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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 73 records · Page 4

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NASA NTRS1998

Future Flight Decks

The evolution of commercial transport flight deck configurations over the past 20-30 years and expected future developments are described. Key factors in the aviation environment are identified that the authors expect will significantly affect flight deck designers. One of these is the requirement for commercial aviation accident rate reduction, which is probably required if global commercial aviation is to grow as projected. Other factors include the growing incrementalism in flight deck implementation, definition of future airspace operations, and expectations of a future pilot corps that will have grown up with computers. Future flight deck developments are extrapolated from observable factors in the aviation environment, recent research results in the area of pilot-centered flight deck systems, and by considering expected advances in technology that are being driven by other than aviation requirements. The authors hypothesize that revolutionary flight deck configuration changes will be possible with development of human-centered flight deck design methodologies that take full advantage of commercial and/or entertainment-driven technologies.

Arbuckle, P. Douglas↗

DOE OSTI2019

Future High Performance Computing Capabilities: Summary Report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee

The ASCAC Subcommittee on Future High Performance Computing (HPC) Capabilities has reviewed opportunities and challenges related to the most promising technologies that are currently planned for the post-exascale (2020's) and post-Moore (2030's and beyond) timeframes. We briefly summarize in this report the key findings and recommendations from this review, from the perspective of planning and research directions that need to be given priority to prepare for the very significant challenges that await us in the post-Moore computing era. An overarching concern that emerged from the subcommittee's deliberations is that DOE has lost considerable momentum in funding and sustaining a research pipeline in the applied math and computer science areas that should have been the "seed corn" for preparing for these future challenges, and it is therefore critical to correct this gap as soon as possible. While the subcommittee understands the paramount importance of DOE's commitment to deliver exascale capabilities, we believe that it is essential for DOE ASCR to fund research and development that looks beyond the Exascale Computing Project (ECP) horizon so as to ensure our nation's continued leadership in HPC and we were glad to learn about the ASCAC exascale transition subcommittee in this regard.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

AMR-Wind: A Performance-Portable, High-Fidelity Flow Solver for Wind Farm Simulations

We present AMR-Wind, a verified and validated high-fidelity computational-fluid-dynamics code for wind farm flows. AMR-Wind is a block-structured, adaptive-mesh, incompressible-flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high-performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR-Wind is spatially and temporally second-order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12-turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.

17 WIND ENERGY↗

NASA NTRS1993

Low Cost Spacecraft Computers: Oxymoron or Future Trend?

This paper describes how future trends in commercial computer technology will simplify (or hinder) selection of computer technology for spacecraft control applications, and what spacecraft electronic system designers can do to circumvent design constraints.

spacecraft↗

NASA NTRS1994

Visual Environments for CFD Research

This viewgraph presentation gives an overview of the visual environments for computational fluid dynamics (CFD) research. It includes details on critical needs from the future computer environment, features needed to attain this environment, prospects for changes in and the impact of the visualization revolution on the human-computer interface, human processing capabilities, limits of personal environment and the extension of that environment with computers. Information is given on the need for more 'visual' thinking (including instances of visual thinking), an evaluation of the alternate approaches for and levels of interactive computer graphics, a visual analysis of computational fluid dynamics, and an analysis of visualization software.

Watson, Val↗

DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗

DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗

NASA NTRS2003

Characterization of future deep space computing loads

This paper reports on the characteristics of a future deep space computing application. This includes the testbed used to make the measurements, the application suite itself, the scenarios measured, the detailed power and performance measurements taken, and the timing characteristics of the system.

deep space mission↗

NASA NTRS2003

Characterization of future deep space computing loads

This paper reports on the characteristics of a future deep space computing application. This includes the testbed used to make the measurements. the application suite itself, the scenarios measured. the detailed power and performance measurements taken, and the timing characteristics ofthe system.

Toomarian, N. Benny↗

DOE OSTI2019

miniVite: A Graph Analytics Benchmarking Tool for Massively Parallel Systems

Benchmarking of high performance computing sys-tems can help provide critical insights for ef?cient design of computing systems and software applications. Although a large number of tools for benchmarking exist, there is a lack of rep-resentative benchmarks for the class of irregular computations as exempli?ed by graph analytics. In this paper, we propose miniVite as a representative graph analytics benchmark tool to test a variety of distributed-memory systems. Graph clustering, popularly known as community detection, is a prototypical graph operation used in numerous scienti?c computing and analytics applications. The goal of clustering is to partition a graph into clusters (or communities) such that each cluster consists of vertices that are densely connected within the cluster and sparsely connected to the rest of the graph. Modu-larity optimization is a popular technique for identifying clusters in a graph. Ef?cient parallelization of modularity optimization-based algorithms is challenging. One successful approach was conceived in Vite, a distributed-memory implementation of the Louvain algorithm that incorporates several heuristics. We introduce miniVite as a representative but simpli?ed variant of Vite, to serve as a prototypical graph analytics benchmarking tool. Unlike other graph-based methods such as breadth-?rst search and betweenness centrality, miniVite represents highly complex computational patterns stressing a variety of system features, which can provide crucial insight for co-design of future computing systems.

community detection, parallel, MPI↗

NASA NTRS1996

A Comparison of Computed and Experimental Flowfields of the RAH-66 Helicopter

This paper compares and evaluates numerical and experimental flowfields of the RAH-66 Comanche helicopter. The numerical predictions were obtained by solving the Thin-Layer Navier-Stokes equations. The computations use actuator disks to investigate the main and tail rotor effects upon the fuselage flowfield. The wind tunnel experiment was performed in the 14 x 22 foot facility located at NASA Langley. A suite of flow conditions, rotor thrusts and fuselage-rotor-tail configurations were tested. In addition, the tunnel model and the computational geometry were based upon the same CAD definition. Computations were performed for an isolated fuselage configuration and for a rotor on configuration. Comparisons between the measured and computed surface pressures show areas of correlation and some discrepancies. Local areas of poor computational grid-quality and local areas of geometry differences account for the differences. These calculations demonstrate the use of advanced computational fluid dynamic methodologies towards a flight vehicle currently under development. It serves as an important verification for future computed results.

vanDam, C. P.↗

DOE OSTI2019

Beyond Coherent Oxide Heterostructures: Atomic-Scale Structure of Misfit Dislocations

Nanoscale design of complex oxide heterostructures and thin films is imperative as they have significant promise in novel technological applications. A coherent interface is formed in oxide heterostructures with small mismatches, and the lattice mismatch is completely compensated by elastic strain. In semi-coherent oxide heterostructures, when an epitaxial layer is grown on the substrate above the critical thickness of the film, misfit dislocations are formed to mitigate the strain between the two materials with dissimilar lattice constants. Key properties of semi-coherent oxide heterostructures are influenced or even controlled by the presence of misfit dislocations. Thus, it is critical to understand the atomic-scale structure of semi-coherent oxide heterostructures, specifically the structure of misfit dislocations that are ubiquitous at such heterointerfaces. Numerous state-of-the-art experiments have reported emergent phenomena at semi-coherent oxide heterostructures, wherein misfit dislocations play a crucial role. Yet, their atomic-scale and nanoscale structure is not always discernable from experiments. Because of large system sizes, computational studies dedicated to examining misfit dislocations in semi-coherent oxide heterostructures are still in their infancy. This review aims to summarize the recent advancements and challenges involved in computational studies elucidating the atomic-scale structure of misfit dislocations in semi-coherent oxide heterostructures and motivate future computational efforts.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1992

Three-dimensional compressible turbulent computations for a nondiffusing S-duct

The PARC3D code was used to compute the compressible turbulent flow within a three dimensional, nondiffusing S-duct. A frame of reference is provided for future computational fluid dynamics studies of internal flows with strong secondary flows and provides an understanding of the performance characteristics of a typical S-duct with attached flow. The predicted results, obtained with both H- and O-grids, are compared with the experimental wall pressure, static and total pressure fields, and velocity vectors. Additionally, computed boundary layer thickness, velocity profiles in wall coordinates, and skin friction values are presented.

Harloff, G. J.↗

NASA NTRS1993

Biological Information Signal Processor

Biological Information Signal Processor (BISP) is computing system analyzing data on deoxyribonucleic acid (DNA) sequences for molecular genetic analysis. Includes coprocessors, specialized microprocessors complementing present and future computers by performing rapidly most-time-consuming DNA-sequence-analyzing functions, establishing relationships (alignments) between both global sequences and defining patterns in multiple sequences. Also includes state-of-art software and data-base systems on both conventional and parallel computer systems to augment analytical abilities of developmental coprocessors.

Chow, Edward T.↗

NASA NTRS1994

Computational Aeroscience at NAS and Future Trends in High Performance Computing

NASA's Numerical Aerodynamic Simulation (NAS) program provides a unique world class supercomputing capability which is readily accessed by the U.S. aeronautics community and offers them the opportunity to perform high speed computations and simulations for a broad range of aerospace research applications. In addition, the NAS program performs on-going research and advanced technology development to ensure the innovative application of newly emerging technologies to computational fluid dynamics and other important aeroscience disciplines. The NAS system and its interaction with industry are described. Furthermore, the results of an analysis of current and future technologies and their potential impact on high performance computing are also presented.

Cooper, David M.↗

DOE OSTI2023

LISE$^{++}_{cute}$, the latest generation of the LISE ++ package, to simulate rare isotope production with fragment-separators

The LISE ++ software for fragment separator simulations has undergone a major update. The package, widely used at rare isotope beam facilities, can be used to predict intensities and purities of rare isotope beams and for planning and running of experiments using in-flight separators. It is especially useful for radioactive beam production as its results can be quickly compared to on-line data. The LISE ++ package has been ported to the Qt-framework in order to support modern compilers and computing methods. The benefits include 64-bit operation and LISE ++ availability on three different platforms: Windows, MacOS and Linux. In addition, the porting provides the ability to take advantage of future computational improvements. The updated package is named LISE$^{++}_{cute}$ to indicate a major step forward from the previous Borland-based versions. In addition to porting to the new platform, new main features and modifications have been added, mostly devoted to improving models and implementing other codes involved in rare isotope production at FRIB. Finally, a summary of modifications completed to improve the functionality of the code are discussed in this work, as well as future plans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Exemplar for simulation challenges: Large-deformation micromechanics of Sylgard 184/glass microballoon syntactic foams.

Sylgard® 184/Glass Microballoon (GMB) potting material is currently used in many NW systems. Analysts need a macroscale constitutive model that can predict material behavior under complex loading and damage evolution. To address this need, ongoing modeling and experimental efforts have focused on study of damage evolution in these materials. Micromechanical finite element simulations that resolve individual GMB and matrix components promote discovery and better understanding of the material behavior. With these simulations, we can study the role of the GMB volume fraction, time-dependent damage, behavior under confined vs. unconfined compression, and the effects of partial damage. These simulations are challenging and push the boundaries of capability even with the high performance computing tools available at Sandia. We summarize the major challenges and the current state of this modeling effort, as an exemplar of micromechanical modeling needs that can motivate advances in future computing efforts.

36 MATERIALS SCIENCE↗

NASA NTRS1993

Low cost spacecraft computers: Oxymoron or future trend?

Over the last few decades, application of current terrestrial computer technology in embedded spacecraft control systems has been expensive and wrought with many technical challenges. These challenges have centered on overcoming the extreme environmental constraints (protons, neutrons, gamma radiation, cosmic rays, temperature, vibration, etc.) that often preclude direct use of commercial off-the-shelf computer technology. Reliability, fault tolerance and power have also greatly constrained the selection of spacecraft control system computers. More recently, new constraints are being felt, cost and mass in particular, that have again narrowed the degrees of freedom spacecraft designers once enjoyed. This paper discusses these challenges, how they were previously overcome, how future trends in commercial computer technology will simplify (or hinder) selection of computer technology for spacecraft control applications, and what spacecraft electronic system designers can do now to circumvent them.

Manning, Robert M.↗