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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
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↗
NASA NTRS2008

Simplified Modeling of Oxidation of Hydrocarbons

A method of simplified computational modeling of oxidation of hydrocarbons is undergoing development. This is one of several developments needed to enable accurate computational simulation of turbulent, chemically reacting flows. At present, accurate computational simulation of such flows is difficult or impossible in most cases because (1) the numbers of grid points needed for adequate spatial resolution of turbulent flows in realistically complex geometries are beyond the capabilities of typical supercomputers now in use and (2) the combustion of typical hydrocarbons proceeds through decomposition into hundreds of molecular species interacting through thousands of reactions. Hence, the combination of detailed reaction- rate models with the fundamental flow equations yields flow models that are computationally prohibitive. Hence, further, a reduction of at least an order of magnitude in the dimension of reaction kinetics is one of the prerequisites for feasibility of computational simulation of turbulent, chemically reacting flows. In the present method of simplified modeling, all molecular species involved in the oxidation of hydrocarbons are classified as either light or heavy; heavy molecules are those having 3 or more carbon atoms. The light molecules are not subject to meaningful decomposition, and the heavy molecules are considered to decompose into only 13 specified constituent radicals, a few of which are listed in the table. One constructs a reduced-order model, suitable for use in estimating the release of heat and the evolution of temperature in combustion, from a base comprising the 13 constituent radicals plus a total of 26 other species that include the light molecules and related light free radicals. Then rather than following all possible species through their reaction coordinates, one follows only the reduced set of reaction coordinates of the base. The behavior of the base was examined in test computational simulations of the combustion of heptane in a stirred reactor at various initial pressures ranging from 0.1 to 6 MPa. Most of the simulations were performed for stoichiometric mixtures; some were performed for fuel/oxygen mole ratios of 1/2 and 2.

Bellan, Josette↗
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 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↗
NASA NTRS1972

Computer system simulation and analysis

A simulation model has been developed as a tool for studying different computer system configurations. The model simulates a computer system in terms of the number and speed of hardware subsystems and the runs processed by the system in terms of equivalent adds for computation and data bits transferred for I/O. The model was written in the GPSS simulation language.

Williams, T. G.↗
NASA NTRS2022

Experimental and Computational Icing Simulation for Large Swept Wings

The purpose of this final report is to summarize the key results, findings and contributions of a large, multi-organization, multi-year effort focused on swept wing icing and aerodynamics. This research effort was jointly sponsored by NASA, FAA and ONERA and was supported by Boeing and the Universities of Illinois, Virginia, and Washington. The overall goal of this research was to improve the experimental and computational simulation capability for icing on large swept wings typical of commercial transports. This research included both ice accretion and aerodynamic studies using the NASA Common Research Model (CRM) as the reference geometry. For this work, a 65% scaled version—CRM65—was used as the full-scale baseline airplane geometry. This program marks the first non-proprietary research to generate and document full-scale swept wing ice accretions in an icing tunnel and then conduct semispan wing aerodynamic testing on scaled ice accretions at high Reynolds number (i.e., up to 11.9×106). During this work, several new experimental and computational techniques were developed or documented and new knowledge about swept wing icing aerodynamics was identified. All are documented in this report.

Aircraft icing↗
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↗
NASA NTRS1988

The use of computer graphic simulation in the development of robotic systems

The use of computer graphic simulation techniques to resolve critical design and operational issues for robotic systems is described. Use of this technology will result in greatly improved systems and reduced development costs. The major design issues in developing effective robotic systems are discussed and the use of ROBOSIM, a NASA developed simulation tool, to address these issues is presented. Three representative simulation case studies are reviewed: off-line programming of the robotic welding development cell for the Space Shuttle Main Engine; the integration of a sensor to control the robot used for removing the Thermal Protection System from the Solid Rocket Booster; and the development of a teleoperator/robot mechanism for the Orbital Maneuvering Vehicle.

Fernandez, Ken↗
NASA NTRS1993

Tensoral: A system for post-processing turbulence simulation data

Many computer simulations in engineering and science -- and especially in computational fluid dynamics (CFD) -- produce huge quantities of numerical data. These data are often so large as to make even relatively simple post-processing of this data unwieldy. The data, once computed and quality-assured, is most likely analyzed by only a few people. As a result, much useful numerical data is under-utilized. Since future state-of-the-art simulations will produce even larger datasets, will use more complex flow geometries, and will be performed on more complex supercomputers, data management issues will become increasingly cumbersome. My goal is to provide software which will automate the present and future task of managing and post-processing large turbulence datasets. My research has focused on the development of these software tools -- specifically, through the development of a very high-level language called 'Tensoral'. The ultimate goal of Tensoral is to convert high-level mathematical expressions (tensor algebra, calculus, and statistics) into efficient low-level programs which numerically calculate these expressions given simulation datasets. This approach to the database and post-processing problem has several advantages. Using Tensoral the numerical and data management details of a simulation are shielded from the concerns of the end user. This shielding is carried out without sacrificing post-processor efficiency and robustness. Another advantage of Tensoral is that its very high-level nature lends itself to portability across a wide variety of computing (and supercomputing) platforms. This is especially important considering the rapidity of changes in supercomputing hardware.

Dresselhaus, Eliot↗
NASA NTRS1987

The use of computer graphic simulation in the development of on-orbit tele-robotic systems

This paper describes the use of computer graphic simulation techniques to resolve critical design and operational issues for robotic systems used for on-orbit operations. These issues are robot motion control, robot path-planning/verification, and robot dynamics. The major design issues in developing effective telerobotic systems are discussed, and the use of ROBOSIM, a NASA-developed computer graphic simulation tool, to address these issues is presented. Simulation plans for the Space Station and the Orbital Maneuvering Vehicle are presented and discussed.

Fernandez, Ken↗
NASA NTRS1991

Neural-Network Simulator

F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

Mitchell, Paul H.↗
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↗
NASA NTRS1995

An equivalent body surface charge model representing three-dimensional bioelectrical activity

A new surface-source model has been developed to account for the bioelectrical potential on the body surface. A single-layer surface-charge model on the body surface has been developed to equivalently represent bioelectrical sources inside the body. The boundary conditions on the body surface are discussed in relation to the surface-charge in a half-space conductive medium. The equivalent body surface-charge is shown to be proportional to the normal component of the electric field on the body surface just outside the body. The spatial resolution of the equivalent surface-charge distribution appears intermediate between those of the body surface potential distribution and the body surface Laplacian distribution. An analytic relationship between the equivalent surface-charge and the surface Laplacian of the potential was found for a half-space conductive medium. The effects of finite spatial sampling and noise on the reconstruction of the equivalent surface-charge were evaluated by computer simulations. It was found through computer simulations that the reconstruction of the equivalent body surface-charge from the body surface Laplacian distribution is very stable against noise and finite spatial sampling. The present results suggest that the equivalent body surface-charge model may provide an additional insight to our understanding of bioelectric phenomena.

NASA Discipline Regulatory Physiology↗
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.↗