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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Emphasizing Spectrum Management for Sustainable Development Research and Applications in Disaster Management

NASA's spaceborne Earth and Heliospheric Observatories and airborne sensors provide a plethora of measurements. These measurements are used in science research to understand the climatology of our home planet and the solar fluxes and cycle of the only star in our solar system 'Sun' which is critical driver for the retention of life on Earth. Specifically, these measurements help us to understand the water and energy cycle, the carbon cycle, weather and climate, atmospheric chemistry, solar variability, and solid Earth and interior to feed into sophisticated mathematical models to analyze and predict the Earth's behavior as an integrated system. The main thrust of this research is on improving the prediction capability in the areas of weather, long term climate and solid Earth processes, and further help the humanity and future generations in terms of societal benefits in managing natural disasters, sustainability issues and many more. This work is further linked with our contributions in the Global Earth Observing System of Systems (GEOSS) Specifically, the data and knowledge resulting from the Earth observing systems and analytical models of the Earth can be made available for assimilation into decision support systems to serve society for disaster management. Through partnerships with national and international agencies and organizations, NASA's Science Mission Directorate's, Applied Sciences Program contributes to benchmarking practical uses of observations and predictions from Earth science remote sensing systems research. The objective is to establish innovative solutions using Earth observations and science information to provide decision support that can be adapted in applications of national and international priority. We along with the international community will continue this critical field of investigation by using our existing and future sensors from space, airborne and insitue environment. In our quest to expanding our knowledge, there will be a need for deploying additional sensors to obtain high spatial, temporal and spectral resolution measurements. These sensors operate in multiple spectral band ranging from UV, visible, infrared, microwave and radio frequency ranges. Of a particular concern is the microwave frequency bands which play a key role in land, ocean, moisture sensing. This is because of a growing commercial demand in the area of high speed broadband communication all over the world, the electronic manufacturers are looking into high frequency microwave spectral bands. This may present a risk to the remote sensing sensors because of additional sources of noise that can impair the highly sensitive passive remote sensing instruments.

Ambrose, Stephen↗
NASA NTRS2007

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage.

Lewis, David↗
NASA NTRS2011

Facility Targeting, Protection and Mission Decision Making Using the VISAC Code

The Visual Interactive Site Analysis Code (VISAC) has been used by DTRA and several other agencies to aid in targeting facilities and to predict the associated collateral effects for the go, no go mission decision making process. VISAC integrates the three concepts of target geometric modeling, damage assessment capabilities, and an event/fault tree methodology for evaluating accident/incident consequences. It can analyze a variety of accidents/incidents at nuclear or industrial facilities, ranging from simple component sabotage to an attack with military or terrorist weapons. For nuclear facilities, VISAC predicts the facility damage, estimated downtime, amount and timing of any radionuclides released. Used in conjunction with DTRA's HPAC code, VISAC also can analyze transport and dispersion of the radionuclides, levels of contamination of the surrounding area, and the population at risk. VISAC has also been used by the NRC to aid in the development of protective measures for nuclear facilities that may be subjected to attacks by car/truck bombs.

Morris, Robert H.↗
NASA NTRS2011

Migrating to 9.1 -- Why Not...How Hard Could It Be?

With 19+ Million documents in the 8.0 Vault. the decision was to migrate only selected top-level Documents, Drawings, Models and Assemblies to Kennedy Space Center's Brand-Spankin-New 9.1 Windchill system. Come with us as we detail our journey. We'll share our triumphs. tools, and approaches, as well as our challenges (and a surprise or two) discovered on the trip.

Little, Keith↗
NASA NTRS2012

Key Decision Record Creation and Approval Module

Retaining good key decision records is critical to ensuring the success of a project or operation. Having adequately documented decisions with supporting documents and rationale can greatly reduce the amount of rework or reinvention over a project's, vehicle's, or facility's lifecycle. Stennis Space Center developed and uses a software tool that automates the Key Decision Record (KDR) process for its engineering and test projects. It provides the ability for a user to log key decisions that are made during the course of a project. By customizing Parametric Technology Corporation's (PTC) Windchill product, the team was able to log all information about a decision, and electronically route that information for approval. Customizing the Windchill product allowed the team to directly connect these decisions to the engineering data that it might affect and notify data owners of the decision. The user interface was created in JSP and Javascript, within the OOTB (Out of the Box) Windchill product, allowing users to create KDRs. Not only does this interface allow users to create and track KDRs, but it also plugs directly into the OOTB ability to associate these decision records with other relevant engineering data such as drawings, designs, models, requirements, or specifications

Hebert, Barrt↗
NASA NTRS2017

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data Via Hyrax Server Data Server

This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.

AWS cost↗
NASA NTRS2017

Task 28: Web Accessible APIs in the Cloud Trade Study

This study explored three candidate architectures for serving NASA Earth Science Hierarchical Data Format Version 5 (HDF5) data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the project are: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and Network Common Data Format Version 4 (netCDF4) data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3).Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.

cost model↗
NASA NTRS2021

Mangrove Mapping with the Freeman-Durden Polarimetric Decomposition and Insar Coherence from ALOS-2

We map mangrove extents in Pongara National Park, Gabon using the Freeman-Durden Decomposition and InSAR Coherence derived from ALOS-2 imagery. Specifically, we obtain a land cover map derived from both this polarimetric decom-position and a 14-day repeat-pass coherence. Our classification model and results are highly interpretable based on a depth 2 decision tree. We further illustrate the correlation between InSAR coherence and height obtaining rough man-grove height estimates from TanDEM-X data. From our results, we observe that repeat-pass interferometric coherence provides invaluable information about mangrove extents and coastal forests. The clear identification of mangrove extents presents a significant opportunity for NISAR, which will pro-vide 12-day repeat pass images over coastal areas globally.

Tien-Hao Liao↗
NASA NTRS2020

Mangrove Mapping With the Freeman-Durden Polarimetric Decomposition and InSAR Coherence From ALOS-2

We map mangrove extents in Pongara National Park, Gabon using the Freeman-Durden Decomposition and InSAR Coherence derived from ALOS-2 imagery. Specifically, we obtain a land cover map derived from both this polarimetric decomposition and a 14-day repeat-pass coherence. Our classification model and results are highly interpretable based on a depth 2 decision tree. We further illustrate the correlation between InSAR coherence and height obtaining rough mangrove height estimates from TanDEM-X data. From our results, we observe that repeat-pass interferometric coherence provides invaluable information about mangrove extents and coastal forests. The clear identification of mangrove extents presents a significant opportunity for NISAR, which will provide 12-day repeat pass images over coastal areas globally.

Thomas, Nathan↗
DOE OSTI2020

A Community Energy Operations and Planning System: Concept, Use cases, Metrics, and Benefits

Community and city leaders are interested in achieving sustainability goals, providing resilient energy infrastructure, and improving economic competitiveness. Community-level data acquisition and analysis can provide energy and associated benefits that are not possible at the single building level. However, there is a lack of organizational structure, common semantic data models, interoperable systems, and methods to support data-driven decision-making for community-scale energy supply and demand systems. We explored the need and opportunity for a Community Energy Operations and Planning System (Community EOPS), a potential data exchange platform. We conducted “customer discovery” interviews, and reviewed literature, public tools, and technology platforms to identify key energy data “users” and use cases in communities. The key users of the Community EOPS could be developers of mixed-use districts, corporate, defense and university campus energy managers, and city managers of cities that own their energy utility. The value could be for community planning and reporting (for energy data-integrated land use planning and community infrastructure investments in microgrids, storage, district heating and cooling), energy efficiency (leveraging optimizations for community scale energy supply and demand), flexible load management (grid-edge load management to offset, shift, and flatten loads for multiple buildings and EV fleets), cost savings and revenue generation (participating in grid services), and social benefits such as energy resilience, equity, and awareness. We developed a conceptual Community EOPS architecture with recommendations for streamlined and prioritized data acquisition, sharing, and integration driven by prioritized use cases, common metrics, and actionable visualizations that can provide value to a community’s users.

Singh, Reshma↗
DOE OSTI2025

A Framework for Assessing Economic and Environmental Trade-offs of Internalized Emission Costs in ERCOT Grid Planning

The power grid is on the cusp of a massive transition driven by three major areas: 1) the growth in demand for electricity, 2) efforts to decarbonize the United States economy, and 3) a desire to mitigate social disparities from the impact of electricity generation on local populations. However, most studies of the electricity sector do not include equity impacts in their models. This study seeks to do so by developing a comprehensive and generalizable model tailored to the Electric Reliability Council of Texas (ERCOT) grid, designed to incorporate the equity impacts of electricity generation in a decarbonized and resilient framework. To integrate equity into our research, we incorporate environmental externalities into our capacity expansion model of ERCOT. Specifically, we factor in intermediate-level local marginal damages of precursor pollutants (NH3, NOx, primary PM2.5, SO2, and VOC) and global pollutant CO2 into the cost of generating electricity. We do this by taking into account county population, county ambient pollution concentration, and generator emission rates. Leveraging open-source modeling tools, such as PowerGenome, pyGRETA, and GenX we construct a county-level model to account for these costs. We integrate these marginal damages into the variable operations and maintenance costs of generators, for both existing and potential future builds. This study’s findings suggest that the value of a dynamic social cost of carbon (SSC) will cover criteria pollutant marginal damages within the ERCOT grid and solar and wind is expected to increase out to 2035. Key metrics evaluated within this research include fuel mix distribution across technologies, transmission and grid infrastructure costs, CO2 emissions, local pollutants marginal damages, and the variation in generation capacity built by the model. These results and framework can be used to support grid decisions that explicitly include distributional and procedural equity within a decarbonized and sustainable grid framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Updating Nuclear Energy Cost Estimates for Net Zero World Initiative

Energy modeling of decarbonized scenarios in integrated energy systems requires nuclear energy parameters that are critical for forecasting, modeling and cost structure analysis. Using updated real-world data has always been a challenge to estimate current nuclear reactors costs and deployment scenarios. Given this, an updated set of parameters for overnight capital costs and operation and maintenance costs are estimated for the Net Zero World initiative using recent reports that provided a vast set of open sources data inputs. This paper follows the methodology developed in the Net Zero World report and applies the new ranges estimated in the Gateway for Accelerated Innovation in Nuclear report that address many of the current challenges in obtaining accurate cost data for advanced nuclear concepts. The final goal is to provide new estimates of the overnight capital costs and operational costs for different countries. The present paper improves the earlier capital cost estimations, building on recent literature that aims to obtain accurate data for modeling and simulation to enhance energy system evaluations and support decision-making in areas like de-carbonization and capacity expansion. Finally, the paper compares the new cost estimates with the old cost results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗
NASA NTRS2010

MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination

Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow tinder cloud, to enable users' flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.

Riggs, George A.↗
NASA NTRS2016

End-of-Discharge and End-of-Life Prediction in Lithium-Ion Batteries with Electrochemistry-Based Aging Models

As batteries become increasingly prevalent in complex systems such as aircraft and electric cars, monitoring and predicting battery state of charge and state of health becomes critical. In order to accurately predict the remaining battery power to support system operations for informed operational decision-making, age-dependent changes in dynamics must be accounted for. Using an electrochemistry-based model, we investigate how key parameters of the battery change as aging occurs, and develop models to describe aging through these key parameters. Using these models, we demonstrate how we can (i) accurately predict end-of-discharge for aged batteries, and (ii) predict the end-of-life of a battery as a function of anticipated usage. The approach is validated through an experimental set of randomized discharge profiles.

batteries↗
DOE OSTI2025

AI Driven Optimization of Public Transit

This project explores the application of AI-driven methods to optimize public transit operations for the Chattanooga Area Regional Transportation Authority (CARTA). By leveraging data analytics, machine learning, and predictive modeling, the initiative seeks to enhance system efficiency, improve rider experience, and support sustainability goals. This research, supported by the National Science Foundation and the U.S. Department of Energy, integrates real-time transit data with advanced computational tools to inform decision-making, optimize routes, and balance operational demands. The work exemplifies a forward-looking model for mid-sized cities aiming to modernize mobility systems through intelligent technology integration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2006

Solar Sails

The Solar Sail Propulsion investment area has been one of the three highest priorities within the In-Space Propulsion Technology (ISPT) Project. In the fall of 2003, the NASA Headquarters' Science Mission Directorate provided funding and direction to mature the technology as far as possible through ground research and development from TRL 3 to 6 in three years. A group of experts from government, industry, and academia convened in Huntsville, Alabama to define technology gaps between what was needed for science missions to the inner solar system and the current state of the art in ultra1ightweight materials and gossamer structure design. This activity set the roadmap for development. The centerpiece of the development would be the ground demonstration of scalable solar sail systems including masts, sails, deployment mechanisms, and attitude control hardware and software. In addition, new materials would be subjected to anticipated space environments to quantify effects and assure mission life. Also, because solar sails are huge structures, and it is not feasible to validate the technology by ground test at full scale, a multi-discipline effort was established to develop highly reliable analytical models to serve as mission assurance evidence in future flight program decision-making. Two separate contractor teams were chosen to develop the SSP System Ground Demonstrator (SGD). After a three month conceptual mission/system design phase, the teams developed a ten meter diameter pathfinder set of hardware and subjected it to thermal vacuum tests to compare analytically predicted structural behavior with measured characteristics. This process developed manufacturing and handling techniques and refined the basic design. In 2005, both contractor teams delivered 20 meter, four quadrant sail systems to the largest thermal vacuum chamber in the world in Plum Brook, Ohio, and repeated the tests. Also demonstrated was the deployment and articulation of attitude control mechanisms. In conjunction with these tests, the stowed sails were subjected to launch vibration and ascent vent tests. Other investments studied radiation effects on the solar sail materials, investigated spacecraft charging issues, developed shape measuring techniques and instruments, produced advanced trajectory modeling capabilities, and identified and resolved gossamer structure dynamics issues. Technology validation flight and application to a He1iophysics science mission is on the horizon.

Young, Roy↗
DOE OSTI2021

Mechanical Loads on Spent Nuclear Fuel in the General 30 cm Package Drop Scenario

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) research program is guided by the high-level goal of closing prioritized knowledge gaps related to spent nuclear fuel (SNF) storage and transportation, which are summarized by Saltzstein et al. (2020). One of the high-priority knowledge gaps is the identification and quantification of mechanical loads that are expected to affect SNF during normal conditions of transportation and storage to inform the range of physical SNF test programs. This report uses modeling and analysis methods to estimate the mechanical loads on spent nuclear fuel (SNF) in the general 30 cm package drop scenario. The drop scenario assumes impact limiters are in place in the transportation configuration and the impact surface is perfectly rigid. The goal of this analysis is to consider the universe of potential mechanical loading conditions that can happen to SNF and present the results in a manner that is useful for materials testing, decision making, and regulatory rule making purposes. This study uses validated finite element models and methods to perform a broad parametric study of key variables that can affect the mechanical loads on SNF during a hypothetical package free drop scenario. Physical drop test data from a cask and fuel assembly drop test campaign is the basis for model validation. Additionally, the results of the parametric study are used to inform a damage model, which uses multiple nonlinear regression to estimate the relationships between input variables and output response. The parametric finite element analyses consider thousands of input variable combinations, while the damage model estimates millions of combinations. The breadth of this study provides confidence that the potential range of mechanical loads that SNF might experience during the general 30 cm package drop scenario are characterized well enough to consider this knowledge gap closed. While this report documents the overall peak values calculated in this study, the 95 th percentile values, the histograms, and the observed trends are equally important. This study covered a large range of SNF temperatures, room temperature to 300°C, and burnups, 10 GWd/MTU to 62 GWd/MTU. Each temperature and burnup combination has a different cladding yield strain, so it is more meaningful to summarize the calculated cladding strain response as its factor of safety, which is defined relative to the yield strain. The factor of safety is calculated as the yield strain divided by the peak cladding strain. A factor of safety greater than unity indicates that the cladding remains below yield, whereas a value less than unity is indicative of plastic deformation. In all cases of this study a safety factor over 1.0 was calculated, although in the most limiting case at 300°C the safety factor was only 1.01, which suggests that yielding could occur when additional loads like rod internal pressure are included. When the temperature is restricted to 200°C the limiting safety factor increases to 1.28, which has significant margin to accommodate internal pressure and potential local cladding defects that could cause a local stress concentration. An important trend in the calculated fuel rod mechanical loads is that the 2 nd highest loaded fuel rod in an assembly tends to be significantly lower than the highest loaded rod. The implication is that even if one rod in an assembly experiences a failure the loads would have to be significantly higher to cause two or more rods to fail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗