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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 397 records · Page 22

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NASA NTRS2023

Highly Restricted Near‐Surface Permafrost Extent During the Mid-Pliocene Warm Period

To better understand how near‐surface permafrost may respond to future warming, we explore the equilibrium spatial extent of near‐surface permafrost during the mid-Pliocene warm period (mPWP), which shares characteristics of the projected future climate. Our simulations, which are constrained by proxy records, suggest highly restricted near‐surface permafrost extent during the mPWP, akin to future large-scale permafrost degradation projections of our model for the end of this century. Our study indicates dramatically smaller-than-present near‐surface permafrost extent in the geological past under climate conditions analogous to those expected if global warming continues unabated. This absence in permafrost will come with critical implications for the global carbon cycle, human livelihoods and infrastructures, and surface and subsurface hydrology.

near‐surface permafrost↗

DOE OSTI2025

Analysis of Hydrogen Supply Chain Readiness in Selected Indo-Pacific Countries

This report explores the low-carbon hydrogen production and procurement targets of Indo-Pacific Economic Framework for Prosperity (IPEF) countries, highlighting key cost and infrastructure considerations. By 2030, production costs are targeted between US$\$$1.4-4.8/kg-H2, with procurement prices at US$\$$2.3/kg-H2, narrowing further by 2050. Midstream costs, including storage and transportation, are critical to meeting these targets and enabling hydrogen trade. The report discusses challenges such as infrastructure readiness, regulatory frameworks, and the need for improved data reporting. It emphasizes the importance of tax incentives, research investments, and port readiness to support the growth of low-carbon hydrogen markets in the region.

08 HYDROGEN↗

NASA NTRS2004

Scalable collaborative risk management technology for complex critical systems

We describe here our project and plans to develop methods, software tools, and infrastructure tools to address challenges relating to geographically distributed software development. Specifically, this work is creating an infrastructure that supports applications working over distributed geographical and organizational domains and is using this infrastructure to develop a tool that supports project development using risk management and analysis techniques where the participants are not collocated.

requirements prioritization↗

DOE OSTI2025

The Workforce Readiness Index: A Local and Regional Assessment Tool for Energy Sector Preparedness

Building up a workforce that is properly trained and adequately sized is essential to ensuring that the deployment of energy generation sources in the United States meets future energy demand. Workforce development to support supply chain or large infrastructure investments typically occurs at a local level. However, there is a critical gap in understanding where and to what extent regional workforces are equipped to meet the needs of an energy industry. The Workforce Readiness Index ("the index") was developed to assess and compare energy sector workforce readiness across the United States at the county level to provide granular information to various stakeholders such as industry members, state decision makers, and training program developers. Workforce readiness is defined as the ability to recruit from the general labor market, transition workers with comparable skill sets, and train a workforce using scalable or existing training programs near a specific location. Therefore, the index evaluates readiness levels based on the likelihood that a county possesses the workforce development infrastructure needed to support the occupations required by an energy-related industry or sector. Furthermore, the index offers a standardized yet flexible approach that captures regional variations and highlights local strengths and challenges.

17 WIND ENERGY↗

DOE OSTI2026

The LCLStream Ecosystem for Multi-Institutional Dataset Exploration

We describe a new end-to-end experimental data streaming framework designed from the ground up to support new types of applications – AI training, extremely high-rate X-ray time-of-flight analysis, crystal structure determination with distributed processing, and custom data science applications and visualizers yet to be created. Throughout, we use design choices merging cloud microservices with traditional HPC batch execution models for security and flexibility. This project makes a unique contribution to the DOE Integrated Research Infrastructure (IRI) landscape. By creating a flexible, API-driven data request service, we address a significant need for high-speed data streaming sources for the X-ray science data analysis community. With the combination of data request API, mutual authentication web security framework, job queue system, high-rate data buffer, and complementary nature to facility infrastructure, the LCLStreamer framework has prototyped and implemented several new paradigms critical for future generation experiments.

Rogers, David [ORNL] (ORCID:0000000251871768)↗

DOE OSTI2026

Mauka Energy FEVER Tool Dataset

Mauka Energy’s dataset, developed under the Forestry Electric Vehicle Energy Routing (FEVER) project and funded by the U.S. Department of Energy’s Small Business Innovation Research program, is a high-resolution geospatial resource designed to support energy modeling for electric log trucks in complex forestry environments. The dataset integrates detailed spatial and road network data to enable accurate simulation of vehicle performance across varied terrain. At its core, the dataset incorporates lidar-derived elevation models, road alignments, and surface classifications from Oregon State University’s McDonald-Dunn Research Forest. These data capture fine-scale variations in slope, curvature, and surface conditions across forest road systems, allowing for vehicle-level analysis of energy consumption and recovery. The dataset also includes data collected on the surrounding public and private road networks in Benton County, Oregon, used in real-world haul routes. These connecting segments provide critical context for modeling transitions between forest operations and regional transportation infrastructure, incorporating attributes such as grade profiles, elevation change, and speed constraints. This combined dataset underpins the development of Mauka Energy’s rolldown tool, which quantifies energy use and regenerative braking potential on downhill and variable-grade segments. By leveraging high-resolution terrain and road data, the FEVER project enables more accurate assessment of electric vehicle feasibility and performance in forestry applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Manufacturing and Additive Design of Electric Machines by 3D Printing (MADE3D) (Final Technical Report)

As the U.S clean energy transition hinges on the growth of offshore wind, this is expected to be a major driver for innovations in manufacturing, material and design advancements to enable robust and cost-competitive wind turbines. The race to build larger and taller turbines rated 10 megawatts (MW) and beyond, has intensified pressure on OEMs in terms of logistics of handling and transporting large wind components, securing critical raw material as well as scaling up necessary domestic production infrastructure to meet the demand. There is increased interest in building lightweight, more efficient, and high-power dense drivetrains that will ease the burden on installation, minimize the raw material demand, increasing domestic sourceability. Despite good efficiency and reliability, existing drivetrain technologies such as direct-drive permanent magnet generators are heavy (> 300 tons), expensive, and often rely on large quantities of rare-earth permanent magnets (PMs), steel and copper.

17 WIND ENERGY↗

DOE OSTI2025

Recycling Wind Energy Systems in the United States Part 1: Providing a Baseline for America's Wind Energy Recycling Infrastructure for Wind Turbines and Systems

The U.S. investments in building this new wind energy capacity will not only mobilize millions of tons of raw and processed materials in existing supply chains, some of which are critical materials, but also create new types and large volumes of end-of-life (EOL) waste streams. Building efficient, cost-effective, and environmentally responsible EOL management infrastructure of wind energy system components is pivotal in diverting upcoming volumes of waste stream from landfills, recovery of critical materials and reducing life cycle emissions from production of primary commodity materials . The primary goal of this report is to organize and communicate findings from this assessment on how alternate materials, designs and manufacturing processes could enable more efficient, cost-effective, and environmentally responsible disassembly and resource recovery from wind energy technologies. The findings of this assessment could inform prioritization of RD&D investment spending to meet Energy Act of 2020 directions. This assessment focused on key RD&D recommendations for three main temporal phases: Short-term (2023-2026), medium-term (2026 through 2035) and long-term (beyond 2035).

17 WIND ENERGY↗

DOE OSTI2026

American Made Infrastructure: Evolution of Federal Incentives and Requirements

Foreign Entity of Concern (FEOC) restrictions in the One Big Beautiful Bill Act (OBBB) represent the latest evolution of a multi-year legislative trajectory responding to national security concerns about foreign control – and particularly FEOC control – of energy infrastructure. Beginning with Executive Order 14017 (February 2021), which initiated comprehensive federal review of critical supply chain vulnerabilities in semiconductors, battery energy storage systems, and critical minerals, policymakers have progressively expanded restrictions on foreign participation. The National Defense Authorization Act (NDAA) 2019 established precedent for component-level prohibitions on foreign information and communications technology procurement, while NDAA 2024 extended these restrictions to six major People’s Republic of China (PRC) battery manufacturers. Complementary measures such as the Build America, Buy America (BABA) Act and the Infrastructure Investment and Jobs Act (IIJA) introduced domestic content thresholds and FEOC eligibility criteria for federal funding programs. The Inflation Reduction Act (IRA) 2022 further operationalized FEOC restrictions through electric vehicle tax credit requirements, creating a scalable framework for excluding foreign-controlled components. Recent executive actions and state-level policies have reinforced this trajectory, reflecting sustained alignment across federal and state governments. Collectively, these developments demonstrate a bipartisan policy approach that pairs incentives for advanced energy deployment with safeguards designed to prevent subsidizing adversaries or entities that present foreign-sourcing risk.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗

NASA NTRS1999

Development of a Free-Flight Simulation Infrastructure

In anticipation of a projected rise in demand for air transportation, NASA and the FAA are researching new air-traffic-management (ATM) concepts that fall under the paradigm known broadly as ":free flight". This paper documents the software development and engineering efforts in progress by Seagull Technology, to develop a free-flight simulation (FFSIM) that is intended to help NASA researchers test mature-state concepts for free flight, otherwise referred to in this paper as distributed air / ground traffic management (DAG TM). Under development is a distributed, human-in-the-loop simulation tool that is comprehensive in its consideration of current and envisioned communication, navigation and surveillance (CNS) components, and will allow evaluation of critical air and ground traffic management technologies from an overall systems perspective. The FFSIM infrastructure is designed to incorporate all three major components of the ATM triad: aircraft flight decks, air traffic control (ATC), and (eventually) airline operational control (AOC) centers.

Miles, Eric S.↗

DOE OSTI2025

A microgrid deployment framework to support drayage electrification

The electrification of heavy-duty commercial vehicles (HDCVs) is key to enhancing air quality and reducing urban air pollution, but it also imposes significant demands on an electric grid not designed for such high loads. Without complementary infrastructure, electrification may yield limited air quality improvements. This article explores the critical role of microgrids—integrating solar photovoltaics and battery storage—in supporting HDCV electrification. We present an integrated framework to identify viable microgrid sites in a given region, estimate deployment costs, and optimize power use to reduce dependence on the grid. As a case study, we apply the framework to the region around the Port of Savannah, GA, USA, demonstrating how targeted microgrid deployment can enhance grid capacity, improve energy resiliency, and support electrified freight transport.

Electrical engineering↗

DOE OSTI2024

EVI-RoadTrip™: Electric Vehicle Infrastructure for Road Trips [SWR-22-17]

The EVI-RoadTrip™ tool offers high-resolution refueling network design and analysis to inform electric vehicle (EV) charging infrastructure development for road trips or long-distance travels. EVI-RoadTrip helps infrastructure planners, analysts, and decision makers evaluate EV energy consumption and corresponding charging demands along the routes-between origin and destination. It considers the projected location and characteristics of charging stations, potential electric grid impacts, and required infrastructure improvements. Strategically located charging stations for long-distance travel are critical to enabling the widespread adoption of EVs by allowing them to travel further beyond city or town boundaries. Sophisticated analysis and planning can identify the points (e.g., corridors) that may require increased availability of EV charging stations to support electrified road trips.

Wood, Eric↗

DOE OSTI2026

Chemical Recommender System: Replacement Suggestions for Small Molecules

The Chemical Recommender System (CRS) is an open-source, high-performance toolkit that enables real-time similarity searches across the complete PubChem database (over 50 million molecules) using commodity hardware. The CRS addresses critical limitations in existing chemical informatics platforms through a novel vector database infrastructure, extensible model integration capabilities, and complete algorithmic transparency. The system implements a vector database deployment with partitioned indexing that achieves a ~60x speedup over traditional approaches. A containerized model integration framework allows researchers to seamlessly incorporate custom predictive models into the full-scale search and scoring pipeline, while complete configurability of search parameters, filtering logic, and scoring functions provides capabilities not available in existing black-box solutions. Beyond structural similarity, the CRS integrates OPERA QSAR models for thermophysical and toxicity predictions, RDKit synthetic accessibility scoring, and user-defined models to compute weighted final replacement scores. The complete system is accessible through an interactive web application supporting real-time progress monitoring, post-processing score re-weighting, automated PDF reporting, and batch processing capabilities.

Nair, Parthiv Anand [Sandia National Laboratories ↗

NASA NTRS2013

Onboard Radar Processor Development for Disaster Response

Natural hazards often result in significant loss of human lives, economic assets and productivity as well as significant damage to the ecosystem. Scientists have reported more frequent and intense natural disasters in recent years, which may well be attributed to climate change. Many of the disaster response efforts were hampered by lack of up-to-date knowledge of the state of the affected areas because damaged infrastructure rendered the areas inaccessible. Radar remote sensing is playing an increasingly critical role in providing timely information to disaster response agencies due to the increasing fidelity and availability of geospatial information products.

VV (vertical transmit and vertical receive)↗

NASA NTRSDate not supplied

Preparations for Laser Rayleigh Scattering Flow Visualization of Inert Ethane Plumes in PSI Environments at the NASA Langley 60-ft Vacuum Sphere

Understanding of the interaction between the plume and the regolith during powered descent are critical for reliable landings and to avoid damaging the vehicle or nearby infrastructure. To further study this complex flowfield, preparations are underway to describe the interrogation of an impinging ethane plume in lunar-relevant conditions within the 60-ft vacuum sphere at LaRC using Rayleigh diagnostics.

Flow Visualization↗

DOE OSTI2024

Critical needs to close monitoring gaps in pan-tropical wetland CH 4 emissions

Global wetlands are the largest and most uncertain natural source of atmospheric methane (CH 4 ). The FLUXNET-CH 4 synthesis initiative has established a global network of flux tower infrastructure, offering valuable data products and fostering a dedicated community for the measurement and analysis of methane flux data. Existing studies using the FLUXNET-CH 4 Community Product v1.0 have provided invaluable insights into the drivers of ecosystem-to-regional spatial patterns and daily-to-decadal temporal dynamics in temperate, boreal, and Arctic climate regions. However, as the wetland CH 4 monitoring network grows, there is a critical knowledge gap about where new monitoring infrastructure ought to be located to improve understanding of the global wetland CH 4 budget. Here we address this gap with a spatial representativeness analysis at existing and hypothetical observation sites, using 16 process-based wetland biogeochemistry models and machine learning. We find that, in addition to eddy covariance monitoring sites, existing chamber sites are important complements, especially over high latitudes and the tropics. Furthermore, expanding the current monitoring network for wetland CH 4 emissions should prioritize, first, tropical and second, sub-tropical semi-arid wetland regions. Considering those new hypothetical wetland sites from tropical and semi-arid climate zones could significantly improve global estimates of wetland CH 4 emissions and reduce bias by 79% (from 76 to 16 TgCH 4 y -1 ), compared with using solely existing monitoring networks. Our study thus demonstrates an approach for long-term strategic expansion of flux observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Evaluating hydrogen permeation through medium-density and high-density polyethylene pipes to enable a hydrogen-compatible infrastructure

As the United States and the global community pursue energy abundance and resilience, hydrogen is becoming a critical energy carrier. The future of hydrogen transport depends on one thing: verifying that today’s pipelines are hydrogen ready. This study investigates the permeation behavior of medium-density polyethylene (MDPE) and high-density polyethylene (HDPE) pipelines under pure hydrogen gas environment at various pressures and temperatures. Using thermal desorption analysis (TDA) and direct pipe permeability measurements, hydrogen loss rates are quantified, revealing minimal permeation losses (< 10.5 g/km/day) under realistic operating conditions. Effects of temperature and pressure with Standard Dimension Ratios (SDR), were evaluated to determine their influence on permeation rates of MDPE and HDPE pipelines. In addition, ex-situ density and degree of crystallinity (DOC) of MDPE and HDPEs after hydrogen exposure were also investigated to understand pressure-dependency of polymer properties. The findings provide essential data for assessing polymer-based pipeline materials for safe and reliable hydrogen transport.

08 HYDROGEN↗