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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 163 records · Page 9

A Search for Short-Period Accreting Pulsars with BATSE

Accreting X-ray pulsar systems can be detected and monitored by the BATSE Pulsar Monitor at full sensitivity only above the Nyquist period of 2.048 s, since it uses the DISCLA data type. Systems with shorter periods than 2 s can be observed, but with a reduced sensitivity, since only the aliased power is measured. While persistent sources in the period range below that have been found by earlier spacecraft, transient systems may still be undiscovered, due to limited time coverage of the galactic plane with all-sky instruments. BATSE data with a time resolution of 31 ms (PSR single-sweep mode) has been collected for four energy channels spanning 20-50 keV , at scheduled times for particular detectors and detector combinations which view the galactic plane. The data spans Nov 1993 to present, with a typical exposure of 15000 s per day to approximately 1/8 of the plane. An accelerated FFT-based search is in progress on these data. Data are segmented into approximately 300 second intervals, barycentered for 3 possible source directions spaced by 30 degrees about the detector normal, with the time series accelerated for each of 15 steps, each spaced by 5 x 10(exp -5). To avoid loss of coherence due to system orbital velocities, FFTs are averaged over each 1/4 day interval separately. Results of this search are presented, including examples of detection of Her X-1, Cen X-3, and other pulsars.

Wilson, R. B.↗

Multi-Sensor Characterization of the Boreal Forest: Initial Findings

Results are presented in an initial apriori knowledge approach toward using complementary multi-sensor multi-temporal imagery in characterizing vegetated landscapes over a site in the Boreal Ecosystem-Atmosphere Study (BOREAS). Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data were segmented using multiple endmember spectral mixture analysis and binary decision tree approaches. Individual date/sensor land cover maps had overall accuracies between 55.0% - 69.8%. The best eight land cover layers from all dates and sensors correctly characterized 79.3% of the cover types. An overlay approach was used to create a final land cover map. An overall accuracy of 71.3% was achieved in this multi-sensor approach, a 1.5% improvement over our most accurate single scene technique, but 8% less than the original input. Black spruce was evaluated to be particularly undermapped in the final map possibly because it was also contained within jack pine and muskeg land coverages.

Reith, Ernest↗

Effects of Daily Centrifugation on Segmental Fluid Distribution in Bed-rested Subjects

The effect of daily centrifugation on segmental fluid distribution have been studied during 21 days of 6 degree head down bedrest. One group (N=7) underwent no countermeasure while the other (N=8) received a daily, one hour, dose (2.5 gz at the foot, decreasing to 1.0 gz at the heart) of artificial gravity (AG) training on the Johnson Space Center short radius centrifuge. Fluid shifts of thoracic(VTO), abdominal (VAB), thigh (VTH), and calf (VCA) regions were measured by the tetrapolar segmental body impedance technique. Untrained subjects reduced their total volume from 18.9 plus or minus 0.5L to 17.9 plus or minus 0.9L (MN plus or minus SE, P less than 0.05) while trained subjects maintained their total volume. In untrained, control, subjects after bed rest, there was a trend toward reduced volume in all segments, with significant reductions in thigh and calf (fig, P less than 0.05). Trained subjects maintained volume in all segments. Our data indicate that artificial gravity treatment counteracts bed rest-induced hypovolemia.

Diedrich, Andre↗

GPM Microwave Imager Engineering Model Results

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (NASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dualfrequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element ofGPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

Newell, David↗

GPM Microwave Imager Design, Predicted Performance and Status

The Global Precipitation Measurement (GPM) Microwave Imager (GMI) Instrument is being developed by Ball Aerospace and Technology Corporation (BATC) for the GPM program at NASA Goddard. The Global Precipitation Measurement (GPM) mission is an international effort managed by the National Aeronautics and Space Administration (t.JASA) to improve climate, weather, and hydro-meteorological predictions through more accurate and more frequent precipitation measurements. The GPM Microwave Imager (GMI) will be used to make calibrated, radiometric measurements from space at multiple microwave frequencies and polarizations. GMI will be placed on the GPM Core Spacecraft together with the Dual-frequency Precipitation Radar (DPR). The DPR is two-frequency precipitation measurement radar, which will operate in the Ku-band and Ka-band of the microwave spectrum. The Core Spacecraft will make radiometric and radar measurements of clouds and precipitation and will be the central element of GPM's space segment. The data products from GPM will provide information concerning global precipitation on a frequent, near-global basis to meteorologists and scientists making weather forecasts and performing research on the global energy and water cycle, precipitation, hydrology, and related disciplines. In addition, radiometric measurements from GMI and radar measurements from the DPR will be used together to develop a retrieval transfer standard for the purpose of calibrating precipitation retrieval algorithms. This calibration standard will establish a reference against which other retrieval algorithms using only microwave radiometers (and without the benefit of the DPR) on other satellites in the GPM constellation will be compared.

Krimchansky, Sergey↗

NASA Tech Briefs, June 2006

Topics covered include: Magnetic-Field-Response Measurement-Acquisition System; Platform for Testing Robotic Vehicles on Simulated Terrain; Interferometer for Low-Uncertainty Vector Metrology; Rayleigh Scattering for Measuring Flow in a Nozzle Testing Facility; "Virtual Feel" Capaciflectors; FETs Based on Doped Polyaniline/Polyethylene Oxide Fibers; Miniature Housings for Electronics With Standard Interfaces; Integrated Modeling Environment; Modified Recursive Hierarchical Segmentation of Data; Sizing Structures and Predicting Weight of a Spacecraft; Stress Testing of Data-Communication Networks; Framework for Flexible Security in Group Communications; Software for Collaborative Use of Large Interactive Displays; Microsphere Insulation Panels; Single-Wall Carbon Nanotube Anodes for Lithium Cells; Tantalum-Based Ceramics for Refractory Composites; Integral Flexure Mounts for Metal Mirrors for Cryogenic Use; Templates for Fabricating Nanowire/Nanoconduit- Based Devices; Measuring Vapors To Monitor the State of Cure of a Resin; Partial-Vacuum-Gasketed Electrochemical Corrosion Cell; Theodolite Ring Lights; Integrating Terrain Maps Into a Reactive Navigation Strategy; Reducing Centroid Error Through Model-Based Noise Reduction; Adaptive Modeling Language and Its Derivatives; Stable Satellite Orbits for Global Coverage of the Moon; and Low-Cost Propellant Launch From a Tethered Balloon

Source record↗

International Space Station Mechanisms and Maintenance Flight Control Documentation and Training Development

International Space Station (ISS) crew and flight controller training documentation is used to aid in training operations. The Generic Simulations References SharePoint (Gen Sim) site is a database used as an aid during flight simulations. The Gen Sim site is used to make individual mission segment timelines, data, and flight information easily accessible to instructors. The Waste and Hygiene Compartment (WHC) training schematic includes simple and complex fluid schematics, as well as overall hardware locations. It is used as a teaching aid during WHC lessons for both ISS crew and flight controllers. ISS flight control documentation is used to support all aspects of ISS mission operations. The Quick Look Database and Consolidated Tool Page are imagery-based references used in real-time to help the Operations Support Officer (OSO) find data faster and improve discussions with the Flight Director and Capsule Communicator (CAPCOM). A Quick Look page was created for the Permanent Multipurpose Module (PMM) by locating photos of the module interior, labeling specific hardware, and organizing them in schematic form to match the layout of the PMM interior. A Tool Page was created for the Maintenance Work Area (MWA) by gathering images, detailed drawings, safety information, procedures, certifications, demonstration videos, and general facts of each MWA component and displaying them in an easily accessible and consistent format. Participation in ISS mechanisms and maintenance lessons, mission simulation On-the-Job Training (OJT), and real-time flight OJT was used as an opportunity to train for day-to-day operations as an OSO, as well as learn how to effectively respond to failures and emergencies during mission simulations and real-time flight operations.

Daugherty, Colin C.↗

The Joint Polar Satellite System (JPSS) Program's Algorithm Change Process (ACP): Past, Present and Future

The Joint Polar Satellite System (JPSS) Program Office is the supporting organization for the Suomi National Polar Orbiting Partnership (S-NPP) and JPSS-1 satellites. S-NPP carries the following sensors: VIIRS, CrIS, ATMS, OMPS, and CERES with instruments that ultimately produce over 25 data products that cover the Earths weather, oceans, and atmosphere. A team of scientists and engineers from all over the United States document, monitor and fix errors in operational software code or documentation with the algorithm change process (ACP) to ensure the success of the S-NPP and JPSS 1 missions by maintaining quality and accuracy of the data products the scientific community relies on. This poster will outline the programs algorithm change process (ACP), identify the various users and scientific applications of our operational data products and highlight changes that have been made to the ACP to accommodate operating system upgrades to the JPSS programs Interface Data Processing Segment (IDPS), so that the program is ready for the transition to the 2017 JPSS-1 satellite mission and beyond.

Joint Polar Satellite System↗

Suomi-NPP VIIRS Day-Night Band On-Orbit Calibration and Performance

The Suomi national polar-orbiting partnership Visible Infrared Imaging Radiometer Suite (VIIRS) instrument has successfully operated since its launch in October 2011. The VIIRS day-night band (DNB) is a panchromatic channel covering wavelengths from 0.5 to 0.9 microns that is capable of observing Earth scenes during both daytime and nighttime at a spatial resolution of 750 m. To cover the large dynamic range, the DNB operates at low-, middle-, and high-gain stages, and it uses an on-board solar diffuser (SD) for its low-gain stage calibration. The SD observations also provide a means to compute the gain ratios of low-to-middle and middle-to-high gain stages. This paper describes the DNB on-orbit calibration methodology used by the VIIRS characterization support team in supporting the NASA Earth science community with consistent VIIRS sensor data records made available by the land science investigator-led processing systems. It provides an assessment and update of the DNB on-orbit performance, including the SD degradation in the DNB spectral range, detector gain and gain ratio trending, and stray-light contamination and its correction. Also presented in this paper are performance validations based on Earth scenes and lunar observations, and comparisons to the calibration methodology used by the operational interface data processing segment.

Chen, Hongda↗

Towards Characterizing the Variability in the Loading Demands of an Unmanned Aerial Vehicle

This paper presents a computational methodology to characterize and quantify the variability in the power demands during the take-off of an unmanned aerial vehicle (UAV). A lithium-ion battery-based power system is used to power the unmanned aerial vehicle, and the capabilities of the unmanned aerial vehicle are driven by the amount of charge in this battery. In order to design the power system, it is necessary to analyze the power and charge requirements of the UAV. This paper focuses on the take-off segment, and aims to quantify the amount of charge that is required for this particular segment. Sparse data is available through different flight tests and this data is used to analyze the flight profile and the charge requirement during take-off. The amount of charge required for take-off depends on several factors that are not only variable but cannot be controlled in reality, and hence, the entire flight profile and the corresponding charge requirement are variable in nature. The information available through flight tests is converted into multi-dimensional sparse data and a new method is developed in this paper for variability characterization using multi-dimensional sparse data. This analysis is useful for prognostics and health management where it is necessary to anticipate future charge requirements in order to compute the end-of-discharge of the battery, and hence, the remaining useful life of the power system.

unmanned aerial vehicle↗

NOAA-20 Visible Infrared Imaging Radiometer Suite day–night band on-orbit calibration and performance

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) instrument has been successfully operating on orbit since November 28, 2017. The day–night band (DNB) onboard NOAA-20 VIIRS is a panchromatic channel covering wavelengths from 0.5 to 0.9 μm, capable of observing the Earth scene in visible/near-infrared spectral range at a spatial resolution of 750 m. The DNB operates at low-, mid-, or high-radiometric gain stages, and it uses an onboard solar diffuser (SD) panel for low-gain stage calibration. The SD observations also provide a means to compute gain ratios between low-to-mid and mid-to-high-gain stages. With their large dynamic range and high sensitivity, the DNB detectors can make observations during both daytime and nighttime. We provide an assessment of the DNB on-orbit performance and behavior in the first two-year mission period and beyond. The calibration methodology used by the VIIRS Characterization Support Team in support of the NASA Earth science community has been described. The trending of on-board calibrators dark-offsets, SD gains, and gain ratios, and signal-to-noise ratio at minimum radiance have been analyzed, especially during key events such as the nadir and cryocooler doors opening. Furthermore, we performed intercomparison studies between Suomi National Polar-orbiting Partnership and NOAA-20 instruments and evaluated DNB radiometric calibration and characterization, including the SD degradation, detector gains, gain ratios, and straylight correction, as well as the calibration comparison between the NOAA Interface Data Processing Segment look-up-tables and our delivery results.

VIIRS↗

SNPP VIIRS Day Night Band: Ten Years of On-Orbit Calibration and Performance

Aboard the polar-orbiting SNPP satellite, the VIIRS instrument has been in operation since launch in October 2011. It is a visible and infrared radiometer with a unique panchromatic channel capability designated as a day-night band (DNB). This channel covers wavelengths from 0.5 to 0.9 µm and is designed with a near-constant spatial resolution for Earth observations 24 h a day. The DNB operates at 3 gain stages (low, middle, and high) to cover a large dynamic range. An onboard solar diffuser (SD) is used for calibration in the low gain stage, and to enable the derivation of gain ratios between the different stages. In this paper, we present the SNPP VIIRS DNB calibration performed by the NASA VIIRS characterization support team (VCST). The DNB calibration algorithms are described to generate the calibration coefficient look up tables (LUTs) for the latest NASA Level 1B Collection 2 products. We provide an evaluation of DNB on-orbit calibration performance. This activity supports the NASA Earth science community by delivering consistent VIIRS sensor data products via the Land Science Investigator-led Processing Systems, including the SD degradation applied for DNB calibrations in detector gain and gain ratio trending. The DNB stray light contamination and its correction are highlighted. Performance validations are presented using comparisons to the calibration methods employed by NOAA’s operational Interface Data Processing Segment. Further work on stray light corrections is also discussed.

VIIRS↗

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗

Segmentation of computer-classified Landsat multispectral scanner data into spatially-connected regions of elk habitat components

Segmentation of computer-classified Landsat multispectral data into spatially-connected regions of ground cover is described. Sorting and hash addressing, techniques commonly used for ordering and searching data records keyed by attributes, are the basis for the region identification and extraction. An example based on the use of spatial regions for evaluating elk habitat components is outlined.

Murray, R.↗

LANDSAT-D program. Volume 2: Ground segment

Raw digital data, as received from the LANDSAT spacecraft, cannot generate images that meet specifications. Radiometric corrections must be made to compensate for aging and for differences in sensitivity among the instrument sensors. Geometric corrections must be made to compensate for off-nadir look angle, and to calculate spacecraft drift from its prescribed path. Corrections must also be made for look-angle jitter caused by vibrations induced by spacecraft equipment. The major components of the LANDSAT ground segment and their functions are discussed.

Source record↗

Classification of multifrequency multilook synthetic aperture radar data

A technique for segmentation of multifrequency multilook intensity synthetic aperture radar (SAR) data into regions of homogeneous and similar backscatter characteristics is presented. Two statistical models, one for the multifrequency multilook SAR intensities and the other for the distribution of the region labels, are combined to obtain the a posteriori probability distribution function of the region labels given the multifrequency speckled intensities. As the maximization of the posterior distribution is computationally intensive, a suboptimal technique for region labeling is proposed. Several examples using both simulated and real multifrequency multilook imagery are given to illustrate the performance of the algorithm.

Rignot, Eric↗