Interactive specification of data displays
On-line graphical language for computer data display
Anderson, R.↗
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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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Infrared astronomical data base and catalog of infrared observations
A computer data base of infrared astronomical observations has been established at NASA/Goddard Space Flight Center. It contains a summary of all infrared (1-100 microns) observations of celestial sources outside the solar system, published in the major scientific journals since 1960, as well as the contents of infrared surveys and catalogs. A Catalog of Infrared Observations (CIO) has been developed from the data base in printed and magnetic tape versions. A bibliographic Guide to the Infrared Astronomical Literature, and an Altas of Infrared Source Names and Positions will be published in conjunction with the catalog. Future plans include development of an interactive data system at Goddard which will give a user direct access to the computerized data.
Schmitz, M.↗
Definition of parameters for computer analysis of neurophysiological data
Parameters for computer analysis of neurophysiological data using EEG from normative library
ELECTROENCEPHALOGRAM /EEG/↗
Reducing the Volume of NASA Earth-Science Data
A computer program reduces data generated by NASA Earth-science missions into representative clusters characterized by centroids and membership information, thereby reducing the large volume of data to a level more amenable to analysis. The program effects an autonomous data-reduction/clustering process to produce a representative distribution and joint relationships of the data, without assuming a specific type of distribution and relationship and without resorting to domain-specific knowledge about the data. The program implements a combination of a data-reduction algorithm known as the entropy-constrained vector quantization (ECVQ) and an optimization algorithm known as the differential evolution (DE). The combination of algorithms generates the Pareto front of clustering solutions that presents the compromise between the quality of the reduced data and the degree of reduction. Similar prior data-reduction computer programs utilize only a clustering algorithm, the parameters of which are tuned manually by users. In the present program, autonomous optimization of the parameters by means of the DE supplants the manual tuning of the parameters. Thus, the program determines the best set of clustering solutions without human intervention.
Lee, Seungwon↗
A study of the flexible body dynamics of the RAE-A satellite
Spacecraft flight data was compared with simulated data computed by the RAE and IMP dynamics simulator computer programs. There was not sufficient data available to provide definitive data on antenna boom position to the Radio Astronomy experimenter. There was, however, enough data to indicate the trend of antenna boom stiffness and temperature gradient. It was possible to obtain a good fit of simulated data to measured spacecraft attitude data when the antenna booms were extended to 450 feet. The value of the RAE-A antenna boom stiffness appears to be significantly less than the preflight ground measured value. It was confirmed that an improved simulation can be obtained by using values of the root angles of the antenna booms and by using an angle of the damper plane of motion, relative to the plane of the antennas, which differed from preflight ground measurements.
Source record↗
An evaluation of Space Shuttle Orbiter forward fuselage surface pressures - Comparison with wind tunnel and theoretical predictions
In order for ground-based pressure distribution techniques to be verified by the actual performance of the Space Shuttle Orbiter in flight, a comparative study of flight pressure data and both wind tunnel and computational data is presented. The flight pressure data, obtained from measurements on the Orbiter's surface during atmospheric reentry, are part of the overall Orbiter flight data system designated Development Flight Instrumentation. Also given is an analysis of the Orbiter pressure data system, including its transducers, their behavior, and their calibration. The two analyses are the bases of an error assessment calculation for the flight data, as well as an explanation of any discrepancies between flight and ground-based data.
Bradley, P. F.↗
Pressure distributions obtained on a 0.10-scale model of the space shuttle Orbiter's forebody in the AEDC 16T propulsion wind tunnel
Pressure distribution test data obtained on a 0.10-scale model of the forward fuselage of the Space Shuttle Orbiter are presented without analysis. The tests were completed in the AEDC 16T Propulsion Wind Tunnel. The 0.10-scale model was tested at angles of attack from -2 deg to 18 deg and angles of side slip from -6 to 6 deg at Mach numbers from 0.25 to 1/5 deg. The tests were conducted in support of the development of the Shuttle Entry Air Data System (SEADS). In addition to modeling the 20 SEADS orifices, the wind-tunnel model was also instrumented with orifices to match Development Flight Instrumentation (DFI) port locations that existed on the Space Shuttle Orbiter Columbia (OV-102) during the Orbiter Flight Test program. This DFI simulation has provided a means of comparisons between reentry flight pressure data and wind-tunnel and computational data.
Siemers, P. M., III↗
Pressure distributions obtained on a 0.10-scale model of the Space Shuttle Orbiter's forebody in the Ames Unitary Plan Wind Tunnel
Pressure distribution test data obtained on a 0.10-scale model of the forward fuselage of the Space Shuttle Orbiter are presented without analysis. The tests were completed in the Ames Unitary Wind Tunnel (UPWT). The UPWT tests were conducted in two different test sections operating in the continuous mode, the 8 x 7 feet and 9 x 7 feet test sections. Each test section has its own Mach number range, 1.6 to 2.5 and 2.5 to 3.5 for the 9 x 7 feet and 8 x 7 feet test section, respectively. The test Reynolds number ranged from 1.6 to 2.5 x 10 to the 6th power ft and 0.6 to 2.0 x 10 to the 6th power ft, respectively. The tests were conducted in support of the development of the Shuttle Entry Air Data System (SEADS). In addition to modeling the 20 SEADS orifices, the wind-tunnel model was also instrumented with orifices to match Development Flight Instrumentation (DFI) port locations that existed on the Space Shuttle Columbia (OV-102) during the Orbiter Flight test program. This DFI simulation has provided a means for comparisons between reentry flight pressure data and wind-tunnel and computational data.
Siemers, P. M., III↗
The Art of Extracting One-Dimensional Flow Properties from Multi-Dimensional Data Sets
The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e:g: thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.
Baurle, R. A.↗
The Extraction of One-Dimensional Flow Properties from Multi-Dimensional Data Sets
The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e.g. thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.
Baurle, Robert A.↗
Urban Energy Systems: Research at Oak Ridge National Laboratory
In the coming decades, our planet will witness unprecedented urban population growth in both established and emerging communities. The development and maintenance of urban infrastructures are highly energy-intensive. Urban areas are dictated by complex intersections among physical, engineered, and human dimensions that have significant implications for traffic congestion, emissions, and energy usage. In this chapter, we highlight recent research and development efforts at Oak Ridge National Laboratory (ORNL), the largest multipurpose science laboratory within the U.S. Department of Energy’s (DOE) national laboratory system, that characterizes the interactions between the human dynamics and critical infrastructures in conjunction with the integration of four distinct components: data, critical infrastructure models, and scalable computation and visualization, all within the context of physical and social systems. Discussions focus on four key topical themes: population and land use, sustainable mobility, the energy-water nexus, and urban resiliency, that are mutually aligned with DOE’s mission and ORNL’s signature science and technology capabilities. Using scalable computing, data visualization, and unique datasets from a variety of sources, the institute fosters innovative interdisciplinary research that integrates ORNL expertise in critical infrastructures including energy, water, transportation, and cyber, and their interactions with the human population.
Bhaduri, Budhu↗
Superconvergent procedures for the computation of engineering data from finite element solutions
The computation of engineering data from finite element solutions based on the virtual work formulation is discussed. It is shown that, using specially chosen virtual displacement functions, it is possible to compute certain functionals from the virtual work expression with much greater efficiency than would be possible by direct methods.
Szabo, B. A.↗
Supporting Data: Photoluminescence of a Uranium(IV) Alkoxide Complex
Supporting computational data for the publication titled:L. R. Valerio, S. Roy Chowdhury, R. Lewis, K. E. Knowles,* B. Vlaisavljevich,* and E. M. Matson* “Photoluminescence of a Uranium(IV) Alkoxide Complex", S ubmitted to JACS Au.
Computational chemistry↗
Planning The Route Of A Robotic Land Vehicle
Algorithm enables experimental robotic land vehicle to follow automatically route computed on basis of terrain-height-map data. Computer executing algorithm merges coarser global topographical data with finer local topographical data obtained through stereoscopic video system as vehicle moves along, then smoothes merged elevation map, interpolates map to evenly-horizontally-spaced grid points, and differentiates map to produce data on slopes and roughness for use in calculations of traversability and optimum route(s). Distance traveled minimized to extent possible consistent with avoidance of obstacles.
Gennery, Donald B.↗
Supporting Data: A Four‐Coordinate Pr 4+ Imidophosphorane Complex
Supporting computational data for the publication titled: A. C. Boggiano, S. Roy Chowdhury, M. D. Roy, M. G. Bernbeck, S. M. Greer, B. Vlaisavljevich,* and H. S. La Pierre* “A Four-Coordinate Pr4+ Imidophosphorane Complex" Angew. Chem. Int. Ed., 2024, e202409789. DOI: 10.1002/anie.202409789
Boggiano, Andrew C.↗
Computer programs for reduction of microphotometer data
Five computer programs for analyzing magnetic tape recordings of digital data from microphotometer
Bell, R. A.↗
Scientific Data Management Beyond Traditional Computing Boundaries
Scientific data management is undergoing a fundamental transformation driven by the convergence of artificial intelligence (AI)/machine learning workflows, distributed computing and storage environments, and exponential data growth. Here, we analyze how these developments address current limitations while enabling new capabilities for cross-facility collaboration and AI-driven research.
Widener, Patrick [Oak Ridge National Laboratory (O↗
Ku-band signal design study
Analytical tools, methods and techniques for assessing the design and performance of the space shuttle orbiter data processing system (DPS) are provided. The computer data processing network is evaluated in the key areas of queueing behavior synchronization and network reliability. The structure of the data processing network is described as well as the system operation principles and the network configuration. The characteristics of the computer systems are indicated. System reliability measures are defined and studied. System and network invulnerability measures are computed. Communication path and network failure analysis techniques are included.
Rubin, I.↗