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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 19 records

LANDSAT 4 band 6 data evaluation

Satellite data collected over Lake Ontario were processed to observed surface temperature values. This involved computing apparent radiance values for each point where surface temperatures were known from averaged digital count values. These radiance values were then converted by using the LOWTRAN 5A atmospheric propagation model. This model was modified by incorporating a spectral response function for the LANDSAT band 6 sensors. A downwelled radiance term derived from LOWTRAN was included to account for reflected sky radiance. A blackbody equivalent source radiance was computed. Measured temperatures were plotted against the predicted temperature. The RMS error between the data sets is 0.51K.

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Establishment of computerized numerical databases on thermophysical and other properties of molten as well as solid materials and data evaluation and validation for generating recommended reliable reference data

The Center for Information and Numerical Data Analysis and Synthesis, (CINDAS), measures and maintains databases on thermophysical, thermoradiative, mechanical, optical, electronic, ablation, and physical properties of materials. Emphasis is on aerospace structural materials especially composites and on infrared detector/sensor materials. Within CINDAS, the Department of Defense sponsors at Purdue several centers: the High Temperature Material Information Analysis Center (HTMIAC), the Ceramics Information Analysis Center (CIAC) and the Metals Information Analysis Center (MIAC). The responsibilities of CINDAS are extremely broad encompassing basic and applied research, measurement of the properties of thin wires and thin foils as well as bulk materials, acquisition and search of world-wide literature, critical evaluation of data, generation of estimated values to fill data voids, investigation of constitutive, structural, processing, environmental, and rapid heating and loading effects, and dissemination of data. Liquids, gases, molten materials and solids are all considered. The responsibility of maintaining widely used databases includes data evaluation, analysis, correlation, and synthesis. Material property data recorded on the literature are often conflicting, diverging, and subject to large uncertainties. It is admittedly difficult to accurately measure materials properties. Systematic and random errors both enter. Some errors result from lack of characterization of the material itself (impurity effects). In some cases assumed boundary conditions corresponding to a theoretical model are not obtained in the experiments. Stray heat flows and losses must be accounted for. Some experimental methods are inappropriate and in other cases appropriate methods are carried out with poor technique. Conflicts in data may be resolved by curve fitting of the data to theoretical or empirical models or correlation in terms of various affecting parameters. Reasons (e.g. phase transitions) must be found for unusual dependence or any anomaly. Such critical evaluation involves knowledge of theory, experience in measurement, familiarity with metallurgy (microstructural behavior) and not inconsiderable judgment. An examination of typical data compiled and analyzed by CINDAS shows that the thermal conductivity of a material reported in the literature may vary by a factor of two of more; the range of reported values increases as temperature increases reflecting the difficulty of high temperature measurements. Often only estimates of melt behavior are available, despite the importance of melt properties in modeling, welding, or other solidification processes. There may be only a few measurements available for properties such as kinematic viscosity, even for widely used materials such as stainless steel. In the face of such a paucity of existing data and in a national environment where too few new data are being generated it is nonetheless the responsibility of CINDAS to select and disseminate recommended values of a wide variety of thermophysical properties.

Ho, C. Y.↗

The MAMS Quick View System-2 (QVS2) - A workstation for NASA aircraft scanner data evaluation

This paper describes a ground-based data-evaluation workstation named Quick View System-2 (QVS2) developed to support postflight evaluation of data supplied by the Multispectral Atmospheric Mapping Sensor (MAMS), one of the four spectrometers that can be used with the Daedalus scanner flown on the ER-2 aircraft. The QVS2 provides advanced analysis capabilities and can be applied to other airborne scanners used throughout NASA for earth-system-science investigations, because of the commonality in the data stream and in the generalized data structure.

Jedlovec, Gary J.↗

LANDSAT 4 band 6 data evaluation

Previously experienced data collection problems were successfully resolved. A limited effort, directed at improved methods of display of TM Band 6 data, has concentrated on implementation of intensity hue and saturation displays using the Band 6 data to control hue. These displays tend to give the appearance of high resolution thermal data and make whole scene thermal interpretation easier by color coding thermal data in a manner that aids visual interpretation. More quantitative efforts were directed at utilizing the reflected bands to define land cover classes and then modifying the thermal displays using long wave optical properties associated with cover type.

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Space Physics Cosmic & Heliospheric Data Evaluation Panel Report

This Cosmic and Heliospheric (C&H) Data Evaluation Panel was charged with the task of identifying and prioritizing important C&H data sets. It was requested to provide C&H community input to the Space Physics Division for a program of revitalizing data holdings. Details and recommendations are provided. Highest C&H priority is assigned to Voyager, Pioneer, Helios, IMP-8, and ISEE-3 data.

Cosmic Heliospheric Data Archive Preservation Spac↗

A PC-based multispectral scanner data evaluation workstation: Application to Daedalus scanners

In late 1989, a personal computer (PC)-based data evaluation workstation was developed to support post flight processing of Multispectral Atmospheric Mapping Sensor (MAMS) data. The MAMS Quick View System (QVS) is an image analysis and display system designed to provide the capability to evaluate Daedalus scanner data immediately after an aircraft flight. Even in its original form, the QVS offered the portability of a personal computer with the advanced analysis and display features of a mainframe image analysis system. It was recognized, however, that the original QVS had its limitations, both in speed and processing of MAMS data. Recent efforts are presented that focus on overcoming earlier limitations and adapting the system to a new data tape structure. In doing so, the enhanced Quick View System (QVS2) will accommodate data from any of the four spectrometers used with the Daedalus scanner on the NASA ER2 platform. The QVS2 is designed around the AST 486/33 MHz CPU personal computer and comes with 10 EISA expansion slots, keyboard, and 4.0 mbytes of memory. Specialized PC-McIDAS software provides the main image analysis and display capability for the system. Image analysis and display of the digital scanner data is accomplished with PC-McIDAS software.

Jedlovec, Gary J.↗

Reliability of nondestructive evaluation data

Program calculates probability of defects at selected confidence levels from nondestructive evaluation data. It provides alternate method of grouping sample data to obtain reasonable value for lower confidence limit with small sample size.

Couchman, J. C.↗

LANDSAT 4 band 6 data evaluation

Comparison of underflight data with satellite estimates of temperature revealed significant gain calibration errors. The source of the LANDSAT 5 band 6 error and its reproducibility is not yet adequately defined. The error can be accounted for using underflight or ground truth data. When underflight data are used to correct the satellite data, the residual error for the scene studied was 1.3K when the predicted temperatures were compared to measured surface temperature.

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Skylab 2 space vehicle data evaluation guide

Vehicle telemetry measurements for all stages of Skylab 2 are presented. The data sources for the launch vehicle and command service module are identified. The data evaluation guide format is described. The system for designating the components of the spacecraft is defined. A list of abbreviations for technical terms used in the reporting documents is included.

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LANDSAT-4 band 6 data evaluation

The radiometric integrity of the LANDSAT-D thematic mapper (TM) thermal infrared channel (band 6) data was evaluated to develop improved radiometric preprocessing calibration techniques for removal of atmospheric effects. Primary data analysis was spent in evaluating the line to line and detector to detector variation in the thermal infrared data. The data studied was in the core area of Lake Ontario where very stable temperatures were expected. The detectors and the scan direction were taken as separate parameters and an analysis of variance was conducted. The data indicate that significant variability exists both between detectors and between scan directions.

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Skylab S192 data evaluation: Comparisons with ERTS-1 results

The author has identified the following significant results. The Skylab S192 data was evaluated by: (1) comparing the classification results using S192 and ERTS-1 data over the Holt County, Nebraska agricultural study area, and (2) investigating the impact of signal-to-noise ratio on classification accuracies using registered S192 and ERTS-1 data. Results indicate: (1) The classification accuracy obtained on S192 data using its best subset of four bands can be expected to be as high as that on ERTS-1 data. (2) When a subset of four S192 bands that are spectrally similar to the ERTS-1 bands was used for classification, an obvious deterioration in the classification accuracy was observed with respect to the ERTS-1 results. (3) The thermal bands 13 and 14 as well as the near IR bands were found to be relatively important in the classification of agricultural data. Although bands 11 and 12 were highly correlated, both were invariably included in the best subsets of the band sizes, four and beyond, according to the divergence criterion. (4) The differentiation of corn from popcorn was difficult on both S192 and ERTS-1 data acquired at an early summer date. (5) The results on both sets of data indicate that it was relatively easy to differentiate grass from any other class.

Chang, C. Y.↗

Method and data evaluation at NASA endocrine laboratory

The biomedical data of the astronauts on Skylab 3 were analyzed to evaluate the univariate statistical methods for comparing endocrine series experiments in relation to other medical experiments. It was found that an information storage and retrieval system was needed to facilitate statistical analyses.

Johnston, D. A.↗

Automated Registration of Multi-Mode Nondestructive Evaluation Data

Registration techniques play a central role in applications of image processing to computer vision, medical imaging, and automatic target tracking. Feature-based techniques such as scale-invariant feature transform (SIFT) and speeded up robust features (SURF) are commonly used to register images derived from a single modality. However, SIFT and SURF struggle to register images from different modalities because the features tend to manifest rather differently and at sometimes very different length-scales. The most successful methods that have been developed to register multi-modal data use information-theoretic approaches. These methods play a key part in nondestructive evaluation scenarios where data that is collected by sensors of different modalities must be registered to be fused. In this paper, automated registration based on normalized mutual information is applied to align data derived from ultrasonic and radiographic inspections of (i) additively manufactured titanium alloy test coupons, and (ii) thin, lithium metal pouch-cell batteries. The quality of the registration is quantified in terms of computational resources and spatial accuracy. In the first case the X-ray computed tomography (XCT) data is captured on a region corresponding to a small subset of the ultrasonic data, while in the case of the lithium batteries the digital radiography (DR) captures a larger region of interest than the ultrasonic data. In both cases the radiographic data resolution is much higher than for ultrasound, but interestingly, in both cases the accuracy of the registration is approximately equal to two-to-three-pixel lengths in the ultrasonic images.

Nondestructive Evaluation↗

MARCE data evaluation

The Get Away Special (GAS) 007 Project Explorer Experiment data recorded and radio downlinked by the Marshall Amateur Radio Club Experiment (MARCE), the first GAS radio experiment, are compared and evaluated. A compatibility assessment, of the student experiments and the MARCE power, control and data systems, during the STS-61C Columbia flight in January 1986 is presented. Analysis of the GAS container's thermal environment, located near the center of the GAS Bridge is discussed.

Stluka, Edward F.↗

Data evaluation, analysis, and scientific study

Extensive work was performed in data analysis and modeling of solar active phenomena. The work consisted in the study of UV data from the Ultraviolet Spectrometer and Polarimeter (UVSP) instrument on board the Solar Maximum Mission satellite. These data were studied in conjunction with X-rays from the Hard X-ray Imaging Spectrometer (HXIS) instrument, and with H-alpha and magnetographic data from ground-based observatories. The processes we studied are the active phenomena which result from the interaction of the solar magnetic fields with the plasma in the outer regions of the solar atmosphere. These processes include some very dynamic processes such as the prominence eruptions and the 'microflares'. Our research aimed at characterizing the following: the observed phenomena, the possible physical models, and the relevance to the chromospheric and coronal heating.

Wu, S. T.↗