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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

The IRGen infrared data base modeler

IRGen is a modeling system which creates three-dimensional IR data bases for real-time simulation of thermal IR sensors. Starting from a visual data base, IRGen computes the temperature and radiance of every data base surface with a user-specified thermal environment. The predicted gray shade of each surface is then computed from the user specified sensor characteristics. IRGen is based on first-principles models of heat transport and heat flux sources, and it accurately simulates the variations of IR imagery with time of day and with changing environmental conditions. The starting point for creating an IRGen data base is a visual faceted data base, in which every facet has been labeled with a material code. This code is an index into a material data base which contains surface and bulk thermal properties for the material. IRGen uses the material properties to compute the surface temperature at the specified time of day. IRGen also supports image generator features such as texturing and smooth shading, which greatly enhance image realism.

Bernstein, Uri↗
NASA NTRS1981

Generic functional requirements for a NASA general-purpose data base management system

Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given.

Lohman, G. M.↗
NASA NTRS1988

The Goddard Infrared Astronomical Data Base

The contents, structure, and principal products of the Goddard Infrared Astronomical Data Base are briefly reviewed. The data base is a machine-readable compilation of data obtained by searching the astronomical literature both in scientific journals and in infrared survey catalogs. The current data base contains more than 140,000 individual observations of at least 30,000 different infrared sources. The principal products of the data base are the Catalog of Infrared Observations and its associated appendices and the Infrared Source Cross-Index.

Mead, Jaylee M.↗
NASA NTRS1989

Development of the data base for near-Earth resources

Development of the data base for near-Earth resources was begun. Specific items accomplished were: (1) Definition of data base contents via discussions among the PSI staff and outside scientist such as Lucy McFadden and Mark Skyes; (2) Discussion/demonstration of dBase capabilities and possible organization of file(s) with L. Alvarez, Steward Observatory; (3) Data base entries for near-Earth asteroids consisting of data from the Russian ephemeris, a forthcoming review chapter for the Asteroids 2 book, and other literature; and (4) Development of a list of asteroid observers worldwide to be contacted during the coordinated phase of the project. A copy of the data base as it now exists is included.

Davis, D. R.↗
NASA NTRS1985

Analysis and forecast intercomparisons using the FGGE SOP-1 data base

The First GARP Global Experiment (FGGE) data base has provided the research community with the most complete global coverage of meteorological informaiton since measurements were first taken. It is important to understand the characteristics of the FGGE data base in terms of its accuracy and representativeness compared to the true state of the atmosphere. The uncertainty associated with the initial conditions used in a numerical model plays a significant role in subsequent error growth as shown by predictability theory. The ultimate limit of forecast skill is directly related to the initial uncertainty. The accuracy of analyses using FGGE data base coupled with the errors due to modeling imperfections determines the present skill of numerical models. An estimte of initial uncertainty is determined by examining differences in several FGGE analyses. The estimate is then used to determine an ultimate limit of forecast skill from derived predictability error growth rates. Several different calculations of predictability error growth are also compared. Finally, present-day forecast skill using FGGE analyses is contrasted to the estimates of ultimate skill, and the partition of model error versus initial uncertainty is discussed.

Baumhefner, D. P.↗
NASA NTRS1985

Towards a Global MAP Data Base

Scientific and ecological needs call for the generation of a global data base of measured data from the Earth's atmosphere, similar but complementary to the data of the meteorological service. Right now there is a large gap between these needs and the available financial means. If this prevails, it might be prohibitive for the generation of such a data base. There must be a compromise between the needs and the means. Priorities must be set. Thus, discussions should be started on which data can be or should be stored. Newly generated data for storage in such a data base is recommended to be handled by the World Data Centers (WDCs). This brief report should help to stimulate discussions and ubsequent actions.

Hartmann, G. K.↗
NASA NTRS1983

Fundamental research data base

A fundamental research data base containing ground truth, image, and Badhwar profile feature data for 17 North Dakota, South Dakota, and Minnesota agricultural sites is described. Image data was provided for a minimum of four acquisition dates for each site and all four images were registered to one another.

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NASA NTRS1972

Space tug economic analysis study. Volume 2: Tug concepts analysis. Appendix: Tug design and performance data base

The tug design and performance data base for the economic analysis of space tug operation are presented. A compendium of the detailed design and performance information from the data base is developed. The design data are parametric across a range of reusable space tug sizes. The performance curves are generated for selected point designs of expendable orbit injection stages and reusable tugs. Data are presented in the form of graphs for various modes of operation.

Source record↗
NASA NTRS1981

Pan Air Geometry Management System (PAGMS): A data-base management system for PAN AIR geometry data

A data-base management system called PAGMS was developed to facilitate the data transfer in applications computer programs that create, modify, plot or otherwise manipulate PAN AIR type geometry data in preparation for input to the PAN AIR system of computer programs. PAGMS is composed of a series of FORTRAN callable subroutines which can be accessed directly from applications programs. Currently only a NOS version of PAGMS has been developed.

Hall, J. F.↗
NASA NTRS1989

Infrared/submillimeter optical properties data base

The general goal was to build a data base containing optical properties, such as reflectance, transmittance, refractive index, in the far infrared to submillimeter wavelength region. This data base would be limited to selected crystalline materials and temperature between 300 and 2 K. The selected materials were: lithium, lead, and strontium; the bromides of potassium and thallium; the carbides of silicone and tungsten; and the materials of KRS5, KRS6, diamond, and sapphire. Last summer, barium fluoride was selected as prototype material for building the data base. This summer the literature search, preparation of the data for barium fluoride was completed. In addition the literature search for data related to the compounds mentioned was completed. The current status is that barium fluoride is in a form suitable for a NASA internal publication. The papers containing the data on the other materials were xeroxed and they are ready to be reduced. On the reverse side, the top figure is a sample combination of data for the index of refraction at 300 K. The lower figure shows the transmittance vs wavelength at 300 and 80 K. These figures are a sample of many which were developed. Since barium fluoride was studied more than most of the materials listed above, it is clear that additional measurements should be made to fill in the gaps present on both temperature and wavelength data.

Alley, Phillip W.↗
NASA NTRS1981

Reporting Capabilities and Management of the DSN Energy Data Base

The DSN Energy Data Base is a collection of computer files developed and maintained by DSN Engineering. The energy consumption data must be updated monthly and summarized and displayed in printed output as desired. The methods used to handle the data and perform these tasks are described.

Hughes, R. D.↗
NASA NTRS2010

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Barlow, Jonathan Spencer↗
NASA NTRS1983

Fundamental research data base

A fundamental research data base was created on a single 9-track 1600 BPI tape containing ground truth, image, and Badhwar profile feature data for 17 North Dakota, South Dakota, and Minnesota agricultural sites. Each site is 5x6 nm in area. Image data has been provided for a minimum of four acquisition dates for each site. All four images have been registered to one another. A list of the order of the files on tape and the dates of acquisition is provided.

Source record↗
NASA NTRS1981

Data base management system analysis and performance testing with respect to NASA requirements

Several candidate Data Base Management Systems (DBM's) that could support the NASA End-to-End Data System's Integrated Data Base Management System (IDBMS) Project, later rescoped and renamed the Packet Management System (PMS) were evaluated. The candidate DBMS systems which had to run on the Digital Equipment Corporation VAX 11/780 computer system were ORACLE, SEED and RIM. Oracle and RIM are both based on the relational data base model while SEED employs a CODASYL network approach. A single data base application which managed stratospheric temperature profiles was studied. The primary reasons for using this application were an insufficient volume of available PMS-like data, a mandate to use actual rather than simulated data, and the abundance of available temperature profile data.

Martin, E. A.↗
NASA NTRS2010

Data-Based Predictive Control with Multirate Prediction Step

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Barlow, Jonathan S.↗
NASA NTRS1991

Geodynamics branch data base for main magnetic field analysis

The data sets used in geomagnetic field modeling at GSFC are described. Data are measured and obtained from a variety of information and sources. For clarity, data sets from different sources are categorized and processed separately. The data base is composed of magnetic observatory data, surface data, high quality aeromagnetic, high quality total intensity marine data, satellite data, and repeat data. These individual data categories are described in detail in a series of notebooks in the Geodynamics Branch, GSFC. This catalog reviews the original data sets, the processing history, and the final data sets available for each individual category of the data base and is to be used as a reference manual for the notebooks. Each data type used in geomagnetic field modeling has varying levels of complexity requiring specialized processing routines for satellite and observatory data and two general routines for processing aeromagnetic, marine, land survey, and repeat data.

Langel, Robert A.↗
NASA NTRS1982

The ORSER LANDSAT Data Base of Pennsylvania

A mosaicked LANDSAT data base for Pennsylvania, installed at the computation center of the Pennsylvania State University is described. Initially constructed by Penn State's Office for Remote Sensing of Earth Resources (ORSER) for the purpose of assisting in state-wide mapping of gypsy moth defoliation, the data base will be available to a variety of potential users. It will provide geometrically correct LANDSAT data accessible by political, jurisdictional, or arbitrary boundaries.

Turner, B. J.↗
NASA NTRS1975

Accessing technical data bases using STDS: A collection of scenarios

A line by line description is given of sessions using the set-theoretic data system (STDS) to interact with technical data bases. The data bases contain data from actual applications at NASA Langley Research Center. The report is meant to be a tutorial document that accompanies set processing in a network environment.

Hardgrave, W. T.↗