SEARCH · Engineering Papers

Results for “computer Science”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

All sources NASA NTRS DOE OSTI

NASA NTRS1994

A Spacelab Expert System for Remote Engineering and Science

NASA's space science program is based on strictly pre-planned activities. This approach does not always result in the best science. We describe an existing computer system that enables space science to be conducted in a more reactive manner through advanced automation techniques that have recently been used in SLS-2 October 1993 space shuttle flight. Advanced computing techniques, usually developed in the field of Artificial Intelligence, allow large portions of the scientific investigator's knowledge to be "packaged" in a portable computer to present advice to the astronaut operator. We strongly believe that this technology has wide applicability to other forms of remote science/engineering. In this brief article, we present the technology of remote science/engineering assistance as implemented for the SLS-2 space shuttle flight. We begin with a logical overview of the system (paying particular attention to the implementation details relevant to the use of the embedded knowledge for system reasoning), then describe its use and success in space, and conclude with ideas about possible earth uses of the technology in the life and medical sciences.

Groleau, Nick↗

NASA NTRS1995

Application of essentially nonoscillatory methods to aeroacoustic flow problems

A finite-difference essentially nonoscillatory (ENO) method has been applied to several of the problems prescribed for the workshop sponsored jointly by the Institute for Computer Applications in Science and Engineering and by NASA Langley Research Center entitled 'Benchmark Problems in Computational Aeroacoustics'. The workshop focused on computational challenges specific to aeroacoustics. Among these are long-distance propagation of a short-wavelength disturbance, propagation of small-amplitude disturbances, and nonreflective boundary conditions. The shock capturing-capability inherent to the ENO method effectively eliminates oscillations near shock waves without the need to add and tune dissipation or filter terms. The method-of-lines approach allows the temporal and spatial operators to be chosen separately in accordance with the demands of a particular problem. The ENO method was robust and accurate for all problems in which the propagating wave was resolved with 8 or more points per wavelength. The finite-wave-model boundary condition, a local nonlinear acoustic boundary condition, performed well for the one-dimensional problems. The buffer-domain approach performed well for the two-dimensional test problem. The amplitude of nonphysical reflections were less than 1 percent of the exiting wave's amplitude.

Atkins, Harold L.↗

NASA NTRS2006

Bioinformatics for Exploration

For the purpose of this paper, bioinformatics is defined as the application of computer technology to the management of biological information. It can be thought of as the science of developing computer databases and algorithms to facilitate and expedite biological research. This is a crosscutting capability that supports nearly all human health areas ranging from computational modeling, to pharmacodynamics research projects, to decision support systems within autonomous medical care. Bioinformatics serves to increase the efficiency and effectiveness of the life sciences research program. It provides data, information, and knowledge capture which further supports management of the bioastronautics research roadmap - identifying gaps that still remain and enabling the determination of which risks have been addressed.

Johnson, Kathy A.↗

NASA NTRS1993

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project.

Holcomb, Lee↗

NASA NTRS1994

NASA High Performance Computing and Communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 1(X)-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientists' abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project, exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects, as well as summaries of early accomplishments and the significance, status, and plans for individual research and development programs within each project. Areas of emphasis include benchmarking, testbeds, software and simulation methods.

Holcomb, Lee↗

NASA NTRS1986

Issues and recommendations associated with distributed computation and data management systems for the space sciences

The primary purpose of the report is to explore management approaches and technology developments for computation and data management systems designed to meet future needs in the space sciences.The report builds on work presented in previous reports on solar-terrestrial and planetary reports, broadening the outlook to all of the space sciences, and considering policy issues aspects related to coordiantion between data centers, missions, and ongoing research activities, because it is perceived that the rapid growth of data and the wide geographic distribution of relevant facilities will present especially troublesome problems for data archiving, distribution, and analysis.

Source record↗

NASA NTRS1995

Data handling and visualization for NASA's science programs

Advanced information systems capabilities are essential to conducting NASA's scientific research mission. Access to these capabilities is no longer a luxury for a select few within the science community, but rather an absolute necessity for carrying out scientific investigations. The dependence on high performance computing and networking, as well as ready and expedient access to science data, metadata, and analysis tools is the fundamental underpinning for the entire research endeavor. At the same time, advances in the whole range of information technologies continues on an almost explosive growth path, reaching beyond the research community to affect the population as a whole. Capitalizing on and exploiting these advances are critical to the continued success of space science investigations. NASA must remain abreast of developments in the field and strike an appropriate balance between being a smart buyer and a direct investor in the technology which serves its unique requirements. Another key theme deals with the need for the space and computer science communities to collaborate as partners to more fully realize the potential of information technology in the space science research environment.

Bredekamp, Joseph H.↗

NASA NTRSDate not supplied

Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)

The scientific community is faced with a need for greatly improved data sharing, analysis, visualization and advanced collaboration based firmly on open science principles. Recent and upcoming launches of new satellite missions with more complex and voluminous data, as well as the ever more urgent need to better understand the global carbon budget and related ecological processes, provided the immediate rational for the ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP). This highly collaborative joint project of ESA and NASA established a framework between ESA and NASA to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by ESA and NASA EO data users. Presented to the public in October 2021, the current version of MAAP provides a common cloud-based platform with computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of global above-ground biomass. Data from the Global Ecosystem Dynamics Investigation (GEDI) mission on the International Space Station and the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) have been instrumental in the first products of MAAP including the first comprehensive map of Boreal above-ground Biomass and a current Global Biomass Harmonization Activity, but the platform is also being specifically designed to support the forthcoming ESA Biomass mission and incorporate data from the upcoming NASA-ISRO SAR (NISAR) mission. While these missions and the corresponding research which includes airborne, field, and calibration/validation data collection and analyses, provide a wealth of data and information relating to global biomass estimation, they also present data storing, processing and sharing challenges. The NISAR mission alone will produce about 80TB/day. These large data volumes present a challenge that would otherwise place accessibility limits on the scientific community and impact scientific progress. Other challenges being addressed by MAAP include: 1) Enabling researchers to easily discover, process, visualize and analyze large volumes of data from both agencies; 2) Providing a wide variety of data in the same coordinate reference frame to enable comparison, analysis, data evaluation, and data generation; 3) Providing a version-controlled science algorithm development environment that supports tools, co-located data and processing resources; and 4) Addressing intellectual property and sharing challenges related to collaborative algorithm development and sharing of data and algorithms. MAAP products can be explored on the MAAP Dashboard at https://earthdata.nasa.gov/maap-biomass or the joint platform entrance at scimaap.net. MAAP also can be accessed through individual NASA (https://maap-project.org) and ESA (https://esa-maap.org/) landing pages.

cloud computing↗

NASA NTRS1987

Asset - An application in mission automation for science planning

Recent advances in computer technology were used to great advantage in planning science observation sequences for the Voyager 2 encounter with Uranus in 1986. Despite a loss of experienced personnel, a challenging schedule, workforce limitations, and the complex nature of the Uranus encounter itself, the resultant science observation timelines were the most highly optimized of the five Voyager encounters with the outer planets. In part, this was due to the development of a microcomputer-based system, called ASSET (Automated Science Sequence Encounter Timelines generator), which was used to design those science observation timelines. This paper details the development of that system. ASSET demonstrates several features essential to the design of the first expert systems for science planning which will be applied for future missions.

Finnerty, D. F.↗

NASA NTRS2012

Evaluating the Efficacy of the Cloud for Cluster Computation

Computing requirements vary by industry, and it follows that NASA and other research organizations have computing demands that fall outside the mainstream. While cloud computing made rapid inroads for tasks such as powering web applications, performance issues on highly distributed tasks hindered early adoption for scientific computation. One venture to address this problem is Nebula, NASA's homegrown cloud project tasked with delivering science-quality cloud computing resources. However, another industry development is Amazon's high-performance computing (HPC) instances on Elastic Cloud Compute (EC2) that promises improved performance for cluster computation. This paper presents results from a series of benchmarks run on Amazon EC2 and discusses the efficacy of current commercial cloud technology for running scientific applications across a cluster. In particular, a 240-core cluster of cloud instances achieved 2 TFLOPS on High-Performance Linpack (HPL) at 70% of theoretical computational performance. The cluster's local network also demonstrated sub-100 ?s inter-process latency with sustained inter-node throughput in excess of 8 Gbps. Beyond HPL, a real-world Hadoop image processing task from NASA's Lunar Mapping and Modeling Project (LMMP) was run on a 29 instance cluster to process lunar and Martian surface images with sizes on the order of tens of gigapixels. These results demonstrate that while not a rival of dedicated supercomputing clusters, commercial cloud technology is now a feasible option for moderately demanding scientific workloads.

Cloud Computing↗

NASA NTRS2000

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Oliker, Leonid↗

NASA NTRS1984

Planetary Science Analysis Support System: Hardware Report

The computeer hardware requirements for a planetary science data analysis support system are described. Present practice, state-of-the-art, and predictable developments are considered. Specific recommendations are presented for those who plan to acquire new computational tools, those who must install and use them, and those who pay for them.

Source record↗

NASA NTRS2013

NASA Center for Climate Simulation (NCCS) Advanced Technology AT5 Virtualized Infiniband Report

The NCCS is part of the Computational and Information Sciences and Technology Office (CISTO) of Goddard Space Flight Center's (GSFC) Sciences and Exploration Directorate. The NCCS's mission is to enable scientists to increase their understanding of the Earth, the solar system, and the universe by supplying state-of-the-art high performance computing (HPC) solutions. To accomplish this mission, the NCCS (https://www.nccs.nasa.gov) provides high performance compute engines, mass storage, and network solutions to meet the specialized needs of the Earth and space science user communities

cloud↗

NASA NTRS1997

How the Theory of Computing Can Help in Space Exploration

The opening of the NASA Pan American Center for Environmental and Earth Sciences (PACES) at the University of Texas at El Paso made it possible to organize the student Center for Theoretical Research and its Applications in Computer Science (TRACS). In this abstract, we briefly describe the main NASA-related research directions of the TRACS center, and give an overview of the preliminary results of student research.

Kreinovich, Vladik↗

NASA NTRS1994

MATH77, Version 4.0

MATH77 is high-quality library of ANSI FORTRAN 77 subprograms implementing contemporary algorithms for basic computational processes of science and engineering. Release 4.0 of MATH77 contains 454 user-callable and 136 lower-level subprograms. MATH77 release 4.0 subroutine library designed to be usable on any computer system supporting full ANSI standard FORTRAN 77 language.

Lawson, Charles L.↗

NASA NTRS2001

Using Computing and Data Grids for Large-Scale Science and Engineering

We use the term "Grid" to refer to a software system that provides uniform and location independent access to geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. These emerging data and computing Grids promise to provide a highly capable and scalable environment for addressing large-scale science problems. We describe the requirements for science Grids, the resulting services and architecture of NASA's Information Power Grid (IPG) and DOE's Science Grid, and some of the scaling issues that have come up in their implementation.

Johnston, William E.↗

NASA NTRS2001

Summary Report of the Orbital X-34 Wing Static Aeroelastic Study

This report documents the results of a computational study conducted on the Orbital Sciences X-34 vehicle to compute its inviscid aerodynamic characteristics taking into account the wing structural flexibility. This was a joint exercise between LaRC and SDRC of California. SDRC modeled the structural details of the wing, and provided the structural deformation for a given pressure distribution on its surfaces. This study was done for a Mach number of 1.35 and an angle of attack of 9 deg.; the freestream dynamic pressure was assumed to be 607 lb/sq ft. Only the wing and the body were simulated in the CFD computations. Two wing configurations were examined. The first had the elevons in the undeflected position and the second had the elevons deflected 20 deg. up. The results indicated that with elevon undeflected, the wing twists by about 1.5 deg. resulting in a reduction in the angle of attack at the wing tip to by 1.5 deg. The maximum vertical deflection of the wing is about 3.71 inches at the wing tip. For the wing with the undeflected elevons, the effect of this wing deformation is to reduce the normal force coefficient (C(sub N)) by 0.012 and introduce a noise up pitching moment coefficient (C(sub m)) of 0.042.

Prabhn, Ramadas K.↗

NASA NTRS2004

Networking Technologies Enable Advances in Earth Science

This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.

Johnson, Marjory↗