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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

LANDSAT demonstration/application and GIS integration in south central Alaska

Automated geographic information systems were developed for two sites in Southcentral Alaska to serve as tests for both the process of integrating classified LANDSAT data into a comprehensive environmental data base and the process of using automated information in land capability/suitability analysis and environmental planning. The Big Lake test site, located approximately 20 miles north of the City of Anchorage, comprises an area of approximately 150 square miles. The Anchorage Hillside test site, lying approximately 5 miles southeast of the central part of the city, extends over an area of some 25 square miles. Map construction and content is described.

Burns, A. W.↗
DOE OSTI2022

Statistical analysis of S—N type environmental fatigue data of Ni-base alloy welds using weibull distribution

In this study, the probabilistic fatigue life model for Ni-base alloys was developed based on the Weibull distribution using statistical analysis of fatigue data reported in NUREG/CR-6909 and the new fatigue data of Alloy 52M/152 and 82/182. The developed Weibull model can consider right-censored data (i.e., non-failed data) and quantify the improved safety (or reliability) based on the level of failure probability. The overall margin in the current fatigue design limit model (ASME design curve + NUREG/CR-6909 F en model) is similar to that of the Weibull model with a cumulative failure probability of approximately 2.5%. The margin in the current fatigue design limit model demonstrated inconsistencies for the Ni-base alloy weld data, whereas the Weibull model showed a consistent margin. Therefore, the Weibull model can systematically mitigate the excessive safety margin.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Mission Operations Insights

The mission description Polar Operational Environmental Satellites (POES): I) Collect and disseminate worldwide meteorological and environmental data: a) Provide day and night information (AVHRR): 1) cloud cover distribution and type; 2) cloud top temperature; 3) Moisture patterns and ice/snow melt. b) Provide vertical temperature and moisture profiles of atmospheres (HIRS, AMSU, MHS. c) Measure global ozone distribution and solar UV radiation (SBUV). d) Measure proton, electro, and charged particle density to provide solar storm warnings (SEM). d) Collect environmental data (DCS): 1) Stationary platforms in remote locations; 2) Free floating platforms on buoys, balloons, migratory animals. II) Provide Search and Rescue capabilities (SARR, SARP): a) Detection and relay of distress signals. b) Has saved thousands of lives around the world.

Littman, Dave↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1973

Cloud type pattern recognition using environmental satellite data

A classification analysis is conducted concerning the tropical cloud types as remotely sensed in the visual and infrared range by ITOS scanning radiometers. A statistical pattern recognition technique is used to examine the ability of coincident dual-channel and single-channel data to classify four main forms of clouds, including cumulus, stratocumulus, cumulonimbus, and cirrus.

Booth, A. L.↗
NASA NTRS1973

Standard methods for analysis and interpretation of Lidar data for environmental monitoring

Lidar is similar in principle to microwave radar but uses a pulsed laser as the source and an optical telescope as the receiver. Lidar observations of elastic scattering from aerosols and more recently Raman scattering from molecules have been performed in the atmosphere with favorable results. A description of the Lidar technique is provided. Lidar measurements of remote visibility are discussed together with the measurement of remote visibility and the determination of molecular concentrations.

Melfi, S. H.↗
NASA NTRS1979

Use of Landsat and environmental satellite data in evapotranspiration estimation from a wildland area

A remote sensing-aided procedure was applied to the watershed-wide estimation of water loss to the atmosphere (evapotranspiration, ET). The approach involved a spatially referenced databank based on both remotely sensed and ground-acquired information. Physical models for both estimation of ET and quantification of input parameters are specified, and results of the investigation are outlined.

Khorram, S.↗
NASA NTRS1992

Program Handles Environmental-Test Data

S3 Data Acquisition and Control System, (S3DACS) monitors, controls, and records information acquired during tests and presents it in various formats for easy access by large number of users. Results automatically stored. Data used in computations, and selectively presented in tabular, graphical, or electronic form. Reports show current or historical events. Network software written in FoxPro/LAN 1.02 and 80386 Assembler.

De Freitas Bart, Frances↗
NASA NTRS1994

GPS Data, Acquisition, Environmental Effects

Precise geodesy with the Global Positioning System (GPS) emerged in the early 1990s from a decade-long incubation to find vigorous application worldwide.

Global Positioning System (GPS) geodetic receivers↗
NASA NTRS2014

Use of the NASA Giovanni Data System for Geospatial Public Health Research: Example of Weather-Influenza Connection

The NASA Giovanni data analysis system has been recognized as a useful tool to access and analyze many different types of remote sensing data. The variety of environmental data types has allowed the use of Giovanni for different application areas, such as agriculture, hydrology, and air quality research. The use of Giovanni for researching connections between public health issues and Earths environment and climate, potentially exacerbated by anthropogenic influence, has been increasingly demonstrated. In this communication, the pertinence of several different data parameters to public health will be described. This communication also provides a case study of the use of remote sensing data from Giovanni in assessing the associations between seasonal influenza and meteorological parameters. In this study, logistic regression was employed with precipitation, temperature and specific humidity as predictors. Specific humidity was found to be associated (p 0.05) with influenza activity in both temperate and tropical climate. In the two temperate locations studied, specific humidity was negatively correlated with influenza; conversely, in the three tropical locations, specific humidity was positively correlated with influenza. Influenza prediction using the regression models showed good agreement with the observed data (correlation coefficient of 0.50.83).

public health↗
NASA NTRS2016

NASA SNPP SIPS - Following in the Path of EOS

NASA's Earth Science Data Information System (ESDIS) Project has been operating NASA's Suomi National Polar-Orbiting Partnership (SNPP) Science Data Segment (SDS) since the launch in October 2011. At launch, the SDS focused primarily on the evaluation of Sensor Data Records (SDRs) and Environmental Data Records (EDRs) produced by the Joint Polar Satellite System (JPSS), a National Oceanic and Atmosphere Administration (NOAA) Program, as to their suitability for Earth system science. During the summer of 2014, NASA transitioned to the production of standard Earth Observing System (EOS)-like science products for all instruments aboard Suomi NPP. The five Science Investigator-led Processing Systems (SIPS): Land, Ocean, Atmosphere, Ozone, and Sounder were established to produce the NASA SNPP standard Level 1, Level 2, and global Level 3 products developed by the SNPP Science Teams and to provide the products to NASA's Distributed Active Archive Centers (DAACs) for archive and distribution to the user community. The processing, archiving and distribution of data from NASA's Clouds and the Earth's Radiant Energy System (CERES) and Ozone Mapper/Profiler Suite (OMPS) Limb instruments will continue. With the implementation of the JPSS Block 2 architecture and the launch of JPSS-1, the SDS will receive SNPP data in near real-time via the JPSS Stored Mission Data Hub (JSH), as well as JPSS-1 and future JPSS-2 data. The SNPP SIPS will ingest EOS compatible Level 0 data from the EOS Data Operations System (EDOS) element for their data processing, enabling the continuous EOS-SNPP-JPSS Satellite Data Record.

near real time↗
NASA NTRS2012

NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

Estes, Sue↗
NASA NTRS2013

NASA Earth Observation Systems and Applications for Public Health and Air Quality Models and Decisions Support

Health and Air Quality providers and researchers need environmental data to study and understand the geographic, environmental, and meteorological differences in disease. Satellite remote sensing of the environment offers a unique vantage point that can fill in the gaps of environmental, spatial, and temporal data for tracking disease. This presentation will demonstrate the need for collaborations between multi-disciplinary research groups to develop the full potential of utilizing Earth Observations in studying health. Satellite earth observations present a unique vantage point of the earth's environment from space, which offers a wealth of health applications for the imaginative investigator. The presentation is directly related to Earth Observing systems and Global Health Surveillance and will present research results of the remote sensing environmental observations of earth and health applications, which can contribute to the public health and air quality research. As part of NASA approach and methodology they have used Earth Observation Systems and Applications for Public Health and Air Quality Models to provide a method for bridging gaps of environmental, spatial, and temporal data for tracking disease. This presentation will provide an overview of projects dealing with infectious diseases, water borne diseases and air quality and how many environmental variables effect human health. This presentation will provide a venue where the results of both research and practice using satellite earth observations to study weather and it's role in public health research.

Estes, Sue↗