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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Current Capabilities at SNL for the Integration of Small Modular Reactors onto Smart Microgrids Using Sandia's Smart Microgrid Technology High Performance Computing and Advanced Manufacturing.

Smart grids are a crucial component for enabling the nation’s future energy needs, as part of a modernization effort led by the Department of Energy. Smart grids and smart microgrids are being considered in niche applications, and as part of a comprehensive energy strategy to help manage the nation’s growing energy demands, for critical infrastructures, military installations, small rural communities, and large populations with limited water supplies. As part of a far-reaching strategic initiative, Sandia National Laboratories (SNL) presents herein a unique, three-pronged approach to integrate small modular reactors (SMRs) into microgrids, with the goal of providing economically-competitive, reliable, and secure energy to meet the nation’s needs. SNL’s triad methodology involves an innovative blend of smart microgrid technology, high performance computing (HPC), and advanced manufacturing (AM). In this report, Sandia’s current capabilities in those areas are summarized, as well as paths forward that will enable DOE to achieve its energy goals. In the area of smart grid/microgrid technology, Sandia’s current computational capabilities can model the entire grid, including temporal aspects and cyber security issues. Our tools include system development, integration, testing and evaluation, monitoring, and sustainment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Development and Application of a Data-Driven Methodology for Validation of Risk-Informed Safety Margin Characterization Models

The document is the Final Technical Progress Report for the Nuclear Energy University Program’s Integrated Research Project (IRP) on “Development and Application of a Data-Driven Methodology for Validation of Risk-Informed Safety Margin Characterization Models” that supports the LWR Sustainability Program’s RISMC R&D Pathway. The project goal is to develop and demonstrate a data-driven methodology for validation of advanced computer models used in nuclear power plant safety analysis. Specifically, the advanced computer models are those in the toolkit developed to support risk-informed safety margin characterization (RISMC), an integrated deterministic/probabilistic safety analysis methodology developed in the Department of Energy’s Light Water Reactor Sustainability (LWR-S) program. The report reflects the progress made towards the project’s stated goal by contributions by researchers and graduate students from universities, with support from researchers from national laboratories and industry companies. The project organization, effort coordination and technical implementation are summarized, followed by discussion of main findings, issues, and path forward. Selected chapters provide a more detailed description of tasks, approaches and respective findings and recommendations. Noteworthy are contributions that serve as guidelines for methodology development. It is also noted that this report is complemented by other milestone reports (as stand-alone deliverables) that provide detailed discussion of the technical developments. The project results have been documented in a number (12) dissertations and these, 50+ peer-reviewed publications in technical journals and conference proceedings.

42 ENGINEERING↗
DOE OSTI2017

Using Modeling and Simulation to Complement Testing for Increased Understanding of Weapon Subassembly Response.

As part of Sandia’s nuclear deterrence mission, the B61-12 Life Extension Program (LEP) aims to modernize the aging weapon system. Modernization requires requalification and Sandia is using high performance computing to perform advanced computational simulations to better understand, evaluate, and verify weapon system performance in conjunction with limited physical testing. The Nose Bomb Subassembly (NBSA) of the B61-12 is responsible for producing a fuzing signal upon ground impact. The fuzing signal is dependent upon electromechanical impact sensors producing valid electrical fuzing signals at impact. Computer generated models were used to assess the timing between the impact sensor’s response to the deceleration of impact and damage to major components and system subassemblies. The modeling and simulation team worked alongside the physical test team to design a large-scale reverse ballistic test to not only assess system performance, but to also validate their computational models. The reverse ballistic test conducted at Sandia’s sled test facility sent a rocket sled with a representative target into a stationary B61-12 (NBSA) to characterize the nose crush and functional response of NBSA components. Data obtained from data recorders and high-speed photometrics were integrated with previously generated computer models in order to refine and validate the model’s ability to reliably simulate real-world effects. Large-scale tests are impractical to conduct for every single impact scenario. By creating reliable computer models, we can perform simulations that identify trends and produce estimates of outcomes over the entire range of required impact conditions. Sandia’s HPCs enable geometric resolution that was unachievable before, allowing for more fidelity and detail, and creating simulations that can provide insight to support evaluation of requirements and performance margins. As computing resources continue to improve, researchers at Sandia are hoping to improve these simulations so they provide increasingly credible analysis of the system response and performance over the full range of conditions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2017

Pillars of the Mantle: Imaging the Interior of the Earth with Adjoint Tomography. In: PEARC17 Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact, Article No. 75

In this work, we investigate global seismic tomographic models obtained by spectral-element simulations of seismic wave propagation and adjoint methods. Global crustal and mantle models are obtained based on an iterative conjugate-gradient type of optimization scheme. Forward and adjoint seismic wave propagation simulations, which result in synthetic seismic data to make measurements and data sensitivity kernels to compute gradient for model updates, respectively, are performed by the SPECFEM3D_GLOBE package [1] [2] at the Oak Ridge Leadership Computing Facility (OLCF) to study the structure of the Earth at unprecedented levels. Using advances in solver techniques that run on the GPUs on Titan at the OLCF, scientists are able to perform large-scale seismic inverse modeling and imaging. Using seismic data from global and regional networks from global CMT earthquakes, scientists are using SPECFEM3D_GLOBE to understand the structure of the mantle layer of the Earth. Visualization of the generated data sets provide an effective way to understand the computed wave perturbations which define the structure of mantle in the Earth.

Pugmire, David↗
NASA NTRS1996

Overset Grid Methods for Multidisciplinary Applications in Rotorcraft Problems

A methodology for the coupling of an advanced computational fluid dynamics method based on an overset grid flow-solver and an advanced computational structural dynamics method based on a finite element analysis is presented. Various procedures for the fluid-structure interactions modeling along with their limitations are also discussed. The flight test data for the four-bladed UH-60A Blackhawk helicopter rotor is chosen for the validation of the results. Convergence and accuracy are tested by numerical experiments with a single-bladed rotor. A comparison of airload predictions with flight test data as well as with a rigid blade case is presented. Grid and interpolation related issues for this aeroelastic application are described.

Ahmad, J. U.↗
NASA NTRS2009

A Future State for NASA Laboratories - Working in the 21st Century

The name "21 st Century Laboratory" is an emerging concept of how NASA (and the world) will conduct research in the very near future. Our approach is to carefully plan for significant technological changes in products, organization, and society. The NASA mission can be the beneficiary of these changes, provided the Agency prepares for the role of 21st Century laboratories in research and technology development and its deployment in this new age. It has been clear for some time now that the technology revolutions, technology "mega-trends" that we are in the midst of now, all have a common element centered around advanced computational modeling of small scale physics. Whether it is nano technology, bio technology or advanced computational technology, all of these megatrends are converging on science at the very small scale where it is profoundly important to consider the quantum effects at play with physics at that scale. Whether it is the bio-technology creation of "nanites" designed to mimic our immune system or the creation of nanoscale infotechnology devices, allowing an order of magnitude increase in computational capability, all involve quantum physics that serves as the heart of these revolutionary changes.

Kegelman, Jerome T.↗
NASA NTRS1982

Computational aerodynamics and design

The role of computational aerodynamics in design is reviewed with attention given to the design process; the proper role of computations; the importance of calibration, interpretation, and verification; the usefulness of a given computational capability; and the marketing of new codes. Examples of computational aerodynamics in design are given with particular emphasis on the Highly Maneuverable Aircraft Technology. Finally, future prospects are noted, with consideration given to the role of advanced computers, advances in numerical solution techniques, turbulence models, complex geometries, and computational design procedures. Previously announced in STAR as N82-33348

Ballhaus, W. F., Jr.↗
DOE OSTI2021

Data Reduction for Science: Brochure from the Advanced Scientific Computing Research Workshop

Data reduction for science holds promise for addressing the challenges of moving, storing, and processing massive data sets produced by the scientific community. Pursuing the PRDs outlined here will enable advances in data streaming, fast feedback and/or autonomous control of experiments, and faster time to scientific insight. These advances will result in a significant improvement in the ability to transport, store, process and interpret experimental, observational, and computational data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1998

NASA's Participation in the National Computational Grid

Over the last several years it has become evident that the character of NASA's supercomputing needs has changed. One of the major missions of the agency is to support the design and manufacture of aero- and space-vehicles with technologies that will significantly reduce their cost. It is becoming clear that improvements in the process of aerospace design and manufacturing will require a high performance information infrastructure that allows geographically dispersed teams to draw upon resources that are broader than traditional supercomputing. A computational grid draws together our information resources into one system. We can foresee the time when a Grid will allow engineers and scientists to use the tools of supercomputers, databases and on line experimental devices in a virtual environment to collaborate with distant colleagues. The concept of a computational grid has been spoken of for many years, but several events in recent times are conspiring to allow us to actually build one. In late 1997 the National Science Foundation initiated the Partnerships for Advanced Computational Infrastructure (PACI) which is built around the idea of distributed high performance computing. The Alliance lead, by the National Computational Science Alliance (NCSA), and the National Partnership for Advanced Computational Infrastructure (NPACI), lead by the San Diego Supercomputing Center, have been instrumental in drawing together the "Grid Community" to identify the technology bottlenecks and propose a research agenda to address them. During the same period NASA has begun to reformulate parts of two major high performance computing research programs to concentrate on distributed high performance computing and has banded together with the PACI centers to address the research agenda in common.

Feiereisen, William J.↗
NASA NTRS1991

A comparison of sea ice parameters computed from Advanced Very High Resolution Radiometer and Landsat satellite imagery and from airborne passive microwave radiometry

AVHRR-derived sea ice parameters from the Bering Sea are compared with those computed from nearly coincident (within 6 hr) Landsat MSS imagery and from the Aircraft Multichannel Microwave Radiometer (AMMR) flown on the NASA DC-8 in order to evaluate the accuracy and reliability of AVHRR-mapped sea-ice concentration and ice edge. Mean ice-concentration differences between AVHRR near-infrared (channel 2) and Landsat MSS data ranged from -0.8 to 1.8 percent with a mean value of 0.5 percent; rms differences ranged from 6.8 to 17.7 percent. Mean differences were larger for AVHRR thermal infrared (channel 4) ice concentrations ranging from -2.2 to 8.4 percent with rms differences from 8.6 to 26.8 percent. Mean differences between AVHRR channel 2 concentrations and the AMMR data ranged from -19.7 to 18.9 percent, while rms values went from 17.0 to 44.8 percent.

Emery, W. J.↗
NASA NTRS1983

NASA's computer science research program

Following a major assessment of NASA's computing technology needs, a new program of computer science research has been initiated by the Agency. The program includes work in concurrent processing, management of large scale scientific databases, software engineering, reliable computing, and artificial intelligence. The program is driven by applications requirements in computational fluid dynamics, image processing, sensor data management, real-time mission control and autonomous systems. It consists of university research, in-house NASA research, and NASA's Research Institute for Advanced Computer Science (RIACS) and Institute for Computer Applications in Science and Engineering (ICASE). The overall goal is to provide the technical foundation within NASA to exploit advancing computing technology in aerospace applications.

Larsen, R. L.↗
DOE OSTI2017

The Institute for Sustained Performance, Energy, and Resilience Final Project Report

Over the course of the five years of the Scientific Discovery through Advanced Computation (SciDAC-3) program, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) exploited a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry, and materials science. The computing systems underpinning this work increased in performance potential from tens to hundreds of PFlop/s, but in the process evolving significantly from architectures in 2011, when SciDAC-3 began. Although Moore's law continues unabated, the end of Dennard scaling has necessitated a fundamental shift in computer architecture focused on power efficiency. To that end, processors are increasingly varied as they strive to satisfy performance, productivity, reliability, and energy efficiency in the face of divergent computational requirements. The diversity among these machines presents a number of challenges to merely porting today's scientific applications, much less achieving good performance. Therefore, at the beginning of SciDAC-3, USC and its collaborators anticipated that both vastly increased scale (e.g., more chips, more cores per chip, wider SIMD) and heterogeneity would exacerbate performance optimization challenges while simultaneously promoting the issues of energy and heterogeneity will exacerbate performance optimization challenges while simultaneously promoting the issues of energy consumption and resilience to the forefront. To ensure that DOE's computational scientists could successfully exploit emerging high performance computing (HPC) systems, DOE SC’s Advanced Scientific Computing Research Program (ASCR) funded the SciDAC-3 Institute for Sustained Performance, Energy, and Resilience (SUPER). Led by USC, this was a broadly based project with expertise in compilers and system tools, performance engineering, energy management, and resilience. SUPER followed the successful model developed in the previous SciDAC-2 Performance Engineering Research Institute (PERI) of leveraging the research investments DOE and others have made and integrating the results to create new capabilities beyond the reach of any one group. To accomplish this, SUPER was organized into multi-institution teams conducting the research activities in performance portability, energy efficiency, exascale resilience, and overall optimization. SUPER researchers also collaborated with other SciDAC-3 institutes, 13 of the 19 Scientific Computation Application Partnerships (SAP), as well as the broader DOE computational sciences community. These collaborations both focused our research on the real challenges facing petascale scientific computing as well as ensured the broad and immediate impact of the results of our research.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Advanced adaptive computational methods for Navier-Stokes simulations in rotorcraft aerodynamics

A phase 2 research and development effort was conducted in area transonic, compressible, inviscid flows with an ultimate goal of numerically modeling complex flows inherent in advanced helicopter blade designs. The algorithms and methodologies therefore are classified as adaptive methods, which are error estimation techniques for approximating the local numerical error, and automatically refine or unrefine the mesh so as to deliver a given level of accuracy. The result is a scheme which attempts to produce the best possible results with the least number of grid points, degrees of freedom, and operations. These types of schemes automatically locate and resolve shocks, shear layers, and other flow details to an accuracy level specified by the user of the code. The phase 1 work involved a feasibility study of h-adaptive methods for steady viscous flows, with emphasis on accurate simulation of vortex initiation, migration, and interaction. Phase 2 effort focused on extending these algorithms and methodologies to a three-dimensional topology.

Stowers, S. T.↗
DOE OSTI2019

Understanding Microstructural Evolution During Rapid Heat Treatment of Microalloyed Steels Through Computational Modeling, Advanced Physical Simulation, and Multiscale Characterization Techniques

An AISI 1045 steel modified with vanadium (V) and niobium (Nb) was studied to evaluate microstructural conditioning prior to and throughout a rapid heat treat process. In order to accomplish this, both computational and physical simulation techniques have been employed with the goal of assessing the microstructural evolution in a medium-carbon bar steel during the rapid austenitization and quenching procedures involved in an induction hardening process. The appropriate thermal profiles for induction hardening were obtained through finite element modeling using Flux 2D software. Physical simulations of the induction hardening process were carried out using a Gleeble{sup ®} 3500. Analysis of prior austenite grain size is complemented by observation of nanoscale carbonitride precipitation via transmission electron microscopy, scanning transmission electron microscopy, and high-energy synchrotron small-angle x-ray scattering. Through a combination of characterization techniques, this study presents a deeper understanding of nano- and microstructural changes occurring in a microalloyed steel during an induction hardening process.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities

Data-driven science and technology have helped achieve meaningful results in areas such as materials/drug discovery and health care, but efforts to apply high-end data science algorithms to the areas of glass and ceramics are still limited. Many glass and ceramic researchers are interested in enhancing their work by using more data and data analytics to efficiently develop better functional materials. Simultaneously, the data science community is looking for a way to access materials data resources to test and validate their advanced computational learning algorithms. To bring together the glass/ceramic and data science communities to address this issue, The American Ceramic Society (ACerS) convened a Glass/Ceramics Data Science Workshop on February 6, 2018, at Nexight Group offices in Silver Spring, Maryland. The workshop, sponsored by the National Institute for Standards and Technology (NIST) Advanced Manufacturing Technologies (AMTech) program, brought together a select group of 20 key leaders in the data science, informatics, and glass/ceramics communities to identify the greatest opportunities and mechanisms for facilitating increased collaboration and coordination between these communities. This article summarizes workshop discussions about the current challenges that limit interactions and collaboration between the glass/ceramic and data science communities, opportunities for a coordinated approach that leverages existing knowledge in both communities, and a clear path toward the enhanced use of data science technologies for functional glass and ceramic research and development.

data science, ceramics, informatics↗
DOE OSTI2018

Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit

Computational simulations, such as Monte Carlo track structure simulations, offer a powerful tool for quantitatively investigating radiation interactions within cells. Additionally, the modelling of the spatial distribution of energy deposition events as well as diffusion of chemical free radical species, within realistic biological geometries, can help provide a comprehensive understanding of the effects of radiation on cells. Track structure simulations, however, generally require advanced computing skills to implement. The TOPAS-nBio toolkit, an extension to TOPAS (TOol for PArticle Simulation), aims to provide users with a comprehensive framework for radiobiology simulations, without the need for advanced computing skills. This includes providing users with an extensive library of advanced, realistic, biological geometries ranging from the micrometer scale (e.g. cells and organelles) down to the nanometer scale (e.g. DNA molecules and proteins). Finally, were we present the geometries available in TOPAS-nBio.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Catalysts by Design: The Power of Theory

Theoretical design of effective catalysts, in conjunction with the identification of guiding design principles and strategies, is a Holy Grail in Chemistry. Although further progress will benefit from additional computational advances, theoretical studies have already enhanced the design of molecular electrocatalysts, photocatalysts, and enzymes. This paper comments on tools, design principles, and remaining challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Energy Efficiency Scaling for 2 Decades (EES2) Roadmap for Computing

In response to the looming crisis in global energy consumption required for advanced computing applications, the United States Department of Energy (DOE) Advanced Materials and Manufacturing Technology Office (AMMTO) is leading a multi-organizational effort to define a roadmap for energy efficiency scaling for two decades (EES2) with the aim to reduce energy use in all aspects of computation by more than a factor of 1000 in two decades. By July of 2024, over 60 organizations representing industry, academia, and the national laboratories have pledged to work in various aspects of research and development to enable energy efficiency in computing including in the development of the EES2 roadmap, with an initial public release in 2024 as the first phase of an ongoing commitment to energy-efficient and sustainable computation.

Kaarsberg, Tina [U.S. Department of Energy (DOE)]↗