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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Advanced Simulation and Computing Fiscal Year 2016 Implementation Plan, Version 0

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The purpose of this IP is to outline key work requirements to be performed and to control individual work activities within the scope of work. Contractors may not deviate from this plan without a revised WA or subsequent IP.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2010

Right Size Determining the Staff Necessary to Sustain Simulation and Computing Capabilities for Nuclear Security

The Advanced Simulation and Computing Campaign, herein referred to as the ASC Program, is a core element of the science-based Stockpile Stewardship Program (SSP), which enables assessment, certification, and maintenance of the safety, security, and reliability of the U.S. nuclear stockpile without the need to resume nuclear testing. The use of advanced parallel computing has transitioned from proof-of-principle to become a critical element for assessing and certifying the stockpile. As the initiative phase of the ASC Program came to an end in the mid-2000s, the National Nuclear Security Administration redirected resources to other urgent priorities, and resulting staff reductions in ASC occurred without the benefit of analysis of the impact on modern stockpile stewardship that is dependent on these new simulation capabilities. Consequently, in mid-2008 the ASC Program management commissioned a study to estimate the essential size and balance needed to sustain advanced simulation as a core component of stockpile stewardship. The ASC Program requires a minimum base staff size of 930 (which includes the number of staff necessary to maintain critical technical disciplines as well as to execute required programmatic tasks) to sustain its essential ongoing role in stockpile stewardship.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis

Reactive molecular dynamics (MD) simulation is a powerful research tool for describing chemical reactions. We eliminate the speed-limiting charge iteration in MD with a novel extended-Lagrangian scheme. The extended-Lagrangian reactive MD (XRMD) code drastically improves energy conservation while substantially reducing time-to-solution. Furthermore, we introduce a new polarizable charge equilibration (PQEq) model to accurately predict atomic charges and polarization. The XRMD code based on hybrid message passing+multithreading achieves a weak-scaling parallel efficiency of 0.977 on 786 432 IBM Blue Gene/Q cores for a 67.6 billion-atom system. The performance is portable to the second-generation Intel Xeon Phi, Knights Landing. Blue Gene/Q simulations for the computational synthesis of materials via novel exfoliation mechanisms for synthesizing atomically thin transition metal dichalcogenide layers will dominate nanomaterials science in this century.

Simulation, Modeling, Performance, and Visualizati↗
DOE OSTI2020

High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Beyond-classical computation in quantum simulation

Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful and meaningful problems, remains a central challenge. Here, we show that superconducting quantum annealing processors can rapidly generate samples in close agreement with solutions of the Schrödinger equation. We demonstrate area-law scaling of entanglement in the model quench dynamics of two-, three-, and infinite-dimensional spin glasses, supporting the observed stretched-exponential scaling of effort for matrix-product-state approaches. We show that several leading approximate methods based on tensor networks and neural networks cannot achieve the same accuracy as the quantum annealer within a reasonable time frame. Thus, quantum annealers can answer questions of practical importance that may remain out of reach for classical computation.

King, Andrew D. [D-Wave Quantum Inc., Burnaby, BC ↗
DOE OSTI2016

FEL Simulation Using Distributed Computing

While simulation tools are available and have been used regularly for simulating light sources, the increasing availability and lower cost of GPU-based processing opens up new opportunities. This poster highlights a method of how accelerating and parallelizing code processing through the use of COTS software interfaces.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Scaling Studies for Advanced High Temperature Reactor Concepts, Final Technical Report: October 2014—December 2017

Computer simulations of nuclear reactor thermal-hydraulic phenomena are often used in the design and licensing of nuclear reactor systems. In order to assess the accuracy of these computer simulations, computer codes and methods are often validated against experimental data. This experimental data must be of sufficiently high quality in order to conduct a robust validation exercise. In addition, this experimental data is generally collected at experimental facilities that are of a smaller scale than the reactor systems that are being simulated due to cost considerations. Therefore, smaller scale test facilities must be designed and constructed in such a fashion to ensure that the prototypical behavior of a particular nuclear reactor system is preserved. The work completed through this project has resulted in scaling analyses and conceptual design development for a test facility capable of collecting code validation data for the following high temperature gas reactor systems and events— 1. Passive natural circulation core cooling system, 2. pebble bed gas reactor concept, 3. General Atomics Energy Multiplier Module reactor, and 4. prismatic block design steam-water ingress event. In the event that code validation data for these systems or events is needed in the future, significant progress in the design of an appropriate integral-type test facility has already been completed as a result of this project. Where applicable, the next step would be to begin the detailed design development and material procurement. As part of this project applicable scaling analyses were completed and test facility design requirements developed. Conceptual designs were developed for the implementation of these design requirements at the Oregon State University (OSU) High Temperature Test Facility (HTTF). The original HTTF is based on a ¼-scale model of a high temperature gas reactor concept with the capability for both forced and natural circulation flow through a prismatic core with an electrical heat source. The peak core region temperature capability is 1400°C. As part of this project, an inventory of test facilities that could be used for these experimental programs was completed. Several of these facilities showed some promise, however, upon further investigation it became clear that only the OSU HTTF had the power and/or peak temperature limits that would allow for the experimental programs envisioned herein. Thus the conceptual design and feasibility study development focused on examining the feasibility of configuring the current HTTF to collect validation data for these experimental programs. In addition to the scaling analyses and conceptual design development, a test plan was developed for the envisioned modified test facility. This test plan included a discussion on an appropriate shakedown test program as well as the specific matrix tests. Finally, a feasibility study was completed to determine the cost and schedule considerations that would be important to any test program developed to investigate these designs and events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Inverse patchy colloids with two and three patches. Analytical and numerical study

We propose an analytical solution of the multi-density Ornstein-Zernike equation supplemented by the associative Percus-Yevick closure relations specifically designed to describe the equilibrium properties of the novel class of patchy colloidal particles represented by the inverse patchy colloids with arbitrary number of patches. Using Baxter’s factorization method, we reduce solution of the problem to the solution of one nonlinear algebraic equation for the fraction of the particles with one non-bonded patch. We present closed-form expressions for the structure (structure factor) and thermodynamic (internal energy) properties of the system in terms of this fraction (and parameters of the model). We perform computer simulation studies and compare theoretical and computer simulation predictions for the pair distribution function, internal energy, and number of single and double bonds formed in the system, for two versions of the model, each with two and three patches. We consider the models with formation of the double bonds blocked by the patch-patch repulsion and the models without patch-patch repulsion. In general very good agreement between theoretical and computer simulation results is observed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

EQSIM—A multidisciplinary framework for fault-to-structure earthquake simulations on exascale computers, part II: Regional simulations of building response

The existing observational database of the regional-scale distribution of strong ground motions and measured building response for major earthquakes continues to be quite sparse. As a result, details of the regional variability and spatial distribution of ground motions, and the corresponding distribution of risk to buildings and other infrastructure, are not comprehensively understood. Utilizing high-performance computing platforms, emerging high-resolution, physics-based ground motion simulations can now resolve frequencies of engineering interest and provide detailed synthetic ground motions at high spatial density. This provides an opportunity for new insight into the distribution of infrastructure seismic demands and risk. In the work presented herein, the EQSIM fault-to-structure computational framework described in a companion paper, McCallen et al., is employed to investigate the regional-scale response of buildings to large earthquakes. A representative M = 7.0 strike-slip event is used to explore the distribution and amplitude of building demand, and comparisons are made between building response computed with fault-to-structure simulations and building response computed with existing measured near-fault earthquake records. New information on the distribution and variability of building response from high-performance parallel simulations is described and analyzed, and favorable first comparisons between building response predicted with both fault-to-structure simulations and real ground motions records are presented.

58 GEOSCIENCES↗
DOE OSTI2024

Electronic structure simulations in the cloud computing environment

The transformative impact of modern computational paradigms and technologies, such as high-performance computing, quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages, such as NWChem, NWChemEx, SPEC, ExaChem, and FLOSIC codes on the Azure Quantum Element (AQE) Microsoft cloud services. We pay particular attention to the intricate workflows for performing composite chemistry simulations, associated data curation, and mechanisms for accuracy assessment, as defined by the enabling cloud Computational Chemistry as a Service (CCaaS). Our focus also extends to Arrows' automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities (LCFs).

computational chemistry, electronic structure, Clo↗
DOE OSTI2021

Transforming Energy through Computational Excellence. Exascale Computing: Combustion; Simulating Effects of Fuel Injection Location in Supersonic Jet Engines

Computational tractable simulations using an adaptive-mesh-refinement solverfor compressible reacting flows help researchers understand how variations in fuel injection location within the supersonic flow cavity impacts combustion efficiency. By identifying the important physical determinants of the combustion processes, this study shows a promising pathway to improving flame stability and combustion efficiency, as well as reducing emissions.

adaptive mesh refinement↗
DOE OSTI2018

Advanced Simulation and Computing FY19 Implementation Plan, Rev. 1

The capabilities that the ASC Program provides at the national laboratories play a vital role in the Nuclear Security Enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY19. The Initial IP, effective August 8, 2018, should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective date TBD, is consistent with the final, enacted appropriation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Advanced Simulation and Computing FY18 Implementation Plan, Rev. 1

The capabilities that the ASC Program provides at the national laboratories play a vital role in the Nuclear Security Enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC Program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Directed Stockpile Work (DSW) and major modernization programs also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these lifetime extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT. Specific work activities and scope contained in this Implementation Plan (IP) represent the full-year annual operating plan for FY18. The Initial IP effective October 1, 2017, should be consistent with the Department’s Base Table when operating under a Continuing Resolution (CR). The final IP, effective March 24, 2018, is consistent with the final, enacted appropriation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluation of phase shifts for nonrelativistic elastic scattering using quantum computers

Simulations of scattering processes are essential in understanding the physics of our universe. Computing relevant scattering quantities from ab initio methods is extremely difficult on classical devices because of the substantial computational resources needed. Here, this work reports the development of an algorithm that makes it possible to obtain phase shifts for generic nonrelativistic elastic scattering processes on a quantum computer. This algorithm is based on extracting phase shifts from the direct implementation of the real-time evolution. The algorithm is improved by a variational procedure making it more accurate and resistant to the quantum noise. The reliability of the algorithm is first demonstrated by means of classical numerical simulations for different potentials and later tested on existing quantum hardware, specifically on IBM quantum processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Parameter inference with deep jointly informed neural networks

Abstract A common challenge in modeling inertial confinement fusion (ICF) experiments with computer simulations is that many of the simulation inputs are unknown and cannot be directly measured. Often, parameters that are measured in the experiment are used to infer the unknown inputs by solving the inverse problem: finding the set of simulation inputs that result in outputs consistent with the experimental observations. In ICF, this process is often referred to as a “post‐shot analysis.” Post‐shot analyses are challenging as the inverse problem is often highly degenerate, the input parameter space is vast, and simulations are computationally expensive. In this work, deep neural network models equipped with model uncertainty estimates are used to train inverse models, which map directly from output to input space, to find the distribution of post‐shot simulations that are consistent with experimental observations. The inverse model approach is compared to Markov chain Monte Carlo (MCMC) sampling of the forward model, which maps from input to output space, for parameter inference tasks of varying complexity. The inverse models perform best when searching vast parameter spaces for post‐shot simulations that are consistent with a large number of observables, where MCMC sampling can be prohibitively expensive. We demonstrate how augmenting inverse models with autoencoders enable the inclusion of several dozen observables in the inverse mapping, reducing the degeneracy of the model and improving the accuracy of the post‐shot analysis.

Humbird, Kelli D.↗
DOE OSTI2016

Morphological Expression of the Coherence and Relative Phase of Optical Inputs to the Photoelectrodeposition of Nanopatterned Se–Te Films

Highly anisotropic and ordered nanoscale lamellar morphologies can be spontaneously generated over macroscopic areas, without the use of a photomask or any templating agents, via the photoelectrodeposition of Se–Te alloy films. To form such structures, the light source can be a single, linearly polarized light source that need not necessarily be highly coherent. In this work, the variation in the morphologies produced by this deposition process was evaluated in response to differences in the coherence and relative phase between multiple simultaneous linearly polarized illumination inputs. Specifically, the morphologies of photoelectrodeposits were evaluated when two tandem same-wavelength sources with discrete linear polarizations, both either mutually incoherent or mutually coherent (with defined phase differences), were used. Additionally, morphologies were simulated via computer modeling of the interfacial light scattering and absorption during the photoelectrochemical growth process. The morphologies that were generated using two coherent, in-phase sources were equivalent to those generated using only a single source. In contrast, the use of two coherent, out-of-phase sources produced a range of morphological patterns. For small out-of-phase addition of orthogonal polarization components, lamellar-type patterns were observed. When fully out-of-phase orthogonal sources (circular polarization) were used, an isotropic, mesh-type pattern was instead generated, similar to that observed when unpolarized illumination was utilized. In intermediate cases, anisotropic lamellar-type patterns were superimposed on the isotropic mesh-type patterns, and the relative height between the two structures scaled with the amount of out-of-phase addition of the orthogonal polarization components. Similar results were obtained when two incoherent sources were utilized. In every case, the long axis of the lamellar-type morphology component aligned parallel to the intensity-weighted average polarization orientation. The observations consistently agreed with computer simulations, indicating that the observed morphologies were fully determined by the nature of the illumination utilized during the growth process. Here, the collective data thus indicated that the photoelectrodeposition process exhibits sensitivity toward the coherency, relative phase, and polarization orientations of all optical inputs and that this sensitivity is physically expressed in the morphology of the deposit.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Study of the characteristics of reconfigurable plasma antenna array

This paper presents a design and simulation of a reconfigurable array of plasma antenna. The plasma column is used as radiating elements instead of metal to create an antenna. The advantages of the plasma antenna over the conventional antenna are its possible to change the operating parameters, such as the working pressure, input power, radius of the discharge tube, resonant frequency, and length of the plasma column. In addition, plasma antenna can be reconfigurable with respect to shape, frequency and radiation parameters in a very short time. The plasma discharge tube was designed with a length of 200 mm, the radius of the plasma column was 2.5 mm and the coupling sleeve was connected to the SMA as the ground. This simulation was performed by using the simulation software Computer Simulation Technology (CST). The frequency is set in the range of 1 GHz to 10 GHz. The performance of the designed antenna was analyzed in term of return loss, gain and radiation pattern. For reconfigurable plasma antenna array, it shows that the gain is increase when the number of antenna element is increase. The combination of the discharge tube and metal rod as an antenna array has been done, and the result shows that an array with the plasma element can achieve higher gain.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗