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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Survey for least bell's vireo in riparian habitat on Vandenberg Air Force Base, Santa Barbara County, California

The least bell's vireo (Vireo bellii pusillus) was listed in 1986 as an endangered species by the U.S. Fish and Wildlife Service. Because of the possibility of the species existing on Vandenberg Air Force Base (VAFB), this survey was conducted to determine if they exist, and if so to prepare a distribution map of the species on the base. Major riparian areas were surveyed on foot for 17 days in April, May, and July 1987. No least bell's vireo were sighted; based on past studies, it is unlikely that there is a significant population on VAFB. There are, however, at least 13 other species of special concern that inhabit VAFB riparian woodlands. Most of these species have declined along the south coast of Santa Barbara County, and many have declined in much of the southern half of California. Riparian areas on VAFB are an important environmental resource for the southern half of California; many of these areas, however, show signs of degradation.

Breininger, David R.↗
NASA NTRS2014

Deep Mapping of Small Solar System Bodies with Galactic Cosmic Ray Secondary Particle Showers

Galactic cosmic rays rain steadily from all directions onto asteroids and comets. The interaction of these high-energy ions produces a cascade of secondary particles, including muons, which can penetrate the solid interiors of small solar system bodies. Muons, which are produced in abundance in Earth's atmosphere, have been used to image large structures on Earth, including the Great Pyramids and the interior of volcanoes. In this study, we demonstrate that the transmitted flux of muons is sensitive to the interior density structure of asteroids and comets, less than a few hundred meters in diameter. Muonography has the potential to fill a critical gap in our knowledge of the deep interiors of small bodies, providing information needed for planetary defense, in situ resource utilization, and planetary science. We use Monte Carlo codes (MCNPX and FLUKA), which accurately model galactic cosmic ray showers, to explore systematic variations in the production of muons in solid surfaces. Results of these calculations confirm the scaling of muon production in Earth's atmosphere to solid regolith materials, as predicted by a simple, semi-empirical model. Muons are primarily produced in the top meter of the regoliths of asteroids and comets. Their rate of production is over three orders of magnitude lower than in Earth's atmosphere and depends strongly on regolith density. In practice, the use of muonography to characterize the interiors of small solar system bodies must overcome their low rate of production and their dependence on regolith density, which can vary over the surface of asteroids and comets. We show that interior contrast can be resolved using a muon telescope (hodoscope) with about 1 sq m aperture with integration times ranging from hours to weeks. Design concepts for a practical hodoscope that could be deployed in situ or on an orbiting spacecraft, are described. Regolith density within the top meter of an asteroid can be determined from radar observations. A concept for a pilot mission that combines remote radar measurements with in situ muonography of a near-Earth asteroid is presented. Perceived challenges and next steps for the development of the concept are described.

Prettyman, T. H.↗
DOE OSTI2020

Draft genome of multiple resistance donor plant Sinapis alba: An insight into SSRs, annotations and phylogenetics

Sinapis alba is a wild member of the Brassicaceae family reported to possess genetic resistance against major biotic and abiotic stresses of oilseed brassicas. However, the resistance nature of S. alba was not exploited generously due to the unavailability of usable genome sequences in public databases. Therefore, the present study was conducted to assemble the first draft genome from raw whole genome shotgun sequences with annotation and develop simple sequence repeat markers for molecular genetics and marker-assisted breeding. Results The raw genome sequences had 96x coverage on the Illumina platform with 170 Gbp data. The developed assembly by SOAPdenovo2 has ~459 Mbp genome size covered in 403,423 contigs with an average size of 1138.04 bp. The assembly was BLASTX with Arabidopsis thaliana which showed 32.9% positive hits between both plants. The top hit species distribution analysis showed the highest similarity with A. thaliana. A total of 809,597 GO level annotations were recorded after BLASTX results, and 34,012 sequences were annotated with different enzyme codes grouped under seven classes. The gene prediction tool AUGUSTUS identified 113,107 probable genes with an average size of 684 bp. The biochemical pathway annotation assigned 16,119 potential genes to 152 KEGG maps and 1751 enzyme codes. The development of potential SSRs from the de-novo assembly yielded 70731 unique primer pairs. Out of 159 randomly selected SSR markers for validation, 149 successfully amplified in S. alba. However, 10 SSR markers did not amplify during the validation experiment. Conclusion The annotated genome assembly with a large number of SSRs was developed in the present study. To the best of our knowledge, this is the first report of S. alba genome assembly development, annotation, and SSRs mining to date. The data presented here will be a very important resource for future crop improvement programs, especially for resistant breeding.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Crosson, William L↗
NASA NTRS2017

Space Exploration

New range Passage Tomb may be the first structure with known astronomical significance. It was built around 3,200 B.C. in Ireland. It's central passage allows light end-to-end for about 2 weeks around winter solstice. The Sun, Moon, Planets, and Stars held significance in early times due to the seasons, significance for food crops, and mythology. Citation: Corel Photography and Windows to the Universe The Greek may be among the first to pursue analytical interpretations of what they saw in the sky. In about 280 B.C. Aristarchus suggested Earth revolves around the Sun and estimated the distance between. Around 130 B.C. Hipparchus developed the first accurate star map. Today still seek to understand how the universe formed and how we came to be and are we alone. Understanding the causes and consequences of climate change using advanced space missions with major Earth science and applications research. center dotFire the public imagination and inspire students to pursue STEM fields. Train college and graduate students to create a U.S. technical workforce with employees that embody the values of competence, innovation, and service. center dotDrive the technical innovations that enable exploration and become the engine of National economic growth. center dotPartner domestically and internationally to leverage resources to extend the reach of research.

space↗
NASA NTRSDate not supplied

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as various means to download and access the data including programmatically through the GeneLab Open API (GLOpenAPI). The open access of datasets in NASA’s OSDR provides a unique opportunity for the scientific community, as well as citizen scientists and students, to continue using OSDR resources to further unlock profound insights into the consequences of space travel on the human body. Through implementation of security measures to protect sensitive human data, the OSDR seeks to strengthen the science exchange between the Biological and Physical Sciences Program and the Human Research Program, per recommendation 4-1 of the 2023-2032 Decadal Survey, and encourage further sharing and dissemination of astronaut data to provide the scientific community with the resources needed to lay the groundwork for developing targeted mitigation strategies to help withstand the rigors of long-duration spaceflight.

Amanda Marie Saravia-butler↗
DOE OSTI2023

Electrically Engaged UnduLation (EEL) Marine Energy System

Current technologies at the forefront of instrumentation for ocean observation through acoustic mapping are powered by batteries that cannot achieve the lasting durations required for high-resolution measurements. Pyro-E has designed an Electrically Engaged unduLation (EEL) system capable of in situ energy harvest and deployment in sub-sea configurations. By extracting kinetic energy from the ocean, EEL proposes to provide power output ranging from 1 mW to 1,000 mW. Such a magnitude of power can sustain active instrumentation with onboard processing of data and over-the-horizon telemetry. Pyro-E and Oak Ridge National Laboratory have utilized software tools and powerful computing resources to develop a techno-economic design of the EEL capable of harvesting 5 W. The material response of the EEL under simulated hydromechanical loads is described through time-accurate predictions. All physical tests were conducted by Pyro-E to guide simulations at Oak Ridge National Laboratory.

16 TIDAL AND WAVE POWER↗
NASA NTRS1975

A study of atmospheric effects on pattern recognition devices

The author has identified the following significant results. ERTS-1 imagery can be applied in the broadscale assessment of forest resources as a supplement to aerial photography and field survey. There was no application to inventory of crop and pasture diseases mainly because of poor quality and low resolution, and unreliability of image acquisition. Inventory of soil erosion was satisfactory in humid eastern New South Wales, but not in semi-arid areas. Patterns of snow cover, areas of water in natural and artificial water bodies, extent of bushfires, and location of coastal mobile sand bodies were readily apparent. ERTS-1 imagery was judged to be a valuable addition to conventional techniques of regional small scale geological mapping. ERTS data was successfully used to map flooding and flood progression. The imagery was found suitable for mapping at 1:1,000,000 scale both on the mainland and in Antarctica, but did not meet accuracy specifications for 1:250,000 mapping.

Thomson, F. J.↗
NASA NTRS1981

Earth resources observation with the Shuttle imaging radar

To fully understand the radar signature of different surface features and covers, observations must be made in a variety of sensor parameters (that is, frequency, polarization, and incidence angle). This makes it possible to choose those sensor parameters that will provide the greatest amount of information about the surface. The Shuttle Imaging Radar (SIR) will be able to obtain surface images at two frequencies (L-band and C-band), at multiple polarizations, and at all incidence angles from near vertical to near grazing. The SIR will operate in the synthetic aperture imaging mode and provide digital images of the surfaces with a resolution of approximately 20 m. As part of the SIR flights, a number of planned large-scale experiments will be carried out in the fields of geologic mapping, vegetation classification, land cover mapping, surface moisture measurements, and ocean surface observation.

Elachi, C.↗
DOE OSTI2020

RAPID STRUCTURE DETECTION IN SUPPORT OF DISASTER RESPONSE : A CASE STUDY OF THE 2018 KILAUEA VOLCANO ERUPTION

Disaster response requires timely damage assessment to prioritize rescue and restoration resources. However, providing critical and actionable knowledge after a natural disaster can be challenging due to the scale and the type of damages. This paper describes how remote sensing and machine learning techniques can be used to support rapid structure detection in the wake of a disaster. We use high resolution satellite imagery to identify structures on Hawaii’s Big Island to support the Federal Emergency Management Agency’s response efforts during the 2018 K¯ilauea lava flow incident. This framework specifically showcases the generalizability of CNN models with no need to collect additional training samples to quickly map structures in pre- and post-event imagery and provide timely information to assist government agencies evaluating the extent and potential loss of disaster. With this case study, we further point out future directions to benefit similar larger scale efforts based on the lessons learned.

Laverdiere, Melanie↗
NASA NTRS1973

Earth Resources Technology Satellite: Non-US standard catalog No. N-13

To provide dissemination of information regarding the availability of Earth Resources Technology Satellite (ERTS) imagery, a Non-U.S. Standard Catalog is published on a monthly schedule. The catalogs identify imagery which has been processed and input to the data files during the preceding month. The Non-U.S. Standard Catalog includes imagery covering all areas except that of the United States, Hawaii, and Alaska. Imagery adjacent to the Continental U.S. and Alaska borders will normally appear in the U.S. Standard Catalog. As a supplement to these catalogs, an inventory of ERTS imagery on 16 millimeter microfilm is available. The catalogs consist of four parts: (1) annotated maps which graphically depict the geographic areas covered by the imagery listed in the current catalog, (2) a computer-generated listing organized by observation identification number (ID) with pertinent information for each image, (3) a computer listing of observations organized by longitude and latitude, and (4) observations which have had changes made in their catalog information since the original entry in the data base.

Source record↗
NASA NTRS1999

National Aeronautics and Space Administration 1999 Accountability Report

This Accountability Report consolidates reports required by various statutes and summarizes NASA's program accomplishments and its stewardship over budget and financial resources. It is a culmination of NASA's management process, which begins with mission definition and program planning, continues with the formulation and justification of budgets for the President and Congress, and ends with the resulting scientific and engineering program accomplishments. The report covers activities from October 1, 1998, through September 30, 1999, with a discussion of some subsequent events. Program accomplishments included the deployment and operation of the Chandra X-ray Observatory, the delivery of supplies and equipment needed to live and operate on the International Space Station, and the development of the first global 3-D map of Mars. Achievements are highlighted in the Statement of the Administrator and summarized in the performance section of this report.

Source record↗
NASA NTRS2013

The Use of NASA GSFC Modular, Reconfigurable, Rapid (MR^2) Small Satellite for the Measurement of Greenhouse Gases

The Small Rocket/Spacecraft Technology (SMART) is an existing microsatellite prototype bus that provides the ability to accommodate focused science (and technology validation) missions without the need to spend large resources typical of high‐performing spacecraft. SMART represents the sum value of GSFC’s long tradition of developing systems that find efficient application in a series of missions, exemplified by two successful major programs: the Multi-mission Modular Spacecraft (MMS), and the Small Explorer Program (SMEX). SMART is based on an evolutionary architecture based drawn from these two experiences: the Modular, Reconfigurable, Rapid (MR2) architecture. This paper shows a SMART-derivative spacecraft (with re-sized structure) used to accommodate the Abundance of Methane via Interferometric Glint Observation (AMIGO) instrument. The principal objective of AMIGO is to map and quantify the abundance of the major greenhouse gases (particularly methane) and to identify and quantify their sources and sinks on a global basis. In addition, a Laser retro-reflector instrument of opportunity is included, to add to the constellation of spacecraft relevant to the definition and regular update of the International Terrestrial Reference Frame (ITRF).

small satellite↗
NASA NTRSDate not supplied

Oregon Wildfires: Integrating ECOSTRESS to Map & Analyze Vegetation Moisture for Wildfire Modeling

Wildfire season in the western USA is starting earlier and gaining in intensity. The Bootleg Fire in Southern Oregon began on July 6th, 2021, and burned over 1675 km2 before it was fully contained on August 15th, 2021. Evapotranspiration (ET) is one indicator of vegetation moisture and there is interest in using high-resolution ET products from ECOsystem and Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in future wildfire modeling. In partnership with the Pacific Northwest National Laboratory and US Forest Service, the team examined ECOSTRESS ET for the two years before the Bootleg Fire and assessed the relationship between ET, topography, and vegetation. Remotely sensed data from Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) along with ancillary data from the National Land Cover Database (NLCD) and Landscape Fire Resource Management Planning Tools (LANDFIRE) were incorporated. The team examined data in relation to soil burn severity from the Burned Area Emergency Response (BAER) program. From ET median composites for April 1st – July 5th, 2021 and 2019, the Bootleg Fire area showed a 7 mm/day decrease in ET and a relative 75% decrease in ET between 2019 and 2021. Approximately 6% of the Bootleg Fire area was identified as having a high soil burn severity and these areas were found predominantly in the evergreen forest land cover class and northward facing slopes with a mean ET decrease of 3 mm/day between 2019 and 2021. The team also analyzed ECOSTRESS Water Use Efficiency products as an additional vegetation moisture indicator of pre-fire conditions in the study area. The end products will allow the partners to assess if higher resolution vegetation moisture datasets from ECOSTRESS will improve wildfire modeling for other susceptible areas.

Brenna Hatch↗
DOE OSTI2025

Automated Fire Detection for Industrial Settings with Pretrained Convolutional Networks

Early fire detection in industrial environments is critical to preventing equipment damage, personal injury, and operational disruptions. Traditional smoke detectors, while effective, often experience delays due to the time required for smoke to reach sensors, allowing fires to spread. Manual fire watch operations and human surveillance of camera feeds are resource-intensive and prone to human error. To address these challenges, this paper explores the application of convolutional neural networks for automated fire detection, specifically in industrial settings. By leveraging 11 different pre-trained machine vision models from TensorFlow and enhancing them with transfer learning on a custom-built industrial fire dataset, we optimized fire detection performance. Here, we analyzed each machine vision model architecture in terms of its depth, width, and input image resolution, considering both resource requirements and detection accuracy. We further explored the option of combining multiple models into an ensemble classifier to evaluate whether the performance improvements could justify the much greater computational complexity and other practical impacts. A cost-benefit analysis is presented to evaluate the trade-offs between performance and computational expense. Our findings identify that EfficientNetV2L, specifically tailored for industrial applications, provides the optimal balance between costs involved in training and using the model versus the overall fire detection performance. Additionally, we present a qualitative analysis of model performance using the technique of gradient-based class activation mapping to provide explainability by visualizing model decisions.

artificial intelligence↗
DOE OSTI2024

Spatially and Temporally Detailed Water and Carbon Footprints of U.S. Electricity Generation and Use

Electricity generation in the United States entails significant water usage and greenhouse gas emissions. However, accurately estimating these impacts is complex due to the intricate nature of the electric grid and the dynamic electricity mix. Existing methods to estimate the environmental consequences of electricity use often generalize across large regions, neglecting spatial and temporal variations in water usage and emissions. Consequently, electric grid dynamics, such as temporal fluctuations in renewable energy resources, are often overlooked in efforts to mitigate environmental impacts. The U.S. Department of Energy (DOE) has initiated the development of resilient energyshed management systems, requiring detailed information on the local electricity mix and its environmental impacts. This study supports DOE's goal by incorporating geographic and temporal variations in the electricity mix of the local electric grid to better understand the environmental impacts of electricity end users. We offer hourly estimates of the U.S. electricity mix, detailing fuel types, water withdrawal intensity, and water consumption intensity for each grid balancing authority through our publicly accessible tool, the Water Integrated Mapping of Power and Carbon Tracker (Water IMPACT). While our primary focus is on evaluating water intensity factors, our dataset and programming scripts for historical and real-time analysis also include evaluations of carbon dioxide (equivalence) intensity within the same modeling framework. This integrated approach offers a comprehensive understanding of the environmental footprint associated with electricity generation and use, enabling informed decision-making to effectively reduce Scope 2 water usage and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

An expanded transcriptome atlas for Bacteroides thetaiotaomicron reveals a small RNA that modulates tetracycline sensitivity

Plasticity in gene expression allows bacteria to adapt to diverse environments. This is particularly relevant in the dynamic niche of the human intestinal tract; however, transcriptional networks remain largely unknown for gut-resident bacteria. Here we apply differential RNA sequencing (RNA-seq) and conventional RNA-seq to the model gut bacterium Bacteroides thetaiotaomicron to map transcriptional units and profile their expression levels across 15 in vivo-relevant growth conditions. We infer stress- and carbon source-specific transcriptional regulons and expand the annotation of small RNAs (sRNAs). Integrating this expression atlas with published transposon mutant fitness data, we predict conditionally important sRNAs. These include MasB, which downregulates tetracycline tolerance. Using MS2 affinity purification and RNA-seq, we identify a putative MasB target and assess its role in the context of the MasB-associated phenotype. These data—publicly available through the Theta-Base web browser (http://micromix.helmholtz-hiri.de/bacteroides/)—constitute a valuable resource for the microbiome community.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Landsat-4 Thematic Mapper scene characteristics of a suburban and rural area

The Thematic Mapper (TM) sensor, which is carried by the Landsat-4 and Landsat-5 satellites, represents the latest generation of an earth resource scanner system. TM applications range from determining the extent and changes of land cover to estimating agricultural yields. The TM has improvements over the Multispectral Scanner (MSS) with respect to spatial resolution, spectral regions, and radiometry. The present paper is concerned with two major objectives related to the analysis of the Landsat TM. One of these objectives is related to an evaluation of the utility of TM in the discrimination of surface cover. In connection with the second objective, an evaluation was conducted of the utility of selected image processing procedures to enhance the capability of Landsat TM to map land cover. It was found that TM data may be used for discriminating smaller targets, such as agricultural fields and city blocks, than previously obtainable with MSS data.

Toll, D. L.↗