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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Detecting a gravitational-radiation background using spacecraft Doppler tracking

The sensitivity of NASA's Deep Space Network spacecraft tracking system to an isotropic cosmological background of gravitational radiation is analyzed. It is found that by using the autocovariance function of the Doppler record in the so-called 'three-way' tracking mode to dig into the noise it is possible to put significant limits on this background with current and future planned deep-space missions.

Hellings, R. W.↗
NASA NTRS1985

Thermal Radiation Analyzer

Thermal Radiation Analyzer System TRASYS II solves radiation related aspects of thermal analysis problems. TRASYS II provides for calculation of internode radiation interchange data and for calculation of incident and absorbed heat rate data originating from environmental radiant heat sources. When TRASYS II used in conjunction with generalized thermal analysis program such as Systems Improved Numerical Differencing Analyzer (SINDA), any thermal problem expressed in terms of lumped parameter RC thermal network solved.

Vogt, R. A.↗
NASA NTRS1985

The effect of the neutral sheet structure of the interplanetary magnetic field on cosmic ray distribution in space

Results of the numerical solution of the anistoropic diffusion equation are presented. The modulation depth of galactic cosmic rays is defined by the degree of curvature of the neutral current sheet in the heliosphere. The effect of the regular interplanetary magnetic field (IMF) on cosmic ray anisotropy in the period of solar activity minimum (in 1976) is analyzed by the data of the neutron super-monitors of the world network, and the heliolatitudinal gradient and cosmic ray diffusion coefficient are defined.

Alania, M. V.↗
NASA NTRS1986

Finite wordlength implementation of a megachannel digital spectrum analyzer

The results of an extensive system analysis of the megachannel spectrum analyzer currently being developed for use in various applications of the Deep Space Network are presented. The intent of this analysis is to quantify the effects of digital quantization errors on system performance. The results of this analysis provide useful guidelines for choosing various system design parameters to enhance system performance.

Satorius, E. H.↗
NASA NTRS1988

Design consideration in constructing high performance embedded Knowledge-Based Systems (KBS)

As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.

Dalton, Shelly D.↗
NASA NTRS1989

Disturbances in the Arizona Monsoon

Numerical modeling simulations of tropical squall lines were begun to determine the role of large scale terrain features over Arizona and Mexico in their initiation and propagation. Installation was completed for a short-base, high resolution lightning location and detection network in and around Tucson. Data from a Doppler wind profiler is being analyzed to determine the role of large scale heating over the inter-mountain plateau region in governing local diurnal wind variations and possible relationships to the monsoon flow. The portable solar photometer for determining high temporal resolution values of the local precipitable water vapor was completed and calibrated. The assembly is nearly completed for a multi-channel microwave passive radiometer to determine local temperature and water vapor profiles.

Gall, Robert↗
NASA NTRS1991

Clouds as calibration targets for AVHRR reflected-solar channels - Results from a two-year study at NOAA/NESDIS

NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) and associated ground-based data have been collected at NOAA/NESDIS, on a daily basis and for 600 days, using five stations within the continental United States in the NOAA solar radiation (SOLRAD) monitoring network. The data have been filtered to include only uniformly overcast conditions and analyzed along the lines described by Paris and Justus (1988). Results from this first long-term pilot operational application of the method are presented. The method is potentially useful for establishing yearly-averaged trends in the radiometric gain of AVHRR Channels. The relatively small data base examined here suggests a precision in the 600 day mean gain of 5 percent or worse, with a significant part of this uncertainty being driven by poor knowlege of the bidirectional reflectance properties of clouds. The results suggest that the method in its present formulation has insufficient precision to be used as a primary method for the measurement of in-orbit gains of reflected-solar radiometers aboard polar orbiting satellites. Intrinsic limitations to the precision and time resolution of the method are discussed, and suggestions are offered for improving the precision of future results.

Abel, Peter↗
NASA NTRS1994

Neural Network Classifies Teleoperation Data

Prototype artificial neural network, implemented in software, identifies phases of telemanipulator tasks in real time by analyzing feedback signals from force sensors on manipulator hand. Prototype is early, subsystem-level product of continuing effort to develop automated system that assists in training and supervising human control operator: provides symbolic feedback (e.g., warnings of impending collisions or evaluations of performance) to operator in real time during successive executions of same task. Also simplifies transition between teleoperation and autonomous modes of telerobotic system.

Fiorini, Paolo↗
NASA NTRS1997

Diagnostic Analyzer for Gearboxes (DAG): User's Guide

This documentation describes the Diagnostic Analyzer for Gearboxes (DAG) software for performing fault diagnosis of gearboxes. First, the user would construct a graphical representation of the gearbox using the gear, bearing, shaft, and sensor tools contained in the DAG software. Next, a set of vibration features obtained by processing the vibration signals recorded from the gearbox using a signal analyzer is required. Given this information, the DAG software uses an unsupervised neural network referred to as the Fault Detection Network (FDN) to identify the occurrence of faults, and a pattern classifier called Single Category-Based Classifier (SCBC) for abnormality scaling of individual vibration features. The abnormality-scaled vibration features are then used as inputs to a Structure-Based Connectionist Network (SBCN) for identifying faults in gearbox subsystems and components. The weights of the SBCN represent its diagnostic knowledge and are derived from the structure of the gearbox graphically presented in DAG. The outputs of SBCN are fault possibility values between 0 and 1 for individual subsystems and components in the gearbox with a 1 representing a definite fault and a 0 representing normality. This manual describes the steps involved in creating the diagnostic gearbox model, along with the options and analysis tools of the DAG software.

Jammu, Vinay B.↗
NASA NTRS1996

Doppler Measurements of the Suns Meridional Flow

Doppler velocity data obtained with the Global Oscillation Network Group (GONG) instruments in Tucson from 1992 August through 1995 April were analyzed to determine the structure and evolution of the Sun's meridional flow. Individual measurements of the flow were derived from line-of-sight velocity images averaged over 17 minutes to remove the p-mode oscillation signal. Typical flow velocities are poleward at approximately 20 m/s, but the results suggest that episodes may occur with much stronger flows. Such variations may help to explain some of the many disparate reports on the strength and structure of the Sun's meridional flow.

Hathaway, David H.↗
NASA NTRS1997

Global Plate Velocities from the Global Positioning System

We have analyzed 204 days of Global Positioning System (GPS) data from the global GPS network spanning January 1991 through March 1996. On the basis of these GPS coordinate solutions, we have estimated velocities for 38 sites, mostly located on the interiors of the Africa, Antarctica, Australia, Eurasia, Nazca, North America, Pacific, and South America plates. The uncertainties of the horizontal velocity components range from 1.2 to 5.0 mm/yr. With the exception of sites on the Pacific and Nazca plates, the GPS velocities agree with absolute plate model predictions within 95% confidence. For most of the sites in North America, Antarctica, and Eurasia, the agreement is better than 2 mm/yr. We find no persuasive evidence for significant vertical motions (less than 3 standard deviations), except at four sites. Three of these four were sites constrained to geodetic reference frame velocities. The GPS velocities were then used to estimate angular velocities for eight tectonic plates. Absolute angular velocities derived from the GPS data agree with the no net rotation (NNR) NUVEL-1A model within 95% confidence except for the Pacific plate. Our pole of rotation for the Pacific plate lies 11.5 deg west of the NNR NUVEL-1A pole, with an angular speed 10% faster. Our relative angular velocities agree with NUVEL-1A except for some involving the Pacific plate. While our Pacific-North America angular velocity differs significantly from NUVEL-1A, our model and NUVEL-1A predict very small differences in relative motion along the Pacific-North America plate boundary itself. Our Pacific-Australia and Pacific- Eurasia angular velocities are significantly faster than NUVEL-1A, predicting more rapid convergence at these two plate boundaries. Along the East Pacific Pise, our Pacific-Nazca angular velocity agrees in both rate and azimuth with NUVFL-1A.

Larson, Kristine M.↗
NASA NTRS2011

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Quattrochi, Dale A.↗
NASA NTRS2011

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Quattrochi, Dale A.↗
NASA NTRS2017

Comparing Eyewitness-Derived Trajectories of Bright Meteors to Instrumentally-Observed Data

The NASA Meteoroid Environment Office (MEO) is often called upon to analyze meteors of public interest observed over the United States. Data from meteor networks are often utilized to accomplish this, as are recordings from the general public. When these methods fail, eyewitness reports are the only resource which can be leveraged. The MEO developed a tool to crudely calculate the trajectories of bright meteors from the eyewitness reports submitted to the American Meteor Society. The tool was tested on eyewitness data for 33 cases and compared to observed data from the NASA All Sky Fireball Network. The tool performed better for cases with more than 75 eyewitness reports than those with fewer than 75, by almost a factor of two across all metrics except for the end height. For these cases, the eyewitness-derived trajectory was about 50 km from the observed trajectory, the radiant was within 15deg, and the speed was within 20% of that observed on average. A description of the tool, example case studies, and general trends are described.

D E Moser↗
NASA NTRSDate not supplied

Hailstorm Analyses and Detection Derived from Current and Historical Satellite Data and Convective Environmental Parameters

We seek to demonstrate the extent to which hailstorms can be detected using a combination of geostationary (GEO) visible and infrared metrics of storm intensity and convective environmental parameters from reanalysis. Hailstorm identifications from low-Earth-orbiting (LEO) passive microwave sensors and maximum expected size of hail (MESH) from ground-based radar serve as a proxy for hail events. Data are analyzed for two warm seasons over the contiguous United States (CONUS). A neural network (NN) is trained to predict hailstorm detection dependent on optimal multi-variate weighting of observed and modeled input. The NN results are then applied to a 15-year Meteosat Second Generation climatology over South Africa to depict where hailstorms are most likely to occur. We also explore the impact of GEO imager resolution on our ability to discriminate hailstorms by matching GOES-13 (4 km) and GOES-16 (2 km) storm intensity metrics against hail characteristics using LEO, MESH, and spotter reports over CONUS during 2017, when both satellites were simultaneously imaging. Such analysis allows us to assess the feasibility of assembling a severe storm climate data record back to GOES-8, in the mid-1990’s. Finer spatial resolution of GOES-16 better resolves the updraft characteristics and intensities that are inherently linked to hail formation; however, GOES-13 can be normalized to achieve comparable detection capability. When intelligently combined with model-derived convective environmental parameters, GEO-derived storm intensity metrics enable high-spatial resolution hail risk assessment at hourly intervals throughout the diurnal cycle anywhere around the world and an improved understanding of hailstorms in the climate system.

Kyle F Itterly↗
NASA NTRSDate not supplied

Onboard Hyperspectral Image Classification via Transfer Learning for Communication-Limited Spacecraft

Employing deep-learning and artificial-intelligence (AI) techniques onboard spacecraft can dramatically improve priority data selection to ensure more effective use of the available downlink. However, deployment of effective deep-learning models requires significant training on the ground, which may not be feasible, due to limited data available in an unexplored environment. Therefore, this research explores building robust classification models for onboard data processing where training data is highly limited using transfer-learning techniques. In this paper, we focus on the use case of hyperspectral imaging for remote sensing, a domain where the high dimensionality of the data from the sensor can rapidly saturate the downlink bandwidth. With this bottleneck, there is an impending need to autonomously and robustly classify data onboard to optimize downlink of high-impact measurements, thus maximizing the scientific utility per bit transmitted to the ground. This paper examines the use of deep neural networks onboard for hyperspectral image classification in a communication-limited scenario to analyze how the models perform with limited training data. The use of transfer learning can ameliorate the issue of poor generalization by transferring features learned from training on a large source dataset for one classification task to the target classification task with limited training data. For two deep-learning models from literature, we compare the accuracy of the models trained using transfer learning to models trained from scratch using a random weight initialization with varying amounts of training data. We demonstrate the feasibility and performance of running inference of the deep-learning models on representative flight-like hardware.

Advanced Avionics, Machine Learning, Data Processi↗
NASA NTRSDate not supplied

Comparing Analysis of Hydrogen Concentration in Astromaterials Nominally Anhydrous Minerals by Multiple SIMS

Secondary Ion Mass Spectrometry (SIMS) is utilized to determine hydrogen (H) concentration in astromaterials nominally anhydrous minerals (NAMs) and their inclusions [e.g., 1]. This data is interpreted to refine the volatile history of planetary bodies. Four instruments are being used to compare H concentration analysis: a large geometry SIMS (The University of Hawaiʻi Cameca IMS 1280), a compact SIMS (Arizona State University (ASU) Cameca IMS 6f), and two Cameca NanoSIMS 50L at ASU and NASA-Johnson Space Center (JSC). Results on the first three instruments are available. Although fundamentally similar, SIMS instruments and their modifications [2] may produce different values or pose advantages for H analysis, especially for shocked samples that are susceptible to contamination filling their fractures. New data from the IMS 1280 is reported, using its microchannel plate (MCP) to image high H signals in grain fractures during pre-sputtering to avoid them as much as possible. Between fractures, 16 OH/ 30 Si was measured with a Cs + 4 nA primary beam, 30 micron spot size, and central ~5x5 micron collection area. First order comparison of H concentration (reported in ppm H 2 O) is achieved on a terrestrial gem quality clinopyroxene (SLP114, 162±12 ppm H 2 O [3]), with 157±7 and 215±40 ppm H 2 O by the IMS 1280 and 6f respectively. SIMS comparison is then extended to analysis of two Martian shergottites: RBT 04262 and NWA 5789. Due to a dense fracture network (< 20 micron) in RBT 04262, only one clinopyroxene hosted glassy inclusion was analyzed (n=6, ≤1 ppm H 2 O), while six olivine grains in NWA 5789 (n=12, ≤ 2 ppm H 2 O) (1s ±0.21) were analyzed. Higher concentrations were obtained for RBT 04262 olivine by the ASU NanoSIMS 50L (up to 350 ppm H 2 O [4]), and IMS 6f (300+ ppm H 2 O, [5]), for which contamination in fractures could not be avoided. Work on the JSC NanoSIMS 50L will further develop the SIMS comparison.

J.-M. Dudley↗