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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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NASA NTRS1992

Computational structures technology and UVA Center for CST

Rapid advances in computer hardware have had a profound effect on various engineering and mechanics disciplines, including the materials, structures, and dynamics disciplines. A new technology, computational structures technology (CST), has recently emerged as an insightful blend between material modeling, structural and dynamic analysis and synthesis on the one hand, and other disciplines such as computer science, numerical analysis, and approximation theory, on the other hand. CST is an outgrowth of finite element methods developed over the last three decades. The focus of this presentation is on some aspects of CST which can impact future airframes and propulsion systems, as well as on the newly established University of Virginia (UVA) Center for CST. The background and goals for CST are described along with the motivations for developing CST, and a brief discussion is made on computational material modeling. We look at the future in terms of technical needs, computing environment, and research directions. The newly established UVA Center for CST is described. One of the research projects of the Center is described, and a brief summary of the presentation is given.

Noor, Ahmed K.↗

DOE OSTI2019

Vectorization of Random Number Generation and Reproducibility of Concurrent Particle Transport Simulation

Efficient random number generation with high quality statistical properties and exact reproducibility of Monte Carlo simulations are important requirements in many areas of computational science. VecRNG is a package providing pseudo-random number generation (pRNG) in the context of a new library VecMath. This library bundles up several general-purpose mathematical utilities, data structures, and algorithms having both SIMD and SIMT (GPUs) support based on VecCore.~Several state-of-the-art RNG algorithms are implemented as kernels supporting parallel generation of random numbers in scalar, vector, and Cuda workflows. In this report, we will present design considerations, implementation details, and computing performance of parallel pRNG engines on both CPU and GPU. Reproducibility of propagating multiple particles in parallel for HEP event simulation is demonstrated, using GeantV-based examples, for both sequential and fine-grain track-level concurrent simulation wor kflows. Strategies for efficient uses of vectorized pRNG and non-overlapping streams of random number sequences in concurrent computing environments is discussed as well.

Jun, S. Y.↗

DOE OSTI2016

High-order hydrodynamic algorithms for exascale computing

Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broad range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1990

A guide to the National Space Science Data Center

This is the second edition of a document that was published to acquaint space and Earth research scientists with an overview of the services offered by the NSSDC. As previously stated, the NSSDC was established by NASA to be the long term archive for data from its space missions. However, the NSSDC has evolved into an organization that provides a multitude of services for scientists throughout the world. Brief articles are presented which discuss these services. At the end of each article is the name, address, and telephone number of the person to contact for additional information. Online Information and Data Systems, Electronic Access, Offline Data Archive, Value Added Services, Mass Storage Activities, and Computer Science Research are all detailed.

Source record↗

DOE OSTI2018

SciDAC – PSI: Plasma Surface Interactions involving Tungsten - A Summary of Project Accomplishments

Gaining physics understanding and predictive capabilities to describe the evolution of plasma facing components (PFC) requires simultaneously addressing complex and diverse physics occurring over a wide range of length and time scales, as well as integrating extensive physical processes across the plasma - surface - bulk materials boundaries. This requires development not only of detailed physics models and computational strategies at each of these scales, but computer science algorithms and methods to strongly couple them in a way that can be robustly validated through comparisons against available data and new experiments. Therefore, the objective of this project is to develop robust, high-fidelity simulation tools capable of predicting the PFC operating lifetime and the PFC impact on plasma contamination, recycling of hydrogenic species, and tritium retention in future magnetic fusion devices, with a focus on tungsten based material systems. Deploying these tools requires the development of a leadershipscale computational code, as well as a host of simulations that span the multiple scales needed to address complex physical and computational issues at the plasma - surface interface and the transition below the surface where neutron damage processes in the bulk material dominate behavior in multiple-component materials systems. Successful development will enable improved prediction of PFC performance needed to ensure magnetic fusion energy development beyond ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2014

Advanced Simulation & Computing FY15 Implementation Plan Volume 2, Rev. 0.5

The Stockpile Stewardship Program (SSP) is a single, highly integrated technical program for maintaining the 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 enhancements to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. As the program approaches the end of its second decade, ASC is intently focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), quantify critical margins and uncertainties, and resolve increasingly difficult analyses needed for the SSP. Where possible, the program also enables the use of high-performance simulation and computing tools to address broader national security needs, such as foreign nuclear weapon assessments and counternuclear terrorism.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Advanced Simulation and Computing Implementation Plan, FY15, Rev. 1

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Geometric modeling for computer aided design

Over the past several years, it has been the primary goal of this grant to design and implement software to be used in the conceptual design of aerospace vehicles. The work carried out under this grant was performed jointly with members of the Vehicle Analysis Branch (VAB) of NASA LaRC, Computer Sciences Corp., and Vigyan Corp. This has resulted in the development of several packages and design studies. Primary among these are the interactive geometric modeling tool, the Solid Modeling Aerospace Research Tool (smart), and the integration and execution tools provided by the Environment for Application Software Integration and Execution (EASIE). In addition, it is the purpose of the personnel of this grant to provide consultation in the areas of structural design, algorithm development, and software development and implementation, particularly in the areas of computer aided design, geometric surface representation, and parallel algorithms.

Schwing, James L.↗

DOE OSTI2015

HPCCloud: A Cloud/Web-Based Simulation Environment

Advanced modeling and simulation has enabled the design of a variety of innovative products and the analysis of numerous complex phenomenon. There are significant barriers to widespread adoption of these tools. In particular, advanced modeling and simulation: (1) is considered complex to use, (2) needs in-house expertise, and (3) requires high capital costs. In this paper, we describe the development of an end-to-end, advanced modeling and simulation cloud platform that encapsulates best practices for scientific computing in the cloud, and demonstrate using Hydra-TH as a prototypical application. As an alternative to traditional advanced modeling and simulation workflows, our Web-based approach simplifies the processes, decreases the need for in-house computational science and engineering experts, and lowers the capital investments. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where the full lifecycle of data from input to final analyzed results can be saved, shared, and even published.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Reimagining Codesign for Advanced Scientific Computing: Unlocking Transformational Opportunities for Future Computing Systems for Science

In March 2021, DOE’s Advanced Scientific Computing Research convened the Workshop on Reimagining Codesign. The workshop was organized around discussions on eight topic areas. From these, the workshop panelists identified four priority research directions, listed below.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

HamPerf: A Hamiltonian-Oriented Approach to Quantum Benchmarking

Quantum computing technologies are undergoing rapid development. The different qubit modalities being considered for quantum computing each have their strengths and weaknesses, making it challenging to compare their performance relative to each other and the state-of-the-art in classical high-performance computing. To better understand the utility of a given quantum processor and to assess when and how it will be able to advance the frontiers of computational science, researchers need a robust approach to quantum benchmarking. A variety of approaches have been proposed, many of which characterize the presence of noise in current quantum devices. These efforts include component-level performance metrics, such as randomized benchmarking and gate set tomography; high-level application-dependent metrics; and devicelevel metrics, such as the Quantum Volume. However, it remains unclear how low-level metrics, such as fidelities and decoherence times, and global device metrics, such as Quantum Volume, relate to the computational utility and practical limitations of quantum processors to solve useful problems. In this paper, we describe our Hamiltonian-oriented approach to quantum benchmarking called HamPerf. Where previous application-dependent approaches specify a suite of benchmarking circuits inspired by applications, we place the problem Hamiltonian at the center. Our strategy allows us to probe the computational performance of a quantum processor on standardized and relevant problem sets, agnostic of the algorithms and hardware used to solve them; it also provides fundamental insights into how device characteristics correlate with computational utility.

Butko, Anastasiia↗

DOE OSTI2016

Advanced Simulation and Computing FY17 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 Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resource, including technical staff, hardware, simulation software, and computer science solutions. ASC is now focused on increasing predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The program continues to improve its unique tools for solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further away from the original test base. Where possible, the program also enables the use of high performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and counter nuclear terrorism.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1986

Applications of artificial intelligence to scientific research

Artificial intelligence (AI) is a growing field which is just beginning to make an impact on disciplines other than computer science. While a number of military and commercial applications were undertaken in recent years, few attempts were made to apply AI techniques to basic scientific research. There is no inherent reason for the discrepancy. The characteristics of the problem, rather than its domain, determines whether or not it is suitable for an AI approach. Expert system, intelligent tutoring systems, and learning programs are examples of theoretical topics which can be applied to certain areas of scientific research. Further research and experimentation should eventurally make it possible for computers to act as intelligent assistants to scientists.

Prince, Mary Ellen↗

DOE OSTI2019

Adiak

Adiak is a computer science data management interface tool for collecting metadata about an application's runs and disseminating it to tools that subscribe to this data. Examples of this metadata could be what user is running an application, what systems it runs on, or application provided name/value pairs. Adiak's capabilities include automated reading of system-level metadata, and a generic type system for applications to register their own name/value metadata. Adiak is currently designed to provide a standard interface that can be integrated with MPI-based applications that run on high performance computing systems. Example tools that use Adiak metadata include performance analysis tools and workflow tools. By allowing the application to specify metadata to Adiak, which then disseminates it to tools, application developers do not have to write to tool-specific interfaces.

LeGendre, MatthewP↗

DOE OSTI2019

Solution-Based Adaptivity as a Paradigm for Computational Fluid Dynamics

This is the final report for the DOE Early Career award. Through innovation in error estimation and solution-based adaptation methods we strive to dramatically improve the efficiency and robustness of computational science and engineering simulations. By solution-based error estimation and adaptation we refer to techniques for estimating numerical error and efficiently reducing it through targeted discretization changes. In such a setting, high-order methods play a key role, though they are just one mechanism for efficient accuracy improvement. Other mechanisms include well known mesh size and stretching optimization, as well as less-practiced mesh motion and basis optimization. With additional work on the latter, we are integrating these techniques into one adaptive suite that maximizes efficiency and robustness of Computational Fluid Dynamics (CFD) calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Algorithms and Abstractions for Assembly in PDE Codes: Workshop Report

The emergence of high-concurrency architectures offering unprecedented performance has brought many high-performance partial differential equation (PDE) discretization codes to the precipice of a major refactor. To help address this challenge a workshop titled "Algorithms and Abstractions for Assembly in PDE Codes" was held in the Computer Science Research Institute at Sandia National Laboratories on May 12th-14th, 2014. This document summarizes the goals of the workshop and the results of the presentations and subsequent discussions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Algorithms to Improve Training for Deep Learning with Diabetic Retinopathy Images

This is a minisymposium presentation I plan to give at the SIAM conference on Computational Science and Engineering on March 1st, 2021. The work is based on research from my SDRD this year and describes a new pooling method we've developed called variable stride. The goal of the minisymposium is to highlight some of the ground-breaking work being done across the National Nuclear Security Administration by graduate students and Postdocs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Advanced Visualization for Scientific Data Analysis and Insight [Slides]

This talk will explore how we have used advanced visualization technologies to support analytical reasoning and knowledge discovery. Specifically, we will present several examples detailing some recent scientific successes using state-of-the-art immersive and high-resolution visualization at the National Renewable Energy Laboratory's Computational Science Center. On multiple occasions, we have observed scientists and engineers discover features in their data using advanced visualization technologies that they had not seen in prior investigations of their data on traditional desktop displays. We have embedded more information into our analytics tools, allowing engineers to explore complex multivariate spaces. We have observed how interactions seem to catalyze understanding.

97 MATHEMATICS AND COMPUTING↗