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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Leiner, Barry M.↗
NASA NTRS2000

Research Institute for Advanced Computer Science

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.

Gross, Anthony R.↗
NASA NTRS1993

Deep Space Network (DSN), Network Operations Control Center (NOCC) computer-human interfaces

The Network Operations Control Center (NOCC) of the DSN is responsible for scheduling the resources of DSN, and monitoring all multi-mission spacecraft tracking activities in real-time. Operations performs this job with computer systems at JPL connected to over 100 computers at Goldstone, Australia and Spain. The old computer system became obsolete, and the first version of the new system was installed in 1991. Significant improvements for the computer-human interfaces became the dominant theme for the replacement project. Major issues required innovating problem solving. Among these issues were: How to present several thousand data elements on displays without overloading the operator? What is the best graphical representation of DSN end-to-end data flow? How to operate the system without memorizing mnemonics of hundreds of operator directives? Which computing environment will meet the competing performance requirements? This paper presents the technical challenges, engineering solutions, and results of the NOCC computer-human interface design.

Ellman, Alvin↗
NASA NTRS1989

Ground data systems resource allocation process

The Ground Data Systems Resource Allocation Process at the Jet Propulsion Laboratory provides medium- and long-range planning for the use of Deep Space Network and Mission Control and Computing Center resources in support of NASA's deep space missions and Earth-based science. Resources consist of radio antenna complexes and associated data processing and control computer networks. A semi-automated system was developed that allows operations personnel to interactively generate, edit, and revise allocation plans spanning periods of up to ten years (as opposed to only two or three weeks under the manual system) based on the relative merit of mission events. It also enhances scientific data return. A software system known as the Resource Allocation and Planning Helper (RALPH) merges the conventional methods of operations research, rule-based knowledge engineering, and advanced data base structures. RALPH employs a generic, highly modular architecture capable of solving a wide variety of scheduling and resource sequencing problems. The rule-based RALPH system has saved significant labor in resource allocation. Its successful use affirms the importance of establishing and applying event priorities based on scientific merit, and the benefit of continuity in planning provided by knowledge-based engineering. The RALPH system exhibits a strong potential for minimizing development cycles of resource and payload planning systems throughout NASA and the private sector.

Berner, Carol A.↗
NASA NTRS1985

The AMPTE Charge Composition Explorer science data system

The instrument complement on all three Active Magnetospheric Particle Tracer Explorer (AMPTE) spacecraft is devoted to the conduction of the unified measurements which are required to achieve the scientific aims. A single science data base for each spacecaft has, therefore, been established with the objective to facilitate unified analysis. The data are kept in Science Data Centers in the U.S., West Germany, and the United Kingdom. The Science Data Center dedicated to the Charge Composition Explorer (CCE) is located at the Applied Physics Laboratory of Johns Hopkins University where it was developed. The present paper is concerned with aspects of the computing center's design, development and operations.

Holland, B. B.↗
NASA NTRS2002

RIACS FY2002 Annual Report

The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. Operated by the Universities Space Research Association (a non-profit university consortium), RIACS is located at the NASA Ames Research Center, Moffett Field, California. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in September 2003. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology (IT) Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1) Automated Reasoning for Autonomous Systems; 2) Human-Centered Computing; and 3) High Performance Computing and Networking. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains including aerospace technology, earth science, life sciences, and astrobiology. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

Leiner, Barry M.↗
NASA NTRS2003

Job Superscheduler Architecture and Performance in Computational Grid Environments

Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.

Shan, Hongzhang↗
NASA NTRS2000

Adjoint Techniques for Topology Optimization of Structures Under Damage Conditions

The objective of this cooperative agreement was to seek computationally efficient ways to optimize aerospace structures subject to damage tolerance criteria. Optimization was to involve sizing as well as topology optimization. The work was done in collaboration with Steve Scotti, Chauncey Wu and Joanne Walsh at the NASA Langley Research Center. Computation of constraint sensitivity is normally the most time-consuming step of an optimization procedure. The cooperative work first focused on this issue and implemented the adjoint method of sensitivity computation (Haftka and Gurdal, 1992) in an optimization code (runstream) written in Engineering Analysis Language (EAL). The method was implemented both for bar and plate elements including buckling sensitivity for the latter. Lumping of constraints was investigated as a means to reduce the computational cost. Adjoint sensitivity computation was developed and implemented for lumped stress and buckling constraints. Cost of the direct method and the adjoint method was compared for various structures with and without lumping. The results were reported in two papers (Akgun et al., 1998a and 1999). It is desirable to optimize topology of an aerospace structure subject to a large number of damage scenarios so that a damage tolerant structure is obtained. Including damage scenarios in the design procedure is critical in order to avoid large mass penalties at later stages (Haftka et al., 1983). A common method for topology optimization is that of compliance minimization (Bendsoe, 1995) which has not been used for damage tolerant design. In the present work, topology optimization is treated as a conventional problem aiming to minimize the weight subject to stress constraints. Multiple damage configurations (scenarios) are considered. Each configuration has its own structural stiffness matrix and, normally, requires factoring of the matrix and solution of the system of equations. Damage that is expected to be tolerated is local and represents a small change in the stiffness matrix compared to the baseline (undamaged) structure. The exact solution to a slightly modified set of equations can be obtained from the baseline solution economically without actually solving the modified system.. Shennan-Morrison-Woodbury (SMW) formulas are matrix update formulas that allow this (Akgun et al., 1998b). SMW formulas were therefore used here to compute adjoint displacements for sensitivity computation and structural displacements in damaged configurations.

Akgun, Mehmet A.↗
NASA NTRS1999

Optimization of Aerospace Structure Subject to Damage Tolerance Criteria

The objective of this cooperative agreement was to seek computationally efficient ways to optimize aerospace structures subject to damage tolerance criteria. Optimization was to involve sizing as well as topology optimization. The work was done in collaboration with Steve Scotti, Chauncey Wu and Joanne Walsh at the NASA Langley Research Center. Computation of constraint sensitivity is normally the most time-consuming step of an optimization procedure. The cooperative work first focused on this issue and implemented the adjoint method of sensitivity computation in an optimization code (runstream) written in Engineering Analysis Language (EAL). The method was implemented both for bar and plate elements including buckling sensitivity for the latter. Lumping of constraints was investigated as a means to reduce the computational cost. Adjoint sensitivity computation was developed and implemented for lumped stress and buckling constraints. Cost of the direct method and the adjoint method was compared for various structures with and without lumping. The results were reported in two papers. It is desirable to optimize topology of an aerospace structure subject to a large number of damage scenarios so that a damage tolerant structure is obtained. Including damage scenarios in the design procedure is critical in order to avoid large mass penalties at later stages. A common method for topology optimization is that of compliance minimization which has not been used for damage tolerant design. In the present work, topology optimization is treated as a conventional problem aiming to minimize the weight subject to stress constraints. Multiple damage configurations (scenarios) are considered. Each configuration has its own structural stiffness matrix and, normally, requires factoring of the matrix and solution of the system of equations. Damage that is expected to be tolerated is local and represents a small change in the stiffness matrix compared to the baseline (undamaged) structure. The exact solution to a slightly modified set of equations can be obtained from the baseline solution economically without actually solving the modified system. Sherrnan-Morrison-Woodbury (SMW) formulas are matrix update formulas that allow this. SMW formulas were therefore used here to compute adjoint displacements for sensitivity computation and structural displacements in damaged configurations.

Akgun, Mehmet A.↗
NASA NTRS1983

BANDIT in NASTRAN

BANDIT has been implemented into the NASTRAN April '83 release. It is now a permanent feature in NASTRAN and will be included in all future releases for all four computing machines (IBM, CDC, UNIVAC, and VAX). Originally BANDIT operated as a preprocessor of NASTRAN. It read the NASTRAN input cards and produced a set of resequencing (SEOGP) cards that would greatly reduce the computational time required by the matrix decomposition module of NASTRAN for a large structure. In the past, many computer centers had installed BANDIT in their systems together with the NASTRAN program. The user would run the BANDIT program and NASTRAN as if they were one program (or two separated programs depending on how the two programs were actually tied together in the computer systems). In some cases, the user was required to pass the input cards and the output SEQGP cards between the two programs, and n others, the data was manipulated through the use of cataloged disc files. Although there is nothing wrong with this BANDIT-NASTRAN arrangement, there are, however, several shortcomings which are mentioned in this paper. The BANDIT in the NASTRAN April '83 release has removed all the deficiencies, and it comes in one version applicable to the four computing machines.

Chan, G. C.↗
NASA NTRS1988

NASA Marshall Space Flight Center solar observatory

A description is provided of the NASA Marshall Space Flight Center's Solar Vector Magnetograph Facility and a summary is given of its observations and data reduction during Jan. to Mar. 1988. The systems that make up the facility are a magnetograph telescope, an H-alpha telescope, a Questar telescope, and a computer center. The data are represented by longitudinal contours with azimuth plots.

Smith, James E.↗
NASA NTRS2009

Hubble Systems Optimize Hospital Schedules

Don Rosenthal, a former Ames Research Center computer scientist who helped design the Hubble Space Telescope's scheduling software, co-founded Allocade Inc. of Menlo Park, California, in 2004. Allocade's OnCue software helps hospitals reclaim unused capacity and optimize constantly changing schedules for imaging procedures. After starting to use the software, one medical center soon reported noticeable improvements in efficiency, including a 12 percent increase in procedure volume, 35 percent reduction in staff overtime, and significant reductions in backlog and technician phone time. Allocade now offers versions for outpatient and inpatient magnetic resonance imaging (MRI), ultrasound, interventional radiology, nuclear medicine, Positron Emission Tomography (PET), radiography, radiography-fluoroscopy, and mammography.

Source record↗
NASA NTRS1983

Development of a statewide Landsat digital data base for forest insect damage assessment

A Joint Research Project (JRP) invlving NASA/Goddard Space Flight Center and the Pennsylvania Bureau of Forestry/Division of Forest Pest Management demonstrates the utility of Landsat data for assessing forest insect damage. A major effort within the project has been the creation of map-registered, statewide Landsat digital data base for Pennsylvania. The data base, developed and stored on computers at the Pennsylvania State University Computation Center, contains Landsat imagery, a Landsat-derived forest resource map, and digitized data layers depicting Forest Pest Management District boundaries and county boundaries. A data management front-end system was also developed to provide an interface between the various layers of information within the data base and image analysis software. This front-end system insures than an automated assessment of defoliation damage can be conducted and summarized by geographic area or jurisdiction of interest.

Williams, D. L.↗
NASA NTRS1989

Environmental impact statement Space Shuttle advanced solid rocket motor program

The proposed action is design, development, testing, and evaluation of Advanced Solid Rocket Motors (ASRM) to replace the motors currently used to launch the Space Shuttle. The proposed action includes design, construction, and operation of new government-owned, contractor-operated facilities for manufacturing and testing the ASRM's. The proposed action also includes transport of propellant-filled rocket motor segments from the manufacturing facility to the testing and launch sites and the return of used and/or refurbished segments to the manufacturing site. Sites being considered for the new facilities include John C. Stennis Space Center, Hancock County, Mississippi; the Yellow Creek site in Tishomingo County, Mississippi, which is currently in the custody and control of the Tennessee Valley Authority; and John F. Kennedy Space Center, Brevard County, Florida. TVA proposes to transfer its site to the custody and control of NASA if it is the selected site. All facilities need not be located at the same site. Existing facilities which may provide support for the program include Michoud Assembly Facility, New Orleans Parish, Louisiana; and Slidell Computer Center, St. Tammany Parish, Louisiana. NASA's preferred production location is the Yellow Creek site, and the preferred test location is the Stennis Space Center.

Source record↗
NASA NTRS1989

Queuing theory models for computer networks

A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

Galant, David C.↗
NASA NTRS1978

CODSTRAN - Composite durability structural analysis

CODSTRAN (COmposite Durability STRucture ANalysis) a NASA Lewis Center computer program for the prediction of defect growth and fracture of composite structures when subjected to service loads is presented. Organization, capabilities and present status are discussed. Organizational aspects include executive, input, output, analysis and composite mechanics modules. Capabilities include: durability assessment of large structures and complex structural parts from composites, structural response due to static, cyclic, transient impact and thermal loads, and criteria for static, cyclic, and dynamic fracture. At the present state of development some of CODSTRAN's analysis capabilities include composite mechanics, static failures, and lamination residual stresses. An application in which CODSTRAN is used to predict the defect growth in a flat specimen, with a center through-slit under tension is studied. When completed, CODSTRAN will account for geometry and material nonlinearities, environmental effects as well as static, cyclic and dynamic fracture.

Chamis, C. C.↗
NASA NTRS1971

The 1970/71 spectral data management programs

The data management programs used by the Stanford Remote Sensing Laboratory to access, modify, and reduce the data obtained from both the NASA IR airborne spectrometer, and Stanford's SG-4 field spectrometer are reported. Many details covered in previous reports are not repeated. References are provided. These programs are written in FORTRAN 4 and S/360 Assembler Language, and are currently running on a S/360 model 67 (operating under OS/MFT) at the Stanford Computation Center Campus Facility.

Marshall, A. A.↗