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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

JPSS-1 VIIRS Version 2 At-Launch Relative Spectral Response Characterization and Performance

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Chris Moeller↗
NASA NTRSDate not supplied

Natural Language Processing for Extracting Rich Disease Data Aligned To Satellite Meteorological Data

Global climate change is redefining our understanding of how diseases spread. In Sri Lanka, vector-borne diseases such as dengue fever, encephalitis, and leptospirosis historically surged during the monsoon seasons when temperatures were high enough for mosquito eggs to hatch. Unfortunately, due to rising temperatures and more erratic rainfall patterns, mosquito eggs can now hatch year-round and are increasingly unpredictable, leading to an alarmingly increasing number of hospitalizations and deaths. More data is needed to adapt our response to these diseases in an increasingly warmer world. In the contemporary landscape, a wealth of disease information is available, yet accessibility remains limited due to unstructured data formats such as PDFs. Therefore, converting unstructured disease reports into structured formats is necessary for effectively leveraging data. This paper introduces a comprehensive framework for collecting unstructured disease reports and transforming them into analyzable formats. By creating separate models tailored to each data format, we can ensure accuracy compared to general models. These straightforward models enhance accessibility and empower other researchers to use our tools. The returned structured data can then be harnessed for analysis, statistical purposes, and informing evidence-based public health interventions, thus facilitating more informed decision-making in healthcare. We deploy this framework to produce geospatial data for Sri Lanka and Brazil for many different conditions and align these data with satellite environmental data, providing for the first time a structured, aligned powerful dataset for disease modeling.

Open Source Open Science↗
NASA NTRS2012

Asthma and Air Quality in the Presence of Fires - A Foundation for Public Health Policy in Florida

Outdoor air quality and its associated impacts on respiratory problems in Florida are of public health significance. Air quality in Florida can be poor during the extended wildfire season, threatening persons with compromised respiratory systems each year. Studies have demonstrated that particulate matter, which is generally elevated in the vicinity of wildfires, is associated with increases in hospital admissions and occurrences of acute asthma exacerbations. However, few studies have examined the modifying effect of socio-demographic characteristics of cities or regional areas on the relationship between air quality and health outcomes. In an ongoing university/multi-agency project, asthma hospital/emergency room (patient) data are being used to create a health outcome indicator of human response to environmental air quality. Environmental data are derived from satellite measurements, with special attention being given to the effect of wildfires and prescribed burns on air quality. This presentation will focus on the environmental data sets particulate matter, location of fires, smoke plumes that are being collected and processed for linkage with health data. After this linkage has been performed, space-time models of asthma rates as a function of air quality data and socio-demographic variables will be developed and validated. The Florida Department of Health (FDOH) will work with county health department staff and representatives from the medical community to establish a protocol with triggers for issuing public health advisories/alerts based on the developed and validated health outcome indicators. From this effort, a science-based policy for issuing public health advisories/alerts for asthma relating to air quality will be developed, giving FDOH the ability to (1) predict, with stated levels of uncertainty, case load of hospital admissions based on air quality, (2) reduce asthma exacerbations by forewarning asthmatics to limit outside activities on poor air quality days, (3) apply management practices on the rates of hospital/emergency room visits for asthma, and (4) provide information that would help translate interventions into policy decisions, thereby reducing the economic burden and increasing well being of asthmatics. Further, the results of the study will be incorporated into Florida s Environmental Public Health Tracking (EPHT) program, which is part of the Centers for Disease Control and Prevention's (CDC's) EPHT network.

Crosson, William↗
NASA NTRS1991

SEAPAK user's guide, version 2.0. Volume 1: System description

The SEAPAK is a user interactive satellite data analysis package that was developed for the processing and interpretation of Nimbus-7/Coastal Zone Color Scanner (CZCS) and the NOAA Advanced Very High Resolution Radiometer (AVHRR) data. Significant revisions were made to version 1.0 of the guide, and the ancillary environmental data analysis module was expanded. The package continues to emphasize user friendliness and user interactive data analyses. Additionally, because the scientific goals of the ocean color research being conducted have shifted to large space and time scales, batch processing capabilities for both satellite and ancillary environmental data analyses were enhanced, thus allowing large quantities of data to be ingested and analyzed in background.

Mcclain, Charles R.↗
DOE OSTI2026

Raw soil carbon dioxide, moisture, temperature and micrometeorological data in the East River Watershed, Colorado June 2021-June 2024. (DE-SC0021139)

This dataset contains raw data from four tripod stations along an elevation gradient on Snodgrass Mountain in the East River Watershed, CO, USA. Each station contains a datalogger connected to 3 soil Carbon Dioxide CO2 gas probes, 3 soil temperature/moisture sensors and a micrometeorological station. Sensors are scanned every minute, and the 30 minute average is reported. The file snodgrass_soil_ESS.csv contains raw data, a row of column descriptors, and units of measurements. some data processing and QA/QC was done to filter out data from sensors that went bad and extreme outliers. CO2 sensors that went bad were replaced with new sensors as soon as possible. This research was performed to investigate the ecohydrological linkages of belowground carbon processes in the East River watershed forested communities to better understand how these ecosystems will respond to a changing cold-season moisture input. This is the second version of this data set and was modified on 10/01/2024. The primary change in the data was the addition of data from the fall of 2022 to June of 2024. In addition, minor QA/QC was done to filter out data from sensors that went bad and extreme outliers. THe filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. This is now the third version of the data set, and was modified 03/25/2026. The primary change in the data was the addition of data from the June of 2024 to December 2025. Further r QA/QC was done with the new data to filter out bad data from faulty sensors and extreme outliers. The filtered data are now NA's in this data frame and primarily the CO2 sensors. Limited to no QA/QC has been done on the other environmental data. ##This additional data was funded under DE-SC0024218( Responses of Plant and Microbial Respiration Sources to Changing Cold Season Climate Drivers in the East River Watershed)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Block Island Environmental Monitoring Data (Weather, Waves & Sensor Depth)

This dataset contains meteorological, oceanographic, and sensor-depth data collected near Block Island during the 2016 and 2017 RODEO field seasons to provide environmental context for concurrent acoustic and survey operations. It includes buoy-derived wind and wave time series, in-situ water temperature logger records, and depth (pressure) records from a sensor mounted on the vertical line array.

17 WIND ENERGY↗
NASA NTRS1996

Towards the Interoperability of Web, Database, and Mass Storage Technologies for Petabyte Archives

At the San Diego Supercomputer Center, a massive data analysis system (MDAS) is being developed to support data-intensive applications that manipulate terabyte sized data sets. The objective is to support scientific application access to data whether it is located at a Web site, stored as an object in a database, and/or storage in an archival storage system. We are developing a suite of demonstration programs which illustrate how Web, database (DBMS), and archival storage (mass storage) technologies can be integrated. An application presentation interface is being designed that integrates data access to all of these sources. We have developed a data movement interface between the Illustra object-relational database and the NSL UniTree archival storage system running in a production mode at the San Diego Supercomputer Center. With this interface, an Illustra client can transparently access data on UniTree under the control of the Illustr DBMS server. The current implementation is based on the creation of a new DBMS storage manager class, and a set of library functions that allow the manipulation and migration of data stored as Illustra 'large objects'. We have extended this interface to allow a Web client application to control data movement between its local disk, the Web server, the DBMS Illustra server, and the UniTree mass storage environment. This paper describes some of the current approaches successfully integrating these technologies. This framework is measured against a representative sample of environmental data extracted from the San Diego Ba Environmental Data Repository. Practical lessons are drawn and critical research areas are highlighted.

Moore, Reagan↗
NASA NTRS1980

STS-1 mission contamination evaluation approach

The space transportation system 1 mission will be the first opportunity to assess the induced environment of the orbiter payload bay region. Two tools were developed to aid in this assessment. The shuttle payload contamination evaluation computer program was developed to provide an analytical tool for prediction of the induced molecular contamination environment of the space shuttle orbiter during its onorbit operations. An induced environment contamination monitor was constructed and tested to measure the space shuttle orbiter contamination environment inside the payload bay during ascent and descent and inside and outside the payload bay during the onorbit phase. Measurements are to be performed during the four orbital flight test series. Measurements planned for the first flight are described and predicted environmental data are discussed. The results indicate that the expected data are within the measurement range of the induced environment contamination monitor instruments evaluated, and therefore it is expected that useful contamination environmental data will be available after the first flight.

Jacobs, S.↗
DOE OSTI2024

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Optimizing aircraft flows at airports using data driven predicted capabilities

A method for safe and efficient use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.

Sweet, Douglas↗
NASA NTRS1975

Application of EREP, LANDSAT, and aircraft image data to environmental problems related to coal mining

Remote sensing techniques were used to study coal mining sites within the Eastern Interior Coal Basin (Indiana, Illinois, and western Kentucky), the Appalachian Coal Basin (Ohio, West Virginia, and Pennsylvania) and the anthracite coal basins of northeastern Pennsylvania. Remote sensor data evaluated during these studies were acquired by LANDSAT, Skylab and both high and low altitude aircraft. Airborne sensors included multispectral scanners, multiband cameras and standard mapping cameras loaded with panchromatic, color and color infrared films. The research conducted in these areas is a useful prerequisite to the development of an operational monitoring system that can be peridically employed to supply state and federal regulatory agencies with supportive data. Further research, however, must be undertaken to systematically examine those mining processes and features that can be monitored cost effectively using remote sensors and for determining what combination of sensors and ground sampling processes provide the optimum combination for an operational system.

Amato, R. V.↗
NASA NTRS1998

NASA's Current Earth Science Program

NASA's Earth science program is a scientific endeavor whose goal is to provide long-term understanding of the Earth as an integrated system of land, water, air and life. A highly developed scientific knowledge of the Earth system is necessary to understand how the environment affects humanity, and how humanity may be affecting the environment. The remote sensing technologies used to gather the global environmental data used in such research also have numerous practical applications. Current applications of remote sensing data demonstrate their practical benefits in areas such as the monitoring of crop conditions and yields, natural disasters and forest fires; hazardous waste clean up; and tracking of vector-borne diseases. The long-term availability of environmental data is essential for the continuity of important research and applications efforts. NASA's Earth observation program has undergone many changes in the recent past.

Charles, Leslie Bermann↗
NASA NTRS1975

Computer mapping of LANDSAT data for environmental applications

The author has identified the following significant results. Land cover overlays and maps produced from LANDSAT are providing information on existing land use and resources throughout the 208 study area. The overlays are being used to delineate drainage areas of a predominant land cover type. Information on cover type is also being combined with other pertinent data to develop estimates of sediment and nutrients flows from the drainage area. The LANDSAT inventory of present land cover together with population projects is providing a basis for developing maps of anticipated land use patterns required to evaluate impact on water quality which may result from these patterns. Overlays of forest types were useful for defining wildlife habitat and vegetational resources in the region. LANDSAT data and computer assisted interpretation was found to be a rapid cost effective procedure for inventorying land cover on a regional basis. The entire 208 inventory which include acquisition of ground truth, LANDSAT tapes, computer processing, and production of overlays and coded tapes was completed within a period of 2 months at a cost of about 0.6 cents per acre, a significant improvement in time and cost over conventional photointerpretation and mapping techniques.

Rogers, R. H.↗
NASA NTRS2011

Technical Tension Between Achieving Particulate and Molecular Organic Environmental Cleanliness: Data from Astromaterial Curation Laboratories

NASA Johnson Space Center operates clean curation facilities for Apollo lunar, Antarctic meteorite, stratospheric cosmic dust, Stardust comet and Genesis solar wind samples. Each of these collections is curated separately due unique requirements. The purpose of this abstract is to highlight the technical tensions between providing particulate cleanliness and molecular cleanliness, illustrated using data from curation laboratories. Strict control of three components are required for curating samples cleanly: a clean environment; clean containers and tools that touch samples; and use of non-shedding materials of cleanable chemistry and smooth surface finish. This abstract focuses on environmental cleanliness and the technical tension between achieving particulate and molecular cleanliness. An environment in which a sample is manipulated or stored can be a room, an enclosed glovebox (or robotic isolation chamber) or an individual sample container.

Allton, J. H.↗
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↗