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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

A postprocessor system for the data reduction and post analysis of NASTRAN results

NASTRAN analysis results are scanned to determine maximum and minimum displacements, forces and stresses. Allowables and margins of safety are computed, and in the case of multiple loading conditions, envelopes for displacements, forces, stresses and margins of safety are also produced for specified element sets. Graphical plots of the reduced or the regular NASTRAN results may be obtained superimposed either of a developed fuselage strip or on a projection of any specified part of the finite element model. The use of the data reduction, post analysis and graphical plotting capabilities provide the analyst with a fast and convenient tool for the study of NASTRAN analysis results and their presentation for project documentation.

Raibstein, A. I.↗
NASA NTRSDate not supplied

Development of Data Reduction Methods for Dynamic Stability Tests in a Magnetic Suspension and Balance System

The NASA/ODU 6-inch Magnetic Suspension and Balance System (MSBS) is operational in a “free-to-yaw” configuration in a subsonic wind tunnel. The MSBS hardware has been heavily modified over recent years to utilize a transverse magnetization scheme, with mixed electromagnetic and motion tracking camera position sensors and a relatively sophisticated control system. The project aims to provide a unique test capability for dynamic stability testing of planetary entry capsules, free from support interference. Aerodynamic tests are being conducted, with a focus of validation of the data reduction methods used to extract dynamic stability parameters. The unique complication is the existence of magnetic, aerodynamic, and mass centers, where magnetic, aerodynamic, and inertia forces respectively are resolved. The paper will report on tests of a family of EEV-like geometries, where the conical half-angle varied between 45 and 60 degrees in steps of 3.75 degrees. The paper will present experimental results from the parametric family of EEV-like geometries. Simulation results will also be presented, based on a two or three degree-of-freedom Simulink model. The model allows the exploration of the effects of non-coincident centers and the sensitivity of results arising from uncertainties in location.

Entry Systems Modeling↗
NASA NTRS1995

Smithsonian stratospheric far-infrared spectrometer and data reduction system

The Smithsonian far-infrared spectrometer (FIRS) is a remote sensing Fourier transform spectrometer that measures the mid- and far-infrared thermal emission spectrum of the stratosphere from balloon and aircraft platforms. The spectrometer has had nine successful balloon flights from 1987 to 1994, flying at float altitudes of 36 - 39 km and collecting 131 hours of midlatitude stratospheric limb spectra. The spectrometer also flew on a NASA CD-8 aircraft, as part of the second Airborne Arctic Stratospheric Expedition (AASE-2), collecting 140 hours of overhead spectra at latitudes ranging from the equator to the north pole. We present here a brief description of the instrument, a discussion of data reduction procedures, an estimation of both random and systematic errors, an outline of the procedure for retrieving mixing ratio profiles, and an explanation of the method of deriving temperature and pressure from the far- and mid-infrared spectra.

Johnson, D. G.↗
NASA NTRS1985

Computerized data reduction techniques for nadir viewing remote sensors

Computer resources have been developed for the analysis and reduction of MAPS experimental data from the OSTA-1 payload. The MAPS Research Project is concerned with the measurement of the global distribution of mid-tropospheric carbon monoxide. The measurement technique for the MAPS instrument is based on non-dispersive gas filter radiometer operating in the nadir viewing mode. The MAPS experiment has two passive remote sensing instruments, the prototype instrument which is used to measure tropospheric air pollution from aircraft platforms and the third generation (OSTA) instrument which is used to measure carbon monoxide in the mid and upper troposphere from space platforms. Extensive effort was also expended in support of the MAPS/OSTA-3 shuttle flight. Specific capabilities and resources developed are discussed.

Tiwari, S. N.↗
NASA NTRS1991

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

A residual acceleration data analysis plan is developed that will allow principal investigators of low-gravity experiments to efficiently process their experimental results in conjunction with accelerometer data. The basic approach consisted of the following program of research: (1) identification of sensitive experiments and sensitivity ranges by order of magnitude estimates, numerical modelling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration data bases.

Rogers, Melissa J. B.↗
NASA NTRS1972

GSFC support for E-24 data reduction and analysis

Reduced and analyzed data from the plasma wave detector on OGO E spacecraft are reported. The bibliography lists 74 publications in scientific books and journals which highlight the analysis program.

Scarf, F. L.↗
NASA NTRS1974

Omega flight-test data reduction sequence

Computer programs for Omega data conversion, summary, and preparation for distribution are presented. Program logic and sample data formats are included, along with operational instructions for each program. Flight data (or data collected in flight format in the laboratory) is provided by the Ohio University Omega receiver base in the form of 6-bit binary words representing the phase of an Omega station with respect to the receiver's local clock. All eight Omega stations are measured in each 10-second Omega time frame. In addition, an event-marker bit and a time-slot D synchronizing bit are recorded. Program FDCON is used to remove data from the flight recorder tape and place it on data-processing cards for later use. Program FDSUM provides for computer plotting of selected LOP's, for single-station phase plots, and for printout of basic signal statistics for each Omega channel. Mean phase and standard deviation are printed, along with data from which a phase distribution can be plotted for each Omega station. Program DACOP simply copies the Omega data deck a controlled number of times, for distribution to users.

Lilley, R. W.↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS1988

Autonomous image data reduction by analysis and interpretation

Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.

Eberlein, Susan↗
NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗
NASA NTRS2002

Spectral Data Reduction via Wavelet Decomposition

The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.

Kaewpijit, S.↗
DOE OSTI2025

Performance analysis and data reduction for exascale scientific workflows

Chimbuko is the first in situ, scalable, workflow-level performance analysis tool for trace-level analysis and visualization of application performance. This tool was developed by the Co-design Center for Online Data Analysis and Reduction and funded by the U.S. Department of Energy’s Exascale Computing Project. We provide a detailed description of Chimbuko’s architecture and illustrate our online and offline visualization with multiple use cases. We also present results for the deployment and scalability of the tool as applied to a high-energy physics workflow running at large scale on the Frontier supercomputer.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

GRACE KBR and Accelerometer Data Reduction and Calibration

The Gravity Recovery and Climate Experiment (GRACE), launched on March 17, 2002, represents the state-of-the-art in geodetic observations of the static and time varying components of the Earth's geopotential field. The fundamental measurement used to observe gravity is the inter-satellite range and range rate between two coplanar, low altitude satellites obtained from a K-band ranging (KBR) system. In addition to the K-band ranging system, each satellite possess a Super-STAR Accelerometer, a GPS receiver/antenna package, Star Cameras and a Laser Retro Reflector (LRR) to complete the compliment of science instruments. The GRACE project has now released two years of Level 1B data derived from the science instruments and sensors. An integral component of our time variable gravity research is the reduction, calibration and analyses of these Level 1B data. In particular we have analyzed several months of K-band ranging (KBR1B), accelerometry (ACC1B) and GPS navigation (GNAV1B) data. Accelerometer calibration and KBR data reduction methodology and results will be presented. We discuss the impact of these analyses on the recovery of time variable gravity.

Rowlands, David D.↗
NASA NTRS1984

Ongoing data reduction, theoretical studies and supporting research in magnetospheric physics

Data from ISEE-3, Pioneer Venus Orbiter, and Voyager 1 and 2 were analyzed. The predictability of local shock macrostructure at ISEE-1, at the Earth's bow shock, from solar wind measurements made up-stream by ISEE-3, was conducted using computer graphic format. Morphology of quasi-parallel shock was reviewed. The review attempted to interrelate various measurements and computations involving the q-parallel structure and foreshock elements connected to it. A new classification for q-parallel morphology was suggested.

Scarf, F. L.↗
NASA NTRS1994

(abstract) Venus Gravity Data Reduction

The Magellan spacecraft has provided high resolution gravity data to its very end, October 13, 1994, when it was consumed by the Venusian atmosphere. After aerobraking in August of 1993 to attain a near circular orbit, excellent high latitude data were acquired which previously were very weak during the elliptical orbit coverage. There are 1500 orbits during the near circular orbit, supplying redundant coverage at different geometries over many features. This allowed the relaxation of apriori constraints, so true amplitudes are being extracted from the data. In this paper we present the results of a 75(sup th) degree and order field that incorporates all the old Pioneer Venus Orbiter data as well as all the Magellan data to September 1994. The new results reflect even higher correlation with topography, higher amplitude values for the highs and lows, and global results that have essentially very little apriori constraint on the solution parameters. We also correlate our new model with the earlier ones based on 60(sup th) and 40(sup th) degree and order presentations.

Magellan Venus gravity orbits topography surface f↗
NASA NTRS2003

Vector-Ordering Filter Procedure for Data Reduction

The vector-ordering filter (VOF) technique involves a procedure for sampling a large population of data vectors to select a subset of data vectors that fully characterize the state space of the large population. The VOF technique enables a large reduction of the volume of data that must be handled in the automated monitoring system and method discussed in the two immediately preceding articles. In so doing, the VOF technique enables the development of data-driven mathematical models of a monitored asset from sets of data that would otherwise exceed the memory capacities of conventional engineering computers. Data-driven mathematical models have been shown to offer high fidelity for purposes of control and monitoring of assets. In practice, a collection of asset-operating observations is acquired with the intention that the collection contain observations characteristic of the full dynamic range of operation of the asset. Often, such a collection contains an extremely large number of observations, many of which are redundant. The VOF technique fills the need for a means to extract, from the original collection of observational data, a reduced data matrix that excludes redundant data while maintaining the full statistical character and dynamic range of the original data. The reduced data matrix can then be used as the input data for development of a mathematical model of the monitored asset, or as training data for a neural-network substitute for an explicit mathematical model of the asset. Alternatively, the reduced data matrix can, itself, be used directly as a mathematical model of the monitored asset, as is commonly done in multivariate state-estimation techniques. The original data are collected from the asset over a range of operating states and are put in matrix form. Each column vector in the original data matrix represents the signal values acquired at a particular operational state of the asset. Thus, the number of columns of the original data matrix equals the number of observed states and the number of rows in this matrix equals the number of signals acquired at each observation. In the VOF technique, one extracts the reduced data matrix from the original data matrix through the selection of a representative subset of the column (state) vectors.

Bickford, Randall L.↗