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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform for modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to model three­phase and single­ phase networks and devices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Innovative Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Numerical simulation of non-isothermal multiphase porous flow combined with reactive transport is used in a wide range of applications, which include nuclear waste repositories, enhanced recovery of petroleum reservoirs, contaminant remediation, geothermal engineering, and carbon sequestration. Understanding and predicting underground phenomena can have enormous impact on how to deal with world issues like climate change, clean water, and renewable energy. The main motivation for this proposal arises from safety assessment of future nuclear waste repositories using the U.S. Department of Energy (DOE) Geologic Disposal Safety Assessment (GDSA) Framework, and performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the nation's only active nuclear waste repository in Carlsbad, New Mexico. I am a technical staff member at Sandia National Laboratories involved in both projects.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A comprehensive framework for validating simulation models of power system equipment using terminal measurements

Accurate simulation of power-plants is essential to the planning and operation of modern power grids. The current methods used to periodically check power-plant simulation models have many open questions about their limitations and accuracy. The research in this project explored using Monte-Carlo Experimentation (MCE) as a means for answering these important questions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Meaningful timescales from Monte Carlo simulations of particle systems with hard-core interactions

A new Markov Chain Monte Carlo method for simulating the dynamics of particle systems characterized by hard-core interactions is introduced. In contrast to traditional Kinetic Monte Carlo approaches, where the state of the system is associated with minima in the energy landscape, in the proposed method, the state of the system is associated with the set of paths traveled by the atoms and the transition probabilities for an atom to be displaced are proportional to the corresponding velocities. In this way, the number of possible state-to-state transitions is reduced to a discrete set, and a direct link between the Monte Carlo time step and true physical time is naturally established. The resulting rejection-free algorithm is validated against event-driven molecular dynamics: the equilibrium and non-equilibrium dynamics of hard disks converge to the exact results with decreasing displacement size.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios

Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. For left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.

Emergency Evacuation↗

The time dependent propensity function for acceleration of spatial stochastic simulation of reaction–diffusion systems

The inhomogeneous stochastic simulation algorithm (ISSA) is a fundamental method for spatial stochastic simulation. However, when diffusion events occur more frequently than reaction events, simulating the diffusion events by ISSA is quite costly. To reduce this cost, we propose to use the time dependent propensity function in each step. In this way we can avoid simulating individual diffusion events, and use the time interval between two adjacent reaction events as the simulation stepsize. We demonstrate that the new algorithm can achieve orders of magnitude efficiency gains over widely-used exact algorithms, scales well with increasing grid resolution, and maintains a high level of accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coupled Lindblad Pseudomode Theory for Simulating Open Quantum Systems

Coupled Lindblad pseudomode theory is a promising approach for simulating non-Markovian quantum dynamics on both classical and quantum platforms, with dynamics that can be realized as a quantum channel. We provide theoretical evidence that the number of coupled pseudomodes only needs to scale as polylog⁡(𝑇/𝜖) in the simulation time 𝑇 and precision 𝜖. Inspired by the realization problem in control theory, we also develop a robust numerical algorithm for constructing the coupled modes that avoid the nonconvex optimization required by existing approaches. We demonstrate the effectiveness of our method by computing population dynamics and absorption spectra for the spin-boson model. Furthermore, this Letter provides a significant theoretical and computational improvement to the coupled Lindblad framework, which impacts a broad range of applications from classical simulations of quantum impurity problems to quantum simulations on near-term quantum platforms.

Anderson impurity model↗

Benefits of digitalizing and employing simulation to increase plant system performance and ensure compliance with technical specifications - 109

The essential services water system in a BWR nuclear power plant was affected by corrosion, soiling and blockages due to ageing. Those episodes affected safety margins hindering the Technical Specifications compliance during periodic system testing. Tecnatom designed, implemented and tested a design modification for the on-line monitoring of this system by integrating it in the existing Digital Control System (DCS). Key system parameters were acquired in real time to be displayed in the Human System Interface, used in performing calculations and stored their historical evolution. The objective was to optimize monitoring and surveillance of the essential service water system. Furthermore, Tecnatom developed an engineering simulator ('What if' simulator) consisting of a hydraulic model of the system. This simulator takes as inputs each heat exchanger performance parameters from the plant DCS, allows the user to change the essential services water system configuration (valves position, UHS level...) and calculates theoretical process values predicting the system real behavior. In a second stage, more system instruments were wired to the DCS for Technical Specifications compliance automatic surveillance regarding opening and closing times of system valves. Operating experience shows important benefits after the digitalization. It enhances on-line information of system operation and automates calculation of load loss factor of each heat exchanger. It eases the evaluation of blockages and soiling in the system allowing optimization of cleaning proceedings. System Surveillance Requirements and Test Requirements reports have been automated optimizing the operation workload. The simulator use enables to identify optimal system configuration increasing safety margins of the system and ensuring Technical Specifications fulfillment. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adaptive variational simulation for open quantum systems

Emerging quantum hardware provides new possibilities for quantum simulation. While much of the research has focused on simulating closed quantum systems, the real-world quantum systems are mostly open. Therefore, it is essential to develop quantum algorithms that can effectively simulate open quantum systems. Here we present an adaptive variational quantum algorithm for simulating open quantum system dynamics described by the Lindblad equation. The algorithm is designed to build resource-efficient ansatze through the dynamical addition of operators by maintaining the simulation accuracy. We validate the effectiveness of our algorithm on both noiseless simulators and IBM quantum processors and observe good quantitative and qualitative agreement with the exact solution. We also investigate the scaling of the required resources with system size and accuracy and find polynomial behavior. Our results demonstrate that near-future quantum processors are capable of simulating open quantum systems.

97 MATHEMATICS AND COMPUTING↗

Trans-oceanic Remote Power Hardware-in-the-Loop: Multi-site Hardware, Integrated Controller, and Electric Network Co-simulation

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources (DERs) including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This paper describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab-lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. We demonstrate its utility by studying real-time PHIL co-simulation of coordinated solar PV firming control of two inverters connected in multiple electric distribution network models, prototypical of U.S. and Australian systems. Here, the novel trans-pacific closed-loop system simulation was conducted in real-time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

STEPS: A Portable Numerical Simulation Toolkit for Electrical Power System Dynamic Studies

Numerical simulation is the key technique for large scale power system analysis. Redistribution of global renewable power via international interconnections requires new simulation tools to study the interconnected systems with different nominal frequencies as a whole. In this paper we introduce an open source simulation toolkit for electrical power systems (STEPS) which is hosted at Github. Its kernel is coded in C++ with major functions of power flow and electro-mechanical dynamic simulation. Flexible options are provided and configurable to improve power flow solution and dynamic simulation. Common devices and models are supported in STEPS for AC/DC hybrid system studies. Studies of interconnected systems with different nominal frequencies is supported in STEPS for research of international interconnection. Application program interfaces are provided and wrapped with Python to enable high-level interfaces for general applications. STEPS is thread safe and parallel computation is supported in both kernel and script levels to accelerate simulation. It is portable and works on Windows and GNU/Linux platforms. Cases from small to large scale systems are thoroughly tested to validate the toolkit with commercial packages as benchmarks.

42 ENGINEERING↗

Influence of changes in initial conditions for the simulation of dynamic systems

Chaos theory is a field of study in mathematics, with applications in several disciplines including meteorology, sociology, physics, engineering, economics, biology, and philosophy. Chaos theory studies the behavior of dynamical systems that are highly sensitive to initial conditions—a paradigm popularly referred to as the butterfly effect. Small differences in initial conditions field widely diverging outcomes for such dynamical systems, rendering long-term prediction impossible in general. This happens even though these systems are deterministic, meaning that their future behavior is fully determined by their initial conditions, with no random elements involved. In this paperinfluence of changes in initial conditions will be presented for the simulation of Lorenz system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Equation-based object-oriented modeling and simulation of data center cooling systems

In this paper, we introduce a newly developed open source data center package in the Modelica Buildings library to support modeling and simulation of cooling and control systems of data centers. The data center package contains major thermal and control component models, such as Computer Room Air Handler, Computer Room Air Conditioner, models of different subsystem configurations such as chillers with differently configured waterside economizers, as well as templates for different systems. Two case studies based on this package are performed to investigate the performances of the cooling and electrical system under normal conditions and emergency situations such as a blackout: one is for a data center powered by conventional energy, and the other is for a data center powered by renewable energy. Simulation results show that the dynamic modeling and multi-domain simulation in the Modelica-based tool make it convenient for users to investigate both normal and emergent operations for conventional and renewable data centers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Simulated moving bed system for CO.sub.2 separation, and method of same

A system and method for separating and/or purification of CO.sub.2 gas from a CO.sub.2 feed stream is described. The system and method include a plurality of fixed sorbent beds, adsorption zones and desorption zones, where the sorbent beds are connected via valve and lines to create a simulated moving bed system, where the sorbent beds move from one adsorption position to another adsorption position, and then into one regeneration position to another regeneration position, and optionally back to an adsorption position. The system and method operate by concentration swing adsorption/desorption and by adsorptive/desorptive displacement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Simulated moving bed system for CO2 separation, and method of same

A system and method for separating and/or purification of CO2 gas from a CO2 feed stream is described. The system and method include a plurality of fixed sorbent beds, adsorption zones and desorption zones, where the sorbent beds are connected via valve and lines to create a simulated moving bed system, where the sorbent beds move from one adsorption position to another adsorption position, and then into one regeneration position to another regeneration position, and optionally back to an adsorption position. The system and method operate by concentration swing adsorption/desorption and by adsorptive/desorptive displacement.

Elliott, Jeannine Elizabeth↗

Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software

We present an implementation of EAM and FS interatomic potentials, which are widely used in simulating metallic systems, in HOOMD-blue, a software designed to perform classical molecular dynamics simulations using GPU accelerations. We first discuss the details of our implementation and then report extensive benchmark tests. We demonstrate that single-precision floating point operations efficiently implemented on GPUs can produce sufficient accuracy when compared against double-precision codes, as demonstrated in test simulations of calculations of the glass-transition temperature of Cu 64.5 Zr 35.5 , and pair correlation function of liquid Ni 3 Al. Our code scales well with the size of the simulating system on NVIDIA Tesla M40 and P100 GPUs. Compared with another popular software LAMMPS running on 32 cores of AMD Opteron 6220 processors, the GPU/CPU performance ratio can reach as high as 4.6. In conclusion, the source code can be accessed through the HOOMD-blue web page for free by any interested user.

36 MATERIALS SCIENCE↗

Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing

The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.

high-performance computing↗