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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Systems engineering considerations for operational support systems

Operations support as considered here is the infrastructure of people, procedures, facilities and systems that provide NASA with the capability to conduct space missions. This infrastructure involves most of the Centers but is concentrated principally at the Johnson Space Center, the Kennedy Space Center, the Goddard Space Flight Center, and the Jet Propulsion Laboratory. It includes mission training and planning, launch and recovery, mission control, tracking, communications, data retrieval and data processing.

Aller, Robert O.↗
NASA NTRS1982

Archiving and retrieval of data from the International Ultraviolet Explorer /IUE/ mission

The data base of IUE spectra available for dissemination to the scientific community presently contains approximately 22,000 separate images. Due to storage space and computer processing time limitations, it was decided to store the data on high density (6250 bpi) specially formatted tapes and to retrieve and reconvert them to the originally supplied format upon request. The archival/retrieval system for the data and an automatic data entry system for creation and maintenance of an indexing data base are described. Suggestion are made for the use of standard formats for future image data storage, retrieval and dissemination.

Warren, W. H., Jr.↗
NASA NTRS2011

Estimation of Smoothing Error in SBUV Profile and Total Ozone Retrieval

Data from the Nimbus-4, Nimbus-7 Solar Backscatter Ultra Violet (SBUV) and seven of the NOAA series of SBUV/2 instruments spanning 41 years are being reprocessed using V8.6 algorithm. The data are scheduled to be released by the end of August 2011. An important focus of the new algorithm is to estimate various sources of errors in the SBUV profiles and total ozone retrievals. We discuss here the smoothing errors that describe the components of the profile variability that the SBUV observing system can not measure. The SBUV(/2) instruments have a vertical resolution of 5 km in the middle stratosphere, decreasing to 8 to 10 km below the ozone peak and above 0.5 hPa. To estimate the smoothing effect of the SBUV algorithm, the actual statistics of the fine vertical structure of ozone profiles must be known. The covariance matrix of the ensemble of measured ozone profiles with the high vertical resolution would be a formal representation of the actual ozone variability. We merged the MLS (version 3) and sonde ozone profiles to calculate the covariance matrix, which in general case, for single profile retrieval, might be a function of the latitude and month. Using the averaging kernels of the SBUV(/2) measurements and calculated total covariance matrix one can estimate the smoothing errors for the SBUV ozone profiles. A method to estimate the smoothing effect of the SBUV algorithm is described and the covariance matrixes and averaging kernels are provided along with the SBUV(/2) ozone profiles. The magnitude of the smoothing error varies with altitude, latitude, season and solar zenith angle. The analysis of the smoothing errors, based on the SBUV(/2) monthly zonal mean time series, shows that the largest smoothing errors were detected in the troposphere and might be as large as 15-20% and rapidly decrease with the altitude. In the stratosphere above 40 hPa the smoothing errors are less than 5% and between 10 and 1 hPa the smoothing errors are on the order of 1%. We validate our estimated smoothing errors by comparing the SBUV ozone profiles with other ozone profiling sensors.

Kramarova, N. A.↗
NASA NTRS1993

Measured space environmental effects to LDEF during retrieval

Data gathered by the Interim Operational Contamination Monitor (IOCM) with regard to the effect of the space environment on the STS-32 Shuttle mission and on the Long Duration Exposure Facility (LDEF) are reported. IOCM measures the deposition of molecular and particulate contamination during all flight phases. It also measures the thermophysical properties of thermal control surfaces by calorimetry, the flux of the ambient atomic oxygen environment, the incident solar flux, and the absolute ambient pressure in the payload bay. The IOCM also provides a structure and sample holders for the exposure of passive material samples to the space environment. One of the more salient results from the STS-32 flight suggests that the LDEF emitted a large number of particulates after berthing into the Shuttle. The mission atomic oxygen fluence was also calculated. Although the fluence was low by normal standards, the Kapton (trademark) passive samples exhibited the onset of erosion. Orbital debris and micrometeoroid impacts also occurred during the retrieval mission. The average perforation diameter was approximately 1.25 micrometers. The largest perforation diameter was measured at 65 micrometers.

Maag, Carl R.↗
DOE OSTI2024

Satellite Retrievals

Data from the SENTINEL-1 satellite constellation (SENTINEL-1a and SENTINEL-1b), from PNNL.

17 WIND ENERGY↗
NASA NTRS1981

Simultaneous disk storage and retrieval

Data are concurrently recorded on disk by one minicomputer and accessed by another, using format of memory blocks, buffering algorithm, and time-sequence addressing. Buffering algorithm works at data rates up to 68,000 words per second; modifications up rate to 160,000 words per second.

Levine, F. E.↗
NASA NTRS2007

Hand Held Device for Wireless Powering and Interrogation of Biomems Sensors and Actuators

A compact, hand-held device for wireless powering, interrogation and data retrieval from at least one implanted sensor. The hand-held device includes an antenna for powering an implanted sensor and for receiving data from the implanted sensor to the hand-held device for at least one of storage, display or analysis. The hand-held device establishes electromagnetic coupling with a low radiating radio frequency power inductor in the implanted sensor at a predefined separation and the antenna geometry allows for the antenna to power, interrogate and retrieve data from the implanted sensor without strapping the hand-held device to a human body housing the implanted sensor The hand-held device optionally allows for activation of the implanted sensor only during interrogation and data retrieval.

Miranda, Felix Antonio↗
NASA NTRS1991

Data storage and retrieval system

The Data Storage and Retrieval System (DSRS) consists of off-the-shelf system components integrated as a file server supporting very large files. These files are on the order of one gigabyte of data per file, although smaller files on the order of one megabyte can be accommodated as well. For instance, one gigabyte of data occupies approximately six 9 track tape reels (recorded at 6250 bpi). Due to this large volume of media, it was desirable to shrink the size of the proposed media to a single portable cassette. In addition to large size, a key requirement was that the data needs to be transferred to a (VME based) workstation at very high data rates. One gigabyte (GB) of data needed to be transferred from an archiveable media on a file server to a workstation in less than 5 minutes. Equivalent size, on-line data needed to be transferred in less than 3 minutes. These requirements imply effective transfer rates on the order of four to eight megabytes per second (4-8 MB/s). The DSRS also needed to be able to send and receive data from a variety of other sources accessible from an Ethernet local area network.

Nakamoto, Glen↗
NASA NTRS1992

Data storage and retrieval system

The Data Storage and Retrieval System (DSRS) consists of off-the-shelf system components integrated as a file server supporting very large files. These files are on the order of one gigabyte of data per file, although smaller files on the order of one megabyte can be accommodated as well. For instance, one gigabyte of data occupies approximately six 9-track tape reels (recorded at 6250 bpi). Due to this large volume of media, it was desirable to 'shrink' the size of the proposed media to a single portable cassette. In addition to large size, a key requirement was that the data needs to be transferred to a (VME based) workstation at very high data rates. One gigabyte (GB) of data needed to be transferred from an archiveable media on a file server to a workstation in less than 5 minutes. Equivalent size, on-line data needed to be transferred in less than 3 minutes. These requirements imply effective transfer rates on the order of four to eight megabytes per second (4-8 MB/s). The DSRS also needed to be able to send and receive data from a variety of other sources accessible from an Ethernet local area network.

Nakamoto, Glen↗
NASA NTRS1978

TESTPLT: Interactive computer procedure for wind-tunnel-data management, retrieval, comparison, and plotting

A method of maintaining, retrieving, comparing, and plotting wind-tunnel data by means of an interactive remote computer terminal is described. The software associated with the method consists of two procedure files, three computer programs, and a submittal file, all of which are discussed. The procedure was based on maintaining the basic wind-tunnel data files in the Langley standard interface tape (SIFT) format. The SIFT format was not part of the present development. Those features of the format essential to the present use were described. The entire method was illustrated by sample executions from a remote terminal.

Heyson, H. H.↗
NASA NTRS2021

Assessing CryoSat-2 Antarctic Snow Freeboard Retrievals Using Data From ICESat-2

NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) laser altimeter launched in Fall 2018, providing an invaluable addition to the polar altimetry record generated by ESA's CryoSat-2 radar altimeter. The simultaneous operation of these two satellite altimeters enables unique comparison studies of sea ice altimetry, utilizing the different frequencies and profiling strategies of the two instruments. Here, we use freeboard data from ICESat-2 to assess Antarctic snow freeboard retrievals from CryoSat-2. We first discuss updates made to a previously published CryoSat-2 retrieval process and show how this Version 2 algorithm improves upon the original method by comparing the new retrievals to ICESat-2 in specific along-track profiles as well as on the basin-scale. In two near-coincident along-track profiles, we find mean snow freeboard differences (standard deviations of differences) of 0.3 (9.3) and 7.6 cm (9.6 cm) with 25 km binned correlation coefficients of 0.77 and 0.89. Monthly mean freeboard differences range between −2.9 (10.8) and 6.6 cm (16.8 cm) basin wide, with the largest differences typically occurring in Austral fall months that is hypothesized to be related to new ice growth and the use of static snow backscatter coefficients in the retrieval. Monthly mean correlation coefficients range between 0.57 and 0.80. While coincident data show good agreement between the two sensors, they highlight issues related to geometric and frequency sampling differences that can impact the freeboard distributions.

S W Fons↗
NASA NTRS1990

A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data

The retrieval algorithm for spaceborne scatterometry proposed by Schultz (1985) is extended. A circular median filter (CMF) method is presented, which operates on wind directions independently of wind speed, removing any implicit wind speed dependence. A cell weighting scheme is included in the algorithm, permitting greater weights to be assigned to more reliable data. The mathematical properties of the ambiguous solutions to the wind retrieval problem are reviewed. The CMF algorithm is tested on twelve simulated data sets. The effects of spatially correlated likelihood assignment errors on the performance of the CMF algorithm are examined. Also, consideration is given to a wind field smoothing technique that uses a CMF.

Schultz, Howard↗
NASA NTRS2016

Applications of SMAP Data to Retrieval of Ocean Surface Wind and Salinity

We have examined the L-band radiometer and radar data from NASA’s Soil Moisture Active Passive (SMAP) mission for ocean research and applications. We find that the SMAP data are in excellent agreement with the geophysical model function (GMF) derived from the Aquarius data up to a wind speed of 20 ms-1. For severe wind conditions, the higher resolution data from SMAP allowed us to assess the sensitivity of L-band radiometer signals to hurricane force winds. We applied the L-band GMF to the retrieval of ocean surface wind and SSS from the SMAP data. Comparison with the European Center for Medium-Range Weather Forecasting, WindSat and RapidSCAT wind speeds suggests that SMAP’s radiometer wind speed reaches an excellent accuracy of about 1.1-1.7 ms-1 below a wind speed of 20 ms-1. We have also found that the maximum wind speed derived from the SMAP radiometer data can reach 140 knots for severe storms and are generally in good agreement with the hurricane track analysis and operational aircraft Stepped Frequency Microwave Radiometer wind speeds. The spatial patterns of the SMAP SSS agree well with climatological distributions, but exhibit several unique spatial and temporal features.

ocean surface wind↗
NASA NTRS1984

Photographic memory: The storage and retrieval of data

The concept of density encoding digital data in a mass-storage computer peripheral is proposed. This concept requires that digital data be encoded as distinguishable density levels (DDLS) of the film to be used as the storage medium. These DDL's are then recorded on the film in relatively large pixels. Retrieval of the data would be accomplished by scanning the photographic record using a relatively small aperture. Multiplexing of the pixels is used to store data of a range greater than the number of DDL's supportable by the film in question. Although a cartographic application is used as an example for the photographic storage of data, any digital data can be stored in a like manner. When the data is inherently spatially-distributed, the aptness of the proposed scheme is even more evident. In such a case, human-readability is an advantage which can be added to those mentioned earlier: speed of acquisition, ease of implementation, and cost effectiveness.

Horton, J.↗
NASA NTRS1986

Cloud and moisture fields derived from the GLA retrievals of HIRS2/MSU data

The GLA retrieval scheme for the analysis of HIRS and MSU radiances is applied to derive cloud and humidity fields from the HIRS2/MSU data for June 1979. For the retrieval of cloud fraction and cloud top pressure, the original algorithm of Susskind et al. (1983) and Susskind et al. (1984) was improved. The derived profiles of the monthly mean fields of cloud fraction and cloud top pressure clearly show the intertropical convergence zone, with the most intense convection in the monsoonal region of the southern Asia and over Central America, which show up as containing the highest cloud top levels and largest cloud amount. For the retrieval of humidity profiles, which are not one of the products of the original processing system, a new algorithm was derived.

Reuter, D.↗
NASA NTRS1977

Retrieval techniques and graphics displays using a computerized stellar data base

The paper describes a stellar data retrieval system for which the data base consists of 28 machine-readable astronomical catalogs. Eleven of these catalogs have been combined into the Goddard Cross Index (GCI), which serves as the computer entry point to these catalogs. The full data entry from any of the GCI catalogs can be retrieved in a single computer run. With this system, it is possible to prepare candidates for observation by searching the data base for stars with given characteristics. Generation of plots of all catalog stars in or near the telescope's field of view to scale of Palomar, other atlases, or to the telescope itself for use as observing charts or to aid in identifying unknown sources, can be accomplished.

Mead, J.↗
NASA NTRS1993

Mapping of taiga forest units using AIRSAR data and/or optical data, and retrieval of forest parameters

A maximum a posteriori Bayesian classifier for multifrequency polarimetric SAR data is used to perform a supervised classification of forest types in the floodplains of Alaska. The image classes include white spruce, balsam poplar, black spruce, alder, non-forests, and open water. The authors investigate the effect on classification accuracy of changing environmental conditions, and of frequency and polarization of the signal. The highest classification accuracy (86 percent correctly classified forest pixels, and 91 percent overall) is obtained combining L- and C-band frequencies fully polarimetric on a date where the forest is just recovering from flooding. The forest map compares favorably with a vegetation map assembled from digitized aerial photos which took five years for completion, and address the state of the forest in 1978, ignoring subsequent fires, changes in the course of the river, clear-cutting of trees, and tree growth. HV-polarization is the most useful polarization at L- and C-band for classification. C-band VV (ERS-1 mode) and L-band HH (J-ERS-1 mode) alone or combined yield unsatisfactory classification accuracies. Additional data acquired in the winter season during thawed and frozen days yield classification accuracies respectively 20 percent and 30 percent lower due to a greater confusion between conifers and deciduous trees. Data acquired at the peak of flooding in May 1991 also yield classification accuracies 10 percent lower because of dominant trunk-ground interactions which mask out finer differences in radar backscatter between tree species. Combination of several of these dates does not improve classification accuracy. For comparison, panchromatic optical data acquired by SPOT in the summer season of 1991 are used to classify the same area. The classification accuracy (78 percent for the forest types and 90 percent if open water is included) is lower than that obtained with AIRSAR although conifers and deciduous trees are better separated due to the presence of leaves on the deciduous trees. Optical data do not separate black spruce and white spruce as well as SAR data, cannot separate alder from balsam poplar, and are of course limited by the frequent cloud cover in the polar regions. Yet, combining SPOT and AIRSAR offers better chances to identify vegetation types independent of ground truth information using a combination of NDVI indexes from SPOT, biomass numbers from AIRSAR, and a segmentation map from either one.

Rignot, Eric↗