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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

GC51D-0831: A Study of the Impact of Dams on Sediment Retention in the Mekong River Basin

Dam construction in the Mekong Basin has many cascading effects on the ecology, economy, and hydrology of the surrounding region. The focus of this study is to utilize the Soil Water Assessment Tool (SWAT), developed at Texas A & M, a rainfall-runoff hydrologic model to determine change in sedimentation in the Mekong Basin after the construction of dams. This study uses land cover land use and reservoir datasets created by the NASA SERVIR-Mekong Regional Land Cover Monitoring System and Dam Inundation Mapping Tool as inputs into the model. The study also builds on the capabilities of the SWAT model by using the sediment trapping efficiency (STE) equation from Brune (1953), rewritten by Kummu & Varis (2007), to calculate STE of dams and estimate change in sediment concentration downstream. The outputs from this study can be used to inform dam operation policies, study the correlation between dams and delta subsidence, and study the impact of dams on river fisheries, which are all pressing issues in the Mekong region.

Earth scienc↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO2. The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
NASA NTRSDate not supplied

Improving Access to the GEOS Composition Forecast Model with API Development and Ingestion into Google Earth Engine

The GEOS Composition Forecast (GEOS-CF) model produces forecast and historical estimates of atmospheric composition and meteorology fields, which provide useful insight into air quality issues and events. In a year for which Canadian wildfires created adverse air quality conditions in the eastern United States, access to model fields such as PM2.5 are in high demand. The GEOS-CF team at the NASA Global Modeling and Assimilation Office (GMAO) first developed in-house solutions to improve data access via the CF API, and recently partnered with Google to ingest a collated set of model diagnostics into the Google Earth Engine (GEE) data repository. GEOS-CF model output is also being ingested into AWS storage. Creating these various open access points to GEOS-CF model diagnostics provides the public with an opportunity to easily interact with air quality information. Users are able to use a temporally consistent global grid of air quality fields in machine learning applications, mapping tools, and data informatics. Hosting GEOS-CF forecasts and the historical timeseries of these chemistry and meteorology fields in GEE allows users to create dynamic JavaScript-based air quality applications in the GEE code editor. GEOS-CF users can also access the model output via the GEE Python application programming interface (API), making it easy to perform various analyses with Python. This presentation will show two examples of accessing the GEOS-CF model through GEE. The first is an example application made in the GEE code editor which allows users to view time series plots and downscaled maps of surface level NO 2 . The second example exhibits using the GEE Python API to create a machine learning model to temporally gap-fill between air quality observations. These examples are an introduction to the many possible benefits of having open access to the GEOS-CF model through multiple platforms.

Callum Wayman↗
NASA NTRSDate not supplied

High-Intensity Radiated Field (HIRF) Map - An Avoidance Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in similar airspace to Transport Category Rotorcraft, thereby requiring them to meet the most severe requirements for High Intensity Radiated Fields (HIRF) certification. The environment is severe for rotorcraft, much more so than for fixed-wing aircraft, due to lower altitude operations, potentially exposing the vehicles to close and direct view of high-power transmitters on the ground. High-level HIRF exposure potentially leads to avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF will be a significant barrier to size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel approach to HIRF protection, which reduces costs by testing and certifying vehicles to a “vehicle tolerance level” that is lower than required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources, calculated based on the vehicle's tolerance level and transmitter characteristics such as transmit power, antenna beamwidth, and direction. Tailored maps are developed, identifying transmitters and avoidance zones within an operating area or along a flight path, allowing for restricted vehicle operations. The HIRF avoidance zones could be smaller for vehicles with higher tolerance levels, enabling them to operate closer to transmitters. Transmitter data can be extracted from regulatory databases like the FCC and NOAA. A map tool is developed in Matlab to calculate and plot HIRF avoidance zones from transmitters in FCC and NOAA databases as proof of concept. Illustrations are presented for AM/FM/TV transmitters, communication satellite dishes, and weather radars. Also illustrated are HIRF zones for smaller transmitters, including land-mobile radios, pagers, microwave links, and cellular towers. An example of flight planning around the transmitters is presented. This method is a substantial deviation from the standard approach and involves slightly higher flight-planning complexity, but the potential cost savings are significant. Future AAM/UAM/UAS aeronautical charts could include these new HIRF avoidance zones.

HIRF↗
NASA NTRSDate not supplied

High-Intensity Radiated Field (HIRF) Map - An Avoidance Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in similar airspace to Transport Category Rotorcraft, thereby requiring them to meet the most severe requirements for HighIntensity Radiated Fields (HIRF) certification. The environment is severe for rotorcraft, much more so than for fixed-wing aircraft, due to lower altitude operations, potentially exposing the vehicles to close and direct view of high-power transmitters on the ground. High-level HIRF exposure potentially leads to avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF will be a significant barrier to size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel approach to HIRF protection, which reduces costs by testing and certifying vehicles to a “vehicle tolerance level” that is lower than required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources, calculated based on the vehicle's tolerance level and transmitter characteristics such as transmit power, antenna beamwidth, and direction. Tailored maps are developed, identifying transmitters and avoidance zones within an operating area or along a flight path, allowing for restricted vehicle operations. The HIRF avoidance zones could be smaller for vehicles with higher tolerance levels, enabling them to operate closer to transmitters. Transmitter data can be extracted from regulatory databases like the FCC and NOAA. A map tool is developed in Matlab to calculate and plot HIRF avoidance zones from transmitters in FCC and NOAA databases as proof of concept. Illustrations are presented for AM/FM/TV transmitters, communication satellite dishes, and weather radars. Also illustrated are HIRF zones for smaller transmitters, including land-mobile radios, pagers, microwave links, and cellular towers. An example of flight planning around the transmitters is presented. This method is a substantial deviation from the standard approach and involves slightly higher flight-planning complexity, but the potential cost savings are significant. Future AAM/UAM/UAS aeronautical charts could include these new HIRF avoidance zones.

HIRF↗
NASA NTRSDate not supplied

Celestial Mapping System for Lunar Surface Mapping and Analytics

Celestial Mapping System (CMS) is a software platform to generate virtual 3D globe for celestial bodies within our solar system. Various layers are built on top of the virtual globe to provide visualization of high resolution imagery, enable precise measurements, build analytical capabilities and broad range of functionalities to assist planetary scientists and mission planners. CMS is built using OpenJDK 11 and will run on a wide variety of platforms such as Linux, Windows, OSX, etc. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The present focus of CMS is on developing lunar mapping tool kits to provide features such as - 3D first person view with zoom and navigational capabilities, realistic terrain visualization based on LRO data, measurement tools, Apollo landing site annotations, stereoscopic view, elevation profiles, line of sight analysis and many more. The application is developed to provide situational and domain awareness on Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on Lunar surface. CMS utilizes NASA WorldWind Java library and OpenGL to achieve high-performance rendering of data and measurements, and also adheres to OGC standards. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. Nomenclature is pulled from USGS Moon IAU2000 database, and lunar parameters are based of the standardized IAU2000 Moon ellipsoid. GDAL (Geospatial Data Abstraction Library) was used to modify and test the accuracy of datasets before integrating into the application. Our high-resolution global elevation model was compared with the LRO LOLA DEM elevation values and tested to ensure accuracy. Celestial Mapping System has several potential use cases for NASA including subsurface lava tubes visualization and analysis, soil analysis, resource visualization and representation on 3D globe.

GIS system↗
NASA NTRS1972

Cartographic application of ERTS imagery

There are no author-identified significant results in this report. Results of a quick look of selected ERTS-1 imagery with respect to cartographic applications and products are presented. The term cartographic is applied to graphics that have been related to an accepted reference figure of the earth within a prescribed degree of accuracy. The results are presented in the form of figures covering: (1) nongeometric relative image quality; (2) geometric properties (preliminary); (3) first phase photoimage products; (4) intermediate phase photoimage products; (5) optimum phase orthophotoquad products; and (6) cartographic applications. Because of its unique vantage point of 920 km, ERTS-1 will be a powerful mapping tool by providing extensive and continuous up-to-date data.

Colvocoresses, A. P.↗
NASA NTRS1973

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. Two new, as yet unfinished vegetation maps are presented. These tend further to substantiate the belief that ERTS-1 imagery is a valuable mapping tool. Newly selected scenes show that vegetation interpretations can be refined through use of non-growing season imagery, particularly through the different spectral characteristics of vegetation lacking foliage and through the effect of vegetation structure on apparent snow cover. Scenes now are available for all test area north of the Alaska Range except Mt. McKinley National Park. No support was obtained for the hypothesis that similar interband ratios, from two areas apparently different spectrally because of different sun angles, would indicate similar surface features. However, attempts to test this hypothesis have so far been casual.

Anderson, J. H.↗
NASA NTRS1984

Industrial use of land observation satellite systems

The principal industrial users of land observation satellite systems are the geological industries; oil/gas, mining, and engineering/environmental companies. The primary system used is LANDSAT/MSS. Currently, use is also being made of the limited amounts of SKYLAB photography, SEASAT and SIR-A radar, and the new LANDSAT/TM data available. Although considered experimental, LANDSAT data is now used operationally by several hundred exploration and engineering companies worldwide as a vastly improved geological mapping tool to help direct more expensive geophysical and drilling phases, leading to more efficient decision-making and results. Future needs include global LANDSAT/TM; higher spatial resolution; stereo and radar; improved data handling, processing distribution and archiving systems, and integrated geographical information systems (GIS). For a promising future, governments must provide overall continuity (government and/or private sector) of such systems, insure continued government R and D, and commit to operating internationally under the civil Open Skies policy.

Henderson, F. B., III↗
NASA NTRS1991

Program Generates Images Of Solid Surfaces

Solid Surface Modeler (SSM) computer program generates three-dimensional computer models of solid surfaces for use in visual analysis and animation. Provides advanced functions, including Constructive Solid Geometry, Skin Construction, Tube Construction, Material Property Editing, and Texture Map Tools. Allows user to change such attributes as color, reflectivity, smoothing, and position of object easily. Model saved in ASCII or binary format for use in another program or saved in edit format for reloading in SSM. Written in standard C.

Goza, Sharon P.↗
NASA NTRS1991

Supercomputing '91; Proceedings of the 4th Annual Conference on High Performance Computing, Albuquerque, NM, Nov. 18-22, 1991

Various papers on supercomputing are presented. The general topics addressed include: program analysis/data dependence, memory access, distributed memory code generation, numerical algorithms, supercomputer benchmarks, latency tolerance, parallel programming, applications, processor design, networks, performance tools, mapping and scheduling, characterization affecting performance, parallelism packaging, computing climate change, combinatorial algorithms, hardware and software performance issues, system issues. (No individual items are abstracted in this volume)

Source record↗
NASA NTRS1993

Evaluation of infrared emission spectroscopy for mapping the Moon's surface composition from lunar orbit

Infrared thermal emission spectroscopy is evaluated for its possible application to compositional mapping of the Moon's surface from lunar orbit. Principles of the mid-IR (approximately 4-25 microns) technique, previous lunar ground-based observations, and laboratory studies of Moon samples are reviewed and summarized. A lunar thermal emission spectrometer experiment is described, patterned after a similar instrument on the Mars Observer spacecraft. Thermal emission spectrometry from a polar-orbiting lunar spacecraft could provide a valuable mapping tool to aid in exploration for lunar resources and help provide understanding of the origin of the Moon and history of lunar surface processes.

Nash, Douglas B.↗
NASA NTRS2002

Geometric Comparisons of Selected Small Topographically Fresh Volcanoes in the Borealis and Elysium Planitia Volcanic Fields, Mars: Implications for Eruptive Styles

MOLA (Mars Orbiter Laser Altimeter) data from small, topographically fresh volcanoes from the Elysium and Borealis regions were gridded and analyzed using GMT (Generic Mapping Tools) programs. Results compare eruptive styles of the two regions, and draw conclusions about the different volcanic regions. Additional information is contained in the original extended abstract.

Taylor, K.↗
NASA NTRS2005

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

Sullivan, Dana↗
NASA NTRS2005

Quantitative Electron Probe Microanalysis: State of the Art

Quantitative electron-probe microanalysis (EPMA) has improved due to better instrument design and X-ray correction methods. Design improvement of the electron column and X-ray spectrometer has resulted in measurement precision that exceeds analytical accuracy. Wavelength-dispersive spectrometer (WDS) have layered-dispersive diffraction crystals with improved light-element sensitivity. Newer energy-dispersive spectrometers (EDS) have Si-drift detector elements, thin window designs, and digital processing electronics with X-ray throughput approaching that of WDS Systems. Using these systems, digital X-ray mapping coupled with spectrum imaging is a powerful compositional mapping tool. Improvements in analytical accuracy are due to better X-ray correction algorithms, mass absorption coefficient data sets,and analysis method for complex geometries. ZAF algorithms have ban superceded by Phi(pz) algorithms that better model the depth distribution of primary X-ray production. Complex thin film and particle geometries are treated using Phi(pz) algorithms, end results agree well with Monte Carlo simulations. For geological materials, X-ray absorption dominates the corretions end depends on the accuracy of mass absorption coefficient (MAC) data sets. However, few MACs have been experimentally measured, and the use of fitted coefficients continues due to general success of the analytical technique. A polynomial formulation of the Bence-Albec alpha-factor technique, calibrated using Phi(pz) algorithms, is used to critically evaluate accuracy issues and can be also be used for high 2% relative and is limited by measurement precision for ideal cases, but for many elements the analytical accuracy is unproven. The EPMA technique has improved to the point where it is frequently used instead of the petrogaphic microscope for reconnaissance work. Examples of stagnant research areas are: WDS detector design characterization of calibration standards, and the need for more complete treatment of the continuum X-ray fluorescence correction.

Carpernter, P. K.↗
NASA NTRS2013

Scheduling Operations for Massive Heterogeneous Clusters

High-performance computing (HPC) programming has become increasingly difficult with the advent of hybrid supercomputers consisting of multicore CPUs and accelerator boards such as the GPU. Manual tuning of software to achieve high performance on this type of machine has been performed by programmers. This is needlessly difficult and prone to being invalidated by new hardware, new software, or changes in the underlying code. A system was developed for task-based representation of programs, which when coupled with a scheduler and runtime system, allows for many benefits, including higher performance and utilization of computational resources, easier programming and porting, and adaptations of code during runtime. The system consists of a method of representing computer algorithms as a series of data-dependent tasks. The series forms a graph, which can be scheduled for execution on many nodes of a supercomputer efficiently by a computer algorithm. The schedule is executed by a dispatch component, which is tailored to understand all of the hardware types that may be available within the system. The scheduler is informed by a cluster mapping tool, which generates a topology of available resources and their strengths and communication costs. Software is decoupled from its hardware, which aids in porting to future architectures. A computer algorithm schedules all operations, which for systems of high complexity (i.e., most NASA codes), cannot be performed optimally by a human. The system aids in reducing repetitive code, such as communication code, and aids in the reduction of redundant code across projects. It adds new features to code automatically, such as recovering from a lost node or the ability to modify the code while running. In this project, the innovators at the time of this reporting intend to develop two distinct technologies that build upon each other and both of which serve as building blocks for more efficient HPC usage. First is the scheduling and dynamic execution framework, and the second is scalable linear algebra libraries that are built directly on the former.

Humphrey, John↗
NASA NTRS2017

Addressing Scalability While Feature Requests Persist. A Look at NASA Worldview's New Features and Their Implementation

Worldview is a high-traffic web mapping application created using the JavaScript mapping library, OpenLayers. This presentation will primarily focus on three new features: A wrapping component that seamlessly shows satellite imagery over the dateline where most maps either stop or wrap the imagery of the same date. An animation feature that allows users to select date ranges over which they can animate. An A/B comparison feature that gives users the power to compare imagery between dates and layers. In response to an increasingly large codebase caused by ongoing feature requests, Worldview is transitioning to a smaller core codebase comprised of external reusable modules. When creating a module with the intention of having someone else reuse it for a different task, one inherently starts generating code that is easier to read and easier to maintain. This presentation will show demos of these features and cover development techniques used to create them. Worldview is a web mapping tool used for education, research, and disaster response. We consume 600+ Imagery products and support time-critical application areas such as wildfire management, air quality measurements, and flood monitoring.

Reusability↗