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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 NTRS2014

Interstellar Organics, the Solar Nebula, and Saturn's Satellite Phoebe

The diffuse interstellar medium inventory of organic material (Pendleton et al. 1994, Pendleton Allamandola 2002) was likely incorporated into the molecular cloud in which the solar nebula condensed. This provided the feedstock for the formation of the Sun, major planets, and the smaller icy bodies in the region outside Neptune's orbit (transneptunian objects, or TNOs). Saturn's satellites Phoebe, Iapetus, and Hyperion open a window to the composition of one class of TNO as revealed by the near-infrared mapping spectrometer (VIMS - Visible and Infrared Mapping Spectrometer) on the Cassini spacecraft at Saturn. Phoebe (mean diameter 213 kilometers) is a former TNO now orbiting Saturn. VIMS spectral maps of Phoebe's surface reveal a complex organic spectral signature consisting of prominent aromatic (CH) and aliphatic hydrocarbon (CH2, CH3) absorption bands (3.2-3.6 meters). Phoebe is the source of a huge debris ring encircling Saturn, and from which particles (5-20 meter size) spiral inward toward Saturn. They encounter Iapetus and Hyperion where they mix with and blanket the native H2O ice of those two bodies. Quantitative analysis of the hydrocarbon bands on Iapetus demonstrates that aromatic CH is 10 times as abundant as aliphatic CH2 plus CH3, significantly exceeding the strength of the aromatic signature in interplanetary dust particles, comet particles, and in carbonaceous meteorites (Cruikshank et al. 2013). A similar excess of aromatics over aliphatics is seen in the qualitative analysis of Hyperion and Phoebe itself (Dalle Ore et al. 2012). The Iapetus aliphatic hydrocarbons show CH2/CH3 4, which is larger than the value found in the diffuse ISM (InterStellar Matter - (2-2.5). Insofar as Phoebe is a primitive body that formed in the outer regions of the solar nebula and has preserved some of the original nebula inventory, it can be key to understanding the content and degree of processing of that nebular material. There are other Phoebe-like TNOs that are presently beyond our ability to study in the organic spectral region, but JWST (James Webb Space Telescope) will open that possibility for a number of objects. We now need to explore and understand the connection of this organic-bearing Solar System material to the solar nebula and the inventory of ISM (Interstellar Medium) materials incorporated therein.

Phoebe↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events, and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, enable detection of atmospheric features during daytime operations with a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗
NASA NTRS2022

Ultraviolet Radiation

The lunar surface has a complex plasma environment due to incoming solar wind flux and charged micron-sized dust particles and the presence of solar ultraviolet (UV) radiation. UV resonance fluorescence of solar radiation provides a sensitive detection of major elemental constituents, such as H, H2, O, C, N, and noble gases in the tenuous daytime lunar atmosphere. Photoemission due to the solar UV radiation is the dominating process in the charging environment, creating a photoelectron “sheath.” Such detections were observed by LADEE UV spectrometer and the Apollo 17 UV spectrometer.

Caitlin Ahrens↗
NASA NTRS1973

Environmental control of lunar samples in the Lunar Receiving Laboratory

The contamination controls used in the Lunar Receiving Laboratory during the processing of lunar samples are described. Initially, the lunar sample containers were opened and the material was examined in a vacuum complex with approximated lunar surface conditions. The process of examining and distributing the samples from this vacuum complex was time consuming. During both Apollo 11 and 12 missions portions of the lunar samples were processed for allocation in a small sterile glove box in a dry nitrogena atmosphere. After Apollo 12 a new system was installed based upon the experience gained from the small glove box. The system uses dry nitrogen as an environmental blanket and has the capability of being sterilized and of maintaining this sterility.

Reynolds, M. A.↗
NASA NTRS1991

Application of Hapke photometric model to three geologic surfaces using PARABOLA bidirectional reflection data

The Geologic Remote Sensing Field Experiment (GRSFE) was conducted in July and September of 1989 to collect data with both ground and airborne instrumentation. A major objective of GRSFE was to collect data which could be used to test radiative transfer models for the extraction of composition and textural surface properties from remotely acquired data. Reported here are the initial results from an application of the Hapke photometric model, using data from the Portable Apparatus for Remote Acquisition of Bidirectional Observations of Land and Atmosphere (PARABOLA), a ground based radiometer with three spectral channels. PARABOLA data was collected in the Lunar Crater Volcanic Field in Nevada, specifically from the region of Lunar Lake, a playa. The Hapke model was found to be inadequate for three relatively common geologic surfaces (a clay-rich, hard packed surface with decimeter sized mudcracks; a cobble site, similar to a playa site, but strewn with basaltic cobbles and pebbles; and a surface mantled basalt lava flow). The model is not at fault; rather, the complexity of most geologic surfaces is not accounted for in the initial assumptions.

Shepard, Michael K.↗
NASA NTRS2000

Future Applications Using Return-Pulse Correlation from Imaging Laser Altimeters

The Laser Vegetation Imaging Sensor (LVIS) is an airborne, wide-swath, digitization-only laser altimeter capable of collecting full return waveforms (i.e. echoes) from laser footprints ranging in diameter from 1 to 80 m across up to a 1 km wide data swath. The return waveform can be used to enhance the accuracy of laser ranging and to provide information about the vertical structure of vegetation and topography within each laser footprint. Although extremely small laser footprints (< 1 0 cm diameter) generally return simple, impulse responses to their target surface, larger footprints typically exhibit complex returns representing the diverse vertical distributions of surfaces contained in each footprint. Only a handful of airborne and spaceborne laser altimeters record the return echo or return pulse that is reflected from the Earth's surface (i.e. NASA's LVIS, SLA, VCL, and GLAS laser altimeters). Waveforms are currently interpreted to extract a timing or ranging point or points to represent the mean ground elevation or the vertical height of vegetation. But, recent progress using pulse shape correlation techniques shows promise for a variety of science applications involving change detection of surface topography and vegetation as well as potential for improving data processing by correlating images or crossovers to solve systematic biases. We show example correlation images from LVIS and discuss instrument design implications and potential science applications.

Blair, J. Bryan↗
NASA NTRS2017

Strategies Toward Automation of Overset Structured Surface Grid Generation

An outline of a strategy for automation of overset structured surface grid generation on complex geometries is described. The starting point of the process consists of an unstructured surface triangulation representation of the geometry derived from a native CAD, STEP, or IGES definition, and a set of discretized surface curves that captures all geometric features of interest. The procedure for surface grid generation is decomposed into an algebraic meshing step, a hyperbolic meshing step, and a gap-filling step. This paper will focus primarily on the high-level plan with details on the algebraic step. The algorithmic procedure for the algebraic step involves analyzing the topology of the network of surface curves, distributing grid points appropriately on these curves, identifying domains bounded by four curves that can be meshed algebraically, concatenating the resulting grids into fewer patches, and extending appropriate boundaries of the concatenated grids to provide proper overlap. Results are presented for grids created on various aerospace vehicle components.

overset↗
NASA NTRS1974

Surface topographical effects on the structural growth of thick sputtered metal and alloy coatings

Thick sputtered S-Monel, silver, and 304 stainless steel coatings were deposited on mica and metal substrates with various surface finishes to investigate the structural growth of the coating by scanning electron microscopy. The geometry and the surface structure of the nodules are characterized. Compositional changes within the coating were analyzed by X-ray dispersion microscopy. Defects in the surface finish (i.e., scratches, inclusions, etc.) act as preferential nucleation sites and form isolated and complex nodules and various surface overgrowths in the coating. The nodule boundaries are very vulnerable to chemical etching and these nodules do not disappear after full annealing. Further, they have undesirable effects on mechanical properties; cracks are initiated at the nodules when the coating is stressed by mechanical forces. These effects are illustrated by micrographs. Nodular growth within a coating can be minimized or eliminated by reducing the surface roughness.

Spalvins, T.↗
NASA NTRS1974

Nodular growth in thick-sputtered metallic coatings

Thick-sputtered S-Monel, silver, and 304 stainless steel coatings were deposited on mica and metal substrates with various surface finishes to investigate the nodular growth in the coating by scanning electron microscopy. The geometry and the surface structure of the nodules are characterized. Compositional changes within the coating were analyzed by energy dispersive X-ray analysis. Defects in the surface finish (i.e., scratches, inclusions, etc.), act as preferential nucleation sites and form isolated and complex nodules and various surface overgrowths in the coating. The nodule boundaries are very vulnerable to chemical etching and these nodules do not disappear after full annealing. Further, they have undesirable effects on mechanical properties; cracks are initiated at the nodules when the coating is stressed by mechanical forces. These effects are illustrated by micrographs. Nodular growth within a coating can be minimized or eliminated by increasing the surface smoothness.

Spalvins, T.↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust, appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust, appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Thermal Analysis↗
NASA NTRSDate not supplied

Lunar Latitude and Terrain Radiator Sensitivity Study

The thermal environment on the moon is highly complex and diverse. The lunar surface near the equator develops extreme hot average temperatures during the lunar day due to solar flux vectors that are nearly orthogonal to the surface. The lunar poles have a cold and uniquely complex thermal environment with low solar elevation angles and permanently shadowed regions located just kilometers from some of the most highly illuminated regions of the moon. Likewise, the topography can range from very flat crater basins to dramatically tall features such as mountains and crater rims. Consequently, when sizing the radiators of a lunar surface vehicle, the specific thermal environment found in the targeted landing or deployment zone must be well understood to build robust appropriately scaled thermal control systems. Here described are parametric studies that characterize the sensitivity of lunar radiator performance to lunar terrain and latitude. Heat rejection is calculated for different radiator tilt angles in a variety of terrain environments. Radiator performance as a function of underside thermal condition is also characterized at lunar latitudes ranging from equatorial to polar. Impacts of latitude and terrain on radiator performance are quantified, and regions are identified where the thermal environment is more or less favorable for specific radiator designs.

Lunar Vehicle Radiator↗
NASA NTRS1978

An examination of the relationships between selected ground properties and Landsat MSS data in an area of complex terrain in southern Italy

The paper deals with the method and results of a study which involved an examination of the statistical relationships between selected ground properties and Landsat MSS data, and whose aim was to assess the applicability of Landsat data to surface cover mapping in areas characterized by high-frequency spatial variations of surface cover type over small areas. The results indicate that by systematic ground data collection it is possible to understand the basic relationships between ground properties and Landsat sensor data in areas of complex surface cover and terrain, and to classify the cover types.

Justice, C. O.↗
NASA NTRS2023

NASCAP Surface Charging Tool Development - Nascap-2k Additional Examples

This document consists of examples of the use of Nascap-2k to analyze moderately complex interactions between spacecraft surfaces and the plasma environment. The narrative assumes familiarity with the use of Nascap-2k and the field of spacecraft-environment interactions. Specific results may be slightly different from those given here due to small differences in the geometry, material selection, and version of Nascap-2k.

Charge Plate Analyzer↗