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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Flight Test of Weather Data Exchange Using the 1090 Extended Squitter (1090ES) and VDL Mode 3 Data Links

This report describes preliminary results of work done by JHU/APL under contract to the NASA Glenn Research Center to support flight testing of the Universal Access Transceiver (UAT) data link as a medium for weather data exchange. It presents a high level architectural description of the use of UAT to meet the program objectives with an identification of issues associated with the use of this data link, including a high level definition of the changes required to UAT avionics and ground-based receivers and supporting ground infrastructure to support implementation of the recommended architecture with focus on the issues associated with these changes.

Griner, James H., Jr.↗
NASA NTRS2010

Asbestos Exposure Assessment Database

Exposure to particular hazardous materials in a work environment is dangerous to the employees who work directly with or around the materials as well as those who come in contact with them indirectly. In order to maintain a national standard for safe working environments and protect worker health, the Occupational Safety and Health Administration (OSHA) has set forth numerous precautionary regulations. NASA has been proactive in adhering to these regulations by implementing standards which are often stricter than regulation limits and administering frequent health risk assessments. The primary objective of this project is to create the infrastructure for an Asbestos Exposure Assessment Database specific to NASA Johnson Space Center (JSC) which will compile all of the exposure assessment data into a well-organized, navigable format. The data includes Sample Types, Samples Durations, Crafts of those from whom samples were collected, Job Performance Requirements (JPR) numbers, Phased Contrast Microscopy (PCM) and Transmission Electron Microscopy (TEM) results and qualifiers, Personal Protective Equipment (PPE), and names of industrial hygienists who performed the monitoring. This database will allow NASA to provide OSHA with specific information demonstrating that JSC s work procedures are protective enough to minimize the risk of future disease from the exposures. The data has been collected by the NASA contractors Computer Sciences Corporation (CSC) and Wyle Laboratories. The personal exposure samples were collected from devices worn by laborers working at JSC and by building occupants located in asbestos-containing buildings.

Arcot, Divya K.↗
NASA NTRSDate not supplied

Hourly Stream Heights – A Short-term Deep Learning Prediction Model

River flooding can have a detrimental impact on a community by causing loss of life, loss or damage to property, and damage to infrastructure. Having the capability to forecast flooding events can prevent the loss of life and mitigate damage to property. A programmatic, data-driven approach using deep learning to forecast a stream’s gauge height every 6 hours has been developed by NASA’s Short-term Prediction Research and Transition Center (SPoRT) and is currently in operation. Based on our end user engagement and feedback, this medium-term product has been successfully adopted by several National Weather Service (NWS) Forecast Offices and River Forecast Centers (RFC). SPoRT is currently researching and developing a short-term hourly deep learning model which will be useful in forecasting flash flood events.

Michael Antia↗
NASA NTRS2024

Considerations for Using Autonomous Flight Termination Software in Crewed Launch Vehicles

Autonomous flight termination systems (AFTS) are being progressively employed onboard launch vehicles to replace ground personnel and infrastructure needed to terminate flight or destruct the vehicle should an anomaly occur. This automation uses on-board real-time data and encoded logic to determine if the flight should be self-terminated. For uncrewed launch vehicles, FTS systems are required to protect the public and governed by the United States Space Force (USSF). For crewed missions, NASA must augment range AFTS requirements for crew safety and certify each flight according to human rating standards, thus adding unique requirements for reuse of software originally intended for uncrewed missions. This bulletin summarizes new information relating to AFTS to raise awareness of key distinctions, summarize considerations and outline best practices for incorporating AFTS into human-rated systems.

Avionics↗
DOE OSTI2021

Integration of Rucio in Belle II

The Belle II experiment, which started taking physics data in April 2019, will multiply the volume of data currently stored on its nearly 30 storage elements worldwide by one order of magnitude to reach about 340 PB of data (raw and Monte Carlo simulation data) by the end of operations. To tackle this massive increase and to manage the data even after the end of the data taking, it was decided to move the Distributed Data Management software from a homegrown piece of software to a widely used Data Management solution in HEP and beyond : Rucio. This contribution describes the work done to integrate Rucio with Belle II distributed computing infrastructure as well as the migration strategy that was successfully performed to ensure a smooth transition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Automated Inventory Solutions in End-User IT Support

Managing IT equipment by hand is prone to errors and delays, severely impacting operational continuity and productivity. Manual inventory systems often result in time delays, inconsistent record-keeping, equipment shortages, and increased workloads for IT staff. At Savannah River National Laboratory (SRNL), my internship focused on creating an automated inventory management solution using Microsoft Power Automate and SharePoint Lists. This solution seamlessly integrates with the existing Microsoft 365 infrastructure, thus eliminating the need for additional software purchases or dedicated server space. By providing real-time updates and reducing manual data entry, the new system ensures a more reliable and maintainable approach to IT asset management.

Information Technology↗
DOE OSTI2022

Wabash CarbonSAFE. Final Report

This document summarizes work detailed in separate Wabash CarbonSAFE reports; the report describes the data collection efforts of the project and consolidates the geologic characterization, well testing, and storage complex modeling results for the Mt. Simon Sandstone and Potosi Dolomite, two distinct reservoirs characterized at the Wabash CarbonSAFE project site. Also presented are summaries of work to characterize the CO 2 source and infrastructure network, as well as summaries of reports analyzing stakeholder engagement options, policy, regulatory and legal considerations, and risk assessment associated with the Wabash CarbonSAFE project site. The report then presents recommendations for the next steps for site characterization, identifies data gaps for future activities, and provides an overall assessment of site potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Los Alamos National Laboratory LiDAR Processing and Hydro-Enforcement Report

This report describes a project conducted by Los Alamos National Laboratory (LANL) and 3AE Green to process and hydro-enforce LiDAR data over approximately 170 square miles. A variety of Government Furnished Information (GFI) including LiDAR (2021), 3-inch pixel resolution natural-color imagery (2018), stormwater infrastructure, culvert, bridge, and building features were analyzed to develop a hydro-enforced digital elevation model (DEM). Where overland flow was obstructed by elevation surface feature, representational cutline features were placed and integrated into the LiDAR-based elevation surface to allow for more appropriate flow across roadbeds and other impediments to natural flow. This hydro-enforced DEM was utilized to model and develop more than 6.5 million three-dimensional (3D) vector flow line features (prior to line joining / merging) representing the derived digital drainage network deliverable.

42 ENGINEERING↗
DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗
DOE OSTI2021

Data-driven model generation for deception defence of cyber-physical environments

Cyber-physical systems have the potential to greatly improve both the economic and the environmental efficiency of our current infrastructure. However, the necessary fusing of the cyber world with the physical world that results from these technologies also creates a host of new attack opportunities. In this work, we discuss how deception can be employed to effectively defend these systems.

Nowak, Kathleen E.↗
DOE OSTI2025

Comparing multi-source urban flood indicators: satellite, simulation, and citizen-reported data

Urban flooding arises from complex mechanisms, making it challenging to capture accurately with a single detection method. This study evaluates three complementary approaches to detect flooding across three Chicago neighborhoods: (i) Sentinel-1 synthetic aperture radar (SAR), offering weather-independent, high-resolution (10 m) imagery of surface inundation; (ii) the storm water management model (SWMM), simulating combined sewer overflow and drainage performance; and (iii) citizen-generated 311 service requests, capturing observed flooding impacts. By analyzing six storms ranging from severe to mild, we examine how each source uniquely contributes to identifying urban flood events. SAR imagery effectively identifies standing water but can miss brief flooding due to satellite revisit constraints. SWMM provides detailed insights into system-wide drainage behavior yet may underestimate localized street-level flooding. Meanwhile, 311 calls reflect real-world flooding impacts but are vulnerable to underreporting. Statistical overlap analysis highlights chronic flood hotspots repeatedly identified across multiple detection methods, indicating persistent infrastructure and topographic vulnerabilities. Temporal analysis further reveals that while SWMM flooding aligns closely with rainfall peaks, 311 calls typically precede or persist beyond these peaks. Our findings emphasize the value of using satellite observations, hydrological modeling, and resident-reported data in a complementary manner to better interpret patterns in flood timing, severity, and spatial distribution—providing insights that can inform targeted infrastructure improvements and contribute to urban flood resilience planning.

311↗
DOE OSTI2023

EmSense: A High-Resolution Emulated Sensor for Experiments with the Smart Grid and Distributed Ledger Technology

This work involves the development of a device - EmSense (“Emulated Sensor”) - that emulates a high-resolution sensor for a power grid. The device collects raw current and voltage sensor data which derive from ORNL's signature library. This library is a dataset that ORNL curates from many different sources that include power systems from various utilities. The EmSense packages the data from the library in the form of IEC 61850 Sampled Value (SV) packets and then broadcasts these SV packets on the network. In another mode, EmSense can generate artificial sinusoidal data that appears as waveforms for voltage and current signals. EmSense has an internal algorithm for determining the period of a signal based on the data so that the period can be specified as a variable in the IEC 61850 packets. The purpose of EmSense is to allow for experimentation with the Dark Net Infrastructure where a variety of power line sensors must be represented along with their typical communication traffic. The EmSense device was developed in coordination with the software for receiving and processing the packets in the Distributed Ledger Technology (DLT) framework of the DarkNet Project. This receiving software must have a methodology for dealing with information of high velocity, variety, and volume. Experimenting with EmSense facilitates the development of such software. The results showed that the DLT framework and the trust-anchoring approach managed to process a large flow of traffic even with up to six instances of EmSense device broadcasting data. This was achieved without overfilling packet queues in the memory of the actual hardware of the DLT devices or causing the Central Processing Unit (CPU) of the hardware to be overwhelmed. The DLTs were also able to store the data in a compact and useful form for later analysis and archival purposes.

Werth, Aaron↗
NASA NTRS2021

PEM Fuel Cell MODEL for Conceptual Design of Hydrogen eVTOL Aircraft

A model and software for design and analysis of a Proton Exchange Membrane fuel cell (PEMFC) system are developed for hydrogen eVTOL aircraft. Examples are provided of stacks designed for 80 kWe and 500 kWe net electrical power. Examples are provided of eVTOL designed for 250 and 400 lb payload. The trade-offs included stack characteristics, hydrogen storage characteristics, and aircraft payload and range. The objectives were to identify the key technology drivers of a hydrogen rotorcraft, establish technology targets for a viable aircraft, and recommend research to address the fundamental pre-competitive barriers. The current U.S. infrastructure on hydrogen informed the targets and recommendations. The key conclusion is that the advances made in cell electrochemical power density over the last decade might allow a PEMFC system to meet, or even beat, piston engine powered light-utility rotorcraft. The development must focus on the key drivers of a hydrogen eVTOL. The drivers are ultra-light stack cooling and short-term hydrogen storage. A stack system of net electrical power 100−150 kWe with specific power 1.1 kWe/kg including air, cooling, and electrical subsystems, and a tank storage of 15% weight fraction hydrogen are the minimum targets to meet the performance of a modern piston-engine rotorcraft, with a range of 180 nautical miles, payload of 400 lb, and gross weight of about 1400 lb. This is defined as the objective aircraft. If only one target is met, an aircraft of half the range could be produced, with a 30% greater gross take-off weight. This is defined as an intermediate aircraft. Because definitive conclusions are premature without weights and loads data on a flight-worthy stack system, it is recommended that a fuel cell powered hydrogen eVTOL demonstrator be built and flown. The existing hydrogen infrastructure for cars provide ample opportunity to create a pilot program. About 12 metric tons of retail hydrogen are available for cars every day in California, which is less than 0.05% of the yearly hydrogen production in the U.S.. A hypothetical fleet of 100 aircraft, operating 3 flights a day, would increase the demand by 2.25 tons per day and require 140 MWh of renewable electricity for green hydrogen.

PEM↗
NASA NTRS2023

Exploring Natural and Social Drivers of Forest Degradation in Post-Soviet Georgia

The Caucasus Mountains harbor high concentrations of endemic species and provide an abundance of ecosystem services yet are significantly understudied compared to other ecosystems in Eurasia. In the country of Georgia, at the heart of the Caucasus region, forest degradation has been the largest land change process over the last thirty years. The prevailing narrative is that legal and illegal cutting of trees for fuelwood is primarily responsible for this process. Yet, since independence from the Soviet Union in 1991, the country has undergone rapid socioeconomic and institutional changes which have not been explored as drivers of forest change. We combine newly available land-cover change estimates, Georgian statistical data, and historical institutional change data to examine socioeconomic drivers of forest degradation. Our analysis controls for concurrent changes in climate that would affect degradation and examines variation at the regional (state) level from 2011 to 2019, as well as at the national level from 1987 to 2019. We find that higher winter temperature and drought are associated with higher degradation at the regional scale, while major institutional changes and drought are associated with higher forest degradation at the national level. Access to natural gas, the major energy alternative to fuelwood, had no significant association with degradation. Our results challenge the narrative that poverty and a lack of alternative energy infrastructure drive forest degradation and suggest that government policies banning household fuelwood cutting, including the new Forest Code of 2020, may not reduce forest degradation. Given these results, improved data on wood harvesting and more research on the commercial drivers of degradation and their links to economic and political reforms is needed to better inform forest policy in the region, especially given ongoing risks from climate change.

Institutions↗
NASA NTRS2006

Moving Towards a Common Ground and Flight Data Systems Architecture for NASA's Exploration Missions

The National Aeronautics and Space Administration has embarked on an ambitious effort to return man to the moon and then on to Mars. The Exploration Vision requires development of major new space and ground assets and poses challenges well beyond those faced by many of NASA's recent programs. New crewed vehicles must be developed. Compatible supply vehicles, surface mobility modules and robotic exploration capabilities will supplement the manned exploration vehicle. New launch systems will be developed as well as a new ground communications and control infrastructure. The development must take place in a cost-constrained environment and must advance along an aggressive schedule. Common solutions and system interoperability and will be critical to the successful development of the Exploration data systems for this wide variety of flight and ground elements. To this end, NASA has assembled a team of engineers from across the agency to identify the key challenges for Exploration data systems and to establish the most beneficial strategic approach to be followed. Key challenges and the planned NASA approach for flight and ground systems will be discussed in the paper. The described approaches will capitalize on new technologies, and will result in cross-program interoperability between spacecraft and ground systems, from multiple suppliers and agencies.

Rader. Steve↗
DOE OSTI2020

Plug-in electric vehicles in China and the USA: a technology and market comparison

As the top two plug-in electric vehicle (PEV) markets in the world, China and the United States of America (USA) have developed different market structures that are influenced by government policies, test procedures, customer acceptance, and vehicle performance. There are differences in PEV test procedures and vehicle class definitions as well. This paper quantifies such differences and compares PEV characteristics and markets in the two countries using actual data collected over several years. First, although China surpasses the USA in annual PEV production because of generous PEV policies and higher charging infrastructure availability, the USA has a higher PEV adoption rate per capita (2.3 versus 0.81 per 1000 people at the end of 2017). Second, the most popular vehicle classes are A00 battery electric vehicles (BEVs) in China but long-range mid-size BEVs in the USA. Moreover, China's electric and plug-in hybrid sport utility vehicle market is growing quickly. Third, the electricity consumption rated under Chinese test procedures is 20%-40% lower than that rated under US procedures. The sales-weighted electricity consumption of an average BEV in China is 23% lower than that in the USA because of larger proportions of small and micro BEVs in China. Fourth, PEV battery cost in the two countries is currently close to $210-$220 kWh. Finally, China has higher numbers of charging infrastructure, and the ratio of PEVs to public chargers is 9.0 in China versus 17.9 in the USA at the end of 2018.

China EV market↗
DOE OSTI2023

Scale‐Dependent Influence of Permafrost on Riverbank Erosion Rates

Abstract Whether permafrost systematically alters the rate of riverbank erosion is a fundamental geomorphic question with significant importance to infrastructure, water quality, and biogeochemistry of high‐latitude watersheds. For over four decades, this question has remained unanswered due to a lack of data. Using remotely sensed imagery, we addressed this knowledge gap by quantifying riverbank erosion rates across the Arctic and subarctic. To compare these rates to non‐permafrost rivers, we assembled a global data set of published riverbank erosion rates. We found that erosion rates in rivers influenced by permafrost are on average nine times lower than non‐permafrost systems; erosion rate differences increase up to 40 times for the largest rivers. To test alternative hypotheses for the observed erosion rate difference, we examined differences in total water yield and erosional efficiency between these rivers and non‐permafrost rivers. Neither of these factors nor differences in river sediment loads provided compelling alternative explanations, leading us to conclude that permafrost limits riverbank erosion rates. This conclusion was supported by field investigations of rates and patterns of erosion along three rivers flowing through discontinuous permafrost in Alaska. Our results show that permafrost limits maximum bank erosion rates on rivers with stream powers greater than 900 Wm −1 . On smaller rivers, however, hydrology rather than thaw rate may be the dominant control on bank erosion. Our findings suggest that Arctic warming and hydrological changes should increase bank erosion rates on large rivers but may reduce rates on rivers with drainage areas less than a few thousand km 2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enabling Seamless Integration of EV Charging Infrastructure with Weak Electric Grids

Widespread adoption of Electric Vehicles (EVs) for light, medium, and heavy-duty applications has gained significant interest. Based on ownership and user preferences, light duty and local delivery medium-duty EVs are typically connected to grid distribution networks whereas larger medium duty and heavy-duty EVs are typically connected to distribution or even sub-transmission networks. Challenges with at-scale EVs and charging infrastructure supporting them include interoperability, distribution network upgrades, surge in demand charges, power quality issues, voltage stability, etc. Based on real-world data, steady-state and dynamic assessments of light-duty EV charging with a focus on DC Fast Charging (DCFC) for weak distribution grids is presented. Three main areas of contributions in this paper include - steady state and dynamic power quality measurements and assessments using real world data, transient assessments of light duty EV integration with weak distribution networks (IEEE 13 node feeder system) under grid-connected and microgrid modes, and formulation of an intelligent charging decision algorithm to enable an impact-minimal charging.

actionable intelligence↗