLC-defined fields at dmax in water. The profile comparison was also used to verify the MLC position offset. The transmission factor and leaf tongue width were derived iteratively by optimizing five clinical patient IMRT QA Results: brain, lung, pancreas, head-and-neck (HN), and prostate. The HN and prostate cases involved splitting fields. Verifications were performed with Mapcheck2 measurements and Monte Carlo calculations. Finally, the MLC model was validated using five test IMRT cases from the AAPM TG119 report. Absolute gamma analyses (3mm/3% and 2mm/2%) were applied. In addition, computed output factors for MLC-defined small fields (22, 33, 44, 66cm) of both 6MV and 18MV were compared to those measured by the Radiological Physics Center (RPC). Results: Both 6MV and 18MV models were determined to have the same MLC parameters: 2.5% transmission, tongue-and-groove 0.05cm, and leaftip 0.3cm. IMRT QA analysis for five cases in TG119 resulted in a 100% passing rate with 3mm/3% gamma analysis for 6MV, and >97.5% for 18MV. With 2mm/2% gamma analysis, the passing rate was >94.6% for 6MV and >90.9% for 18MV. The difference between computed output factors in RayStation and RPC measurements was less than 2% for all MLCdefined fields, which meets the RPC's acceptance criterion. Conclusion: The rounded leaf-end MLC model in RayStation 4.0 planning system was verified and IMRT commissioning was clinically acceptable. The IMRT commissioning was well validated using guidance from the
Adiabatic quantum optimization for associative memory recall
Seddiqi, Hadayat; Humble, Travis S.
2014-12-22
Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are stored in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.
Adiabatic quantum optimization for associative memory recall
Seddiqi, Hadayat; Humble, Travis S.
2014-12-22
Hopfield networks are a variant of associative memory that recall patterns stored in the couplings of an Ising model. Stored memories are conventionally accessed as fixed points in the network dynamics that correspond to energetic minima of the spin state. We show that memories stored in a Hopfield network may also be recalled by energy minimization using adiabatic quantum optimization (AQO). Numerical simulations of the underlying quantum dynamics allow us to quantify AQO recall accuracy with respect to the number of stored memories and noise in the input key. We investigate AQO performance with respect to how memories are storedmore » in the Ising model according to different learning rules. Our results demonstrate that AQO recall accuracy varies strongly with learning rule, a behavior that is attributed to differences in energy landscapes. Consequently, learning rules offer a family of methods for programming adiabatic quantum optimization that we expect to be useful for characterizing AQO performance.« less
Cofer, W.F.
1992-03-01
The microplane concrete material model is based upon assumptions regarding the behavior of the material components. At any point, the response to the strain tensor on arbitrarily oriented surfaces is considered. Simple, softening stress-strain relationships are assumed in directions perpendicular and parallel to the surfaces. The macroscopic material behavior is then composed of the sum of the effects. The implementation of this model into the explicit, nonlinear, dynamic finite element program, DYNA3D, is described. To avoid the spurious mesh sensitivity that accompanies material failure, a weighted integral strain averaging approach is used to ensure that softening is nonlocal. This method is shown to be effective for limiting the failure zone in a concrete rod subjected to an impulse loading. 36 refs., 7 figs.
Radial electric field 3D modeling for wire arrays driving dynamic hohlraums on Z.
Mock, Raymond Cecil
2007-06-01
The anode-cathode structure of the Z-machine wire array results in a higher negative radial electric field (Er) on the wires near the cathode relative to the anode. The magnitude of this field has been shown to anti-correlate with the axial radiation top/bottom symmetry in the DH (Dynamic Hohlraum). Using 3D modeling, the structure of this field is revealed for different wire-array configurations and for progressive mechanical alterations, providing insight for minimizing the negative Er on the wire array in the anode-to-cathode region of the DH. Also, the 3D model is compared to Sasorov's approximation, which describes Er at the surface of the wire in terms of wire-array parameters.
Kelic, Andjelka; Zagonel, Aldo A.
2008-12-01
A system dynamics model was developed in response to the apparent decline in STEM candidates in the United States and a pending shortage. The model explores the attractiveness of STEM and STEM careers focusing on employers and the workforce. Policies such as boosting STEM literacy, lifting the H-1B visa cap, limiting the offshoring of jobs, and maintaining training are explored as possible solutions. The system is complex, with many feedbacks and long time delays, so solutions that focus on a single point of the system are not effective and cannot solve the problem. A deeper understanding of parts of the system that have not been explored to date is necessary to find a workable solution.
A unified electrostatic and cavitation model for first-principles molecular dynamics in solution
Scherlis, D A; Fattebert, J; Gygi, F; Cococcioni, M; Marzari, N
2005-11-14
The electrostatic continuum solvent model developed by Fattebert and Gygi is combined with a first-principles formulation of the cavitation energy based on a natural quantum-mechanical definition for the surface of a solute. Despite its simplicity, the cavitation contribution calculated by this approach is found to be in remarkable agreement with that obtained by more complex algorithms relying on a large set of parameters. The model allows for very efficient Car-Parrinello simulations of finite or extended systems in solution, and demonstrates a level of accuracy as good as that of established quantum-chemistry continuum solvent methods. They apply this approach to the study of tetracyanoethylene dimers in dichloromethane, providing valuable structural and dynamical insights on the dimerization phenomenon.
Quench dynamics near a quantum critical point: Application to the sine-Gordon model
De Grandi, C.; Polkovnikov, A.; Gritsev, V.
2010-06-01
We discuss the quench dynamics near a quantum critical point focusing on the sine-Gordon model as a primary example. We suggest a unified approach to sudden and slow quenches, where the tuning parameter {lambda}(t) changes in time as {lambda}(t){approx}{upsilon}t{sup r}, based on the adiabatic expansion of the excitation probability in powers of {upsilon}. We show that the universal scaling of the excitation probability can be understood through the singularity of the generalized adiabatic susceptibility {chi}{sub 2r+2}({lambda}), which for sudden quenches (r=0) reduces to the fidelity susceptibility. In turn this class of susceptibilities is expressed through the moments of the connected correlation function of the quench operator. We analyze the excitations created after a sudden quench of the cosine potential using a combined approach of form-factors expansion and conformal perturbation theory for the low-energy and high-energy sector, respectively. We find the general scaling laws for the probability of exciting the system, the density of excited quasiparticles, the entropy and the heat generated after the quench. In the two limits where the sine-Gordon model maps to hard-core bosons and free massive fermions we provide the exact solutions for the quench dynamics and discuss the finite temperature generalizations.
Water Usage for In-Situ Oil Shale Retorting – A Systems Dynamics Model
Earl D. Mattson; Larry Hull; Kara Cafferty
2012-12-01
A system dynamic model was construction to evaluate the water balance for in-situ oil shale conversion. The model is based on a systems dynamics approach and uses the Powersim Studio 9™ software package. Three phases of an insitu retort were consider; a construction phase primarily accounts for water needed for drilling and water produced during dewatering, an operation phase includes the production of water from the retorting process, and a remediation phase water to remove heat and solutes from the subsurface as well as return the ground surface to its natural state. Throughout these three phases, the water is consumed and produced. Consumption is account for through the drill process, dust control, returning the ground water to its initial level and make up water losses during the remedial flushing of the retort zone. Production of water is through the dewatering of the retort zone, and during chemical pyrolysis reaction of the kerogen conversion. The major water consumption was during the remediation of the insitu retorting zone.
Modeling and Optimization of Direct Chill Casting to Reduce Ingot Cracking
Das, S.K.; Ningileri, S.; Long, Z.; Saito, K.; Khraisheh, M.; Hassan, M.H.; Kuwana, K.; Han, Q.; Viswanathan, S.; Sabau, A.S.; Clark, J.; Hyrn, J. (ANL)
2006-08-15
Approximately 68% of the aluminum produced in the United States is first cast into ingots prior to further processing into sheet, plate, extrusions, or foil. The direct chill (DC) semi-continuous casting process has been the mainstay of the aluminum industry for the production of ingots due largely to its robust nature and relative simplicity. Though the basic process of DC casting is in principle straightforward, the interaction of process parameters with heat extraction, microstructural evolution, and development of solidification stresses is too complex to analyze by intuition or practical experience. One issue in DC casting is the formation of stress cracks [1-15]. In particular, the move toward larger ingot cross-sections, the use of higher casting speeds, and an ever-increasing array of mold technologies have increased industry efficiencies but have made it more difficult to predict the occurrence of stress crack defects. The Aluminum Industry Technology Roadmap [16] has recognized the challenges inherent in the DC casting process and the control of stress cracks and selected the development of 'fundamental information on solidification of alloys to predict microstructure, surface properties, and stresses and strains' as a high-priority research need, and the 'lack of understanding of mechanisms of cracking as a function of alloy' and 'insufficient understanding of the aluminum solidification process', which is 'difficult to model', as technology barriers in aluminum casting processes. The goal of this Aluminum Industry of the Future (IOF) project was to assist the aluminum industry in reducing the incidence of stress cracks from the current level of 5% to 2%. Decreasing stress crack incidence is important for improving product quality and consistency as well as for saving resources and energy, since considerable amounts of cast metal could be saved by eliminating ingot cracking, by reducing the scalping thickness of the ingot before rolling, and by
Rong Xing; Ghaly, Michael; Frey, Eric C.
2013-06-15
Purpose: In yttrium-90 ({sup 90}Y) microsphere brachytherapy (radioembolization) of unresectable liver cancer, posttherapy {sup 90}Y bremsstrahlung single photon emission computed tomography (SPECT) has been used to document the distribution of microspheres in the patient and to help predict potential side effects. The energy window used during projection acquisition can have a significant effect on image quality. Thus, using an optimal energy window is desirable. However, there has been great variability in the choice of energy window due to the continuous and broad energy distribution of {sup 90}Y bremsstrahlung photons. The area under the receiver operating characteristic curve (AUC) for the ideal observer (IO) is a widely used figure of merit (FOM) for optimizing the imaging system for detection tasks. The IO implicitly assumes a perfect model of the image formation process. However, for {sup 90}Y bremsstrahlung SPECT there can be substantial model-mismatch (i.e., difference between the actual image formation process and the model of it assumed in reconstruction), and the amount of the model-mismatch depends on the energy window. It is thus important to account for the degradation of the observer performance due to model-mismatch in the optimization of the energy window. The purpose of this paper is to optimize the energy window for {sup 90}Y bremsstrahlung SPECT for a detection task while taking into account the effects of the model-mismatch. Methods: An observer, termed the ideal observer with model-mismatch (IO-MM), has been proposed previously to account for the effects of the model-mismatch on IO performance. In this work, the AUC for the IO-MM was used as the FOM for the optimization. To provide a clinically realistic object model and imaging simulation, the authors used a background-known-statistically and signal-known-statistically task. The background was modeled as multiple compartments in the liver with activity parameters independently following a
Integrated controls design optimization
Lou, Xinsheng; Neuschaefer, Carl H.
2015-09-01
A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.
DISSELKAMP RS
2011-01-06
Boehmite (e.g., aluminum oxyhydroxide) is a major non-radioactive component in Hanford and Savannah River nuclear tank waste sludge. Boehmite dissolution from sludge using caustic at elevated temperatures is being planned at Hanford to minimize the mass of material disposed of as high-level waste (HLW) during operation of the Waste Treatment Plant (WTP). To more thoroughly understand the chemistry of this dissolution process, we have developed an empirical kinetic model for aluminate production due to boehmite dissolution. Application of this model to Hanford tank wastes would allow predictability and optimization of the caustic leaching of aluminum solids, potentially yielding significant improvements to overall processing time, disposal cost, and schedule. This report presents an empirical kinetic model that can be used to estimate the aluminate production from the leaching of boehmite in Hanford waste as a function of the following parameters: (1) hydroxide concentration; (2) temperature; (3) specific surface area of boehmite; (4) initial soluble aluminate plus gibbsite present in waste; (5) concentration of boehmite in the waste; and (6) (pre-fit) Arrhenius kinetic parameters. The model was fit to laboratory, non-radioactive (e.g. 'simulant boehmite') leaching results, providing best-fit values of the Arrhenius A-factor, A, and apparent activation energy, E{sub A}, of A = 5.0 x 10{sup 12} hour{sup -1} and E{sub A} = 90 kJ/mole. These parameters were then used to predict boehmite leaching behavior observed in previously reported actual waste leaching studies. Acceptable aluminate versus leaching time profiles were predicted for waste leaching data from both Hanford and Savannah River site studies.
A NEW DYNAMICAL MODEL FOR THE BLACK HOLE BINARY LMC X-1
Orosz, Jerome A.; Steeghs, Danny; McClintock, Jeffrey E. E-mail: D.T.H.Steeghs@warwick.ac.uk
2009-05-20
We present a dynamical model of the high mass X-ray binary LMC X-1 based on high-resolution optical spectroscopy and extensive optical and near-infrared photometry. From our new optical data we find an orbital period of P = 3.90917 {+-} 0.00005 days. We present a refined analysis of the All Sky Monitor data from RXTE and find an X-ray period of P = 3.9094 {+-} 0.0008 days, which is consistent with the optical period. A simple model of Thomson scattering in the stellar wind can account for the modulation seen in the X-ray light curves. The V - K color of the star (1.17 {+-} 0.05) implies A{sub V} = 2.28 {+-} 0.06, which is much larger than previously assumed. For the secondary star, we measure a radius of R {sub 2} = 17.0 {+-} 0.8 R {sub sun} and a projected rotational velocity of V {sub rot}sin i = 129.9 {+-} 2.2 km s{sup -1}. Using these measured properties to constrain the dynamical model, we find an inclination of i = 36.{sup 0}38 {+-} 1.{sup 0}92, a secondary star mass of M {sub 2} = 31.79 {+-} 3.48 M {sub sun}, and a black hole mass of 10.91 {+-} 1.41 M {sub sun}. The present location of the secondary star in a temperature-luminosity diagram is consistent with that of a star with an initial mass of 35 M {sub sun} that is 5 Myr past the zero-age main sequence. The star nearly fills its Roche lobe ({approx}90% or more), and owing to the rapid change in radius with time in its present evolutionary state, it will encounter its Roche lobe and begin rapid and possibly unstable mass transfer on a timescale of a few hundred thousand years.
Dyson, Brian; Chang, N.-B. . E-mail: nchang@even.tamuk.edu
2005-07-01
Both planning and design of municipal solid waste management systems require accurate prediction of solid waste generation. Yet achieving the anticipated prediction accuracy with regard to the generation trends facing many fast-growing regions is quite challenging. The lack of complete historical records of solid waste quantity and quality due to insufficient budget and unavailable management capacity has resulted in a situation that makes the long-term system planning and/or short-term expansion programs intangible. To effectively handle these problems based on limited data samples, a new analytical approach capable of addressing socioeconomic and environmental situations must be developed and applied for fulfilling the prediction analysis of solid waste generation with reasonable accuracy. This study presents a new approach - system dynamics modeling - for the prediction of solid waste generation in a fast-growing urban area based on a set of limited samples. To address the impact on sustainable development city wide, the practical implementation was assessed by a case study in the city of San Antonio, Texas (USA). This area is becoming one of the fastest-growing regions in North America due to the economic impact of the North American Free Trade Agreement (NAFTA). The analysis presents various trends of solid waste generation associated with five different solid waste generation models using a system dynamics simulation tool - Stella[reg]. Research findings clearly indicate that such a new forecasting approach may cover a variety of possible causative models and track inevitable uncertainties down when traditional statistical least-squares regression methods are unable to handle such issues.
Narashimhan, T.N.; White, A.F.; Tokunaga, T.
1986-12-01
At Riverton, Wyoming, low pH process waters from an abandoned uranium mill tailings pile have been infiltrating into and contaminating the shallow water table aquifer. The contamination process has been governed by transient infiltration rates, saturated-unsaturated flow, as well as transient chemical reactions between the many chemical species present in the mixing waters and the sediments. In the first part of this two-part series the authors presented field data as well as an interpretation based on a static mixing models. As an upper bound, the authors estimated that 1.7% of the tailings water had mixed with the native groundwater. In the present work they present the results of numerical investigation of the dynamic mixing process. The model, DYNAMIX (DYNamic MIXing), couples a chemical speciation algorithm, PHREEQE, with a modified form of the transport algorithm, TRUMP, specifically designed to handle the simultaneous migration of several chemical constituents. The overall problem of simulating the evolution and migration of the contaminant plume was divided into three sub problems that were solved in sequential stages. These were the infiltration problem, the reactive mixing problem, and the plume-migration problem. The results of the application agree reasonably with the detailed field data. The methodology developed in the present study demonstrates the feasibility of analyzing the evolution of natural hydrogeochemical systems through a coupled analysis of transient fluid flow as well as chemical reactions. It seems worthwhile to devote further effort toward improving the physicochemical capabilities of the model as well as to enhance its computational efficiency.
Optimal charging profiles for mechanically constrained lithium-ion batteries
Suthar, B; Ramadesigan, V; De, S; Braatz, RD; Subramanian, VR
2014-01-01
The cost and safety related issues of lithium-ion batteries require intelligent charging profiles that can efficiently utilize the battery. This paper illustrates the application of dynamic optimization in obtaining the optimal current profile for charging a lithium-ion battery using a single-particle model while incorporating intercalation-induced stress generation. In this paper, we focus on the problem of maximizing the charge stored in a given time while restricting the development of stresses inside the particle. Conventional charging profiles for lithium-ion batteries (e.g., constant current followed by constant voltage) were not derived by considering capacity fade mechanisms. These charging profiles are not only inefficient in terms of lifetime usage of the batteries but are also slower since they do not exploit the changing dynamics of the system. Dynamic optimization based approaches have been used to derive optimal charging and discharging profiles with different objective functions. The progress made in understanding the capacity fade mechanisms has paved the way for inclusion of that knowledge in deriving optimal controls. While past efforts included thermal constraints, this paper for the first time presents strategies for optimally charging batteries by guaranteeing minimal mechanical damage to the electrode particles during intercalation. In addition, an executable form of the code has been developed and provided. This code can be used to identify optimal charging profiles for any material and design parameters.
Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. S.; Resat, Haluk
2012-10-02
The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of
Kaper, Tasso J. Kramer, Mark A.; Rotstein, Horacio G.
2013-12-15
Rhythmic neuronal oscillations across a broad range of frequencies, as well as spatiotemporal phenomena, such as waves and bumps, have been observed in various areas of the brain and proposed as critical to brain function. While there is a long and distinguished history of studying rhythms in nerve cells and neuronal networks in healthy organisms, the association and analysis of rhythms to diseases are more recent developments. Indeed, it is now thought that certain aspects of diseases of the nervous system, such as epilepsy, schizophrenia, Parkinson's, and sleep disorders, are associated with transitions or disruptions of neurological rhythms. This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases.
Model of fracture of metal melts and the strength of melts under dynamic conditions
Mayer, P. N. Mayer, A. E.
2015-07-15
The development of a continuum model of deformation and fracture of melts is needed for the description of the behavior of metals in extreme states, in particular, under high-current electron and ultrashort laser irradiation. The model proposed includes the equations of mechanics of a two-phase continuum and the equations of the kinetics of phase transitions. The change (exchange) of the volumes of dispersed and carrier phases and of the number of dispersed particles is described, and the energy and mass exchange between the phases due to phase transitions is taken into account. Molecular dynamic (MD) calculations are carried out with the use of the LAMMPS program. The continuum model is verified by MD, computational, and experimental data. The strength of aluminum, copper, and nickel is determined at various temperatures and strain rates. It is shown that an increase in the strain rate leads to an increase in the strength of a liquid metal, while an increase in temperature leads to a decrease in its strength.
Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics
Carlberg, Kevin; Tuminaro, Ray; Boggs, Paul
2015-03-11
Our work proposes a model-reduction methodology that preserves Lagrangian structure and achieves computational efficiency in the presence of high-order nonlinearities and arbitrary parameter dependence. As such, the resulting reduced-order model retains key properties such as energy conservation and symplectic time-evolution maps. We focus on parameterized simple mechanical systems subjected to Rayleigh damping and external forces, and consider an application to nonlinear structural dynamics. To preserve structure, the method first approximates the system's “Lagrangian ingredients''---the Riemannian metric, the potential-energy function, the dissipation function, and the external force---and subsequently derives reduced-order equations of motion by applying the (forced) Euler--Lagrange equation with thesemore » quantities. Moreover, from the algebraic perspective, key contributions include two efficient techniques for approximating parameterized reduced matrices while preserving symmetry and positive definiteness: matrix gappy proper orthogonal decomposition and reduced-basis sparsification. Our results for a parameterized truss-structure problem demonstrate the practical importance of preserving Lagrangian structure and illustrate the proposed method's merits: it reduces computation time while maintaining high accuracy and stability, in contrast to existing nonlinear model-reduction techniques that do not preserve structure.« less
Chandrasekhar Potluri,; Madhavi Anugolu; Marco P. Schoen; D. Subbaram Naidu
2013-08-01
In this work, an array of three surface Electrography (sEMG) sensors are used to acquired muscle extension and contraction signals for 18 healthy test subjects. The skeletal muscle force is estimated using the acquired sEMG signals and a Non-linear Wiener Hammerstein model, relating the two signals in a dynamic fashion. The model is obtained from using System Identification (SI) algorithm. The obtained force models for each sensor are fused using a proposed fuzzy logic concept with the intent to improve the force estimation accuracy and resilience to sensor failure or misalignment. For the fuzzy logic inference system, the sEMG entropy, the relative error, and the correlation of the force signals are considered for defining the membership functions. The proposed fusion algorithm yields an average of 92.49% correlation between the actual force and the overall estimated force output. In addition, the proposed fusionbased approach is implemented on a test platform. Experiments indicate an improvement in finger/hand force estimation.
Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions
Oprisan, Sorinel Adrian; Oprisan, Ana
2005-03-31
Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells -- EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.
U.S. Department of Energy (DOE) all webpages (Extended Search)
COER HYDRODYNAMIC MODELING COMPETITION: MODELING THE DYNAMIC RESPONSE OF A FLOATING BODY USING THE WEC-SIM AND FAST SIMULATION TOOLS Michael Lawson Braulio Barahona Garzon Fabian Wendt Yi-Hsiang Yu National Renewable Energy Laboratory Golden, Colorado, USA Carlos Michelen Sandia National Laboratories Albuquerque, New Mexico, USA ABSTRACT The Center for Ocean Energy Research (COER) at the University of Maynooth in Ireland organized a hydrodynamic modeling competition in conjunction with OMAE2015.
Zhou, Zhi; de Bedout, Juan Manuel; Kern, John Michael; Biyik, Emrah; Chandra, Ramu Sharat
2013-01-22
A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.
Moro, Erik A.
2012-06-07
Optical fiber sensors offer advantages over traditional electromechanical sensors, making them particularly well-suited for certain measurement applications. Generally speaking, optical fiber sensors respond to a desired measurand through modulation of an optical signal's intensity, phase, or wavelength. Practically, non-contacting fiber optic displacement sensors are limited to intensity-modulated and interferometric (or phase-modulated) methodologies. Intensity-modulated fiber optic displacement sensors relate target displacement to a power measurement. The simplest intensity-modulated sensor architectures are not robust to environmental and hardware fluctuations, since such variability may cause changes in the measured power level that falsely indicate target displacement. Differential intensity-modulated sensors have been implemented, offering robustness to such intensity fluctuations, and the speed of these sensors is limited only by the combined speed of the photodetection hardware and the data acquisition system (kHz-MHz). The primary disadvantages of intensity-modulated sensing are the relatively low accuracy (?m-mm for low-power sensors) and the lack of robustness, which consequently must be designed, often with great difficulty, into the sensor's architecture. White light interferometric displacement sensors, on the other hand, offer increased accuracy and robustness. Unlike their monochromatic-interferometer counterparts, white light interferometric sensors offer absolute, unambiguous displacement measurements over large displacement ranges (cm for low-power, 5 mW, sources), necessitating no initial calibration, and requiring no environmental or feedback control. The primary disadvantage of white light interferometric displacement sensors is that their utility in dynamic testing scenarios is limited, both by hardware bandwidth and by their inherent high-sensitivity to Doppler-effects. The decision of whether to use either an intensity
U.S. Department of Energy (DOE) all webpages (Extended Search)
gasifier optimization The Gasifier Optimization and Plant Supporting Systems key technology area focuses on improving the performance and reducing the costs of advanced gasifiers. Specifically, current projects focus on creating models to better understand the kinetics and particulate behavior of fuel inside a gasifier. This work supports development of a highly advanced gasifier optimally configured with its supporting systems, which would incorporate the most aggressive and successful
Modelling on dynamics properties of a stationary argon cascaded arc plasma flows
Wei, G. D.; Qi, X.; Yang, L.
2014-03-15
The gas dynamics properties of a stationary arc plasma flows are studied through the numerical simulations. A two dimensional axis-symmetric turbulent magneto-hydrodynamic plasma model is developed with the commercial code ANSYS FLUENT. The reliable ?-? model is used to account for turbulence. In this paper, the plasma is assumed to be a fluid following NavierStokes equations, respecting local thermodynamic equilibrium, and described by only one temperature. Distributions of the pressure, velocity, temperature, density, and electric potential inside of thus cascaded arc are obtained for an arc current density of 10{sup 6}?A/m{sup 2}. The pressure inside the arc varies from 10{sup 5}?Pa to 100?Pa. The temperature at the arc axis can reach as high as 13?600?K. The electric potential drops uniformly along the axis with a magnitude of 160?V. In addition, distributions of the sonic velocity and Mach number are shown to describe supersonic behavior of thus cascaded arc, which have a good agreement with the analytical formula.
Wind Turbine Modeling for Computational Fluid Dynamics: December 2010 - December 2012
Tossas, L. A. M.; Leonardi, S.
2013-07-01
With the shortage of fossil fuel and the increasing environmental awareness, wind energy is becoming more and more important. As the market for wind energy grows, wind turbines and wind farms are becoming larger. Current utility-scale turbines extend a significant distance into the atmospheric boundary layer. Therefore, the interaction between the atmospheric boundary layer and the turbines and their wakes needs to be better understood. The turbulent wakes of upstream turbines affect the flow field of the turbines behind them, decreasing power production and increasing mechanical loading. With a better understanding of this type of flow, wind farm developers could plan better-performing, less maintenance-intensive wind farms. Simulating this flow using computational fluid dynamics is one important way to gain a better understanding of wind farm flows. In this study, we compare the performance of actuator disc and actuator line models in producing wind turbine wakes and the wake-turbine interaction between multiple turbines. We also examine parameters that affect the performance of these models, such as grid resolution, the use of a tip-loss correction, and the way in which the turbine force is projected onto the flow field.
Nomura, K.; Vretenar, D.; Niksic, T.; Otsuka, T.; Shimizu, N.
2011-07-15
Microscopic energy density functionals have become a standard tool for nuclear structure calculations, providing an accurate global description of nuclear ground states and collective excitations. For spectroscopic applications, this framework has to be extended to account for collective correlations related to restoration of symmetries broken by the static mean field, and for fluctuations of collective variables. In this paper, we compare two approaches to five-dimensional quadrupole dynamics: the collective Hamiltonian for quadrupole vibrations and rotations and the interacting boson model (IBM). The two models are compared in a study of the evolution of nonaxial shapes in Pt isotopes. Starting from the binding energy surfaces of {sup 192,194,196}Pt, calculated with a microscopic energy density functional, we analyze the resulting low-energy collective spectra obtained from the collective Hamiltonian, and the corresponding IBM Hamiltonian. The calculated excitation spectra and transition probabilities for the ground-state bands and the {gamma}-vibration bands are compared to the corresponding sequences of experimental states.
Brigantic, Robert T.; Papatyi, Anthony F.; Perkins, Casey J.
2010-09-30
This report summarizes a study and corresponding model development conducted in support of the United States Pacific Command (USPACOM) as part of the Federal Energy Management Program (FEMP) American Reinvestment and Recovery Act (ARRA). This research was aimed at developing a mathematical programming framework and accompanying optimization methodology in order to simultaneously evaluate energy efficiency (EE) and renewable energy (RE) opportunities. Once developed, this research then demonstrated this methodology at a USPACOM installation - Camp H.M. Smith, Hawaii. We believe this is the first time such an integrated, joint EE and RE optimization methodology has been constructed and demonstrated.
Yuan Hongping; Chini, Abdol R.; Lu Yujie; Shen Liyin
2012-03-15
Highlights: Black-Right-Pointing-Pointer We proposes a model for projecting C and D waste reduction of construction projects. Black-Right-Pointing-Pointer The model can simulate effects of various management strategies on waste reduction. Black-Right-Pointing-Pointer The model integrates all essential variables that affect C and D waste reduction. Black-Right-Pointing-Pointer By using the model, best strategies could be identified before being implemented. - Abstract: During the past few decades, construction and demolition (C and D) waste has received increasing attention from construction practitioners and researchers worldwide. A plethora of research regarding C and D waste management has been published in various academic journals. However, it has been determined that existing studies with respect to C and D waste reduction are mainly carried out from a static perspective, without considering the dynamic and interdependent nature of the whole waste reduction system. This might lead to misunderstanding about the actual effect of implementing any waste reduction strategies. Therefore, this research proposes a model that can serve as a decision support tool for projecting C and D waste reduction in line with the waste management situation of a given construction project, and more importantly, as a platform for simulating effects of various management strategies on C and D waste reduction. The research is conducted using system dynamics methodology, which is a systematic approach that deals with the complexity - interrelationships and dynamics - of any social, economic and managerial system. The dynamic model integrates major variables that affect C and D waste reduction. In this paper, seven causal loop diagrams that can deepen understanding about the feedback relationships underlying C and D waste reduction system are firstly presented. Then a stock-flow diagram is formulated by using software for system dynamics modeling. Finally, a case study is used to
Zuo, Wangda; Chen, Qingyan
2011-06-01
To design a healthy indoor environment, it is important to study airborne particle distribution indoors. As an intermediate model between multizone models and computational fluid dynamics (CFD), a fast fluid dynamics (FFD) model can be used to provide temporal and spatial information of particle dispersion in real time. This study evaluated the accuracy of the FFD for predicting transportation of particles with low Stokes number in a duct and in a room with mixed convection. The evaluation was to compare the numerical results calculated by the FFD with the corresponding experimental data and the results obtained by the CFD. The comparison showed that the FFD could capture major pattern of particle dispersion, which is missed in models with well-mixed assumptions. Although the FFD was less accurate than the CFD partially due to its simplification in numeric schemes, it was 53 times faster than the CFD.
William J. Gutowski; Joseph M. Prusa, Piotr K. Smolarkiewicz
2012-04-09
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.
Control and optimization system
Xinsheng, Lou
2013-02-12
A system for optimizing a power plant includes a chemical loop having an input for receiving an input parameter (270) and an output for outputting an output parameter (280), a control system operably connected to the chemical loop and having a multiple controller part (230) comprising a model-free controller. The control system receives the output parameter (280), optimizes the input parameter (270) based on the received output parameter (280), and outputs an optimized input parameter (270) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.
U.S. Department of Energy (DOE) all webpages (Extended Search)
COER Hydrodynamic Modeling Competition: Modeling the Dynamic Response of a Floating Body Using the WEC-Sim and FAST Simulation Tools Preprint M. Lawson, B. Barahona Garzon, F. Wendt, and Y-H. Yu National Renewable Energy Laboratory C. Michelen Sandia National Laboratories To be presented at the 34 th International Conference on Ocean, Offshore, and Arctic Engineering (OMAE 2015) St. John's, Newfoundland, Canada May 31-June 5, 2015 Conference Paper NREL/CP-5000-63594 March 2015 NOTICE The
Quantum diffusion dynamics in nonlinear systems: A modified kicked-rotor model
Gong Jiangbin [Department of Physics and Centre of Computational Science and Engineering, National University of Singapore, 117542 (Singapore); Wang Jiao [Temasek Laboratories and Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex Systems (Singapore), National University of Singapore, 117542 (Singapore)
2007-09-15
Using a simple method analogous to a quantum rephasing technique, a simple modification to a paradigm of classical and quantum chaos is proposed. The interesting quantum maps thus obtained display remarkably rich quantum dynamics. Emphasis is placed on the destruction of dynamical localization without breaking periodicity, unbounded quantum anomalous diffusion in integrable systems, and transient dynamical localization. Experimental realizations of this work are also discussed.
Quasi-static and dynamic responses of advanced high strength steels: Experiments and modeling
Khan, Akhtar; Baig, Muneer; Choi, Shi Hoon; Yang, Hoe Seok; Sun, Xin
2012-03-01
Measured responses of advanced high strength steels (AHSS) and their tailor welded blanks (TWBs), over a wide range of strain-rates (10*4 to 103 s*1) are presented. The steels investigated include transformation induced plasticity (TRIP), dual phase (DP), and drawing quality (DQ) steels. The TWBs include DQ-DQ and DP-DP laser welds. A tensile split Hopkinson pressure bar (SHPB) was used for the dynamic experiments. AHSS and their TWB's were found to exhibit positive strain-rate sensitivity. The Khan-Huang-Liang (KHL) constitutive model is shown to correlate and predict the observed responses reasonably well. Micro-texture characterization of DQ steels, DQ-DQ and DP-DP laser welds were performed to investigate the effect of strain-rate on texture evolution of these materials. Electron backscatter diffraction (EBSD) technique was used to analyze the micro-texture evolution and kernel average misorientation (KAM) map. Measurement of micro-hardness profile across the cross section of tensile samples was conducted to understand the effect of initial microstructure on ductility of laser weld samples.
A Numerical Model For The Dynamics Of Pyroclastic Flows At Galeras...
Open Energy Information (Open El) [EERE & EIA]
with the time; (2) dynamic pressure change; and (3) particle concentration along the computer domain from the eruption to the impact with a topographic barrier located more than...
State-of-the-art review of computational fluid dynamics modeling for fluid-solids systems
Lyczkowski, R.W.; Bouillard, J.X.; Ding, J.; Chang, S.L.; Burge, S.W.
1994-05-12
As the result of 15 years of research (50 staff years of effort) Argonne National Laboratory (ANL), through its involvement in fluidized-bed combustion, magnetohydrodynamics, and a variety of environmental programs, has produced extensive computational fluid dynamics (CFD) software and models to predict the multiphase hydrodynamic and reactive behavior of fluid-solids motions and interactions in complex fluidized-bed reactors (FBRS) and slurry systems. This has resulted in the FLUFIX, IRF, and SLUFIX computer programs. These programs are based on fluid-solids hydrodynamic models and can predict information important to the designer of atmospheric or pressurized bubbling and circulating FBR, fluid catalytic cracking (FCC) and slurry units to guarantee optimum efficiency with minimum release of pollutants into the environment. This latter issue will become of paramount importance with the enactment of the Clean Air Act Amendment (CAAA) of 1995. Solids motion is also the key to understanding erosion processes. Erosion rates in FBRs and pneumatic and slurry components are computed by ANL`s EROSION code to predict the potential metal wastage of FBR walls, intervals, feed distributors, and cyclones. Only the FLUFIX and IRF codes will be reviewed in the paper together with highlights of the validations because of length limitations. It is envisioned that one day, these codes with user-friendly pre and post-processor software and tailored for massively parallel multiprocessor shared memory computational platforms will be used by industry and researchers to assist in reducing and/or eliminating the environmental and economic barriers which limit full consideration of coal, shale and biomass as energy sources, to retain energy security, and to remediate waste and ecological problems.
Nopharatana, Annop; Pullammanappallil, Pratap C.; Clarke, William P.
2007-07-01
A series of batch, slurry anaerobic digestion experiments were performed where the soluble and insoluble fractions, and unwashed MSW were separately digested in a 200 l stirred stainless steel vessel at a pH of 7.2 and a temperature of 38 deg. C. It was found that 7% of the total MSW COD was readily soluble, of which 80% was converted to biogas; 50% of the insoluble fraction was solubilised, of this only 80% was converted to biogas. The rate of digesting the insoluble fraction was about four times slower than the rate of digesting the soluble fraction; 48% of the total COD was converted to biogas and 40% of the total nitrogen was converted to ammonia. Soluble and insoluble fractions were broken down simultaneously. The minimum time to convert 95% of the degradable fraction to biogas was 20 days. The lag phase for the degradation of insoluble fraction of MSW can be overcome by acclimatising the culture with the soluble fraction. The rate of digestion and the methane yield was not affected by particle size (within the range of 2-50 mm). A dynamic model was developed to describe batch digestion of MSW. The parameters of the model were estimated using data from the separate digestion of soluble and insoluble fractions and validated against data from the digestion of unwashed MSW. Trends in the specific aceticlastic and formate-utilising methanogenic activity were used to estimate initial methanogenic biomass concentration and bacterial death rate coefficient. The kinetics of hydrolysis of insoluble fraction could be adequately described by a Contois equation and the kinetics of acidogenesis, and aceticlastic and hydrogen utilising methanogenesis by Monod equations.
Eranki, Pragnya L.; Manowitz, David H.; Bals, Bryan D.; Izaurralde, Roberto C.; Kim, Seungdo; Dale, Bruce E.
2013-07-23
An array of feedstock is being evaluated as potential raw material for cellulosic biofuel production. Thorough assessments are required in regional landscape settings before these feedstocks can be cultivated and sustainable management practices can be implemented. On the processing side, a potential solution to the logistical challenges of large biorefi neries is provided by a network of distributed processing facilities called local biomass processing depots. A large-scale cellulosic ethanol industry is likely to emerge soon in the United States. We have the opportunity to influence the sustainability of this emerging industry. The watershed-scale optimized and rearranged landscape design (WORLD) model estimates land allocations for different cellulosic feedstocks at biorefinery scale without displacing current animal nutrition requirements. This model also incorporates a network of the aforementioned depots. An integrated life cycle assessment is then conducted over the unified system of optimized feedstock production, processing, and associated transport operations to evaluate net energy yields (NEYs) and environmental impacts.
Joseph W. Nielsen; Akira Tokurio; Robert Hiromoto; Jivan Khatry
2014-06-01
Traditional Probabilistic Risk Assessment (PRA) methods have been developed and are quite effective in evaluating risk associated with complex systems, but lack the capability to evaluate complex dynamic systems. These time and energy scales associated with the transient may vary as a function of transition time to a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems, while complete, results in issues associated with combinatorial explosion. In order to address the combinatorial complexity arising from the number of possible state configurations and discretization of transition times, a characteristic scaling metric (LENDIT length, energy, number, distribution, information and time) is proposed as a means to describe systems uniformly and thus provide means to describe relational constraints expected in the dynamics of a complex (coupled) systems. Thus when LENDIT is used to characterize four sets state, system, resource and response (S2R2) describing reactor operations (normal and off-normal), LENDIT and S2R2 in combination have the potential to branch and bound the state space investigated by DPRA. In this paper we introduce the concept of LENDIT scales and S2R2 sets applied to a branch-and-bound algorithm and apply the methods to a station black out transient (SBO).
Kollikkathara, Naushad; Feng Huan; Yu Danlin
2010-11-15
As planning for sustainable municipal solid waste management has to address several inter-connected issues such as landfill capacity, environmental impacts and financial expenditure, it becomes increasingly necessary to understand the dynamic nature of their interactions. A system dynamics approach designed here attempts to address some of these issues by fitting a model framework for Newark urban region in the US, and running a forecast simulation. The dynamic system developed in this study incorporates the complexity of the waste generation and management process to some extent which is achieved through a combination of simpler sub-processes that are linked together to form a whole. The impact of decision options on the generation of waste in the city, on the remaining landfill capacity of the state, and on the economic cost or benefit actualized by different waste processing options are explored through this approach, providing valuable insights into the urban waste-management process.
March-Leuba, S.; Jansen, J.F.; Kress, R.L.; Babcock, S.M. ); Dubey, R.V. . Dept. of Mechanical and Aerospace Engineering)
1992-08-01
A new program package, Symbolic Manipulator Laboratory (SML), for the automatic generation of both kinematic and static manipulator models in symbolic form is presented. Critical design parameters may be identified and optimized using symbolic models as shown in the sample application presented for the Future Armor Rearm System (FARS) arm. The computer-aided development of the symbolic models yields equations with reduced numerical complexity. Important considerations have been placed on the closed form solutions simplification and on the user friendly operation. The main emphasis of this research is the development of a methodology which is implemented in a computer program capable of generating symbolic kinematic and static forces models of manipulators. The fact that the models are obtained trigonometrically reduced is among the most significant results of this work and the most difficult to implement. Mathematica, a commercial program that allows symbolic manipulation, is used to implement the program package. SML is written such that the user can change any of the subroutines or create new ones easily. To assist the user, an on-line help has been written to make of SML a user friendly package. Some sample applications are presented. The design and optimization of the 5-degrees-of-freedom (DOF) FARS manipulator using SML is discussed. Finally, the kinematic and static models of two different 7-DOF manipulators are calculated symbolically.
March-Leuba, S.; Jansen, J.F.; Kress, R.L.; Babcock, S.M.; Dubey, R.V.
1992-08-01
A new program package, Symbolic Manipulator Laboratory (SML), for the automatic generation of both kinematic and static manipulator models in symbolic form is presented. Critical design parameters may be identified and optimized using symbolic models as shown in the sample application presented for the Future Armor Rearm System (FARS) arm. The computer-aided development of the symbolic models yields equations with reduced numerical complexity. Important considerations have been placed on the closed form solutions simplification and on the user friendly operation. The main emphasis of this research is the development of a methodology which is implemented in a computer program capable of generating symbolic kinematic and static forces models of manipulators. The fact that the models are obtained trigonometrically reduced is among the most significant results of this work and the most difficult to implement. Mathematica, a commercial program that allows symbolic manipulation, is used to implement the program package. SML is written such that the user can change any of the subroutines or create new ones easily. To assist the user, an on-line help has been written to make of SML a user friendly package. Some sample applications are presented. The design and optimization of the 5-degrees-of-freedom (DOF) FARS manipulator using SML is discussed. Finally, the kinematic and static models of two different 7-DOF manipulators are calculated symbolically.
Malikopoulos, Andreas
2015-01-01
The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion. Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.
Malikopoulos, Andreas
2015-01-01
The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and we show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.more » Both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.« less
Harrison, Alan K; Shashkov, Mikhail J; Fung, Jimmy; Canfield, Thomas R; Kamm, James R
2010-10-14
We have extended the Sub-Scale Dynamics (SSD) closure model for multi-fluid computational cells. Volume exchange between two materials is based on the interface area and a notional interface translation velocity, which is derived from a linearized Riemann solution. We have extended the model to cells with any number of materials, computing pressure-difference-driven volume and energy exchange as the algebraic sum of pairwise interactions. In multiple dimensions, we rely on interface reconstruction to provide interface areas and orientations, and centroids of material polygons. In order to prevent unphysically large or unmanageably small material volumes, we have used a flux-corrected transport (FCT) approach to limit the pressure-driven part of the volume exchange. We describe the implementation of this model in two dimensions in the FLAG hydrodynamics code. We also report on Lagrangian test calculations, comparing them with others made using a mixed-zone closure model due to Tipton, and with corresponding calculations made with only single-material cells. We find that in some cases, the SSD model more accurately predicts the state of material in mixed cells. By comparing the algebraic forms of both models, we identify similar dependencies on state and dynamical variables, and propose explanations for the apparent higher fidelity of the SSD model.
U.S. Department of Energy (DOE) all 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 the most effient use of NERSC HPSS: File sizes of about 1 GB or larger will give the best network performance (see graph below) Files sizes greater than about 500 GB can be more difficult to work with and lead to longer transfer times. Files larger than 15 TB cannot be uploaded to HPSS. Aggregate groups of small files
U.S. Department of Energy (DOE) all webpages (Extended Search)
IPR 2008 Capital Investment Review CIR 2012 Quarterly Business Review Focus 2028 2011 Strategic Capital Discussions Access to Capital Debt Optimization Asset Management Cost...
Compartment modeling of dynamic brain PETThe impact of scatter corrections on parameter errors
Hggstrm, Ida Karlsson, Mikael; Larsson, Anne; Schmidtlein, C. Ross
2014-11-01
Purpose: The aim of this study was to investigate the effect of scatter and its correction on kinetic parameters in dynamic brain positron emission tomography (PET) tumor imaging. The 2-tissue compartment model was used, and two different reconstruction methods and two scatter correction (SC) schemes were investigated. Methods: The GATE Monte Carlo (MC) software was used to perform 2 15 full PET scan simulations of a voxelized head phantom with inserted tumor regions. The two sets of kinetic parameters of all tissues were chosen to represent the 2-tissue compartment model for the tracer 3?-deoxy-3?-({sup 18}F)fluorothymidine (FLT), and were denoted FLT{sub 1} and FLT{sub 2}. PET data were reconstructed with both 3D filtered back-projection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM). Images including true coincidences with attenuation correction (AC) and true+scattered coincidences with AC and with and without one of two applied SC schemes were reconstructed. Kinetic parameters were estimated by weighted nonlinear least squares fitting of image derived timeactivity curves. Calculated parameters were compared to the true input to the MC simulations. Results: The relative parameter biases for scatter-eliminated data were 15%, 16%, 4%, 30%, 9%, and 7% (FLT{sub 1}) and 13%, 6%, 1%, 46%, 12%, and 8% (FLT{sub 2}) for K{sub 1}, k{sub 2}, k{sub 3}, k{sub 4}, V{sub a}, and K{sub i}, respectively. As expected, SC was essential for most parameters since omitting it increased biases by 10 percentage points on average. SC was not found necessary for the estimation of K{sub i} and k{sub 3}, however. There was no significant difference in parameter biases between the two investigated SC schemes or from parameter biases from scatter-eliminated PET data. Furthermore, neither 3DRP nor OSEM yielded the smallest parameter biases consistently although there was a slight favor for 3DRP which produced less biased k{sub 3} and K{sub i} estimates while
Colvin, J D; Minich, R W; Kalantar, D H
2007-03-29
The recent diagnostic capability of the Omega laser to study solid-solid phase transitions at pressures greater than 10 GPa and at strain rates exceeding 10{sup 7} s{sup -1} has also provided valuable information on the dynamic elastic-plastic behavior of materials. We have found, for example, that plasticity kinetics modifies the effective loading and thermodynamic paths of the material. In this paper we derive a kinetics equation for the time-dependent plastic response of the material to dynamic loading, and describe the model's implementation in a radiation-hydrodynamics computer code. This model for plasticity kinetics incorporates the Gilman model for dislocation multiplication and saturation. We discuss the application of this model to the simulation of experimental velocity interferometry data for experiments on Omega in which Fe was shock compressed to pressures beyond the {alpha}-to-{var_epsilon} phase transition pressure. The kinetics model is shown to fit the data reasonably well in this high strain rate regime and further allows quantification of the relative contributions of dislocation multiplication and drag. The sensitivity of the observed signatures to the kinetics model parameters is presented.
U.S. Department of Energy (DOE) all webpages (Extended Search)
Tropical Cirrus Cloud Properties and Dynamical Processes Derived from ECMWF Model Output and Ground-Based Measurements Over Nauru Island J. M. Comstock and J. H. Mather Pacific Northwest National Laboratory Richland, Washington C. Jakob Bureau of Meteorology Research Centre Melbourne, Australia Introduction Identifying the mechanisms responsible for the formation of cirrus clouds is important in understanding the role of cirrus in the tropical atmosphere. Thin cirrus clouds near the tropical
Skinner, F. K.; Department of Medicine , University of Toronto, 200 Elizabeth Street, Toronto, Ontario M5G 2C4; Department of Physiology, University of Toronto Medical Sciences Building, 3rd Floor, 1 King's College Circle, Toronto, Ontario M5S 1A8 ; Ferguson, K. A.; Department of Physiology, University of Toronto Medical Sciences Building, 3rd Floor, 1 King's College Circle, Toronto, Ontario M5S 1A8
2013-12-15
There is an undisputed need and requirement for theoretical and computational studies in Neuroscience today. Furthermore, it is clear that oscillatory dynamical output from brain networks is representative of various behavioural states, and it is becoming clear that one could consider these outputs as measures of normal and pathological brain states. Although mathematical modeling of oscillatory dynamics in the context of neurological disease exists, it is a highly challenging endeavour because of the many levels of organization in the nervous system. This challenge is coupled with the increasing knowledge of cellular specificity and network dysfunction that is associated with disease. Recently, whole hippocampus in vitro preparations from control animals have been shown to spontaneously express oscillatory activities. In addition, when using preparations derived from animal models of disease, these activities show particular alterations. These preparations present an opportunity to address challenges involved with using models to gain insight because of easier access to simultaneous cellular and network measurements, and pharmacological modulations. We propose that by developing and using models with direct links to experiment at multiple levels, which at least include cellular and microcircuit, a cycling can be set up and used to help us determine critical mechanisms underlying neurological disease. We illustrate our proposal using our previously developed inhibitory network models in the context of these whole hippocampus preparations and show the importance of having direct links at multiple levels.
Synchronized Phasor Data for Analyzing Wind Power Plant Dynamic Behavior and Model Validation
Wan, Y. H.
2013-01-01
The U.S. power industry is undertaking several initiatives that will improve the operations of the power grid. One of those is the implementation of 'wide area measurements' using phasor measurement units (PMUs) to dynamically monitor the operations and the status of the network and provide advanced situational awareness and stability assessment. This project seeks to obtain PMU data from wind power plants and grid reference points and develop software tools to analyze and visualize synchrophasor data for the purpose of better understanding wind power plant dynamic behaviors under normal and contingency conditions.
Grotjahn, Richard; Black, Robert; Leung, Ruby; Wehner, Michael F.; Barlow, Mathew; Bosilovich, Michael; Gershunov, Alexander; Gutowski, Jr., William J.; Gyakum, John R.; Katz, Richard W.; Lee, Yun -Young; Lim, Young -Kwon; Prabhat, -
2015-05-22
This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic to planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so more
Grotjahn, Richard; Black, Robert; Leung, Ruby; Wehner, Michael F.; Barlow, Mathew; Bosilovich, Michael; Gershunov, Alexander; Gutowski, Jr., William J.; Gyakum, John R.; Katz, Richard W.; et al
2015-05-22
This paper reviews research approaches and open questions regarding data, statistical analyses, dynamics, modeling efforts, and trends in relation to temperature extremes. Our specific focus is upon extreme events of short duration (roughly less than 5 days) that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). Methods used to define extreme events statistics and to identify and connect LSMPs to extreme temperatures are presented. Recent advances in statistical techniques can connect LSMPs to extreme temperatures through appropriately defined covariates that supplements more straightforward analyses. A wide array of LSMPs, ranging from synoptic tomore » planetary scale phenomena, have been implicated as contributors to extreme temperature events. Current knowledge about the physical nature of these contributions and the dynamical mechanisms leading to the implicated LSMPs is incomplete. There is a pressing need for (a) systematic study of the physics of LSMPs life cycles and (b) comprehensive model assessment of LSMP-extreme temperature event linkages and LSMP behavior. Generally, climate models capture the observed heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreaks frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Climate models have been used to investigate past changes and project future trends in extreme temperatures. Overall, modeling studies have identified important mechanisms such as the effects of large-scale circulation anomalies and land-atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs more specifically to understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated so
Energy Science and Technology Software Center (OSTI)
1998-04-20
PRODMOD is an integrated computational tool for performing dynamic simulation and optimization for the entire high level waste complex at the Savannah River Site (SRS) It is being used at SRS for planning purposes so that all waste can be processed efficiently. The computational tool 1) optimizes waste blending sequences, 2) minimizes waste volume production, 3) reduces waste processing time, 4) provides better process control and understanding, and 5) assists strategic planning, scheduling, and costmore » estimation. PRODMOD has been developed using Aspen Technology''s software development package SPEEDUP. PRODMOD models all the key HLW processing operations at SRS: storage and evaporation: saltcake production and dissolution: filtration (dewatering): precipitation: sludge and precipitate washing: glass, grout, and organics production. Innovative approaches have been used in making PRODMOD a very fast computational tool. These innovative approaches are 1) constructing a dynamic problem as a steady state problem 2) mapping between event-space (batch processes) and time-space (dynamic processes) without sacrificing the details in the batch process. The dynamic nature of the problem is constructed in linear form where time dependence is implicit. The linear constructs and mapping algorithms have made it possible to devise a general purpose optimization scheme which couples the optimization driver with the PRODMOD simulator. The optimization scheme is capable of generating single or multiple optimal input conditions for different types of objective functions over single or multiple years of operations depending on the nature of the objective function and operating constraints.« less
U.S. Department of Energy (DOE) all webpages (Extended Search)
Copyright © 2016, Intel Corporation. All rights reserved. *Other names and brands may be claimed as the property of others. Optimization Notice 2 Agenda Scaling with MPI Performance Snapshot Tuning MPI Performance with Intel® Trace Analyzer and Collector Copyright © 2016, Intel Corporation. All rights reserved. *Other names and brands may be claimed as the property of others. Optimization Notice 4 Application Growth Problem Growth Cluster Growth Application/Tool Performance Application Size
Browning, J. R.; Jonkman, J.; Robertson, A.; Goupee, A. J.
2014-01-01
In this study, high-quality computer simulations are required when designing floating wind turbines because of the complex dynamic responses that are inherent with a high number of degrees of freedom and variable metocean conditions. In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50th scale inmore » a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states. Wave basin tests with the spar attached to a scale model of the NREL 5-megawatt reference wind turbine were performed at the Maritime Research Institute Netherlands under the DeepCwind project. This project included free-decay tests, tests with steady or turbulent wind and still water (both periodic and irregular waves with no wind), and combined wind/wave tests. The resulting data from the 1/50th model was scaled using Froude scaling to full size and used to calibrate and validate a full-size simulated model in FAST. Results of the model calibration and validation include successes, subtleties, and limitations of both wave basin testing and FAST modeling capabilities.« less
Browning, J. R.; Jonkman, J.; Robertson, A.; Goupee, A. J.
2014-01-01
In this study, high-quality computer simulations are required when designing floating wind turbines because of the complex dynamic responses that are inherent with a high number of degrees of freedom and variable metocean conditions. In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50^{th} scale in a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states. Wave basin tests with the spar attached to a scale model of the NREL 5-megawatt reference wind turbine were performed at the Maritime Research Institute Netherlands under the DeepCwind project. This project included free-decay tests, tests with steady or turbulent wind and still water (both periodic and irregular waves with no wind), and combined wind/wave tests. The resulting data from the 1/50th model was scaled using Froude scaling to full size and used to calibrate and validate a full-size simulated model in FAST. Results of the model calibration and validation include successes, subtleties, and limitations of both wave basin testing and FAST modeling capabilities.
Vanderbei, Robert J.; P Latin-Small-Letter-Dotless-I nar, Mustafa C.; Bozkaya, Efe B.
2013-02-15
An American option (or, warrant) is the right, but not the obligation, to purchase or sell an underlying equity at any time up to a predetermined expiration date for a predetermined amount. A perpetual American option differs from a plain American option in that it does not expire. In this study, we solve the optimal stopping problem of a perpetual American option (both call and put) in discrete time using linear programming duality. Under the assumption that the underlying stock price follows a discrete time and discrete state Markov process, namely a geometric random walk, we formulate the pricing problem as an infinite dimensional linear programming (LP) problem using the excessive-majorant property of the value function. This formulation allows us to solve complementary slackness conditions in closed-form, revealing an optimal stopping strategy which highlights the set of stock-prices where the option should be exercised. The analysis for the call option reveals that such a critical value exists only in some cases, depending on a combination of state-transition probabilities and the economic discount factor (i.e., the prevailing interest rate) whereas it ceases to be an issue for the put.
Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application
Hale, Richard Edward; Cetiner, Sacit M.; Fugate, David L.; Batteh, John J; Tiller, Michael M.
2015-01-01
Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individual component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.
RF system models for the CERN Large Hadron Collider with application to longitudinal dynamics
Mastorides, T.; Rivetta, C.; Fox, J.D.; Winkle, D.Van; Baudrenghien, P.; /CERN
2011-03-03
The LHC RF station-beam interaction strongly influences the longitudinal beam dynamics, both single bunch and collective effects. Non-linearities and noise generated within the Radio Frequency (RF) accelerating system interact with the beam and contribute to beam motion and longitudinal emittance blowup. Thus, the noise power spectrum of the RF accelerating voltage strongly affects the longitudinal beam distribution. Furthermore, the coupled-bunch instabilities are also directly affected by the RF components and the configuration of the Low Level RF (LLRF) feedback loops. In this work we present a formalism relating the longitudinal beam dynamics with the RF system configurations, an estimation of collective effects stability margins, and an evaluation of longitudinal sensitivity to various LLRF parameters and configurations.
Using System Dynamics to Model the Transition to Biofuels in the United States: Preprint
Bush, B.; Duffy, M.; Sandor, D.; Peterson, S.
2008-06-01
Transitioning to a biofuels industry that is expected to displace about 30% of current U.S. gasoline consumption requires a robust biomass-to-biofuels system-of-systems that operates in concert with the existing markets. This paper discusses employing a system dynamics approach to investigate potential market penetration scenarios for cellulosic ethanol and to help government decision makers focus on areas with greatest potential.
Rutqvist, Jonny; Cappa, Frederic; Rinaldi, Antonio P.; Godano, Maxime
2014-12-31
We summarize recent modeling studies of injection-induced fault reactivation, seismicity, and its potential impact on surface structures and nuisance to the local human population. We used coupled multiphase fluid flow and geomechanical numerical modeling, dynamic wave propagation modeling, seismology theories, and empirical vibration criteria from mining and construction industries. We first simulated injection-induced fault reactivation, including dynamic fault slip, seismic source, wave propagation, and ground vibrations. From co-seismic average shear displacement and rupture area, we determined the moment magnitude to about M_{w} = 3 for an injection-induced fault reactivation at a depth of about 1000 m. We then analyzed the ground vibration results in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and frequency content, with comparison to the U.S. Bureau of Mines vibration criteria for cosmetic damage to buildings, as well as human-perception vibration limits. For the considered synthetic M_{w} = 3 event, our analysis showed that the short duration, high frequency ground motion may not cause any significant damage to surface structures, and would not cause, in this particular case, upward CO_{2} leakage, but would certainly be felt by the local population.
Rutqvist, Jonny; Cappa, Frederic; Rinaldi, Antonio P.; Godano, Maxime
2014-12-31
We summarize recent modeling studies of injection-induced fault reactivation, seismicity, and its potential impact on surface structures and nuisance to the local human population. We used coupled multiphase fluid flow and geomechanical numerical modeling, dynamic wave propagation modeling, seismology theories, and empirical vibration criteria from mining and construction industries. We first simulated injection-induced fault reactivation, including dynamic fault slip, seismic source, wave propagation, and ground vibrations. From co-seismic average shear displacement and rupture area, we determined the moment magnitude to about Mw = 3 for an injection-induced fault reactivation at a depth of about 1000 m. We then analyzed themore » ground vibration results in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and frequency content, with comparison to the U.S. Bureau of Mines’ vibration criteria for cosmetic damage to buildings, as well as human-perception vibration limits. For the considered synthetic Mw = 3 event, our analysis showed that the short duration, high frequency ground motion may not cause any significant damage to surface structures, and would not cause, in this particular case, upward CO2 leakage, but would certainly be felt by the local population.« less
Nelson, R.A. Jr.; Pimentel, D.A.; Jolly-Woodruff, S.; Spore, J.
1998-04-01
In this report, a phenomenological model of simultaneous bottom-up and top-down quenching is developed and discussed. The model was implemented in the TRAC-PF1/MOD2 computer code. Two sets of closure relationships were compared within the study, the Absolute set and the Conditional set. The Absolute set of correlations is frequently viewed as the pure set because the correlations is frequently viewed as the pure set because the correlations utilize their original coefficients as suggested by the developer. The Conditional set is a modified set of correlations with changes to the correlation coefficient only. Results for these two sets indicate quite similar results. This report also summarizes initial results of an effort to investigate nonlinear optimization techniques applied to the closure model development. Results suggest that such techniques can provide advantages for future model development work, but that extensive expertise is required to utilize such techniques (i.e., the model developer must fully understand both the physics of the process being represented and the computational techniques being employed). The computer may then be used to improve the correlation of computational results with experiments.
Energy Science and Technology Software Center (OSTI)
2015-08-04
Electrolyte systems are common in advanced electrochemical devices and have numerous other industrial, scientific, and medical applications. For example, 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 characterizemore » 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 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. This technology earned an R&D 100 award in 2014. Although it is applied most frequently to lithium-ion and sodium-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
Understanding polarization properties of InAs quantum dots by atomistic modeling of growth dynamics
Tasco, Vittorianna; Todaro, Maria Teresa; De Giorgi, Milena; Passaseo, Adriana; Usman, Muhammad
2013-12-04
A model for realistic InAs quantum dot composition profile is proposed and analyzed, consisting of a double region scheme with an In-rich internal core and an In-poor external shell, in order to mimic the atomic scale phenomena such as In-Ga intermixing and In segregation during the growth and overgrowth with GaAs. The parameters of the proposed model are derived by reproducing the experimentally measured polarization data. Further understanding is developed by analyzing the strain fields which suggests that the two-composition model indeed results in lower strain energies than the commonly applied uniform composition model.
Fuzzy logic controller optimization
Sepe, Jr., Raymond B; Miller, John Michael
2004-03-23
A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.
Ivanov, A.; Sanchez, V.; Imke, U.; Ivanov, K.
2012-07-01
In order to increase the accuracy and the degree of spatial resolution of core design studies, coupled Three-Dimensional (3D) neutronics (deterministic and Monte Carlo) and 3D thermal hydraulics (CFD and sub-channel) codes are being developed worldwide. In this paper the optimization of a coupling between MCNP5 code and an in-house development thermal-hydraulics code SUBCHANFLOW is presented. Various improvements of the coupling methodology are presented. With the help of novel interpolation tool a consistent methodology for the preparation of thermal scattering data library have been developed, ensuring that inelastic scattering from bound nuclei is treated at the correct moderator temperature. Trough the utilization of a hybrid coupling with discrete energy Monte-Carlo code KENO a methodology for acceleration of the coupled calculation is being demonstrated. In this approach an additional coupling between KENO and SUBCHANFLOW was developed, the converged results of which are used as initial conditions for the MCNP-SUBCHANFLOW coupling. Acceleration of fission source distribution convergence, by sampling fission source distribution from the power distribution obtained by KENO is also demonstrated. (authors)
Lawson, Mi. J.; Li, Y.; Sale, D. C.
2011-01-01
This paper describes the development of a computational fluid dynamics (CFD) methodology to simulate the hydrodynamics of horizontal-axis tidal current turbines (HATTs). First, an HATT blade was designed using the blade element momentum method in conjunction with a genetic optimization algorithm. Several unstructured computational grids were generated using this blade geometry and steady CFD simulations were used to perform a grid resolution study. Transient simulations were then performed to determine the effect of time-dependent flow phenomena and the size of the computational timestep on the numerical solution. Qualitative measures of the CFD solutions were independent of the grid resolution. Conversely, quantitative comparisons of the results indicated that the use of coarse computational grids results in an under prediction of the hydrodynamic forces on the turbine blade in comparison to the forces predicted using more resolved grids. For the turbine operating conditions considered in this study, the effect of the computational timestep on the CFD solution was found to be minimal, and the results from steady and transient simulations were in good agreement. Additionally, the CFD results were compared to corresponding blade element momentum method calculations and reasonable agreement was shown. Nevertheless, we expect that for other turbine operating conditions, where the flow over the blade is separated, transient simulations will be required.
Michael Harold; Vemuri Balakotaiah
2010-05-31
In this project a combined experimental and theoretical approach was taken to advance our understanding of lean NOx trap (LNT) technology. Fundamental kinetics studies were carried out of model LNT catalysts containing variable loadings of precious metals (Pt, Rh), and storage components (BaO, CeO{sub 2}). The Temporal Analysis of Products (TAP) reactor provided transient data under well-characterized conditions for both powder and monolith catalysts, enabling the identification of key reaction pathways and estimation of the corresponding kinetic parameters. The performance of model NOx storage and reduction (NSR) monolith catalysts were evaluated in a bench scale NOx trap using synthetic exhaust, with attention placed on the effect of the pulse timing and composition on the instantaneous and cycle-averaged product distributions. From these experiments we formulated a global model that predicts the main spatio-temporal features of the LNT and a mechanistic-based microkinetic models that incorporates a detailed understanding of the chemistry and predicts more detailed selectivity features of the LNT. The NOx trap models were used to determine its ability to simulate bench-scale data and ultimately to evaluate alternative LNT designs and operating strategies. The four-year project led to the training of several doctoral students and the dissemination of the findings as 47 presentations in conferences, catalysis societies, and academic departments as well 23 manuscripts in peer-reviewed journals. A condensed review of NOx storage and reduction was published in an encyclopedia of technology.
Browning, J. R.; Jonkman, J.; Robertson, A.; Goupee, A. J.
2012-11-01
In 2007, the FAST wind turbine simulation tool, developed and maintained by the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL), was expanded to include capabilities that are suitable for modeling floating offshore wind turbines. In an effort to validate FAST and other offshore wind energy modeling tools, DOE funded the DeepCwind project that tested three prototype floating wind turbines at 1/50th scale in a wave basin, including a semisubmersible, a tension-leg platform, and a spar buoy. This paper describes the use of the results of the spar wave basin tests to calibrate and validate the FAST offshore floating simulation tool, and presents some initial results of simulated dynamic responses of the spar to several combinations of wind and sea states.
Self-consistency tests of large-scale dynamics parameterizations for single-column modeling
Edman, Jacob P.; Romps, David M.
2015-03-18
Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, but WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.
Self-consistency tests of large-scale dynamics parameterizations for single-column modeling
Edman, Jacob P.; Romps, David M.
2015-03-18
Large-scale dynamics parameterizations are tested numerically in cloud-resolving simulations, including a new version of the weak-pressure-gradient approximation (WPG) introduced by Edman and Romps (2014), the weak-temperature-gradient approximation (WTG), and a prior implementation of WPG. We perform a series of self-consistency tests with each large-scale dynamics parameterization, in which we compare the result of a cloud-resolving simulation coupled to WTG or WPG with an otherwise identical simulation with prescribed large-scale convergence. In self-consistency tests based on radiative-convective equilibrium (RCE; i.e., no large-scale convergence), we find that simulations either weakly coupled or strongly coupled to either WPG or WTG are self-consistent, butmore » WPG-coupled simulations exhibit a nonmonotonic behavior as the strength of the coupling to WPG is varied. We also perform self-consistency tests based on observed forcings from two observational campaigns: the Tropical Warm Pool International Cloud Experiment (TWP-ICE) and the ARM Southern Great Plains (SGP) Summer 1995 IOP. In these tests, we show that the new version of WPG improves upon prior versions of WPG by eliminating a potentially troublesome gravity-wave resonance.« less
Model Fidelity Study of Dynamic Transient Loads in a Wind Turbine Gearbox: Preprint
Guo, Y.; Keller, J.; Moan, T.; Xing, Y.
2013-04-01
Transient events cause high loads in the drivetrain components so measuring and calculating these loads can improve confidence in drivetrain design. This paper studies the Gearbox Reliability Collaborative 750kW wind turbine gearbox response during transient events using a combined experimental and modeling approach. The transient events include emergency shut-downs and start-ups measured during a field testing period in 2009. The drivetrain model is established in the multibody simulation tool Simpack. A detailed study of modeling fidelity required for accurate load prediction is performed and results are compared against measured loads. A high fidelity model that includes shaft and housing flexibility and accurate bearing stiffnesses is important for the higher-speed stage bearing loads. Each of the transient events has different modeling requirements.
Finite temperature spin-dynamics and phase transitions in spin-orbital models
Chen, C.-C.
2010-04-29
We study finite temperature properties of a generic spin-orbital model relevant to transition metal compounds, having coupled quantum Heisenberg-spin and Ising-orbital degrees of freedom. The model system undergoes a phase transition, consistent with that of a 2D Ising model, to an orbitally ordered state at a temperature set by short-range magnetic order. At low temperatures the orbital degrees of freedom freeze-out and the model maps onto a quantum Heisenberg model. The onset of orbital excitations causes a rapid scrambling of the spin spectral weight away from coherent spin-waves, which leads to a sharp increase in uniform magnetic susceptibility just below the phase transition, reminiscent of the observed behavior in the Fe-pnictide materials.
Vimmerstedt, Laura J.; Bush, Brian W.; Peterson, Steven O.
2015-09-03
This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.
Yabusaki, Steven B.; Fang, Yilin; Waichler, Scott R.
2008-12-04
Subsurface simulation is being used to build, test, and couple conceptual process models to better understand controls on a 0.4 km by 1.0 km uranium plume that has persisted above the drinking water standard in the groundwater of the Hanford 300 Area over the last 15 years. At this site, uranium-contaminated sediments in the vadose zone and aquifer are subject to significant variations in water levels and velocities driven by the diurnal, weekly, seasonal, and episodic Columbia River stage dynamics. Groundwater flow reversals typically occur twice a day with significant exchange of river water and groundwater in the near-river aquifer. Mixing of the dilute solution chemistry of the river with the groundwater complicates the uranium sorption behavior as the mobility of U(VI) has been shown experimentally to be a function of pH, carbonate, calcium, and uranium. Furthermore, uranium mass transfer between solid and aqueous phases has been observed to be rate-limited in the context of the high groundwater velocities resulting from the river stage fluctuations and the highly transmissive sediments (hydraulic conductivities ~1500 m/d). One- and two-dimensional vertical cross-sectional simulations of variably-saturated flow and reactive transport, based on laboratory-derived models of distributed rate mass transfer and equilibrium multicomponent surface complexation, are used to assess uranium transport at the dynamic vadose zone aquifer interface as well as changes to uranium mobility due to incursions of river water into the aquifer.
Fluid Dynamics and Solid Mechanics
U.S. Department of Energy (DOE) all webpages (Extended Search)
and Solid Mechanics Basic and applied research in theoretical continuum dynamics, modern hydrodynamic theory, materials modeling, global climate modeling, numerical...
Modeling of a negative ion source. I. Gas kinetics and dynamics in the expansion region
Taccogna, F.; Schneider, R.; Longo, S.; Capitelli, M.
2007-07-15
The vibrational population distribution of the electronic ground state of H{sub 2} in the expansion region of a negative ion source is investigated using a kinetic Monte Carlo model. Operative conditions are referred to the inductively coupled plasma radio frequency negative ion source developed at IPP-Garching. The different excitation and relaxation processes are discussed, both bulk and surface contributions. In particular, due to the relatively high plasma density, the relevant role of direct low energy electron-impact excitation, surface Auger neutralization, and vibration-translation deactivation are recovered. Results of the present model will be used as input data for the neutral source model in the extraction region.
Modelling of the internal dynamics and density in a tens of joules plasma focus device
Marquez, Ariel; Gonzalez, Jose; Tarifeno-Saldivia, Ariel; Pavez, Cristian; Soto, Leopoldo; Clausse, Alejandro
2012-01-15
Using MHD theory, coupled differential equations were generated using a lumped parameter model to describe the internal behaviour of the pinch compression phase in plasma focus discharges. In order to provide these equations with appropriate initial conditions, the modelling of previous phases was included by describing the plasma sheath as planar shockwaves. The equations were solved numerically, and the results were contrasted against experimental measurements performed on the device PF-50J. The model is able to predict satisfactorily the timing and the radial electron density profile at the maximum compression.
Arefinia, Zahra [Research Institute for Applied Physics and Astronomy, University of Tabriz, Tabriz 51666-14766 (Iran, Islamic Republic of); Asgari, Asghar, E-mail: asgari@tabrizu.ac.ir [Research Institute for Applied Physics and Astronomy, University of Tabriz, Tabriz 51666-14766 (Iran, Islamic Republic of); School of Electrical, Electronic, and Computer Engineering, University of Western Australia, Crawley, WA 6009 (Australia)
2014-05-21
Based on the ability of In{sub x}Ga{sub 1?x}N materials to optimally span the solar spectrum and their superior radiation resistance, solar cells based on p-type In{sub x}Ga{sub 1?x}N with low indium contents and interfacing with graphene film (G/In{sub x}Ga{sub 1?x}N), is proposed to exploit the benefit of transparency and work function tunability of graphene. Then, their solar power conversion efficiency modeled and optimized using a new analytical approach taking into account all recombination processes and accurate carrier mobility. Furthermore, their performance was compared with graphene on silicon counterparts and G/p-In{sub x}Ga{sub 1?x}N showed relatively smaller short-circuits current (?7?mA/cm{sup 2}) and significantly higher open-circuit voltage (?4?V) and efficiency (?30%). The thickness, doping concentration, and indium contents of p-In{sub x}Ga{sub 1?x}N and graphene work function were found to substantially affect the performance of G/p-In{sub x}Ga{sub 1?x}N.
User Guide for PV Dynamic Model Simulation Written on PSCAD Platform
U.S. Department of Energy (DOE) all webpages (Extended Search)
... terminal of the PV inverter, the higher harmonic components of the currents are filtered ... Model A voltage-source inverter (VSI) synthesizes a voltage source connected to the grid. ...
U.S. Department of Energy (DOE) all webpages (Extended Search)
Optimization Performance and Optimization Performance Monitoring Last edited: 2012-01-09 12:31:03
U.S. Department of Energy (DOE) all webpages (Extended Search)
Optimization Performance and Optimization Performance Monitoring Last edited: 2012-01-09 12:31:03...
Using System Dynamics to Model the Transition to Biofuels in the United States
Bush, B.; Duffy, M.; Sandor, D.; Peterson, S.
2008-01-01
Today, the U.S. consumes almost 21 million barrels of crude oil per day; approximately 60% of the U.S. demand is supplied by imports. The transportation sector alone accounts for two-thirds of U.S. petroleum use. Biofuels, liquid fuels produced from domestically-grown biomass, have the potential to displace about 30% of current U.S. gasoline consumption. Transitioning to a biofuels industry on this scale will require the creation of a robust biomass-to-biofuels system-of-systems that operates in concert with the existing agriculture, forestry, energy, and transportation markets. The U.S. Department of Energy is employing a system dynamics approach to investigate potential market penetration scenarios for cellulosic ethanol, and to aid decision makers in focusing government actions on the areas with greatest potential to accelerate the deployment of biofuels and ultimately reduce the nationpsilas dependence on imported oil.
Carr, S.S.
1992-01-01
Limb-scan observations of Doppler line profiles from the (OII) lambda 7320A emission at F-Region altitudes, made with the Fabry-Perot interferometer (FPI) on the Dynamics Explorer-2 (DE-2) spacecraft, have been analyzed to provide measurements of the meridional component of the ion convection velocity along the instrument line-of-sight. The DE-2 results presented here demonstrate the first spaceborne use of the remote-sensing Doppler techniques for measurements of ionospheric convection. The FPI meridional ion drift measurements have been compared with nearly simultaneous in situ ion drift measurements from the Retarding Potential Analyzer (RPA) on DE 2. Once allowance is made for the temporal lag between the in situ and remote measurements, the results from the two techniques are found to be in good agreement, within specified experimental errors, giving confidence in the FPI measurements.
From many body wee partons dynamics to perfect fluid: a standard model for heavy ion collisions
Venugopalan, R.
2010-07-22
We discuss a standard model of heavy ion collisions that has emerged both from experimental results of the RHIC program and associated theoretical developments. We comment briefly on the impact of early results of the LHC program on this picture. We consider how this standard model of heavy ion collisions could be solidified or falsified in future experiments at RHIC, the LHC and a future Electro-Ion Collider.
Furnish, M.D.; Boslough, M.B.; Gray, G.T. III; Remo, J.L.
1994-07-01
We describe methods for measuring dynamical properties for two material categories of interest in understanding large-scale extraterrestrial impacts: iron-nickel and underdense materials (e.g. snow). Particular material properties measured by the present methods include Hugoniot release paths and constitutive properties (stress vs. strain). The iron-nickel materials lend themselves well to conventional shock and quasi-static experiments. As examples, a suite of experiments is described including six impact tests (wave profile compression/release) over the stress range 2--20 GPa, metallography, quasi-static and split Hopkinson pressure bar (SHPB) mechanical testing, and ultrasonic mapping and sound velocity measurements. Temperature sensitivity of the dynamic behavior was measured at high and low strain rates. Among the iron-nickel materials tested, an octahedrite was found to have behavior close to that of Armco iron under shock and quasi-static conditions, while an ataxite exhibited a significantly larger quasi-static yield strength than did the octahedrite or a hexahedrite. The underdense materials pose three primary experimental difficulties. First, the samples are friable; they can melt or sublimate during storage, preparation and testing. Second, they are brittle and crushable; they cannot withstand such treatment as traditional machining or launch in a gun system. Third, with increasing porosity the calculated Hugoniot density becomes rapidly more sensitive to errors in wave time-of-arrival measurements. Carefully chosen simulants eliminate preservation (friability) difficulties, but the other difficulties remain. A family of 36 impact tests was conducted on snow and snow simulants at Sandia, yielding reliable Hugoniot and reshock states, but limited release property information. Other methods for characterizing these materials are discussed.
Dr. Ralph E. White; Dr. Branko N. Popov
2002-04-01
The dissolution of NiO cathodes during cell operation is a limiting factor to the successful commercialization of molten carbonate fuel cells (MCFCs). Lithium cobalt oxide coating onto the porous nickel electrode has been adopted to modify the conventional MCFC cathode which is believed to increase the stability of the cathodes in the carbonate melt. The material used for surface modification should possess thermodynamic stability in the molten carbonate and also should be electro catalytically active for MCFC reactions. Two approaches have been adopted to get a stable cathode material. First approach is the use of LiNi{sub 0.8}Co{sub 0.2}O{sub 2}, a commercially available lithium battery cathode material and the second is the use of tape cast electrodes prepared from cobalt coated nickel powders. The morphology and the structure of LiNi{sub 0.8}Co{sub 0.2}O{sub 2} and tape cast Co coated nickel powder electrodes were studied using scanning electron microscopy and X-Ray diffraction studies respectively. The electrochemical performance of the two materials was investigated by electrochemical impedance spectroscopy and polarization studies. A three phase homogeneous model was developed to simulate the performance of the molten carbonate fuel cell cathode. The homogeneous model is based on volume averaging of different variables in the three phases over a small volume element. The model gives a good fit to the experimental data. The model has been used to analyze MCFC cathode performance under a wide range of operating conditions.
THE LICK AGN MONITORING PROJECT 2011: DYNAMICAL MODELING OF THE BROAD-LINE REGION IN Mrk 50
Pancoast, Anna; Brewer, Brendon J.; Treu, Tommaso; Bennert, Vardha N.; Sand, David J.; Barth, Aaron J.; Cooper, Michael C.; Canalizo, Gabriela; Filippenko, Alexei V.; Li, Weidong; Cenko, S. Bradley; Clubb, Kelsey I.; Gates, Elinor L.; Greene, Jenny E.; Malkan, Matthew A.; Stern, Daniel; Assef, Roberto J.; Woo, Jong-Hak; Bae, Hyun-Jin; Buehler, Tabitha; and others
2012-07-20
We present dynamical modeling of the broad-line region (BLR) in the Seyfert 1 galaxy Mrk 50 using reverberation mapping data taken as part of the Lick AGN Monitoring Project (LAMP) 2011. We model the reverberation mapping data directly, constraining the geometry and kinematics of the BLR, as well as deriving a black hole mass estimate that does not depend on a normalizing factor or virial coefficient. We find that the geometry of the BLR in Mrk 50 is a nearly face-on thick disk, with a mean radius of 9.6{sup +1.2}{sub -0.9} light days, a width of the BLR of 6.9{sup +1.2}{sub -1.1} light days, and a disk opening angle of 25 {+-} 10 deg above the plane. We also constrain the inclination angle to be 9{sup +7}{sub -5} deg, close to face-on. Finally, the black hole mass of Mrk 50 is inferred to be log{sub 10}(M{sub BH}/M{sub Sun }) = 7.57{sup +0.44}{sub -0.27}. By comparison to the virial black hole mass estimate from traditional reverberation mapping analysis, we find the normalizing constant (virial coefficient) to be log{sub 10} f = 0.78{sup +0.44}{sub -0.27}, consistent with the commonly adopted mean value of 0.74 based on aligning the M{sub BH}-{sigma}* relation for active galactic nuclei and quiescent galaxies. While our dynamical model includes the possibility of a net inflow or outflow in the BLR, we cannot distinguish between these two scenarios.
Development and Application of a Strength and Damage Model for Rock under Dynamic Loading
Antoun, T H; Lomov, I N; Glenn, L A
2001-03-12
Simulating the behavior of geologic materials under impact loading conditions requires the use of a constitutive model that includes the effects of bulking, yielding, damage, porous compaction and loading rate on the material response. This paper describes the development, implementation and calibration of a thermodynamically consistent constitutive model that incorporates these features. The paper also describes a computational study in which the model was used to perform numerical simulations of PILE DRIVER, a deeply-buried underground nuclear explosion detonated in granite at the Nevada Test Site. Particle velocity histories, peak velocity and peak displacement as a function of slant range obtained from the code simulations compare favorably with PILE DRIVER data. The simulated attenuation of peak velocity and peak displacement also agrees with the results from several other spherical wave experiments in granite.
Test Cases for Wind Power Plant Dynamic Models on Real-Time Digital Simulator: Preprint
Singh, M.; Muljadi, E.; Gevorgian, V.
2012-06-01
The objective of this paper is to present test cases for wind turbine generator and wind power plant models commonly used during commissioning of wind power plants to ensure grid integration compatibility. In this paper, different types of wind power plant models based on the Western Electricity Coordinating Council Wind Generator Modeling Group's standardization efforts are implemented on a real-time digital simulator, and different test cases are used to gauge their grid integration capability. The low-voltage ride through and reactive power support capability and limitations of wind turbine generators under different grid conditions are explored. Several types of transient events (e.g., symmetrical and unsymmetrical faults, frequency dips) are included in the test cases. The differences in responses from different types of wind turbine are discussed in detail.
Fisher, R. A.; Muszala, S.; Verteinstein, M.; Lawrence, P.; Xu, C.; McDowell, N. G.; Knox, R. G.; Koven, C.; Holm, J.; Rogers, B. M.; Lawrence, D.; Bonan, G.
2015-04-29
We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.
Fisher, R. A.; Muszala, S.; Verteinstein, M.; Lawrence, P.; Xu, C.; McDowell, N. G.; Knox, R. G.; Koven, C.; Holm, J.; Rogers, B. M.; et al
2015-04-29
We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leafmore » trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.« less
Lovley, Derek R
2012-12-28
The goal of this research was to provide computational tools to predictively model the behavior of two microbial communities of direct relevance to Department of Energy interests: 1) the microbial community responsible for in situ bioremediation of uranium in contaminated subsurface environments; and 2) the microbial community capable of harvesting electricity from waste organic matter and renewable biomass. During this project the concept of microbial electrosynthesis, a novel form of artificial photosynthesis for the direct production of fuels and other organic commodities from carbon dioxide and water was also developed and research was expanded into this area as well.
Kohut, Sviataslau V.; Staroverov, Viktor N.; Ryabinkin, Ilya G.
2014-05-14
We describe a method for constructing a hierarchy of model potentials approximating the functional derivative of a given orbital-dependent exchange-correlation functional with respect to electron density. Each model is derived by assuming a particular relationship between the self-consistent solutions of KohnSham (KS) and generalized KohnSham (GKS) equations for the same functional. In the KS scheme, the functional is differentiated with respect to density, in the GKS schemewith respect to orbitals. The lowest-level approximation is the orbital-averaged effective potential (OAEP) built with the GKS orbitals. The second-level approximation, termed the orbital-consistent effective potential (OCEP), is based on the assumption that the KS and GKS orbitals are the same. It has the form of the OAEP plus a correction term. The highest-level approximation is the density-consistent effective potential (DCEP), derived under the assumption that the KS and GKS electron densities are equal. The analytic expression for a DCEP is the OCEP formula augmented with kinetic-energy-density-dependent terms. In the case of exact-exchange functional, the OAEP is the Slater potential, the OCEP is roughly equivalent to the localized HartreeFock approximation and related models, and the DCEP is practically indistinguishable from the true optimized effective potential for exact exchange. All three levels of the proposed hierarchy require solutions of the GKS equations as input and have the same affordable computational cost.
Dopant profile modeling by rare event enhanced domain-following molecular dynamics
Beardmore, Keith M.; Jensen, Niels G.
2002-01-01
A computer-implemented molecular dynamics-based process simulates a distribution of ions implanted in a semiconductor substrate. The properties of the semiconductor substrate and ion dose to be simulated are first initialized, including an initial set of splitting depths that contain an equal number of virtual ions implanted in each substrate volume determined by the splitting depths. A first ion with selected velocity is input onto an impact position of the substrate that defines a first domain for the first ion during a first timestep, where the first domain includes only those atoms of the substrate that exert a force on the ion. A first position and velocity of the first ion is determined after the first timestep and a second domain of the first ion is formed at the first position. The first ion is split into first and second virtual ions if the first ion has passed through a splitting interval. The process then follows each virtual ion until all of the virtual ions have come to rest. A new ion is input to the surface and the process repeats until all of the ion dose has been input. The resulting ion rest positions form the simulated implant distribution.
Thermoacoustic wave propagation modeling using a dynamically adaptive wavelet collocation method
Vasilyev, O.V.; Paolucci, S.
1996-12-31
When a localized region of a solid wall surrounding a compressible medium is subjected to a sudden temperature change, the medium in the immediate neighborhood of that region expands. This expansion generates pressure waves. These thermally-generated waves are referred to as thermoacoustic (TAC) waves. The main interest in thermoacoustic waves is motivated by their property to enhance heat transfer by inducing convective motion away from the heated area. Thermoacoustic wave propagation in a two-dimensional rectangular cavity is studied numerically. The thermoacoustic waves are generated by raising the temperature locally at the walls. The waves, which decay at large time due to thermal and viscous diffusion, propagate and reflect from the walls creating complicated two-dimensional patterns. The accuracy of numerical simulation is ensured by using a highly accurate, dynamically adaptive, multilevel wavelet collocation method, which allows local refinements to adapt to local changes in solution scales. Subsequently, high resolution computations are performed only in regions of large gradients. The computational cost of the method is independent of the dimensionality of the problem and is O(N), where N is the total number of collation points.
A dynamic model for evaluating radionuclide distribution in forests from nuclear accidents
Schell, W.R.; Linkov, I.; Myttenaere, C.
1996-03-01
The Chernobyl Nuclear Power Plant accident in 1986 caused radionuclide contamination in most countries in Eastern and Western Europe. A prime example is Belarus where 23% of the total land area received chronic levels; about 1.5 X 10{sup 6} ha of forested lands were contaminated with 40-190 kBq m{sup -2} and 2.5 X 10{sup 4} ha received greater than 1,480 kBq m{sup -2} of {sup 137}Cs and other long-lived radionuclides such as {sup 90}Sr and {sup 239,240}Pu. Since the radiological dose to the forest ecosystem will tend to accumulate over long time periods (decades to centuries), we need to determine what countermeasures can be taken to limit this dose so that the affected regions can, once again, safely provide habitat and natural forest products. To address some of these problems, our initial objective is to formulate a generic model, FORESTPATH, which describes the major kinetic processes and pathways of radionuclide movement in forests and natural ecosystems and which can be used to predict future radionuclide concentrations. The model calculates the time-dependent radionuclide concentrations in different compartments of the forest ecosystem based on the information available on residence half-times in two forest types: coniferous and deciduous. The results show that the model reproduces well the radionuclide cycling pattern found in the literature for deciduous and coniferous forests. Variability analysis was used to access the relative importance of specific parameter values in the generic model performance. The FORESTPASTH model can be easily adjusted for site-specific applications. 92 refs., 5 figs., 6 tabs.
Fuel Efficiency and Emissions Optimization of Heavy-Duty Diesel...
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
and Emissions Optimization of Heavy-Duty Diesel Engines using Model-Based Transient Calibration Fuel Efficiency and Emissions Optimization of Heavy-Duty Diesel Engines using ...
FEMP Completes 2000th Renewable Energy Optimization Screening...
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
FEMP Completes 2000th Renewable Energy Optimization Screening FEMP Completes 2000th Renewable Energy Optimization Screening July 23, 2015 - 12:03pm Addthis REopt models the complex ...
Giera, Brian; Lawrence Livermore National Lab.; Henson, Neil; Kober, Edward M.; Shell, M. Scott; Squires, Todd M.
2015-02-27
We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnahan–Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as is the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drivemore » strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles.« less
Integrated Dynamic Gloabal Modeling of Land Use, Energy and Economic Growth
Atul Jain, University of Illinois, Urbana-Champaign, IL Brian O'Neill, NCAR, Boulder, CO
2009-10-14
The overall objective of this collaborative project is to integrate an existing general equilibrium energy-economic growth model with a biogeochemical cycles and biophysical models in order to more fully explore the potential contribution of land use-related activities to future emissions scenarios. Land cover and land use change activities, including deforestation, afforestation, and agriculture management, are important source of not only CO2, but also non-CO2 GHGs. Therefore, contribution of land-use emissions to total emissions of GHGs is important, and consequently their future trends are relevant to the estimation of climate change and its mitigation. This final report covers the full project period of the award, beginning May 2006, which includes a sub-contract to Brown University later transferred to the National Center for Atmospheric Research (NCAR) when Co-PI Brian O'Neill changed institutional affiliations.
Prasad, Manish; Conforti, Patrick F.; Garrison, Barbara J.
2007-08-28
The coarse grained chemical reaction model is enhanced to build a molecular dynamics (MD) simulation framework with an embedded Monte Carlo (MC) based reaction scheme. The MC scheme utilizes predetermined reaction chemistry, energetics, and rate kinetics of materials to incorporate chemical reactions occurring in a substrate into the MD simulation. The kinetics information is utilized to set the probabilities for the types of reactions to perform based on radical survival times and reaction rates. Implementing a reaction involves changing the reactants species types which alters their interaction potentials and thus produces the required energy change. We discuss the application of this method to study the initiation of ultraviolet laser ablation in poly(methyl methacrylate). The use of this scheme enables the modeling of all possible photoexcitation pathways in the polymer. It also permits a direct study of the role of thermal, mechanical, and chemical processes that can set off ablation. We demonstrate that the role of laser induced heating, thermomechanical stresses, pressure wave formation and relaxation, and thermochemical decomposition of the polymer substrate can be investigated directly by suitably choosing the potential energy and chemical reaction energy landscape. The results highlight the usefulness of such a modeling approach by showing that various processes in polymer ablation are intricately linked leading to the transformation of the substrate and its ejection. The method, in principle, can be utilized to study systems where chemical reactions are expected to play a dominant role or interact strongly with other physical processes.
A hybrid programming model for compressible gas dynamics using openCL
Bergen, Benjamin Karl; Daniels, Marcus G; Weber, Paul M
2010-01-01
The current trend towards multicore/manycore and accelerated architectures presents challenges, both in portability, and also in the choices that developers must make on how to use the resources that these architectures provide. This paper explores some of the possibilities that are enabled by the Open Computing Language (OpenCL), and proposes a programming model that allows developers and scientists to more fully subscribe hybrid compute nodes, while, at the same time, reducing the impact of system failure.
Next Generation Calibration Models with Dimensional Modeling...
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
Calibration Models with Dimensional Modeling Next Generation Calibration Models with ... Calibration Optimization for Next Generation Diesel Engines An Accelerated Aging ...
Hydra modeling of experiments to study ICF capsule fill hole dynamics using surrogate targets
Elliott, J B
2007-08-27
In this section the results of HYDRA [1] design simulations will be discussed. The simulations were conducted in two dimensional, RZ geometry, with the fill tube on axis. The radiation transport was treated in the diffusion approximation using 15 energy groups. Opacities were calculated. The equations of state (EOS) for all materials used were from a combined analytic/Thomas-Fermi EOS which uses a modified Cowan model for the ion EOS, and uses a scaled Thomas-Fermi table for the electron EOS.
Dynamic modeling of physical phenomena for probabilistic assessment of spent fuel accidents
Benjamin, A.S.
1997-11-01
If there should be an accident involving drainage of all the water from a spent fuel pool, the fuel elements will heat up until the heat produced by radioactive decay is balanced by that removed by natural convection to air, thermal radiation, and other means. If the temperatures become high enough for the cladding or other materials to ignite due to rapid oxidation, then some of the fuel might melt, leading to an undesirable release of radioactive materials. The amount of melting is dependent upon the fuel loading configuration and its age, the oxidation and melting characteristics of the materials, and the potential effectiveness of recovery actions. The authors have developed methods for modeling the pertinent physical phenomena and integrating the results with a probabilistic treatment of the uncertainty distributions. The net result is a set of complementary cumulative distribution functions for the amount of fuel melted.
High-order continuum kinetic method for modeling plasma dynamics in phase space
Vogman, G. V.; Colella, P.; Shumlak, U.
2014-12-15
Continuum methods offer a high-fidelity means of simulating plasma kinetics. While computationally intensive, these methods are advantageous because they can be cast in conservation-law form, are not susceptible to noise, and can be implemented using high-order numerical methods. Advances in continuum method capabilities for modeling kinetic phenomena in plasmas require the development of validation tools in higher dimensional phase space and an ability to handle non-cartesian geometries. To that end, a new benchmark for validating Vlasov-Poisson simulations in 3D (x,vx,vy) is presented. The benchmark is based on the Dory-Guest-Harris instability and is successfully used to validate a continuum finite volumemore » algorithm. To address challenges associated with non-cartesian geometries, unique features of cylindrical phase space coordinates are described. Preliminary results of continuum kinetic simulations in 4D (r,z,vr,vz) phase space are presented.« less
Bifurcation and chaos in the simple passive dynamic walking model with upper body
Li, Qingdu; Guo, Jianli; Yang, Xiao-Song
2014-09-01
We present some rich new complex gaits in the simple walking model with upper body by Wisse et al. in [Robotica 22, 681 (2004)]. We first show that the stable gait found by Wisse et al. may become chaotic via period-doubling bifurcations. Such period-doubling routes to chaos exist for all parameters, such as foot mass, upper body mass, body length, hip spring stiffness, and slope angle. Then, we report three new gaits with period 3, 4, and 6; for each gait, there is also a period-doubling route to chaos. Finally, we show a practical method for finding a topological horseshoe in 3D Poincar map, and present a rigorous verification of chaos from these gaits.
ANALYTICAL MODELS OF EXOPLANETARY ATMOSPHERES. I. ATMOSPHERIC DYNAMICS VIA THE SHALLOW WATER SYSTEM
Heng, Kevin; Workman, Jared E-mail: jworkman@coloradomesa.edu
2014-08-01
Within the context of exoplanetary atmospheres, we present a comprehensive linear analysis of forced, damped, magnetized shallow water systems, exploring the effects of dimensionality, geometry (Cartesian, pseudo-spherical, and spherical), rotation, magnetic tension, and hydrodynamic and magnetic sources of friction. Across a broad range of conditions, we find that the key governing equation for atmospheres and quantum harmonic oscillators are identical, even when forcing (stellar irradiation), sources of friction (molecular viscosity, Rayleigh drag, and magnetic drag), and magnetic tension are included. The global atmospheric structure is largely controlled by a single key parameter that involves the Rossby and Prandtl numbers. This near-universality breaks down when either molecular viscosity or magnetic drag acts non-uniformly across latitude or a poloidal magnetic field is present, suggesting that these effects will introduce qualitative changes to the familiar chevron-shaped feature witnessed in simulations of atmospheric circulation. We also find that hydrodynamic and magnetic sources of friction have dissimilar phase signatures and affect the flow in fundamentally different ways, implying that using Rayleigh drag to mimic magnetic drag is inaccurate. We exhaustively lay down the theoretical formalism (dispersion relations, governing equations, and time-dependent wave solutions) for a broad suite of models. In all situations, we derive the steady state of an atmosphere, which is relevant to interpreting infrared phase and eclipse maps of exoplanetary atmospheres. We elucidate a pinching effect that confines the atmospheric structure to be near the equator. Our suite of analytical models may be used to develop decisively physical intuition and as a reference point for three-dimensional magnetohydrodynamic simulations of atmospheric circulation.
Modekurti, Srinivasarao; Bhattacharyya, Debangsu; Zitney, Stephen E.
2013-07-31
A one-dimensional, non-isothermal, pressure-driven dynamic model has been developed for a two-stage bubbling fluidized bed (BFB) adsorber-reactor for solid-sorbent carbon dioxide (CO{sub 2}) capture using Aspen Custom Modeler® (ACM). The BFB model for the flow of gas through a continuous phase of downward moving solids considers three regions: emulsion, bubble, and cloud-wake. Both the upper and lower reactor stages are of overflow-type configuration, i.e., the solids leave from the top of each stage. In addition, dynamic models have been developed for the downcomer that transfers solids between the stages and the exit hopper that removes solids from the bottom of the bed. The models of all auxiliary equipment such as valves and gas distributor have been integrated with the main model of the two-stage adsorber reactor. Using the developed dynamic model, the transient responses of various process variables such as CO{sub 2} capture rate and flue gas outlet temperatures have been studied by simulating typical disturbances such as change in the temperature, flowrate, and composition of the incoming flue gas from pulverized coal-fired power plants. In control studies, the performance of a proportional-integral-derivative (PID) controller, feedback-augmented feedforward controller, and linear model predictive controller (LMPC) are evaluated for maintaining the overall CO{sub 2} capture rate at a desired level in the face of typical disturbances.
Baosheng Jin; Rui Xiao; Zhongyi Deng; Qilei Song
2009-07-01
To concentrate CO{sub 2} in combustion processes by efficient and energy-saving ways is a first and very important step for its sequestration. Chemical looping combustion (CLC) could easily achieve this goal. A chemical-looping combustion system consists of a fuel reactor and an air reactor. Two reactors in the form of interconnected fluidized beds are used in the process: (1) a fuel reactor where the oxygen carrier is reduced by reaction with the fuel, and (2) an air reactor where the reduced oxygen carrier from the fuel reactor is oxidized with air. The outlet gas from the fuel reactor consists of CO{sub 2} and H{sub 2}O, while the outlet gas stream from the air reactor contains only N{sub 2} and some unused O{sub 2}. The water in combustion products can be easily removed by condensation and pure carbon dioxide is obtained without any loss of energy for separation. Until now, there is little literature about mathematical modeling of chemical-looping combustion using the computational fluid dynamics (CFD) approach. In this work, the reaction kinetic model of the fuel reactor (CaSO{sub 4}+ H{sub 2}) is developed by means of the commercial code FLUENT and the effects of partial pressure of H{sub 2} (concentration of H{sub 2}) on chemical looping combustion performance are also studied. The results show that the concentration of H{sub 2} could enhance the CLC performance.
Weather forecast-based optimization of integrated energy systems.
Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.
2009-03-01
In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.
High-order continuum kinetic method for modeling plasma dynamics in phase space
Vogman, G. V.; Colella, P.; Shumlak, U.
2014-12-15
Continuum methods offer a high-fidelity means of simulating plasma kinetics. While computationally intensive, these methods are advantageous because they can be cast in conservation-law form, are not susceptible to noise, and can be implemented using high-order numerical methods. Advances in continuum method capabilities for modeling kinetic phenomena in plasmas require the development of validation tools in higher dimensional phase space and an ability to handle non-cartesian geometries. To that end, a new benchmark for validating Vlasov-Poisson simulations in 3D (x,v_{x},v_{y}) is presented. The benchmark is based on the Dory-Guest-Harris instability and is successfully used to validate a continuum finite volume algorithm. To address challenges associated with non-cartesian geometries, unique features of cylindrical phase space coordinates are described. Preliminary results of continuum kinetic simulations in 4D (r,z,v_{r},v_{z}) phase space are presented.
[SIAM conference on optimization
Not Available
1992-05-10
Abstracts are presented of 63 papers on the following topics: large-scale optimization, interior-point methods, algorithms for optimization, problems in control, network optimization methods, and parallel algorithms for optimization problems.
Anastasia Gribik; Doona Guillen, PhD; Daniel Ginosar, PhD
2008-09-01
Currently multi-tubular fixed bed reactors, fluidized bed reactors, and slurry bubble column reactors (SBCRs) are used in commercial Fischer Tropsch (FT) synthesis. There are a number of advantages of the SBCR compared to fixed and fluidized bed reactors. The main advantage of the SBCR is that temperature control and heat recovery are more easily achieved. The SBCR is a multiphase chemical reactor where a synthesis gas, comprised mainly of H2 and CO, is bubbled through a liquid hydrocarbon wax containing solid catalyst particles to produce specialty chemicals, lubricants, or fuels. The FT synthesis reaction is the polymerization of methylene groups [-(CH2)-] forming mainly linear alkanes and alkenes, ranging from methane to high molecular weight waxes. The Idaho National Laboratory is developing a computational multiphase fluid dynamics (CMFD) model of the FT process in a SBCR. This paper discusses the incorporation of absorption and reaction kinetics into the current hydrodynamic model. A phased approach for incorporation of the reaction kinetics into a CMFD model is presented here. Initially, a simple kinetic model is coupled to the hydrodynamic model, with increasing levels of complexity added in stages. The first phase of the model includes incorporation of the absorption of gas species from both large and small bubbles into the bulk liquid phase. The driving force for the gas across the gas liquid interface into the bulk liquid is dependent upon the interfacial gas concentration in both small and large bubbles. However, because it is difficult to measure the concentration at the gas-liquid interface, coefficients for convective mass transfer have been developed for the overall driving force between the bulk concentrations in the gas and liquid phases. It is assumed that there are no temperature effects from mass transfer of the gas phases to the bulk liquid phase, since there are only small amounts of dissolved gas in the liquid phase. The product from the
The earliest events in protein folding: Helix dynamics in proteins and model peptides
Dyer, R.B.; Williams, S.; Woodruff, W.H. [Los Alamos National Lab., NM (United States)] [and others
1996-12-31
The earliest events in protein folding are critically important in determining the folding pathway, but have proved difficult to study by conventional approaches. We have developed new rapid initiation methods and structure-specific probes to interrogate the earliest events of protein folding. Our focus is the pathways. Folding or unfolding reactions are initiated on a fast timescale (10 ns) using a laser induced temperature jump (15 C) and probed with time-resolved infrared spectroscopy. We obtained the kinetics of the helix-coil transition for a model 21-residue peptide. The observed rate constant k{sub obs} = k{sub f} + k{sub u} for reversible kinetics; from the observed rate (6 x 10{sup 6} s{sup -1}) and the equilibrium constant favoring folding of 7.5 at 27 C, we calculate a folding lifetime of 180 ns and an unfolding lifetime of 1.4 {mu}s. The {open_quotes}molten globule{close_quotes} form of apomyoglobin (horse, pH*3, 0.15M NaCl) shows similar kinetics for helix that is unconstrained by tertiary structure (helix with an unusually low Amide I frequency, near 1633 cm{sup -1}). In {open_quotes}native{close_quotes} apomyoglobin (horse, pH*5.3, 10 mM NaCl) two very different rates (45 ns and 70 {mu}s) are observed and we infer that a third occurs on a timescales inaccessible to our experiment (> 1 ms). We suggest that the slower processes are due to helix formation that is rate-limited by the formation of tertiary structure.
Ostorero, L.; Moderski, R.; Stawarz, L.; Diaferio, A.; Kowalska, I.; Cheung, C.C.; Kataoka, J.; Begelman, M.C.; Wagner, S.J.; ,
2010-06-07
In a dynamical-radiative model we recently developed to describe the physics of compact, GHz-Peaked-Spectrum (GPS) sources, the relativistic jets propagate across the inner, kpc-sized region of the host galaxy, while the electron population of the expanding lobes evolves and emits synchrotron and inverse-Compton (IC) radiation. Interstellar-medium gas clouds engulfed by the expanding lobes, and photoionized by the active nucleus, are responsible for the radio spectral turnover through free-free absorption (FFA) of the synchrotron photons. The model provides a description of the evolution of the GPS spectral energy distribution (SED) with the source expansion, predicting significant and complex high-energy emission, from the X-ray to the {gamma}-ray frequency domain. Here, we test this model with the broad-band SEDs of a sample of eleven X-ray emitting GPS galaxies with Compact-Symmetric-Object (CSO) morphology, and show that: (i) the shape of the radio continuum at frequencies lower than the spectral turnover is indeed well accounted for by the FFA mechanism; (ii) the observed X-ray spectra can be interpreted as non-thermal radiation produced via IC scattering of the local radiation fields off the lobe particles, providing a viable alternative to the thermal, accretion-disk dominated scenario. We also show that the relation between the hydrogen column densities derived from the X-ray (N{sub H}) and radio (N{sub HI}) data of the sources is suggestive of a positive correlation, which, if confirmed by future observations, would provide further support to our scenario of high-energy emitting lobes.
Tidwell, Vincent Carroll; Sun, Amy Cha-Tien; Peplinski, William J.; Klise, Geoffrey Taylor
2012-04-01
Water resource management requires collaborative solutions that cross institutional and political boundaries. This work describes the development and use of a computer-based tool for assessing the impact of additional water allocation from the Gila River and the San Francisco River prescribed in the 2004 Arizona Water Settlements Act. Between 2005 and 2010, Sandia National Laboratories engaged concerned citizens, local water stakeholders, and key federal and state agencies to collaboratively create the Gila-San Francisco Decision Support Tool. Based on principles of system dynamics, the tool is founded on a hydrologic balance of surface water, groundwater, and their associated coupling between water resources and demands. The tool is fitted with a user interface to facilitate sensitivity studies of various water supply and demand scenarios. The model also projects the consumptive use of water in the region as well as the potential CUFA (Consumptive Use and Forbearance Agreement which stipulates when and where Arizona Water Settlements Act diversions can be made) diversion over a 26-year horizon. Scenarios are selected to enhance our understanding of the potential human impacts on the rivers ecological health in New Mexico; in particular, different case studies thematic to water conservation, water rights, and minimum flow are tested using the model. The impact on potential CUFA diversions, agricultural consumptive use, and surface water availability are assessed relative to the changes imposed in the scenarios. While it has been difficult to gage the acceptance level from the stakeholders, the technical information that the model provides are valuable for facilitating dialogues in the context of the new settlement.
Dynamic procedure for filtered gyrokinetic simulations
Morel, P.; Banon Navarro, A.; Albrecht-Marc, M.; Carati, D.; Merz, F.; Goerler, T.; Jenko, F.
2012-01-15
Large eddy simulations (LES) of gyrokinetic plasma turbulence are investigated as interesting candidates to decrease the computational cost. A dynamic procedure is implemented in the gene code, allowing for dynamic optimization of the free parameters of the LES models (setting the amplitudes of dissipative terms). Employing such LES methods, one recovers the free energy and heat flux spectra obtained from highly resolved direct numerical simulations. Systematic comparisons are performed for different values of the temperature gradient and magnetic shear, parameters which are of prime importance in ion temperature gradient driven turbulence. Moreover, the degree of anisotropy of the problem, which can vary with parameters, can be adapted dynamically by the method that shows gyrokinetic large eddy simulation to be a serious candidate to reduce numerical cost of gyrokinetic solvers.
Nichols, B.D.; Mueller, C.; Necker, G.A.; Travis, J.R.; Spore, J.W.; Lam, K.L.; Royl, P.; Redlinger, R.; Wilson, T.L.
1998-10-01
Los Alamos National Laboratory (LANL) and Forschungszentrum Karlsruhe (FzK) are developing GASFLOW, a three-dimensional (3D) fluid dynamics field code as a best-estimate tool to characterize local phenomena within a flow field. Examples of 3D phenomena include circulation patterns; flow stratification; hydrogen distribution mixing and stratification; combustion and flame propagation; effects of noncondensable gas distribution on local condensation and evaporation; and aerosol entrainment, transport, and deposition. An analysis with GASFLOW will result in a prediction of the gas composition and discrete particle distribution in space and time throughout the facility and the resulting pressure and temperature loadings on the walls and internal structures with or without combustion. A major application of GASFLOW is for predicting the transport, mixing, and combustion of hydrogen and other gases in nuclear reactor containments and other facilities. It has been applied to situations involving transporting and distributing combustible gas mixtures. It has been used to study gas dynamic behavior (1) in low-speed, buoyancy-driven flows, as well as sonic flows or diffusion dominated flows; and (2) during chemically reacting flows, including deflagrations. The effects of controlling such mixtures by safety systems can be analyzed. The code version described in this manual is designated GASFLOW 2.1, which combines previous versions of the United States Nuclear Regulatory Commission code HMS (for Hydrogen Mixing Studies) and the Department of Energy and FzK versions of GASFLOW. The code was written in standard Fortran 90. This manual comprises three volumes. Volume I describes the governing physical equations and computational model. Volume II describes how to use the code to set up a model geometry, specify gas species and material properties, define initial and boundary conditions, and specify different outputs, especially graphical displays. Sample problems are included
An optimization framework for workplace charging strategies ...
U.S. Department of Energy (DOE) all webpages (Extended Search)
addressing different eligible levels of charging technology and employees' demographic distributions. The optimization model is to minimize the lifetime cost of...
Churchfield, M. J.; Moriarty, P. J.; Hao, Y.; Lackner, M. A.; Barthelmie, R.; Lundquist, J.; Oxley, G. S.
2014-12-01
The focus of this work is the comparison of the dynamic wake meandering model and large-eddy simulation with field data from the Egmond aan Zee offshore wind plant composed of 36 3-MW turbines. The field data includes meteorological mast measurements, SCADA information from all turbines, and strain-gauge data from two turbines. The dynamic wake meandering model and large-eddy simulation are means of computing unsteady wind plant aerodynamics, including the important unsteady meandering of wakes as they convect downstream and interact with other turbines and wakes. Both of these models are coupled to a turbine model such that power and mechanical loads of each turbine in the wind plant are computed. We are interested in how accurately different types of waking (e.g., direct versus partial waking), can be modeled, and how background turbulence level affects these loads. We show that both the dynamic wake meandering model and large-eddy simulation appear to underpredict power and overpredict fatigue loads because of wake effects, but it is unclear that they are really in error. This discrepancy may be caused by wind-direction uncertainty in the field data, which tends to make wake effects appear less pronounced.
Optimal lattice-structured materials
Messner, Mark C.
2016-07-09
This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describingmore » the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.« less
Samolyuk, German D.; Osetskiy, Yury N.; Stoller, Roger E.
2015-06-03
We used molecular dynamics modeling of atomic displacement cascades to characterize the nature of primary radiation damage in 3C-SiC. We demonstrated that the most commonly used interatomic potentials are inconsistent with ab initio calculations of defect energetics. Both the Tersoff potential used in this work and a modified embedded-atom method potential reveal a barrier to recombination of the carbon interstitial and carbon vacancy which is much higher than the density functional theory (DFT) results. The barrier obtained with a newer potential by Gao and Weber is closer to the DFT result. This difference results in significant differences in the cascademore » production of point defects. We have completed both 10 keV and 50 keV cascade simulations in 3C-SiC at a range of temperatures. In contrast to the Tersoff potential, the Gao-Weber potential produces almost twice as many C vacancies and interstitials at the time of maximum disorder (~0.2 ps) but only about 25% more stable defects at the end of the simulation. Only about 20% of the carbon defects produced with the Tersoff potential recombine during the in-cascade annealing phase, while about 60% recombine with the Gao-Weber potential.« less
Samolyuk, German D.; Osetskiy, Yury N.; Stoller, Roger E.
2015-06-03
We used molecular dynamics modeling of atomic displacement cascades to characterize the nature of primary radiation damage in 3C-SiC. We demonstrated that the most commonly used interatomic potentials are inconsistent with ab initio calculations of defect energetics. Both the Tersoff potential used in this work and a modified embedded-atom method potential reveal a barrier to recombination of the carbon interstitial and carbon vacancy which is much higher than the density functional theory (DFT) results. The barrier obtained with a newer potential by Gao and Weber is closer to the DFT result. This difference results in significant differences in the cascade production of point defects. We have completed both 10 keV and 50 keV cascade simulations in 3C-SiC at a range of temperatures. In contrast to the Tersoff potential, the Gao-Weber potential produces almost twice as many C vacancies and interstitials at the time of maximum disorder (~0.2 ps) but only about 25% more stable defects at the end of the simulation. Only about 20% of the carbon defects produced with the Tersoff potential recombine during the in-cascade annealing phase, while about 60% recombine with the Gao-Weber potential.
Mapping of Reservoir Properties and Facies Through Integration of Static and Dynamic Data
Reynolds, Albert C.; Oliver, Dean S.; Zhang, Fengjun; Dong, Yannong; Skjervheim, Jan Arild; Liu, Ning
2003-03-10
The goal of this project was to develop computationally efficient automatic history matching techniques for generating geologically plausible reservoir models which honor both static and dynamic data. Solution of this problem was necessary for the quantification of uncertainty in future reservoir performance predictions and for the optimization of reservoir management.
Putting combustion optimization to work
Spring, N.
2009-05-15
New plants and plants that are retrofitting can benefit from combustion optimization. Boiler tuning and optimization can complement each other. The continuous emissions monitoring system CEMS, and tunable diode laser absorption spectroscopy TDLAS can be used for optimisation. NeuCO's CombustionOpt neural network software can determine optimal fuel and air set points. Babcock and Wilcox Power Generation Group Inc's Flame Doctor can be used in conjunction with other systems to diagnose and correct coal-fired burner performance. The four units of the Colstrip power plant in Colstrips, Montana were recently fitted with combustion optimization systems based on advanced model predictive multi variable controls (MPCs), ABB's Predict & Control tool. Unit 4 of Tampa Electric's Big Bend plant in Florida is fitted with Emerson's SmartProcess fuzzy neural model based combustion optimisation system. 1 photo.
Optimal Electric Utility Expansion
Energy Science and Technology Software Center (OSTI)
1989-10-10
SAGE-WASP is designed to find the optimal generation expansion policy for an electrical utility system. New units can be automatically selected from a user-supplied list of expansion candidates which can include hydroelectric and pumped storage projects. The existing system is modeled. The calculational procedure takes into account user restrictions to limit generation configurations to an area of economic interest. The optimization program reports whether the restrictions acted as a constraint on the solution. All expansionmore » configurations considered are required to pass a user supplied reliability criterion. The discount rate and escalation rate are treated separately for each expansion candidate and for each fuel type. All expenditures are separated into local and foreign accounts, and a weighting factor can be applied to foreign expenditures.« less
Preliminary TES design optimization study for a simple periodic brick plant
Drake, J.B.; Olszewski, M.; Solomon, A.D.
1989-03-01
A general optimization method has been developed for maximizing the return on investment for a brick plant re-using waste heat with the capability of storing energy over periods when a kiln is not operating. The duct connections between devices and storage along with the operating schedule of flow rates in these ducts are the independent variables available for control. A combination of combinatorial search algorithms along with a dynamic programming model and the simplex method are layered to provide the optimization technique.
Optimal segmentation and packaging process
Kostelnik, Kevin M.; Meservey, Richard H.; Landon, Mark D.
1999-01-01
A process for improving packaging efficiency uses three dimensional, computer simulated models with various optimization algorithms to determine the optimal segmentation process and packaging configurations based on constraints including container limitations. The present invention is applied to a process for decontaminating, decommissioning (D&D), and remediating a nuclear facility involving the segmentation and packaging of contaminated items in waste containers in order to minimize the number of cuts, maximize packaging density, and reduce worker radiation exposure. A three-dimensional, computer simulated, facility model of the contaminated items are created. The contaminated items are differentiated. The optimal location, orientation and sequence of the segmentation and packaging of the contaminated items is determined using the simulated model, the algorithms, and various constraints including container limitations. The cut locations and orientations are transposed to the simulated model. The contaminated items are actually segmented and packaged. The segmentation and packaging may be simulated beforehand. In addition, the contaminated items may be cataloged and recorded.
Yu, Miao; Wang, Guiling; Chen, Haishan
2016-03-01
Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to
Gabl, Sonja; Schröder, Christian; Braun, Daniel; Steinhauser, Othmar; Weingärtner, Hermann
2014-05-14
Combining simulation and model theories, this paper analyses the impact of pair dynamics on the intermolecular nuclear Overhauser effect (NOE) in liquids. For the first time, we give a distance resolved NOE. When applied to the ionic liquid 1-ethyl-3-methyl-imidazolium tetrafluoroborate the NOE turns out to be of long-range nature. This behaviour translates to the experimentally measured cross- and longitudinal relaxation rates. We were able to calculate the heteronuclear NOE from simulation data, despite the high computational effort. Model theories are computationally less demanding and cover the complete frequency range of the respective spectral density function, they are usually based on a very simple pair distribution function and the solution of the diffusion equation. In order to model the simulated data sufficiently, these simplifications in structure and dynamics have to be generalised considerably.
Combustion and Emissions Modeling
U.S. Department of Energy (DOE) all webpages (Extended Search)
Combustion and Emissions Modeling This email address is being protected from spambots. You need JavaScript enabled to view it. - Computational Fluid Dynamics Project Leader Background Modern transportation engines are designed to use the available fuel resources efficiently and minimize harmful emissions. Optimization of these designs is based on a wealth of practical design, construction and operating experiences, and use of modern testing facilities and sophisticated analyses of the combustion
H–J–B Equations of Optimal Consumption-Investment and Verification Theorems
Nagai, Hideo
2015-04-15
We consider a consumption-investment problem on infinite time horizon maximizing discounted expected HARA utility for a general incomplete market model. Based on dynamic programming approach we derive the relevant H–J–B equation and study the existence and uniqueness of the solution to the nonlinear partial differential equation. By using the smooth solution we construct the optimal consumption rate and portfolio strategy and then prove the verification theorems under certain general settings.
Nguyen, Ba Nghiep; Gao, Fei; Henager, Charles H.; Kurtz, Richard J.
2014-05-01
This article proposes a new method to estimate the thermal conductivity of SiC/SiC composites subjected to neutron irradiation. The modeling method bridges different scales from the atomic scale to the scale of a 2D SiC/SiC composite. First, it studies the irradiation-induced point defects in perfect crystalline SiC using molecular dynamics (MD) simulations to compute the defect thermal resistance as a function of vacancy concentration and irradiation dose. The concept of defect thermal resistance is explored explicitly in the MD data using vacancy concentrations and thermal conductivity decrements due to phonon scattering. Point defect-induced swelling for chemical vapor deposited (CVD) SiC as a function of irradiation dose is approximated by scaling the corresponding MD results for perfect crystal ?-SiC to experimental data for CVD-SiC at various temperatures. The computed thermal defect resistance, thermal conductivity as a function of grain size, and definition of defect thermal resistance are used to compute the thermal conductivities of CVD-SiC, isothermal chemical vapor infiltrated (ICVI) SiC and nearly-stoichiometric SiC fibers. The computed fiber and ICVI-SiC matrix thermal conductivities are then used as input for an Eshelby-Mori-Tanaka approach to compute the thermal conductivities of 2D SiC/SiC composites subjected to neutron irradiation within the same irradiation doses. Predicted thermal conductivities for an irradiated Tyranno-SA/ICVI-SiC composite are found to be comparable to available experimental data for a similar composite ICVI-processed with these fibers.
Rakowski, Cynthia L.; Serkowski, John A.; Richmond, Marshall C.; Perkins, William A.
2010-12-01
In 2003, an extension of the existing ice and trash sluiceway was added at Bonneville Powerhouse 2 (B2). This extension started at the existing corner collector for the ice and trash sluiceway adjacent to Bonneville Powerhouse 2 and the new sluiceway was extended to the downstream end of Cascade Island. The sluiceway was designed to improve juvenile salmon survival by bypassing turbine passage at B2, and placing these smolt in downstream flowing water minimizing their exposure to fish and avian predators. In this study, a previously developed computational fluid dynamics model was modified and used to characterized tailrace hydraulics and sluiceway egress conditions for low total river flows and low levels of spillway flow. STAR-CD v4.10 was used for seven scenarios of low total river flow and low spill discharges. The simulation results were specifically examined to look at tailrace hydraulics at 5 ft below the tailwater elevation, and streamlines used to compare streamline pathways for streamlines originating in the corner collector outfall and adjacent to the outfall. These streamlines indicated that for all higher spill percentage cases (25% and greater) that streamlines from the corner collector did not approach the shoreline at the downstream end of Bradford Island. For the cases with much larger spill percentages, the streamlines from the corner collector were mid-channel or closer to the Washington shore as they moved downstream. Although at 25% spill at 75 kcfs total river, the total spill volume was sufficient to "cushion" the flow from the corner collector from the Bradford Island shore, areas of recirculation were modeled in the spillway tailrace. However, at the lowest flows and spill percentages, the streamlines from the B2 corner collector pass very close to the Bradford Island shore. In addition, the very flow velocity flows and large areas of recirculation greatly increase potential predator exposure of the spillway passed smolt. If there is
Sootblowing optimization for improved boiler performance
James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J
2013-07-30
A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.
Sootblowing optimization for improved boiler performance
James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.
2012-12-25
A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.
Dynamic ray tracing and traveltime corrections for global seismic tomography
Tian Yue Hung, S.-H.; Nolet, Guust; Montelli, Raffaella; Dahlen, F.A.
2007-09-10
We present a dynamic ray tracing program for a spherically symmetric Earth that may be used to compute Frechet kernels for traveltime and amplitude anomalies at finite frequency. The program works for arbitrarily defined phases and background models. The numerical precisions of kinematic and dynamic ray tracing are optimized to produce traveltime errors under 0.1 s, which is well below the data uncertainty in global seismology. This tolerance level is obtained for an integration step size of about 20 km for the most common seismic phases. We also give software to compute ellipticity, crustal and topographic corrections and attenuation.
U.S. Department of Energy (DOE) all webpages (Extended Search)
scour-tracc-cfd TRACC RESEARCH Computational Fluid Dynamics Computational Structural Mechanics Transportation Systems Modeling Computational Fluid Dynamics Overview of CFD: Video Clip with Audio Computational fluid dynamics (CFD) research uses mathematical and computational models of flowing fluids to describe and predict fluid response in problems of interest, such as the flow of air around a moving vehicle or the flow of water and sediment in a river. Coupled with appropriate and prototypical
Yi, Jianbing; Yang, Xuan Li, Yan-Ran; Chen, Guoliang
2015-10-15
Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the
U.S. Department of Energy (DOE) all webpages (Extended Search)
Performance and Optimization Performance and Optimization Benchmarking Software on Hopper and Carver PURPOSE Test the performance impact of multithreading with representative...
Hydrogen Transition (HyTRANS) Model
Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)
optimization of an objective function that reflects private costs and benefits. ... Platform, Requirements & Availability HyTRANS is a dynamic, non- linear optimization, ...
Not Available
1989-01-01
Various papers on rotorcraft dynamics are presented. Individual topics addressed include: aeromechanical stability of helicopters, evolution and test history of the V-22 Aeroelastic Model Series, helicopter individual blade control through optimal output feedback, dynamic characteristics of composite beam structures, dynamic testing of thin-walled composite box beams in a vacuum chamber, fundamental dynamics issues for comprehensive rotorcraft analyses, and development of the second generation Comprehensive Helicopter Analysis System. Also considered are: experiences in NASTRAN airframe vibration predictions, application of CRFD program to total helicopter dynamics, vibration reduction on servoflap controlled rotor using HHC, V-22 MSC/NASTRAN airframe vibration analysis and correlation, responses of helicopter rotors to vibratory airloads, helicopter rotor load calculations, prediction and alleviation of V-22 rotor dynamic loads, free wake analysis of rotor configurations for reduced vibratory airloads.
Loth, E.; Tryggvason, G.; Tsuji, Y.; Elghobashi, S. E.; Crowe, Clayton T.; Berlemont, A.; Reeks, M.; Simonin, O.; Frank, Th; Onishi, Yasuo; Van Wachem, B.
2005-09-01
Slurry flows occur in many circumstances, including chemical manufacturing processes, pipeline transfer of coal, sand, and minerals; mud flows; and disposal of dredged materials. In this section we discuss slurry flow applications related to radioactive waste management. The Hanford tank waste solids and interstitial liquids will be mixed to form a slurry so it can be pumped out for retrieval and treatment. The waste is very complex chemically and physically. The ARIEL code is used to model the chemical interactions and fluid dynamics of the waste.
Herczfeld, P R; Fischl, R
1980-01-01
The program objectives were to (1) assess the feasibility of using the TRNSYS computer code for solar heating and cooling control studies and modify it wherever possible, and (2) develop a new dynamic model of the solar collector which reflects the performance of the collector under transient conditions. Also, the sensitivity of the performance of this model to the various system parameters such as collector time constants, flow rates, turn-on and turn-off temperature set points, solar insolation, etc., was studied. Results are presented and discussed. (WHK)
Smyth, Padhraic
2013-07-22
This is the final report for a DOE-funded research project describing the outcome of research on non-homogeneous hidden Markov models (NHMMs) and coupled ocean-atmosphere (O-A) intermediate-complexity models (ICMs) to identify the potentially predictable modes of climate variability, and to investigate their impacts on the regional-scale. The main results consist of extensive development of the hidden Markov models for rainfall simulation and downscaling specifically within the non-stationary climate change context together with the development of parallelized software; application of NHMMs to downscaling of rainfall projections over India; identification and analysis of decadal climate signals in data and models; and, studies of climate variability in terms of the dynamics of atmospheric flow regimes.
Energy Science and Technology Software Center (OSTI)
2007-02-16
Pynamic is a benchmark designed to test a system's ability to handle the Dynamic Linking and Loading (DLL) requirements of Python-based scientific applications. This benchmark is developed to add a workload to our testing environment, a workload that represents a newly emerging class of DLL behaviors. Pynamic buildins on pyMPI, and MPI extension to Python C-extension dummy codes and a glue layer that facilitates linking and loading of the generated dynamic modules into the resultingmore » pyMPI. Pynamic is configurable, enabling modeling the static properties of a specific code as described in section 5. It does not, however, model any significant computationss of the target and hence, it is not subjected to the same level of control as the target code. In fact, HPC computer vendors and tool developers will be encouraged to add it to their tesitn suite once the code release is completed. an ability to produce and run this benchmark is an effective test for valifating the capability of a compiler and linker/loader as well as an OS kernel and other runtime system of HPC computer vendors. In addition, the benchmark is designed as a test case for stressing code development tools. Though Python has recently gained popularity in the HPC community, it heavy DLL operations have hindered certain HPC code development tools, notably parallel debuggers, from performing optimally.« less
Wind Electrolysis: Hydrogen Cost Optimization
Saur, G.; Ramsden, T.
2011-05-01
This report describes a hydrogen production cost analysis of a collection of optimized central wind based water electrolysis production facilities. The basic modeled wind electrolysis facility includes a number of low temperature electrolyzers and a co-located wind farm encompassing a number of 3MW wind turbines that provide electricity for the electrolyzer units.
Dynamical principles in neuroscience
Rabinovich, Mikhail I.; Varona, Pablo; Selverston, Allen I.; Abarbanel, Henry D. I.
2006-10-15
Dynamical modeling of neural systems and brain functions has a history of success over the last half century. This includes, for example, the explanation and prediction of some features of neural rhythmic behaviors. Many interesting dynamical models of learning and memory based on physiological experiments have been suggested over the last two decades. Dynamical models even of consciousness now exist. Usually these models and results are based on traditional approaches and paradigms of nonlinear dynamics including dynamical chaos. Neural systems are, however, an unusual subject for nonlinear dynamics for several reasons: (i) Even the simplest neural network, with only a few neurons and synaptic connections, has an enormous number of variables and control parameters. These make neural systems adaptive and flexible, and are critical to their biological function. (ii) In contrast to traditional physical systems described by well-known basic principles, first principles governing the dynamics of neural systems are unknown. (iii) Many different neural systems exhibit similar dynamics despite having different architectures and different levels of complexity. (iv) The network architecture and connection strengths are usually not known in detail and therefore the dynamical analysis must, in some sense, be probabilistic. (v) Since nervous systems are able to organize behavior based on sensory inputs, the dynamical modeling of these systems has to explain the transformation of temporal information into combinatorial or combinatorial-temporal codes, and vice versa, for memory and recognition. In this review these problems are discussed in the context of addressing the stimulating questions: What can neuroscience learn from nonlinear dynamics, and what can nonlinear dynamics learn from neuroscience?.
Roberto, Baccoli; Ubaldo, Carlini; Stefano, Mariotti; Roberto, Innamorati; Elisa, Solinas; Paolo, Mura
2010-06-15
This paper deals with the development of methods for non steady state test of solar thermal collectors. Our goal is to infer performances in steady-state conditions in terms of the efficiency curve when measures in transient conditions are the only ones available. We take into consideration the method of identification of a system in dynamic conditions by applying a Graybox Identification Model and a Dynamic Adaptative Linear Neural Network (ALNN) model. The study targets the solar collector with evacuated pipes, such as Dewar pipes. The mathematical description that supervises the functioning of the solar collector in transient conditions is developed using the equation of the energy balance, with the aim of determining the order and architecture of the two models. The input and output vectors of the two models are constructed, considering the measures of 4 days of solar radiation, flow mass, environment and heat-transfer fluid temperature in the inlet and outlet from the thermal solar collector. The efficiency curves derived from the two models are detected in correspondence to the test and validation points. The two synthetic simulated efficiency curves are compared with the actual efficiency curve certified by the Swiss Institute Solartechnik Puffung Forschung which tested the solar collector performance in steady-state conditions according to the UNI-EN 12975 standard. An acquisition set of measurements of only 4 days in the transient condition was enough to trace through a Graybox State Space Model the efficiency curve of the tested solar thermal collector, with a relative error of synthetic values with respect to efficiency certified by SPF, lower than 0.5%, while with the ALNN model the error is lower than 2.2% with respect to certified one. (author)
1996-12-31
Over the next four years, the Progetto Energia project will be building several cogeneration plants to help satisfy the increasing demands of Italy`s industrial users and the country`s demand for electrical power. Located at six different sites within Italy, these combined-cycle cogeneration plants will supply a total of 500 MW of electricity and 100 tons/hr of process steam to Italian industries and residences. To ensure project success, a dynamic model of the 50-MW base unit was developed. The goal established for the model was to predict the dynamic behavior of the complex thermodynamic system in order to assess equipment performance and control system effectiveness for normal operation and, more importantly, abrupt load changes. In addition to fulfilling its goals, the dynamic study guided modifications to controller logic that significantly improved steam drum pressure control and bypassed steam desuperheating performance simulations of normal and abrupt transient events allowed engineers to define optimum controller gain coefficients. The dynamic study will undoubtedly reduce the associated plant start-up costs and contribute to a smooth commercial plant acceptance. As a result of the work, the control system has already been through its check-out and performance evaluation, usually performed during the plant start-up phase. Field engineers will directly benefit from this effort to identify and resolve control system {open_quotes}bugs{close_quotes} before the equipment reaches the field. High thermal efficiency, rapid dispatch and high plant availability were key reasons why the natural gas combined-cycle plant was chosen. Other favorable attributes of the combined-cycle plant contributing to the decision were: Minimal environmental impact; a simple and effective process and control philosophy to result in safe and easy plant operation; a choice of technologies and equipment proven in a large number of applications.
Energy Science and Technology Software Center (OSTI)
2007-03-01
Aristos is a Trilinos package for nonlinear continuous optimization, based on full-space sequential quadratic programming (SQP) methods. Aristos is specifically designed for the solution of large-scale constrained optimization problems in which the linearized constraint equations require iterative (i.e. inexact) linear solver techniques. Aristos' unique feature is an efficient handling of inexactness in linear system solves. Aristos currently supports the solution of equality-constrained convex and nonconvex optimization problems. It has been used successfully in the areamore » of PDE-constrained optimization, for the solution of nonlinear optimal control, optimal design, and inverse problems.« less
About an Optimal Visiting Problem
Bagagiolo, Fabio Benetton, Michela
2012-02-15
In this paper we are concerned with the optimal control problem consisting in minimizing the time for reaching (visiting) a fixed number of target sets, in particular more than one target. Such a problem is of course reminiscent of the famous 'Traveling Salesman Problem' and brings all its computational difficulties. Our aim is to apply the dynamic programming technique in order to characterize the value function of the problem as the unique viscosity solution of a suitable Hamilton-Jacobi equation. We introduce some 'external' variables, one per target, which keep in memory whether the corresponding target is already visited or not, and we transform the visiting problem in a suitable Mayer problem. This fact allows us to overcome the lacking of the Dynamic Programming Principle for the originary problem. The external variables evolve with a hysteresis law and the Hamilton-Jacobi equation turns out to be discontinuous.
Design Optimization of Vena Cava Filters: An application to dual filtration devices
Singer, M A; Wang, S L; Diachin, D P
2009-12-03
Pulmonary embolism (PE) is a significant medical problem that results in over 300,000 fatalities per year. A common preventative treatment for PE is the insertion of a metallic filter into the inferior vena cava that traps thrombi before they reach the lungs. The goal of this work is to use methods of mathematical modeling and design optimization to determine the configuration of trapped thrombi that minimizes the hemodynamic disruption. The resulting configuration has implications for constructing an optimally designed vena cava filter. Computational fluid dynamics is coupled with a nonlinear optimization algorithm to determine the optimal configuration of trapped model thrombus in the inferior vena cava. The location and shape of the thrombus are parameterized, and an objective function, based on wall shear stresses, determines the worthiness of a given configuration. The methods are fully automated and demonstrate the capabilities of a design optimization framework that is broadly applicable. Changes to thrombus location and shape alter the velocity contours and wall shear stress profiles significantly. For vena cava filters that trap two thrombi simultaneously, the undesirable flow dynamics past one thrombus can be mitigated by leveraging the flow past the other thrombus. Streamlining the shape of thrombus trapped along the cava wall reduces the disruption to the flow, but increases the area exposed to abnormal wall shear stress. Computer-based design optimization is a useful tool for developing vena cava filters. Characterizing and parameterizing the design requirements and constraints is essential for constructing devices that address clinical complications. In addition, formulating a well-defined objective function that quantifies clinical risks and benefits is needed for designing devices that are clinically viable.
Protein Dynamics and Biocatalysis
U.S. Department of Energy (DOE) all webpages (Extended Search)
Protein Dynamics and Biocatalysis Protein Dynamics and Biocatalysis 1998 Annual Report Grand Challenge Projects biocatalysis.gif A model of the Michaelis complex for the TEM-1/penicillin system from molecular dynamics simulations. Investigators: P. A. Bash, Northwestern University Medical School and M. Karplus, Harvard University Research Objectives A guiding principle of molecular biology is that the structure of a biomolecule defines its function. This principle is especially true in the case
Thermodynamic Metrics and Optimal Paths
Sivak, David; Crooks, Gavin
2012-05-08
A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.
Optimized nanoporous materials.
Braun, Paul V.; Langham, Mary Elizabeth; Jacobs, Benjamin W.; Ong, Markus D.; Narayan, Roger J.; Pierson, Bonnie E.; Gittard, Shaun D.; Robinson, David B.; Ham, Sung-Kyoung; Chae, Weon-Sik; Gough, Dara V.; Wu, Chung-An Max; Ha, Cindy M.; Tran, Kim L.
2009-09-01
Nanoporous materials have maximum practical surface areas for electrical charge storage; every point in an electrode is within a few atoms of an interface at which charge can be stored. Metal-electrolyte interfaces make best use of surface area in porous materials. However, ion transport through long, narrow pores is slow. We seek to understand and optimize the tradeoff between capacity and transport. Modeling and measurements of nanoporous gold electrodes has allowed us to determine design principles, including the fact that these materials can deplete salt from the electrolyte, increasing resistance. We have developed fabrication techniques to demonstrate architectures inspired by these principles that may overcome identified obstacles. A key concept is that electrodes should be as close together as possible; this is likely to involve an interpenetrating pore structure. However, this may prove extremely challenging to fabricate at the finest scales; a hierarchically porous structure can be a worthy compromise.
Razm-Pa, M; Emami, F
2015-01-31
We report a new circuit model for a self-assembled quantum-dot (SAQD) laser made of InGaAs/GaAs structures. The model is based on the excited state and standard rate equations, improves the previously suggested circuit models and also provides and investigates the performance of this kind of laser. The carrier dynamic effects on static and dynamic characteristics of a SAQD laser are analysed. The phonon bottleneck problem is simulated. Quantum-dot lasers are shown to be quite sensitive to the crystal quality outside and inside quantum dots. The effects of QD coverage factor, inhomogeneous broadening, the physical source of which is the size fluctuation of quantum dots formed by self-assembly of atoms, and cavity length on the SAQD laser characteristics are analysed. The results of simulation show that an increase in the cavity length and in the QD coverage factor results in the growth of the output power. On the other hand, an increase in the coverage factor and a degradation of inhomogeneous broadening lead to an increase in the modulation bandwidth. The effect of the QD height (cylindrical shape) and stripe width of the laser cavity on QD laser modulation is also analysed. (lasers)
New Spectroscopic Technique Reveals the Dynamics of Operating...
U.S. Department of Energy (DOE) all webpages (Extended Search)
New Spectroscopic Technique Reveals the Dynamics of Operating Battery Electrodes Print ... have become indispensable in studying and the eventual optimization of battery materials. ...
Adjoints and Large Data Sets in Computational Fluid Dynamics...
U.S. Department of Energy (DOE) all webpages (Extended Search)
Oana Marin Speaker(s) Title: Postdoctoral Appointee, MCS Optimal flow control and stability analysis are some of the fields within Computational Fluid Dynamics (CFD) that...
Price, R; Veltchev, I; Cherian, G; Ma, C
2014-06-01
Purpose: Multiple publications exist concerning fixed-jaw utilization to avoid linac carriage shifts and reduce intensity modulated radiotherapy (IMRT) treatment times. The purpose of this work is to demonstrate delivery QA discrepancies and illustrate the need for improved treatment planning system (TPS) commissioning for non-routine use. Methods: A 6cm diameter spherical target was delineated on a virtual phantom containing the Iba Matrixx linear array within the Varian Eclipse TPS. Optimization was performed for target coverage for the following 3 scenarios: a single open, zero degree field where the X and Y jaws completely cover the target; the same field using an asymmetric, fixed-jaw technique where the upper Y jaw does not cover the superior 2cm of the target; and both of the aforementioned directed at the target at 315 and 45 degree gantry angles, respectively. This final orientation was also irradiated on a linac for delivery analysis. A sarcoma patient case was also analyzed where the fixed jaw technique was utilized for kidney sparing. Results: The open beam results were as predicted but the fixed-jaw results demonstrate a pronounced fluence increase along the asymmetric, upper jaw. Analysis of the delivery of the combined beam plan Resultin 83% of pixels evaluated passing gamma criteria of 3%, 3mm DTA. Analysis for the sarcoma patient, in the plane of the shielded kidney, indicated 93% passing although the maximum dose discrepancies in this region were approximately 23%. Conclusion: Optimization within the target is routinely performed using MLC leaf-end characteristics. The fixed-jaw technique forces optimization of target coverage to utilize the penumbra profiles of the associated beamdefining jaw. If the profiles were collected using a common 0.125cc ionization chamber, the resolution may be insufficient resulting in a planvs.-delivery mismatch. It is recommended that high-resolution beam characteristics be considered when non-routine planning
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
Atchley, Adam L.; Painter, Scott L.; Harp, Dylan R.; Coon, Ethan T.; Wilson, Cathy J.; Liljedahl, Anna K.; Romanovsky, V. E.
2015-09-01
Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. Thus, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth system models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth system models challenge validation and parameterization of hydrothermal models. A recently developed surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to achieve the goals of constructing a process-rich model based on plausible parameters and to identify fine-scale controls of ALT in ice-wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze–thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g., troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
Atchley, Adam L.; Painter, Scott L.; Harp, Dylan R.; Coon, Ethan T.; Wilson, Cathy J.; Liljedahl, Anna K.; Romanovsky, V. E.
2015-09-01
Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. Thus, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth system models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth system models challenge validation and parameterization of hydrothermal models. A recently developed surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to achieve the goals of constructing a process-rich model based on plausible parameters and to identify fine-scale controls of ALT in ice-wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze–thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g., troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less
Coffin, D.W.
1996-10-01
With the development of on-line and real-time process simulations, one obtains the ability to predict and control the process; thus, the opportunity exists to improve energy efficiency, decrease materials wastes, and maintain product quality. Developing this capability was the objective of the this research program. A thermomechanical pulp mill was simulated using both a first principles model and a neural network. The models made use of actual process data and a model that calculated the mass and energy balance of the mill was successfully implemented and run at the mill on an hourly basis. The attempt to develop a model that accurately predicted the quality of the pulp was not successful. It was concluded that the key fro a successful implementation of a real-time control model, such as a neural net model, is availability of on-line sensors that sufficiently characterize the pulp.
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
Atchley, A. L.; Painter, S. L.; Harp, D. R.; Coon, E. T.; Wilson, C. J.; Liljedahl, A. K.; Romanovsky, V. E.
2015-04-14
Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurementsmore » to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.« less
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83)
Atchley, A. L.; Painter, S. L.; Harp, D. R.; Coon, E. T.; Wilson, C. J.; Liljedahl, A. K.; Romanovsky, V. E.
2015-04-14
Climate change is profoundly transforming the carbon-rich Arctic tundra landscape, potentially moving it from a carbon sink to a carbon source by increasing the thickness of soil that thaws on a seasonal basis. However, the modeling capability and precise parameterizations of the physical characteristics needed to estimate projected active layer thickness (ALT) are limited in Earth System Models (ESMs). In particular, discrepancies in spatial scale between field measurements and Earth System Models challenge validation and parameterization of hydrothermal models. A recently developed surface/subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements to calibrate and identify fine scale controls of ALT in ice wedge polygon tundra in Barrow, Alaska. An iterative model refinement procedure that cycles between borehole temperature and snow cover measurements and simulations functions to evaluate and parameterize different model processes necessary to simulate freeze/thaw processes and ALT formation. After model refinement and calibration, reasonable matches between simulated and measured soil temperatures are obtained, with the largest errors occurring during early summer above ice wedges (e.g. troughs). The results suggest that properly constructed and calibrated one-dimensional thermal hydrology models have the potential to provide reasonable representation of the subsurface thermal response and can be used to infer model input parameters and process representations. The models for soil thermal conductivity and snow distribution were found to be the most sensitive process representations. However, information on lateral flow and snowpack evolution might be needed to constrain model representations of surface hydrology and snow depth.
Keane, R.E.; Long, D.G.; Menakis, J.P.; Hann, W.J.; Bevins, C.D.
1996-10-01
The paper details the landscape succession model developed for the coarse-scale assessment called CRBSUM (Columbia River Basin SUccession Model) and presents some general results of the application of this model to the entire basin. CRBSUM was used to predict future landscape characteristics to evaluate management alternatives for both mid-and coarse-scale efforts. A test and sensitivity analysis of CRBSUM is also presented. This paper was written as a users guide for those who wish to run the model and interprete results, and its was also written as documentation for some results of the Interior Columbia River Basin simulation effort.
Optimization of chemical etching process in niobium cavities
Tajima, T. (Tsuyoshi); Trabia, M.; Culbreth, W.; Subramanian, S.
2004-01-01
Superconducting niobium cavities are important components of linear accelerators. Buffered chemical polishing (BCP) on the inner surface of the cavity is a standard procedure to improve its performance. The quality of BCP, however, has not been optimized well in terms of the uniformity of surface smoothness. A finite element computational fluid dynamics (CFD) model was developed to simulate the chemical etching process inside the cavity. The analysis confirmed the observation of other researchers that the iris section of the cavity received more etching than the equator regions due to higher flow rate. The baffle, which directs flow towards the walls of the cavity, was redesigned using optimization techniques. The redesigned baffle significantly improves the performance of the etching process. To verify these results an experimental setup for flow visualization was created. The setup consists of a high speed, high resolution CCD camera. The camera is positioned by a computer-controlled traversing mechanism. A dye injecting arrangement is used for tracking the fluid path. Experimental results are in general agreement with CFD and optimization results.
Quasi-Optimal Elimination Trees for 2D Grids with Singularities
Paszyńska, A.; Paszyński, M.; Jopek, K.; Woźniak, M.; Goik, D.; Gurgul, P.; AbouEisha, H.; Moshkov, M.; Calo, V. M.; Lenharth, A.; et al
2015-01-01
We consmore » truct quasi-optimal elimination trees for 2D finite element meshes with singularities. These trees minimize the complexity of the solution of the discrete system. The computational cost estimates of the elimination process model the execution of the multifrontal algorithms in serial and in parallel shared-memory executions. Since the meshes considered are a subspace of all possible mesh partitions, we call these minimizers quasi-optimal. We minimize the cost functionals using dynamic programming. Finding these minimizers is more computationally expensive than solving the original algebraic system. Nevertheless, from the insights provided by the analysis of the dynamic programming minima, we propose a heuristic construction of the elimination trees that has cost O N e log N e , where N e is the number of elements in the mesh. We show that this heuristic ordering has similar computational cost to the quasi-optimal elimination trees found with dynamic programming and outperforms state-of-the-art alternatives in our numerical experiments.« less
Palm: Easing the Burden of Analytical Performance Modeling
Tallent, Nathan R.; Hoisie, Adolfy
2014-06-01
Analytical (predictive) application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult because they must be both accurate and concise. To ease the burden of performance modeling, we developed Palm, a modeling tool that combines top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. To express insight, Palm defines a source code modeling annotation language. By coordinating models and source code, Palm's models are `first-class' and reproducible. Unlike prior work, Palm formally links models, functions, and measurements. As a result, Palm (a) uses functions to either abstract or express complexity (b) generates hierarchical models (representing an application's static and dynamic structure); and (c) automatically incorporates measurements to focus attention, represent constant behavior, and validate models. We discuss generating models for three different applications.
Ruyer, C. Gremillet, L. Debayle, A.; Bonnaud, G.
2015-03-15
We present a predictive model of the nonlinear phase of the Weibel instability induced by two symmetric, counter-streaming ion beams in the non-relativistic regime. This self-consistent model combines the quasilinear kinetic theory of Davidson et al. [Phys. Fluids 15, 317 (1972)] with a simple description of current filament coalescence. It allows us to follow the evolution of the ion parameters up to a stage close to complete isotropization, and is thus of prime interest to understand the dynamics of collisionless shock formation. Its predictions are supported by 2-D and 3-D particle-in-cell simulations of the ion Weibel instability. The derived approximate analytical solutions reveal the various dependencies of the ion relaxation to isotropy. In particular, it is found that the influence of the electron screening can affect the results of simulations using an unphysical electron mass.
Knoll, W.; Peters, J.; Kursula, P.; Gerelli, Y.; Natali, F.
2014-11-28
Myelin is an insulating, multi-lamellar membrane structure wrapped around selected nerve axons. Increasing the speed of nerve impulses, it is crucial for the proper functioning of the vertebrate nervous system. Human neurodegenerative diseases, such as multiple sclerosis, are linked to damage to the myelin sheath through demyelination. Myelin exhibits a well defined subset of myelin-specific proteins, whose influence on membrane dynamics, i.e., myelin flexibility and stability, has not yet been explored in detail. In a first paper [W. Knoll, J. Peters, P. Kursula, Y. Gerelli, J. Ollivier, B. Demé, M. Telling, E. Kemner, and F. Natali, Soft Matter 10, 519 (2014)] we were able to spotlight, through neutron scattering experiments, the role of peripheral nervous system myelin proteins on membrane stability at room temperature. In particular, the myelin basic protein and peripheral myelin protein 2 were found to synergistically influence the membrane structure while keeping almost unchanged the membrane mobility. Further insight is provided by this work, in which we particularly address the investigation of the membrane flexibility in the low temperature regime. We evidence a different behavior suggesting that the proton dynamics is reduced by the addition of the myelin basic protein accompanied by negligible membrane structural changes. Moreover, we address the importance of correct sample preparation and characterization for the success of the experiment and for the reliability of the obtained results.
Peterson, Steve; Bush, Brian; Vimmerstedt, Laura
2015-07-19
This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.
Optimal segmentation and packaging process
Kostelnik, K.M.; Meservey, R.H.; Landon, M.D.
1999-08-10
A process for improving packaging efficiency uses three dimensional, computer simulated models with various optimization algorithms to determine the optimal segmentation process and packaging configurations based on constraints including container limitations. The present invention is applied to a process for decontaminating, decommissioning (D and D), and remediating a nuclear facility involving the segmentation and packaging of contaminated items in waste containers in order to minimize the number of cuts, maximize packaging density, and reduce worker radiation exposure. A three-dimensional, computer simulated, facility model of the contaminated items are created. The contaminated items are differentiated. The optimal location, orientation and sequence of the segmentation and packaging of the contaminated items is determined using the simulated model, the algorithms, and various constraints including container limitations. The cut locations and orientations are transposed to the simulated model. The contaminated items are actually segmented and packaged. The segmentation and packaging may be simulated beforehand. In addition, the contaminated items may be cataloged and recorded. 3 figs.
CASL - Materials and Performance Optimization (MPO)
U.S. Department of Energy (DOE) all webpages (Extended Search)
Materials and Performance Optimization (MPO) The Materials and Performance Optimization (MPO) focus area within CASL has recently developed and released a 3D modeling framework known as MAMBA (MPO Advanced Model for Boron Analysis) to predict CRUD deposition on nuclear fuel rods. CRUD, which refers to Chalk River Unidentified Deposit, is predominately a nickel-ferrite spinel corrosion product that deposits on hot fuel clad surfaces in nuclear reactors. CRUD has a lower thermal conductivity than
Tian, Hanqin; Lu, Chaoqun; Yang, Jia; Banger, Kamaljit; Huntzinger, Deborah N.; Schwalm, Christopher R.; Michalak, Anna M.; Cook, Robert; Ciais, Philippe; Hayes, Daniel; Huang, Maoyi; Ito, Akihiko; Jain, Atul K.; Lei, Huimin; Mao, Jiafu; Pan, Shufen; Post, Wilfred M.; Peng, Shushi; Poulter, Benjamin; Ren, Wei; Ricciuto, Daniel; Schaefer, Kevin; Shi, Xiaoying; Tao, Bo; Wang, Weile; Wei, Yaxing; Yang, Qichun; Zhang, Bowen; Zeng, Ning
2015-06-05
Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO₂) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901–2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 10¹⁵ g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr⁻¹ with a median value of 51 Pg C yr⁻¹ during 2001–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901–2010 ranges from –70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO₂ and nitrogen deposition over intact ecosystems increased SOC stocks—even though the responses varied significantly
Tian, Hanqin; Lu, Chaoqun; Yang, Jia; Banger, Kamaljit; Huntzinger, Deborah N.; Schwalm, Christopher R.; Michalak, Anna M.; Cook, Robert; Ciais, Philippe; Hayes, Daniel; et al
2015-06-05
Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO₂) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-longmore » (1901–2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 10¹⁵ g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr⁻¹ with a median value of 51 Pg C yr⁻¹ during 2001–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901–2010 ranges from –70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO₂ and nitrogen deposition over intact ecosystems increased SOC stocks—even though the responses varied
Murray, P.E.; Smartt, H.B.; Johnson, J.A.
1997-12-31
We develop a model of the depth of penetration of the weld pool in gas metal arc welding (GMAW) which demonstrates interaction between the arc, filler wire and weld pool. This model is motivated by the observations of Essers and Walter which suggest a relationship between droplet momentum and penetration depth. A model of gas metal arc welding was augmented to include an improved model of mass transfer and a simple model of accelerating droplets in a plasma jet to obtain the mass and momentum of impinging droplets. The force of the droplets and depth of penetration is correlated by a dimensionless linear relation used to predict weld pool depth for a range of values of arc power and contact tip to workpiece distance. Model accuracy is examined by comparing theoretical predictions and experimental measurements of the pool depth obtained from bead on plate welds of carbon steel in an argon rich shielding gas. Moreover, theoretical predictions of pool depth are compared to the results obtained from the heat conduction model due to Christensen et al. which suggest that in some cases the momentum of impinging droplets is a better indicator of the depth of the weld pool and the presence of a deep, narrow penetration.
Diwekar, Urmila; Shastri, Yogendra (Vishwamitra Research Institute Clarendon Hills, IL); Subrmanyan, Karthik; Zitney, S.E.
2007-11-04
APECS (Advanced Process Engineering Co-Simulator) is an integrated software suite that combines the power of process simulation with high-fidelity, computational fluid dynamics (CFD) for improved design, analysis, and optimization of process engineering systems. The APECS system uses commercial process simulation (e.g., Aspen Plus) and CFD (e.g., FLUENT) software integrated with the process-industry standard CAPE-OPEN (CO) interfaces. This breakthrough capability allows engineers to better understand and optimize the fluid mechanics that drive overall power plant performance and efficiency. The focus of this paper is the CAPE-OPEN complaint stochastic modeling and reduced order model computational capability around the APECS system. The usefulness of capabilities is illustrated with coal fired, gasification based, FutureGen power plant simulation. These capabilities are used to generate efficient reduced order models and optimizing model complexities.
Wenzel, W.J.; Wallwork-Barber, K.M.; Rodgers, J.C.; Gallegos, A.F.
1982-01-01
Long-term simulations of uranium transport in the soil-crop-beef food chain were performed using the BIOTRAN model. Experimental data means from an extensive Pantex beef cattle study are presented. Experimental data were used to validate the computer model. Measurements of uranium in air, soil, water, range grasses, feed, and cattle tissues are compared to simulated uranium output values in these matrices when the BIOTRAN model was set at the measured soil and air values. The simulations agreed well with experimental data even though metabolic details for ruminants and uranium chemical form in the environment remain to be studied.
Presentation given by Oak Ridge National Laboratory at 2015 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting about MA3T—modeling...
Lawson, M. J.; Li, Y.; Sale, D. C.
2011-10-01
This paper describes the development of a computational fluid dynamics (CFD) methodology to simulate the hydrodynamics of horizontal-axis tidal current turbines. Qualitative measures of the CFD solutions were independent of the grid resolution. Conversely, quantitative comparisons of the results indicated that the use of coarse computational grids results in an under prediction of the hydrodynamic forces on the turbine blade in comparison to the forces predicted using more resolved grids. For the turbine operating conditions considered in this study, the effect of the computational timestep on the CFD solution was found to be minimal, and the results from steady and transient simulations were in good agreement. Additionally, the CFD results were compared to corresponding blade element momentum method calculations and reasonable agreement was shown. Nevertheless, we expect that for other turbine operating conditions, where the flow over the blade is separated, transient simulations will be required.
Diegert, Carl F.
2006-12-01
We define a new diagnostic method where computationally-intensive numerical solutions are used as an integral part of making difficult, non-contact, nanometer-scale measurements. The limited scope of this report comprises most of a due diligence investigation into implementing the new diagnostic for measuring dynamic operation of Sandia's RF Ohmic Switch. Our results are all positive, providing insight into how this switch deforms during normal operation. Future work should contribute important measurements on a variety of operating MEMS devices, with insights that are complimentary to those from measurements made using interferometry and laser Doppler methods. More generally, the work opens up a broad front of possibility where exploiting massive high-performance computers enable new measurements.
Spent fuel storage and waste management fuel cycle optimization using CAFCA
Brinton, S.; Kazimi, M.
2013-07-01
Spent fuel storage modeling is at the intersection of nuclear fuel cycle system dynamics and waste management policy. A model that captures the economic parameters affecting used nuclear fuel storage location options, which complements fuel cycle economic assessment has been created using CAFCA (Code for Advanced Fuel Cycles Assessment) of MIT. Research has also expanded to the study on dependency of used nuclear fuel storage economics, environmental impact, and proliferation risk. Three options of local, regional, and national storage were studied. The preliminary product of this research is the creation of a system dynamics tool known as the Waste Management Module which provides an easy to use interface for education on fuel cycle waste management economic impacts. Storage options costs can be compared to literature values with simple variation available for sensitivity study. Additionally, a first of a kind optimization scheme for the nuclear fuel cycle analysis is proposed and the applications of such an optimization are discussed. The main tradeoff for fuel cycle optimization was found to be between economics and most of the other identified metrics. (authors)
Optimization of Post Combustion in Steelmaking (TRP 9925)
Dr. Richard J. Fruehan; Dr. R. J. Matway
2004-03-31
In the electric arc furnace (EAF), and the basic oxygen furnace (BOF) for producing steel, the major off gas is carbon monoxide (CO). If the CO can be combusted to CO{sub 2}, and the energy transferred to the metal, this reaction will reduce the energy consumed in the EAF and allow for more scrap melting in the BOF which would significantly lower the energy required to produce steel. This reaction is referred to as post combustion. In order to optimize the post combustion process, computational fluid dynamic models (CFD) of the two steelmaking processes were developed. Before the models could be fully developed information on reactions affecting post combustion had to be obtained. The role of the reaction of CO{sub 2} with scrap (iron) was measured at the temperatures relevant to post combustion in laboratory experiments. The experiments were done to separate the effects of gas phase mass transfer, chemical kinetics, and solid state mass transfer through the iron oxide formed by the reaction. The first CFD model was for the EAF using the FIDAP-CFD{trademark} code. Whereas this model gave some useful results it was incomplete due to problems with the FIDAP program. In the second EAF model, the CFX{trademark} code was used and was much more successful. The full 3-D model included all forms of heat transfer and the back reactions of CO{sub 2} with the metal and scrap. The model for the EAF was a full 3-D model and consisted of a primary oxygen lance with side wall injectors for post combustion. The model could predict the degree of post combustion and heat transfer. The BOF model was a slice of the BOF for which there was symmetry. The model could predict post combustion, heat transfer, temperature profiles and the effect of operating variables such as oxygen flow rates and distribution. The present research developed several new models such as limited combustion and depostcombustion. These were all documented by MSA Pass as a sub-contract. Instruction manuals were
Danish, Mohammad Suman, Sawan Srinivasan, Balaji
2014-12-15
The pressure Hessian tensor plays a key role in shaping the behavior of the velocity gradient tensor, and in turn, that of many incumbent non-linear processes in a turbulent flow field. In compressible flows, the role of pressure Hessian is even more important because it represents the level of fluid-thermodynamic coupling existing in the flow field. In this work, we first perform a direct numerical simulation-based study to clearly identify, isolate, and understand various important inviscid mechanisms that govern the evolution of the pressure Hessian tensor in compressible turbulence. The ensuing understanding is then employed to introduce major improvements to the existing Lagrangian model of the pressure Hessian tensor (the enhanced Homogenized Euler equation or EHEE) in terms of (i) non-symmetric, non-isentropic effects and (ii) improved representation of the anisotropic portion of the pressure Hessian tensor. Finally, we evaluate the new model extensively by comparing the new model results against known turbulence behavior over a range of Reynolds and Mach numbers. Indeed, the new model shows much improved performance as compared to the EHEE model.
Gao, Xujiao; Mamaluy, Denis; Mickel, Patrick R.; Marinella, Matthew
2015-09-08
In this paper, we present a fully-coupled electrical and thermal transport model for oxide memristors that solves simultaneously the time-dependent continuity equations for all relevant carriers, together with the time-dependent heat equation including Joule heating sources. The model captures all the important processes that drive memristive switching and is applicable to simulate switching behavior in a wide range of oxide memristors. The model is applied to simulate the ON switching in a 3D filamentary TaOx memristor. Simulation results show that, for uniform vacancy density in the OFF state, vacancies fill in the conduction filament till saturation, and then fill outmore » a gap formed in the Ta electrode during ON switching; furthermore, ON-switching time strongly depends on applied voltage and the ON-to-OFF current ratio is sensitive to the filament vacancy density in the OFF state.« less
Gao, Xujiao; Mamaluy, Denis; Mickel, Patrick R.; Marinella, Matthew
2015-09-08
In this paper, we present a fully-coupled electrical and thermal transport model for oxide memristors that solves simultaneously the time-dependent continuity equations for all relevant carriers, together with the time-dependent heat equation including Joule heating sources. The model captures all the important processes that drive memristive switching and is applicable to simulate switching behavior in a wide range of oxide memristors. The model is applied to simulate the ON switching in a 3D filamentary TaOx memristor. Simulation results show that, for uniform vacancy density in the OFF state, vacancies fill in the conduction filament till saturation, and then fill out a gap formed in the Ta electrode during ON switching; furthermore, ON-switching time strongly depends on applied voltage and the ON-to-OFF current ratio is sensitive to the filament vacancy density in the OFF state.