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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessment of Economic Viability of Direct Current Fast Charging Infrastructure Investments for Electric Vehicles in the United States

As the global transportation sector increasingly adopts electric vehicles, the demand for advanced and accessible charging infrastructure is rising. In addition to at-home electric vehicle (EV) charging, there is a growing need for the swift development of commercial direct current fast charging (DCFC) stations to meet on-the-go EV charging demands. While government funds are available to support the expansion of the EV charging network in the United States, the establishment of a robust nationwide EV charging infrastructure requires significant private sector investment. This study was conducted to assess the economic feasibility of various business models for fast charging stations in the U.S. using two case studies and exploring different operational strategies including sole ownership and collaborative ventures with public and private entities. The results indicate that based on the current adoption and utilization rates in the U.S., the business model involving an owner-operator collaborating with a public partner ensures profitability and protects the investment in DCFC stations from financial losses. The study also highlights that demand charges and electricity retail prices are the factors that affect the profitability of a DCFC station.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Scaleup of Microwave Powder Bed Fusion for Lunar Infrastructure Construction

NASA and its partners are seeking to establish a sustainable and permanent presence on the Moon. Like explorers on Earth, making use of natural resources upon arrival at the destination will be paramount. In-situ resource utilization of the lunar regolith will enable efficient construction of lunar infrastructure. Transforming the granular regolith into a solid can be achieved in many ways. One method is to use microwave energy to sinter the regolith into various structures. The lunar regolith has a low thermal conductivity, but microwaves can volumetrically heat it to bind the granular particles together in an energy efficient manner. One concept that is being developed and evaluated to sinter the regolith into infrastructure uses the Moon’s surface as a powder bed. Regolith would be added to the sintered lunar structure to build up layers to create structures such as landing pads, blast shields, roads, etc. Microwave systems, concept of operations, and sintering protocols are being developed to create a sub-element structure targeted for a lunar demonstration mission.

microwave↗
NASA NTRS2022

Developing a Vision for Heliophysics Infrastructure

The current infrastructure in heliophysics acts as a barrier towards progress due to the lack of intelligent connections between the many valuable resources in our field. Due to the large scale of this problem, the path to a productive infrastructure requires community collaboration towards a common vision. This white paper presents a broad overview of what that vision could be and a path forward.

Infrastructure↗
DOE OSTI2024

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges: Preprint

Recent advancement in autonomous driving vehicles and V2X communication has attracted increasing attention towards Intelligent Transportation Systems to build a safe and reliable traffic intersection. However, most of the systems are still at the initial stages and require significant progress to become a reality. This paper presents an overview of NREL Infrastructure Perception and Control (IPC) framework which is an open-source track-data fusion engine which takes input from infrastructure-based perception sensors and cooperatively shared messages from Connected Autonomous Vehicles (CAVs) and Connected Vehicle (CVs) and the challenges associated with deploying such cooperative perception framework at a four-way traffic intersection in the city of Colorado Springs, CO, USA. The sensor data is collected by deploying two radars and two LiDAR sensors on the IPC mobile lab and two radars on diagonally opposite traffic poles at the proposed intersection. The sensor output results imply the need for rapid sensor calibration to bring the collective perception to a common coordinate frame, the importance of time synchronization between the sensors in order to capture accurate spatial and temporal alignment of the objects, and the need for a health monitoring system with fail safe closed-loop detection model for real-time deployment.

camera↗
DOE OSTI2024

Visualizing Organizational Influence on Energy Infrastructure

Energy Infrastructure components depend on an evolving, interdependent business ecosystem exposed to long-term, legal, adversarial tactics. An INL-Naval Postgraduate School partnership was designed to support INL Lab Directed Research and Development, NPS graduate research projects, and joint publications. The Technology, Organization, and Person of interest Graph Extraction, Analysis, and Reporting (TOP GEAR) enumerates networks of organizations and people that own, operate, and maintain regional infrastructure assets. TOP GEAR allows analysts to model current and future state what-if scenarios that include technological and policy mitigations.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2026

Operations and Maintenance for Electric Vehicle Charging Infrastructure in Indian Country

This fact sheet provides an overview of operations and maintenance (O&M) costs, responsibilities, and contracts to help ensure EV charging infrastructure remains functional and reliable in Indian Country. O&M planning is important for Tribes to consider at the beginning of EV charging infrastructure projects to help ensure charger uptime and longevity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Cybersecurity for Digital Energy Infrastructure : Trends, Threats, and Cyber-Informed Engineering

This presentation discusses the rise in digital energy infrastructure and associated threats. It covers an in-depth risk assessment of digital energy equipment and provides real world examples of threats, vulnerabilities, and known incidents. Research conducted by INL assessing and addressing these risks follows, concluding with a dive into Cyber-Informed Engineering (CIE) and it's application to digital energy infrastructure, using battery energy storage systems (BESS) as an example.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Land-use analysis using infrastructure representations and high-resolution flood inundation mapping techniques

In the face of climate change and population growth in coastal regions, land-use analysis efforts are more challenging than ever. Land-use decision-makers in coastal communities are burdened with the difficult choices of where to place new homes versus other assets. While there has been an increased focus on hazard mitigation and disaster resilience in the field of planning, evidence points towards continued development in risk-prone areas including flood zones. Residential development within flood zones specifically continues to be a major issue. To help counter this trend, this study introduces a novel land-use analysis method, coupling topographic flood inundation mapping techniques with digital elevation model (DEM) adaptations. This Topographic Model Scenario Generation workflow can be used by planners early in the land-use decision making process and provides an alternative to high-computational hydraulic models. The analysis also includes the identification of strengths and weaknesses of topographic models' recognition of built infrastructure assets, adding to a limited body of knowledge addressing recommended uses of such models. Levees and canals prove particularly functional in this context while detention ponds less so, likely due to a lack of total water mass accountability. Lastly, we provide a functional demonstration in Southeast Texas to illustrate the workflow's ability to create multiple infrastructure scenarios and visualize their effects across different flood events.

42 ENGINEERING↗
DOE OSTI2026

System-of-systems optimization of hydrogen infrastructure for heavy-duty freight corridors: The interstate 10 case study

Medium and heavy-duty freight transportation requires hydrogen energy infrastructure that is cost-effective, operationally reliable, spatially coherent, and resilient to demand variability along major corridors. This paper presents an integrated hydrogen corridor planning framework using Oak Ridge National Laboratory's OR-AGENT that couples freight-driven, route-resolved hydrogen demand modeling with optimized station siting, sizing, and station-level techno-economic analysis. The framework is demonstrated for the Interstate 10 freight corridor and the Houston-to-Los-Angeles region. Hydrogen demand is derived from high-resolution origin–destination freight data, duty-cycle characterization, and physics-based energy consumption modeling. Candidate refueling sites are selected from existing heavy-duty diesel fueling locations and optimized subject to onboard storage and station capacity constraints. Resulting station throughputs are evaluated using established techno-economic models for electrolytic hydrogen production and dispensing infrastructure. Results show that a regional, portfolio-level aggregation, average dispensed electrolytic hydrogen cost of $6.87–$7.26/kg is currently feasible, and is strongly influenced by demand density and utilization.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗
DOE OSTI2025

Evaluating system responses to electric vehicle charging infrastructure expansion through data-driven simulation

Understanding the system responses to electric vehicle (EV) charging infrastructure expansion, including vehicle charging needs, station utilization, and energy consumption, is critical for effective planning to meet growing charging demand without unnecessary resource investment. This study evaluates the system responses to EV charging infrastructure expansion, focusing on charging needs, station utilization, and energy consumption. Using trip data from the National Household Travel Survey and origin–destination patterns, we simulated trip chains in downtown Atlanta with 10 % EV penetration. We assessed 32 scenarios involving different charging port power levels and siting strategies. Furthermore, we found that higher-power ports were more sensitive to placement, with concentrated expansion boosting station utilization more than uniform expansion. Adding high-power ports did not always increase peak energy consumption; in some cases, a few 400 kW ports reduced overall consumption compared to 150 kW ports by enabling faster charging and higher vehicle turnover.

Electric vehicle↗
DOE OSTI2026

Demonstration of an All-Refractory Corrosion-Resistant Molten Salt Pumping and Storage Infrastructure Up to 950 degrees C

Concentrating solar power (CSP) with thermal energy storage (TES) has an estimated cost similar to solar photovoltaics (PV) with lithium-ion batteries (LIB), but CSP + TES has the potential for significantly reduced cost by operating above 700 degrees C. However, this requires a TES medium and containment infrastructure which are chemically compatible and do not degrade above 700 degrees C. MgCl2-KCl-NaCl (MKN) salt is a promising medium, but when MKN salt has small amounts of water and oxygen dissolved in it, it excessively corrodes conventional commercial alloys. Here, we consider refractory materials including graphite, carbon-carbon composite (C/C), and molybdenum because they maintain high mechanical strength at elevated temperatures and are expected to resist corrosion by MKN salt. While selection of refractory materials is often constrained by the need to remain chemically stable in air, this work uses an enclosure filled with inert gas to allow the use of materials like graphite and molybdenum. Notably, graphite components can seal against liquids unlike many brittle refractory materials. We demonstrate a centrifugal pump and mechanical seals made of refractory materials in a laboratory-scale circulation loop, which successfully operated continuously for more than 49 h at temperatures ranging from 750 degrees C to 950 degrees C with no mechanical failures or chemical degradation of the refractory materials. To the best of our knowledge, this is the highest temperature molten salt circulation loop that has been successfully developed, and this refractory infrastructure allows for operation at even much higher temperatures (<1600 degrees C) if a storage medium with a lower vapor pressure is used. The principles of this architecture are relevant to other applications with high temperature flowing metals and salts including Generation IV nuclear fission reactors for power production and molten salt electrolysis reactors for metallurgical processing.

14 SOLAR ENERGY↗
DOE OSTI2026

Time Matters: A Survival Analysis of Public Electric Vehicle Charging Infrastructure Utilization

The rapid adoption of plug-in electric vehicles (PEVs) places significant demands on public charging infrastructure, making it critical to understand and optimize charger utilization. This study provides one of the most comprehensive analyses of charging behavior to date by applying a survival analysis to a dataset of nearly 16 million level 2 (L2) and direct current (DC) fast charger sessions across the United States from 2017 to 2022. Using Kaplan-Meier curves and log rank tests, our analysis reveals statistically significant and distinct duration patterns influenced by charger type, time of day, and day of the week. We find that L2 charging sessions exhibit high variability tied to venue type, whereas DC sessions are more uniform, typically lasting 30-45 min. This study introduces the operational efficiency score (OES), a metric for standardizing the performance evaluation of charging stations. Our findings offer actionable insights for optimizing charger deployment, developing dynamic pricing strategies to reduce vehicle dwell time, and improving load management for grid operators, ultimately enhancing the efficiency and availability of public charging infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Energy, power, and infrastructure demands from electrifying airport ground support equipment at United States airports

As the airline industry seeks to reduce costs and transition to clean energy, electric ground support equipment is emerging as a favorable option. The integration of electric ground support equipment into airport operations requires careful planning for vehicle deployment, charging infrastructure, and grid impacts. We develop a flexible, bottom-up modeling framework to assess energy and infrastructure needs across more than 300 U.S. airports. Our analysis estimates site-specific power and energy demand, equipment counts by type, charger requirements, and costs. Here we quantify the magnitude of new electrical loads created by the electrification of airport ground support equipment, finding that peak power demand at the largest airports can reach up to 20 megawatts, with annual electricity consumption approaching 51,000 megawatt-hours. We further show that behind-the-meter battery energy storage systems and solar photovoltaic systems can reduce peak load and lower total system costs by as much as 10 million dollars.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Multiparameter optical fiber sensing for energy infrastructure through nanoscale light–matter interactions: From hardware to software, science to commercial opportunities

Monitoring of energy infrastructure through robust yet economical sensing platforms is becoming an area of increased importance, with ubiquitous applications including the electrical grid, natural gas and oil transportation pipelines, H2 infrastructure (storage and transportation), carbon storage, power generation, and subsurface environments. Plasmonic and functional nanomaterial enabled fiber optic sensors show excellent promise for a wide range of sensing applications due to their versatility to be engineered for specific analytes of interest while retaining inherent advantages of the optical fiber sensor platform. Through the design of novel sensing layers, the optical transduction mechanism and wavelength dependence can also be tailored for ease of integration with low-cost interrogation systems enabling an inexpensive yet highly functional optical fiber sensing platform. In addition, recent advances in artificial intelligence and machine learning theoretical methods have been leveraged to simultaneously extract multiple parameters through multi-wavelength interrogation such that unique wavelengths can also serve as unique sensing elements, analogous to electronic nose sensor technologies. The concept of an optical fiber based “photonic nose” via multiple interrogation wavelengths and/or sensor nodes offers a compelling platform technology to realize multiparameter speciation of chemical analytes within complex gas mixtures. In this Perspective, we further generalize the notion of multiparameter sensing through the novel “photonic nervous system” concept based upon low-cost, functionalized optical fiber sensor probes monitoring a variety of distinct analyte classes (physical, chemical, electromagnetic, etc.) simultaneously to provide broad situational awareness via integrated sensors.

Su, Yang-Duan (ORCID:0000000214820902)↗
DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗
DOE OSTI2026

Characterizing Uncertainty in Synthetic Tropical Cyclone Hazard Models for U.S. Energy Infrastructure Resilience

Tropical Cyclones (TCs) are intense storms that pose a persistent and considerable risk to coastal communities and infrastructure in the global tropics and subtropics, including the United States (US). With known limitations associated with observations and high-resolution earth system models, synthetic TC models that capture a wide spectrum of storm possibilities have been developed to robustly quantify TC risk. Here we examine the simulation of various TC features in the North Atlantic relevant for US coastal risk in three synthetic TC models forced with ERA5 reanalysis: MIT, CHAZ and RAFT. While there is a broad agreement among these models in terms of their representation of salient TC characteristics, certain differences do exist. To connect these modeling uncertainties with energy infrastructure resilience, we apply fragility curves that link simulated TC intensities to damage probabilities, demonstrating how uncertainty in storm states may translate into that in coastal impacts. Our study indicates that acknowledging and accounting for inter-model uncertainty leads to more reliable risk assessments, strengthening science-to-action pathways for managing risks associated with TCs.

Baby John, Effy↗