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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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Research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, fluid mechanics including fluid dynamics, acoustics, and combustion, aerodynamics, and computer science during the period 1 Apr. 1992 - 30 Sep. 1992 is summarized.
The focus of the Research Institute for Advanced Computer Science (RIACS) is to explore matches between advanced computing architectures and the processes of scientific research. An architecture evaluation of the MIT static dataflow machine, specification of a graphical language for expressing distributed computations, and specification of an expert system for aiding in grid generation for two-dimensional flow problems was initiated. Research projects for 1984 and 1985 are summarized.
Faculty in the Department of Physical, Environmental and Computer Sciences strongly believe in the concept that undergraduate research and research-related activities must be integrated into the fabric of our undergraduate Science and Technology curricula. High level skills, such as problem solving, reasoning, collaboration and the ability to engage in research, are learned for advanced study in graduate school or for competing for well paying positions in the scientific community. One goal of our academic programs is to have a pipeline of research activities from high school to four year college, to graduate school, based on the GISS Institute on Climate and Planets model.
Graph and network theory play a fundamental role in quantum computer sciences, including quantum information and computation. Random graphs and complex network theory are pivotal in predicting novel quantum phenomena, where entangled links are represented by edges. Quantum algorithms have been developed to enhance solutions for various network problems, giving rise to quantum graph computing and quantum graph learning (QGL). Here, in this review, we explore graph theory and graph learning methods as powerful tools for quantum computers to generate efficient solutions to problems beyond the reach of classical systems. We delve into the development of quantum complex network theory and its applications in quantum computation, materials discovery, and research. We also discuss quantum machine learning (QML) methodologies for effective image classification using qubits, quantum gates, and quantum circuits. Additionally, the paper addresses the challenges of QGL and algorithms, emphasizing the steps needed to develop flexible QGL solvers. This review presents a comprehensive overview of the fields of QGL and QML, highlights recent advancements, and identifies opportunities for future research.
Research project reports pertaining to physics, space sciences, computer systems, information processing, and control systems
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.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period April 1, 1995 through September 30, 1995.
This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period October 1, 1998 through March 31, 1999.
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.
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.
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.
Progress reports and technical updates of programs being performed by NASA centers are covered. Presentations in viewgraph form are included for topics in three categories: computer science, data systems and space station applications.
A viewgraph describing the use of multiple frameworks by NASA, GSA, and U.S. Government agencies is presented. The contents include: 1) Federal Systems Integration and Management Center (FEDSIM) and NASA Center for Computational Sciences (NCCS) Environment; 2) Ruling Frameworks; 3) Implications; and 4) Reconciling Multiple Frameworks.
Progress reports and technical updates of programs being performed by NASA centers are covered. Presentations in viewgraph form, along with abstracts, are included for topics in three catagories: computer science, data systems, and space station applications.
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.
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.
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.
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.