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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

A digital algorithm for spectral deconvolution with noise filtering and peak picking: NOFIPP-DECON

Noise-filtering, peak-picking deconvolution software incorporates multiple convoluted convolute integers and multiparameter optimization pattern search. The two theories are described and three aspects of the software package are discussed in detail. Noise-filtering deconvolution was applied to a number of experimental cases ranging from noisy, nondispersive X-ray analyzer data to very noisy photoelectric polarimeter data. Comparisons were made with published infrared data, and a man-machine interactive language has evolved for assisting in very difficult cases. A modified version of the program is being used for routine preprocessing of mass spectral and gas chromatographic data.

Edwards, T. R.↗
NASA NTRSDate not supplied

Implementing Geometric Surface Imperfections into Sandwich Composite Cylinder Finite Element Method Models

The buckling responses of certain cylindrical shell structures are extremely sensitive to geometric surface imperfections. The NASA Engineering and Safety Center (NESC) Shell Buckling Knockdown Factor Project (SBKF) is conducting research to develop analysis-based buckling design recommendations. Experiments are used to verify the analysis-based factors, but the sensitivity of the test articles to geometric imperfections requires implementing as-manufactured imperfections into high-fidelity finite element method models. Data collection methods such as structured light scanning are used for all geometric surface data used in this work. Common preprocessing and visualization steps used in SBKF are discussed, and steps on how surface scans are prepared for implementation into a finite element model is described. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS), written specifically for the use with SBKF, is briefly described and uses eight functions to extract, modify, and write geometric imperfections into Abaqus input files. Results of the pre-processing methods and results from Py_TIGIRS are provided and compared for Composite Test Article (CTA) 8.2B. Excellent agreement between the visualized scan data and the FEM-extracted geometry is demonstrated. A brief example of why geometric surface imperfections are significant in nonlinear numerical analyses for thin cylinders in axial compression is provided as motivation to use tools such as Py_TIGIRS. Future development of Py_TIGIRS including expansion to structures of arbitrary geometry is planned.

Sandwich structures↗
NASA NTRS1986

A prototype expert system in OPS5 for data error detection

AA This prototype expert system, called Trajectory Preprocessing System (TRAPS), contains 49 rules and at present runs on an IBM PC in the OPS5+ software package from Artelligence, Inc. A prototype expert system has been developed in the OPS5 language to perform error checking on data which spacecraft builders/users supply to the NASA Goddard Space Flight Center for processing on the Communications Link Analysis and Simulation System (CLASS) computer. This prototype expert system, called Trajectory Preprocessing System (TRAPS), contains 49 rules and at presentruns on an IBM PC in the OPS5+ software package from Artelligence, Inc. In its operational phase, TRAPS will run in the Oak Ridge Productional Language (ORPL) on the CLASS computer (a Perkin-Elmer 3244 supermini). ORPL, an implementation of OPS5 by the Oak Ridge National Laboratory in MULTIFORTH on a Hewlett-Packard 9836 desktop computer, is now being ported to SS-FORTH on the CLASS computer. This paper discusses the expert system problem domain, development approach, tools, results, and future plans stemming from the TRAPS project.

Rash, James↗
NASA NTRS2002

Onboard Processor for Compressing HSI Data

With EO-1 Hyperion and MightySat in orbit NASA and the DoD are showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor greater than 100, while retaining the necessary spectral fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our initial spectral compression experiments leverage commercial-off-the-shelf (COTS) spectral exploitation algorithms for segmentation, material identification and spectral compression that ASIT has developed. ASIT will also support the modification and integration of this COTS software into the OBP. Other commercially available COTS software for spatial compression will also be employed as part of the overall compression processing sequence. Over the next year elements of a high-performance reconfigurable OBP will be developed to implement proven preprocessing steps that distill the HSI data stream in both spectral and spatial dimensions. The system will intelligently reduce the volume of data that must be stored, transmitted to the ground, and processed while minimizing the loss of information.

Cook, Sid↗
NASA NTRS1983

Multisatellite attitude determination/optical aspect bias determination (MSAD/OABIAS) system description and operating guide. Volume 1: Introduction and analysis

The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS System provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.

Joseph, M.↗
NASA NTRS1983

Multisatellite attitude determination/optical aspect bias determination (MSAD/OABIAS) system description and operating guide. Volume 3: Operating guide

The Multisatellite Attitude Determination/Optical Aspect Bias Determination (MSAD/OABIAS) System, designed to determine spin axis orientation and biases in the alignment or performance of optical or infrared horizon sensors and Sun sensors used for spacecraft attitude determination, is described. MSAD/OABIAS uses any combination of eight observation models to process data from a single onboard horizon sensor and Sun sensor to determine simultaneously the two components of the attitude of the spacecraft, the initial phase of the Sun sensor, the spin rate, seven sensor biases, and the orbital in-track error associated with the spacecraft ephemeris information supplied to the system. In addition, the MSAD/OABIAS system provides a data simulator for system and performance testing, an independent deterministic attitude system for preprocessing and independent testing of biases determined, and a multipurpose data prediction and comparison system.

Joseph, M.↗
NASA NTRS2003

Analysis of ETMS Data Quality for Traffic Flow Management Decisions

The data needed for air traffic flow management decision support tools is provided by the Enhanced Traffic Management System (ETMS). This includes both the tools that are in current use and the ones being developed for future deployment. Since the quality of decision support provided by all these tools will be influenced by the quality of the input ETMS data, an assessment of ETMS data quality is needed. Motivated by this desire, ETMS data quality is examined in this paper in terms of the unavailability of flight plans, deviation from the filed flight plans, departure delays, altitude errors and track data drops. Although many of these data quality issues are not new, little is known about their extent. A goal of this paper is to document the magnitude of data quality issues supported by numerical analysis of ETMS data. Guided by this goal, ETMS data for a 24-hour period were processed to determine the number of aircraft with missing flight plan messages at any given instant of time. Results are presented for aircraft above 18,000 feet altitude and also at all altitudes. Since deviation from filed flight plan is also a major cause of trajectory-modeling errors, statistics of deviations are presented. Errors in proposed departure times and ETMS-generated vertical profiles are also shown. A method for conditioning the vertical profiles for improving demand prediction accuracy is described. Graphs of actual sector counts obtained using these vertical profiles are compared with those obtained using the Host data for sectors in the Fort Worth Center to demonstrate the benefit of preprocessing. Finally, results are presented to quantify the extent of data drops. A method for propagating track positions during ETMS data drops is also described.

Chatterji, Gano B.↗
NASA NTRS1977

Digital exploitation of synthetic aperture radar

A digital processing and analysis scheme for use with digitized synthetic aperture radar data was developed. Using data from a four channel system, the imagery is preprocessed using specially designed software and then analyzed using preexisting facilities originally intended for use with MSS type data. Geometric and radiometric correction may be performed if desired, as well as classification analysis, Fast Fourier transform, filtering and level slice and display functions. The system provides low cost output in real time, permitting interactive imagery analysis. System information flow diagrams as well as sample output products are shown.

Wagner, H. L.↗
NASA NTRS1981

Potential utility of the thematic mapper for surface mine monitoring

One of many potential applications of the thematic mapper (TM) is surface mine monitoring. To assess this potential, data acquired by an aircraft multispectral scanner over Pennsylvania surface mines were preprocessed to simulate the anticipated spectral, spatial, and radiometric characteristics of TM data. False color imagery and thematic maps were derived from the simulated data and compared to imagery and maps derived from LANDSAT multispectral scanner subsystems data. On the basis of this comparison, TM data should definitely increase the detail and accuracy of remotely acquired surface mine information and may enable the remote determination of compliance with reclamation regulations.

Irons, J. R.↗
NASA NTRS1987

A computer code to calculate line by line atmospheric transmission spectra on a microcomputer

A computer program is described which calculates line by line atmospheric transmission spectra on a microcomputer. Radiance calculations are not included. The program is written in FORTRAN and could be modified to run on a microcomputer other than the one on which it was implemented, except that the plotting routine would have to be replaced. The program is based on the 1978 Air Force Geophysics Laboratory LASER routine, and uses absorption line data from the 1982 update of the AFGL Atmospheric Absorption Line Parameters Compilation; segments of needed line data are taken from the tape, preprocessed into the form used by the program and stored on floppy disks. The program calculates transmission spectra over a variety of paths and spanning an arbitrarily chosen wavelength or frequency range; the path may be chosen to be horizontal, vertical or slanted at any zenith angle, and may extend between any two altitudes between 0 and 15 km. Aerosol effects are included, presently based on the 1976 Shettle and Fenn models, plus some molecular continuum effects and Rayleigh scattering.

Safren, H. G.↗
NASA NTRS1991

Improved Computation of Dynamic Stresses

Method combining modified computational procedure with preprocessing and postprocessing program yields additional data and reduces time and cost of using DYNRE1 module of STARDYNE computer program to compute distributions of stresses in machinery under dynamic loads.

Ghosh, Tarun K.↗
NASA NTRS1992

Image masking using polygon fills and morphological transformations

Polygon-fill operations and morphological transformations are effective computational tools for the land-masking and coastline-correction preprocessing operations often applied to AVHRR data prior to oceanographic applications. These masking operations, in conjunction with cloud-screening techniques, can be used on such other oceanographically significant remote-sensing data as those of the Coastal Zone Color Scanner, GOES, and Landsat. The sensitivity of the methods to regional variations in atmospheric conditions and land-ocean temperature gradients is assessed for tropical, midlatitude, and high latitude regions.

Simpson, James J.↗
NASA NTRS2005

A least-squares parameter estimation algorithm for switched hammerstein systems with applications to the VOR

A "Multimode" or "switched" system is one that switches between various modes of operation. When a switch occurs from one mode to another, a discontinuity may result followed by a smooth evolution under the new regime. Characterizing the switching behavior of these systems is not well understood and, therefore, identification of multimode systems typically requires a preprocessing step to classify the observed data according to a mode of operation. A further consequence of the switched nature of these systems is that data available for parameter estimation of any subsystem may be inadequate. As such, identification and parameter estimation of multimode systems remains an unresolved problem. In this paper, we 1) show that the NARMAX model structure can be used to describe the impulsive-smooth behavior of switched systems, 2) propose a modified extended least squares (MELS) algorithm to estimate the coefficients of such models, and 3) demonstrate its applicability to simulated and real data from the Vestibulo-Ocular Reflex (VOR). The approach will also allow the identification of other nonlinear bio-systems, suspected of containing "hard" nonlinearities.

Evaluation Studies↗
NASA NTRSDate not supplied

Making NASA GES DISC Level 2 Data GIS Analysis Ready

There are many valuable data hosted by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for GIS applications in the areas of extreme weather events, climatic anomaly, and public health. However, using NASA Earth Science Data poses some challenges for GIS users. Many of these users are not experts in Earth Observation and have little knowledge about NASA's Earth science data. In the GIS community, GeoTiff is the most widely used raster format, whereas NASA's data is primarily in complex multidimensional netCDF and HDF formats. This complexity makes it difficult for GIS users, especially those who are unfamiliar with these formats. Although GIS software like ArcGIS has made progress in processing multidimensional netCDF data, certain issues still remain, particularly with level 2 data. In this study, we use TROPSpheric Monitoring instrument (TROPOMI) level 2 data as an example to demonstrate how to make such data GIS analysis ready. The process involves: 1. Creating a feature layer from the TROPOMI level 2 data. 2. Converting the feature layer to a gridded raster dataset. 3. Mosaicking gridded raster datasets into a raster dataset covering the entire desired extent. 4. Generating a symbology with a GIBS-specific style that aligns with the visual standards and requirements of GIBS. 5. Publishing image services. By performing these preprocessing and transformation steps, NASA level 2 data can be made compatible and ready for use within GIS software for various spatial analysis and visualization tasks.

Geographic Information System↗
NASA NTRS2007

Advanced Systems for Monitoring Underwater Sounds

The term "Passive Acoustic Monitoring System" (PAMS) describes a developmental sensing-and-data-acquisition system for recording underwater sounds. The sounds (more precisely, digitized and preprocessed versions from acoustic transducers) are subsequently analyzed by a combination of data processing and interpretation to identify and/or, in some cases, to locate the sources of those sounds. PAMS was originally designed to locate the sources such as fish of species that one knows or seeks to identify. The PAMS unit could also be used to locate other sources, for example, marine life, human divers, and/or vessels. The underlying principles of passive acoustic sensing and analyzing acoustic-signal data in conjunction with temperature and salinity data are not new and not unique to PAMS. Part of the uniqueness of the PAMS design is that it is the first deep-sea instrumentation design to provide a capability for studying soniferous marine animals (especially fish) over the wide depth range described below. The uniqueness of PAMS also lies partly in a synergistic combination of advanced sensing, packaging, and data-processing design features with features adapted from proven marine instrumentation systems. This combination affords a versatility that enables adaptation to a variety of undersea missions using a variety of sensors. The interpretation of acoustic data can include visual inspection of power-spectrum plots for identification of spectral signatures of known biological species or artificial sources. Alternatively or in addition, data analysis could include determination of relative times of arrival of signals at different acoustic sensors arrayed at known locations. From these times of arrival, locations of acoustic sources (and errors in those locations) can be estimated. Estimates of relative locations of sources and sensors can be refined through analysis of the attenuation of sound in the intervening water in combination with water-temperature and salinity data acquired by instrumentation systems other than PAMS. A PAMS is packaged as a battery-powered unit, mated with external sensors, that can operate in the ocean at any depth from 2 m to 1 km. A PAMS includes a pressure housing, a deep-sea battery, a hydrophone (which is one of the mating external sensors), and an external monitor and keyboard box. In addition to acoustic transducers, external sensors can include temperature probes and, potentially, underwater cameras. The pressure housing contains a computer that includes a hard drive, DC-to- DC power converters, a post-amplifier board, a sound card, and a universal serial bus (USB) 4-port hub.

Lane, Michael↗
NASA NTRS1977

Blob - An unsupervised clustering approach to spatial preprocessing of MSS imagery

A basic concept of MSS data processing has been developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called 'blobs'). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.

Kauth, R. J.↗
NASA NTRS1980

Digital preprocessing of SEASAT imagery

A model for radar image data is derived for use in developing enhancement techniques. This model describes the image data as the result of a multiplicative-convolved noise process. This information is then used to design a minimum mean square error (MMSE) filter. The resulting filter is implemented adaptively to change with local statistics. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure is thus developed. This technique has been implemented and tested using digitally correlated SEASAT-A synthetic aperture radar (SAR) imagery.

Frost, V. S.↗