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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structured Adaptive Mesh Refinement Adaptations to Retain Performance Portability With Increasing Heterogeneity

Adaptive mesh refinement (AMR) is an important method that enables many mesh-based applications to run at effectively higher resolution within limited computing resources by allowing high resolution only where really needed. This advantage comes at a cost, however: greater complexity in the mesh management machinery and challenges with load distribution. With the current trend of increasing heterogeneity in hardware architecture, AMR presents an orthogonal axis of complexity. Additionally, the usual techniques, such as asynchronous communication and hierarchy management for parallelism and memory that are necessary to obtain reasonable performance are very challenging to reason about with AMR. Different groups working with AMR are bringing different approaches to this challenge. Here, we examine the design choices of several AMR codes and also the degree to which demands placed on them by their users influence these choices.

42 ENGINEERING↗
DOE OSTI2021

pnnl/HiParTI

A Hierarchical Parallel Tensor Infrastructure (HiParTI), is to support fast essential sparse tensor operations and tensor decompositions on multicore CPU and GPU architectures. It consists of sparse tensor decompositions, CANDECOMP/PARAFAC (CP) and Tucker decompositions, fundamental tensor operations, and tensor transformations

Li, Jiajia↗
NASA NTRS1988

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Nashman, Marilyn↗
NASA NTRS1987

Spacecraft on-board SAR processing technology

This paper provides an assessment of the on-board SAR processing technology for Eos-type missions. The proposed Eos SAR sensor and flight data system are introduced, and the SAR processing requirements are described. The SAR on-board SAR processor architecture selection is discussed, and a baseline processor architecture using a frequency-domain processor for range correlation and a modular fault-tolerant VLSI time-domain parallel array for azimuth correlation are described. The mass storage and VLSI technologies needed for implementing the proposed SAR processing are assessed. It is shown that acceptable processor power and mass characteristics should be feasible for Eos-type applications. A proposed development strategy for the on-board SAR processor is presented.

Liu, K. Y.↗
NASA NTRS1993

CRAY mini manual. Revision D

This document briefly describes the use of the CRAY supercomputers that are an integral part of the Supercomputing Network Subsystem of the Central Scientific Computing Complex at LaRC. Features of the CRAY supercomputers are covered, including: FORTRAN, C, PASCAL, architectures of the CRAY-2 and CRAY Y-MP, the CRAY UNICOS environment, batch job submittal, debugging, performance analysis, parallel processing, utilities unique to CRAY, and documentation. The document is intended for all CRAY users as a ready reference to frequently asked questions and to more detailed information contained in the vendor manuals. It is appropriate for both the novice and the experienced user.

Tennille, Geoffrey M.↗
NASA NTRS1990

Validated Fault Tolerant Architectures for Space Station

Viewgraphs on validated fault tolerant architectures for space station are presented. Topics covered include: fault tolerance approach; advanced information processing system (AIPS); and fault tolerant parallel processor (FTPP).

Lala, Jaynarayan H.↗
NASA NTRS1995

Development and Application of the Collaborative Optimization Architecture in a Multidisciplinary Design Environment

Collaborative optimization is a design architecture applicable in any multidisciplinary analysis environment but specifically intended for large-scale distributed analysis applications. In this approach, a complex problem is hierarchically de- composed along disciplinary boundaries into a number of subproblems which are brought into multidisciplinary agreement by a system-level coordination process. When applied to problems in a multidisciplinary design environment, this scheme has several advantages over traditional solution strategies. These advantageous features include reducing the amount of information transferred between disciplines, the removal of large iteration-loops, allowing the use of different subspace optimizers among the various analysis groups, an analysis framework which is easily parallelized and can operate on heterogenous equipment, and a structural framework that is well-suited for conventional disciplinary organizations. In this article, the collaborative architecture is developed and its mathematical foundation is presented. An example application is also presented which highlights the potential of this method for use in large-scale design applications.

Braun, R. D.↗
DOE OSTI2023

High-fidelity parallel entangling gates on a neutral-atom quantum computer

The ability to perform entangling quantum operations with low error rates in a scalable fashion is a central element of useful quantum information processing. Neutral-atom arrays have recently emerged as a promising quantum computing platform, featuring coherent control over hundreds of qubits and any-to-any gate connectivity in a flexible, dynamically reconfigurable architecture. The main outstanding challenge has been to reduce errors in entangling operations mediated through Rydberg interactions. Here we report the realization of two-qubit entangling gates with 99.5% fidelity on up to 60 atoms in parallel, surpassing the surface-code threshold for error correction. Our method uses fast, single-pulse gates based on optimal control, atomic dark states to reduce scattering and improvements to Rydberg excitation and atom cooling. We benchmark fidelity using several methods based on repeated gate applications, characterize the physical error sources and outline future improvements. Finally, we generalize our method to design entangling gates involving a higher number of qubits, which we demonstrate by realizing low-error three-qubit gates. By enabling high-fidelity operation in a scalable, highly connected system, these advances lay the groundwork for large-scale implementation of quantum algorithms, error-corrected circuits and digital simulations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Operation of Direct Drive Systems: Experiments in Peak Power Tracking and Multi-Thruster Control

Direct-drive power and propulsion systems have the potential to significantly reduce the mass of high-power solar electric propulsion spacecraft, among other advantages. Recent experimental direct-drive work has significantly mitigated or retired the technical risks associated with single-thruster operation, so attention is now moving toward systems-level areas of interest. One of those areas is the use of a Hall thruster system as a peak power tracker to fully use the available power from a solar array. A simple and elegant control based on the incremental conductance method, enhanced by combining it with the unique properties of Hall thruster systems, is derived here and it is shown to track peak solar array power very well. Another area of interest is multi-thruster operation and control. Dualthruster operation was investigated in a parallel electrical configuration, with both thrusters operating from discharge power provided by a single solar array. Startup and shutdown sequences are discussed, and it is shown that multi-thruster operation and control is as simple as for a single thruster. Some system architectures require operation of multiple cathodes while they are electrically connected together. Four different methods to control the discharge current emitted by individual cathodes in this configuration are investigated, with cathode flow rate control appearing to be advantageous. Dual-parallel thruster operation with equal cathode current sharing at total powers up to 10 kW is presented.

solar electric propulsion (SEP) vehicles↗
DOE OSTI2022

Mass transport limitations in polymer electrolyte water electrolyzers using spatially-resolved current measurement

Here this work utilizes spatially-resolved current measurements to provide insight into mass transport limitations in electrolyzers that are not observable from traditional polarization measurement. In this study, two types of flow-fields (parallel and triple-serpentine) and two types of diffusion media (patterned porous thin titanium foil LGDLs and Ir-coated titanium felt PTLs) were examined. A non-uniform current distribution dominated by mass transport limitations was observed to be instigated by the restriction of liquid water transport to catalyst sites. Additionally, conditions are revealed which yield similar polarization performance but dissimilar current distributions. In such cases, the transport limitations for different architectures and porous media affect polarization in different regions of the active area. Furthermore, the triple-serpentine flow-field used in this study performs better than the parallel flow-field under mass transport limited operating conditions. This indicates that the parallel flow-field used in this study is more susceptible to starvation than the triple-serpentine flow-field for the electrolyzer studied.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1989

Group implicit concurrent algorithms in nonlinear structural dynamics

During the 70's and 80's, considerable effort was devoted to developing efficient and reliable time stepping procedures for transient structural analysis. Mathematically, the equations governing this type of problems are generally stiff, i.e., they exhibit a wide spectrum in the linear range. The algorithms best suited to this type of applications are those which accurately integrate the low frequency content of the response without necessitating the resolution of the high frequency modes. This means that the algorithms must be unconditionally stable, which in turn rules out explicit integration. The most exciting possibility in the algorithms development area in recent years has been the advent of parallel computers with multiprocessing capabilities. So, this work is mainly concerned with the development of parallel algorithms in the area of structural dynamics. A primary objective is to devise unconditionally stable and accurate time stepping procedures which lend themselves to an efficient implementation in concurrent machines. Some features of the new computer architecture are summarized. A brief survey of current efforts in the area is presented. A new class of concurrent procedures, or Group Implicit algorithms is introduced and analyzed. The numerical simulation shows that GI algorithms hold considerable promise for application in coarse grain as well as medium grain parallel computers.

Ortiz, M.↗
DOE OSTI2020

Garnet-Type Solid-State Electrolytes: Materials, Interfaces, and Batteries

Solid-state batteries with desirable advantages, including high-energy density, wide temperature tolerance, and fewer safety-concerns, have been considered as a promising energy storage technology to replace organic liquid electrolyte-dominated Li-ion batteries. Solid-state electrolytes (SSEs) as the most vital component in solid-state batteries largely lead the future battery development. Among different types of solid-state electrolytes, garnet-type Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolytes have particularly high ionic conductivity (10 –3 to 10 –4 S/cm) and good chemical stability against Li metal, offering a great opportunity for solid-state Li-metal batteries. Since the discovery of garnet-type LLZO in 2007, there has been an increasing interest in the development of garnet-type solid-state electrolytes and all solid-state batteries. Garnet-type electrolyte has been considered one of the most promising and important solid-state electrolytes for batteries with potential benefits in energy density, electrochemical stability, high temperature stability, and safety. In this Review, we will survey recent development of garnet-type LLZO electrolytes with discussions of experimental studies and theoretical results in parallel, LLZO electrolyte synthesis strategies and modifications, stability of garnet solid electrolytes/electrodes, emerging nanostructure designs, degradation mechanisms and mitigations, and battery architectures and integrations. We will also provide a target-oriented research overview of garnet-type LLZO electrolyte and its application in various types of solid-state battery concepts (e.g., Li-ion, Li–S, and Li–air), and we will demonstrate opportunities and perspectives as guides for future development of solid electrolytes and solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

The Astronomy Commons Platform: A Deployable Cloud-based Analysis Platform for Astronomy

Abstract We present a scalable, cloud-based science platform solution designed to enable next-to-the-data analyses of terabyte-scale astronomical tabular data sets. The presented platform is built on Amazon Web Services (over Kubernetes and S3 abstraction layers), utilizes Apache Spark and the Astronomy eXtensions for Spark for parallel data analysis and manipulation, and provides the familiar JupyterHub web-accessible front end for user access. We outline the architecture of the analysis platform, provide implementation details and rationale for (and against) technology choices, verify scalability through strong and weak scaling tests, and demonstrate usability through an example science analysis of data from the Zwicky Transient Facility’s 1Bn+ light-curve catalog. Furthermore, we show how this system enables an end user to iteratively build analyses (in Python) that transparently scale processing with no need for end-user interaction. The system is designed to be deployable by astronomers with moderate cloud engineering knowledge, or (ideally) IT groups. Over the past 3 yr, it has been utilized to build science platforms for the DiRAC Institute, the ZTF partnership, the LSST Solar System Science Collaboration, and the LSST Interdisciplinary Network for Collaboration and Computing, as well as for numerous short-term events (with over 100 simultaneous users). In a live demo instance, the deployment scripts, source code, and cost calculators are accessible. 4 4 http://hub.astronomycommons.org/

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Implementation of an ADI method on parallel computers

The implementation of an ADI method for solving the diffusion equation on three parallel/vector computers is discussed. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, an SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The Gaussian elimination algorithm is used to solve a set of tridiagonal systems on the FLEX/32 and CRAY/2 while the cyclic elimination algorithm is used to solve these systems on the MPP. The implementation of the method is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.

Fatoohi, Raad A.↗
NASA NTRS1991

Fast Parallel Computation Of Manipulator Inverse Dynamics

Method for fast parallel computation of inverse dynamics problem, essential for real-time dynamic control and simulation of robot manipulators, undergoing development. Enables exploitation of high degree of parallelism and, achievement of significant computational efficiency, while minimizing various communication and synchronization overheads as well as complexity of required computer architecture. Universal real-time robotic controller and simulator (URRCS) consists of internal host processor and several SIMD processors with ring topology. Architecture modular and expandable: more SIMD processors added to match size of problem. Operate asynchronously and in MIMD fashion.

Fijany, Amir↗
NASA NTRS1993

Parallel O(log n) algorithms for open- and closed-chain rigid multibody systems based on a new mass matrix factorization technique

In this paper, parallel O(log n) algorithms for computation of rigid multibody dynamics are developed. These parallel algorithms are derived by parallelization of new O(n) algorithms for the problem. The underlying feature of these O(n) algorithms is a drastically different strategy for decomposition of interbody force which leads to a new factorization of the mass matrix (M). Specifically, it is shown that a factorization of the inverse of the mass matrix in the form of the Schur Complement is derived as M(exp -1) = C - B(exp *)A(exp -1)B, wherein matrices C, A, and B are block tridiagonal matrices. The new O(n) algorithm is then derived as a recursive implementation of this factorization of M(exp -1). For the closed-chain systems, similar factorizations and O(n) algorithms for computation of Operational Space Mass Matrix lambda and its inverse lambda(exp -1) are also derived. It is shown that these O(n) algorithms are strictly parallel, that is, they are less efficient than other algorithms for serial computation of the problem. But, to our knowledge, they are the only known algorithms that can be parallelized and that lead to both time- and processor-optimal parallel algorithms for the problem, i.e., parallel O(log n) algorithms with O(n) processors. The developed parallel algorithms, in addition to their theoretical significance, are also practical from an implementation point of view due to their simple architectural requirements.

Fijany, Amir↗
DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗
DOE OSTI2020

FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks

Parallel training of an ensemble of Deep Neural Networks (DNN) on a cluster of nodes is an effective approach to shorten the process of neural network architecture search and hyper-parameter tuning for a given learning task. Prior efforts have shown that data sharing, where the common preprocessing operation is shared across the DNN training pipelines, saves computational resources and improves pipeline efficiency. Data sharing strategy, however, performs poorly for a heterogeneous set of DNNs where each DNN has varying computational needs and thus different training rate and convergence speed. This paper proposes FLEET, a flexible ensemble DNN training framework for efficiently training a heterogeneous set of DNNs. We build FLEET via several technical innovations. We theoretically prove that an optimal resource allocation is NP-hard and propose a greedy algorithm to efficiently allocate resources for training each DNN with data sharing. We integrate data-parallel DNN training into ensemble training to mitigate the differences in training rates and introduce checkpointing into this context to address the issue of different convergence speeds. Experiments show that FLEET significantly improves the training efficiency of DNN ensembles without compromising the quality of the result.

Guan, Hui↗