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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The growth of the UniTree mass storage system at the NASA Center for Computational Sciences: Some lessons learned

In October 1992, the NASA Center for Computational Sciences made its Convex-based UniTree system generally available to users. The ensuing months saw growth in every area. Within 26 months, data under UniTree control grew from nil to over 12 terabytes, nearly all of it stored on robotically mounted tape. HiPPI/UltraNet was added to enhance connectivity, and later HiPPI/TCP was added as well. Disks and robotic tape silos were added to those already under UniTree's control, and 18-track tapes were upgraded to 36-track. The primary data source for UniTree, the facility's Cray Y-MP/4-128, first doubled its processing power and then was replaced altogether by a C98/6-256 with nearly two-and-a-half times the Y-MP's combined peak gigaflops. The Convex/UniTree software was upgraded from version 1.5 to 1.7.5, and then to 1.7.6. Finally, the server itself, a Convex C3240, was upgraded to a C3830 with a second I/O bay, doubling the C3240's memory and capacity for I/O. This paper describes insights gained and reinforced with the burgeoning demands on the UniTree storage system and the significant increases in performance gained from the many upgrades.

Tarshish, Adina↗
NASA NTRS1990

Research in progress in applied mathematics, numerical analysis, and computer science

Research conducted at the Institute in Science and Engineering in applied mathematics, numerical analysis, and computer science is summarized. The Institute conducts unclassified basic research in applied mathematics in order to extend and improve problem solving capabilities in science and engineering, particularly in aeronautics and space.

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NASA NTRS1984

Overview of the NASA/RECON educational, research, and development activities of the Computer Science Departments of the University of Southwestern Louisiana and Southern University

This document presents a brief overview of the scope of activities undertaken by the Computer Science Departments of the University of Southern Louisiana (USL) and Southern University (SU) pursuant to a contract with NASA. Presented are only basic identification data concerning the contract activities since subsequent entries within the Working Paper Series will be oriented specifically toward a detailed development and presentation of plans, methodologies, and results of each contract activity. Also included is a table of contents of the entire USL/DBMS NASA/RECON Working Paper Series.

Dominick, Wayne D.↗
NASA NTRS2004

SANs and Large Scale Data Migration at the NASA Center for Computational Sciences

Evolution and migration are a way of life for provisioners of high-performance mass storage systems that serve high-end computers used by climate and Earth and space science researchers: the compute engines come and go, but the data remains. At the NASA Center for Computational Sciences (NCCS), disk and tape SANs are deployed to provide high-speed I/O for the compute engines and the hierarchical storage management systems. Along with gigabit Ethernet, they also enable the NCCS's latest significant migration: the transparent transfer of 300 Til3 of legacy HSM data into the new Sun SAM-QFS cluster.

Salmon, Ellen M.↗
NASA NTRS2003

Bayesian Research at the NASA Ames Research Center,Computational Sciences Division

NASA Ames Research Center is one of NASA s oldest centers, having started out as part of the National Advisory Committee on Aeronautics, (NACA). The site, about 40 miles south of San Francisco, still houses many wind tunnels and other aviation related departments. In recent years, with the growing realization that space exploration is heavily dependent on computing and data analysis, its focus has turned more towards Information Technology. The Computational Sciences Division has expanded rapidly as a result. In this article, I will give a brief overview of some of the past and present projects with a Bayesian content. Much more than is described here goes on with the Division. The web pages at http://ic.arc. nasa.gov give more information on these, and the other Division projects.

Morris, Robin D.↗
DOE OSTI2026

Fostering Computational Thinking within Elementary Classrooms through a Research-Practice Partnership: A Strategy for Broadening Participation in Computer Science

This paper describes a research-practice partnership involving twenty elementary teachers and a support team of university researchers and K-12 learning specialists. Over five years, the partnership explored ways to highlight and to expand computational thinking within math and science instruction. The project sought to increase student awareness, confidence, and fluency with computational thinking as a problem-solving approach, with particular attention to students from groups historically underrepresented in computer science. Based on feedback from across the partnership – together with analysis of student attitude and problem-solving data – this experience report identifies successes, challenges, and recommendations for future study.

Broadening participation↗
NASA NTRS1987

Development and application of unified algorithms for problems in computational science

A framework is presented for developing computationally unified numerical algorithms for solving nonlinear equations that arise in modeling various problems in mathematical physics. The concept of computational unification is an attempt to encompass efficient solution procedures for computing various nonlinear phenomena that may occur in a given problem. For example, in Computational Fluid Dynamics (CFD), a unified algorithm will be one that allows for solutions to subsonic (elliptic), transonic (mixed elliptic-hyperbolic), and supersonic (hyperbolic) flows for both steady and unsteady problems. The objectives are: development of superior unified algorithms emphasizing accuracy and efficiency aspects; development of codes based on selected algorithms leading to validation; application of mature codes to realistic problems; and extension/application of CFD-based algorithms to problems in other areas of mathematical physics. The ultimate objective is to achieve integration of multidisciplinary technologies to enhance synergism in the design process through computational simulation. Specific unified algorithms for a hierarchy of gas dynamics equations and their applications to two other areas: electromagnetic scattering, and laser-materials interaction accounting for melting.

Shankar, Vijaya↗
NASA NTRS1993

Space and Earth Sciences, Computer Systems, and Scientific Data Analysis Support, Volume 1

This Final Progress Report covers the specific technical activities of Hughes STX Corporation for the last contract triannual period of 1 June through 30 Sep. 1993, in support of assigned task activities at Goddard Space Flight Center (GSFC). It also provides a brief summary of work throughout the contract period of performance on each active task. Technical activity is presented in Volume 1, while financial and level-of-effort data is presented in Volume 2. Technical support was provided to all Division and Laboratories of Goddard's Space Sciences and Earth Sciences Directorates. Types of support include: scientific programming, systems programming, computer management, mission planning, scientific investigation, data analysis, data processing, data base creation and maintenance, instrumentation development, and management services. Mission and instruments supported include: ROSAT, Astro-D, BBXRT, XTE, AXAF, GRO, COBE, WIND, UIT, SMM, STIS, HEIDI, DE, URAP, CRRES, Voyagers, ISEE, San Marco, LAGEOS, TOPEX/Poseidon, Pioneer-Venus, Galileo, Cassini, Nimbus-7/TOMS, Meteor-3/TOMS, FIFE, BOREAS, TRMM, AVHRR, and Landsat. Accomplishments include: development of computing programs for mission science and data analysis, supercomputer applications support, computer network support, computational upgrades for data archival and analysis centers, end-to-end management for mission data flow, scientific modeling and results in the fields of space and Earth physics, planning and design of GSFC VO DAAC and VO IMS, fabrication, assembly, and testing of mission instrumentation, and design of mission operations center.

Estes, Ronald H.↗
NASA NTRS1986

Summary of research in applied mathematics, numerical analysis, and computer sciences

The major categories of current ICASE research programs addressed include: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effective numerical methods; computational problems in engineering and physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and computer systems and software, especially vector and parallel computers.

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NASA NTRS2000

On The Computational Capabilities of Physical Systems: Relationship With Conventional Computer Science - Part 2

In the first of this pair of papers, it was proven that there cannot be a physical computer to which one can properly pose any and all computational tasks concerning the physical universe. It was then further proven that no physical computer C can correctly carry out all computational tasks that can be posed to C. As a particular example, this result means that no physical computer that can, for any physical system external to that computer, take the specification of that external system's state as input and then correctly predict its future state before that future state actually occurs; one cannot build a physical computer that can be assured of correctly "processing information faster than the universe does". These results do not rely on systems that are infinite, and/or non-classical, and/or obey chaotic dynamics. They also hold even if one uses an infinitely fast, infinitely dense computer, with computational powers greater than that of a Turing Machine. This generality is a direct consequence of the fact that a novel definition of computation - "physical computation" - is needed to address the issues considered in these papers, which concern real physical computers. While this novel definition does not fit into the traditional Chomsky hierarchy, the mathematical structure and impossibility results associated with it have parallels in the mathematics of the Chomsky hierarchy. This second paper of the pair presents a preliminary exploration of some of this mathematical structure. Analogues of Chomskian results concerning universal Turing Machines and the Halting theorem are derived, as are results concerning the (im)possibility of certain kinds of error-correcting codes. In addition, an analogue of algorithmic information complexity, "prediction complexity", is elaborated. A task-independent bound is derived on how much the prediction complexity of a computational task can differ for two different reference universal physical computers used to solve that task, a bound similar to the "encoding" bound governing how much the algorithm information complexity of a Turing machine calculation can differ for two reference universal Turing machines. Finally, it is proven that either the Hamiltonian of our universe proscribes a certain type of computation, or prediction complexity is unique (unlike algorithmic information complexity), in that there is one and only version of it that can be applicable throughout our universe.

Wolpert, David H.↗