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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Analysis of Electric Heavy-Duty Driving and Infrastructure Requirements

The analysis discussed in this report was performed as part of DOE award DE-EE0009232 to model the effects of charging Heavy Duty Battery Electric Trucks (HDBETs) on the grid. This project combines best in class freight modeling by the National Renewable Energy Laboratory (NREL) with advanced distribution modeling by EPRI using detailed data from Xcel Energy and Salt River Project to analyze the effects of depot charging and utility-grade transmission modeling by Tri-State Transmission and Generation Association Inc. to analyze the effects of en-route charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis for Quantitative Risk Assessments of Hydrogen Infrastructure

Typical QRAs provide deterministic estimates and understanding of risks posed but are constructed using significant assumptions and uncertainties due to limited data availability and historical momentum of using nominal estimates. This report presents a hydrogen QRA analysis using HyRAM+ that incorporates uncertainty with Latin hypercube sampling and sensitivity analysis using linear regression.

08 HYDROGEN↗
DOE OSTI2024

FY 2024 Multidimensional Data Correlation Platform Data Management Infrastructure Progress: Materials Laboratory

This report provides an inventory of the equipment available at the ORNL Manufacturing Demonstration Facility (MDF) for sample preparation and material characterization, including both destructive and non-destructive techniques that generate critical data to support the development of the Multi-Dimensional Data Correlation (MDDC) framework. The success of the MDDC framework depends heavily on the quality and completeness of the data it can access. Therefore, it is essential to establish a comprehensive inventory of the technologies available to the Advanced Materials and Manufacturing Technologies (AMMT) multi-laboratory team. This starts by gathering information about the types of data they produce, the data collection and transfer protocols used, file formats, and data storage requirements for experiments. This information is then carefully evaluated to create the operations and trackables elements of the Damara Tern platform, which is the foundation of the MDDC framework.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Securing Digital Energy Infrastructure: Procurement, Contracting, and Supply Chain Risk Management Guidance

Recognizing the scale of this industry challenge, the United States (U.S.) Department of Energy (DOE) Grid Deployment Office (GDO) and Cybersecurity Energy Security & Emergency Response office have launched a multi-year BESS supply chain security initiative to identify consequence-driven approaches to addressing BESS supply chain security and provide resources to support prioritization of supply chain security efforts associated with the procurement of BESS equipment and services. This guide is one element of the supporting resources to be provided and sets forth a framework and guidance for procurement bidding, selection, risk analysis, and agreements stakeholders can implement to mitigate cybersecurity risks across the entirety of battery system component ecosystem, including the interconnected software and hardware required for control and monitoring BESSs.

25 ENERGY STORAGE↗
DOE OSTI2024

ReLIC: Full-Scale Realization of Reinforcement Learning for Infrastructure Control

Prior efforts have shown that deep reinforcement learning (DRL) may provide a new method for controlling networked power systems. Though successful, prior approaches have not yet demonstrated their behavior on systems of realistic scale. This effort examined multiple theoretical and technical approaches to allow a DRL model to operate over a system of 2,000 buses or more. We find that allowing the DRL models to run training episodes in parallel provides near limitless efficiency gains, allowing us to train successful agents to behave on our Kuramoto transmission model of up to 4,000 buses. We further show that we can expand our PowerWorld DRL implementation to systems of up to 25 buses but struggle to go beyond this limit due to PowerWorld’s inability to run multiple instances at once. Finally, we examine a multi-agent approach and find that it performs as well if not better than our existing centralized approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evolving Multi-hazard Machine Learning Modeling for Advanced Risk-Informed Infrastructure Resilience Assessment

The socioeconomic impacts of pipeline incidents have escalated over the past three decades, revealing the limitation of traditional risk modeling methods when applied to extensive pipeline networks. This research aims to develop machine learning (ML) models that effectively identify, rank, and predict the diverse hazards and socioeconomic consequences associated with pipeline incidents. Utilizing historical data on pipeline incidents alongside weather and oceanographic data from the 1980s onward, the Houston metropolitan area serves as a testbed for the proposed methodologies. The research segments the combined datasets into three consecutive periods, demonstrating the efficacy of the updated model in predicting future events, particularly concerning precipitation rate data. Despite the challenges posed by a relatively limited dataset, local-level ML modeling offers valuable insights into the spatial and temporal dynamics of multiple hazards that contribute to pipeline incidents. These findings hold significant implications for future research, particularly in understanding and mitigating risks in various locations across the Gulf Coast and other coastal regions.

42 ENGINEERING↗
DOE OSTI2025

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES) - Report on Technology Down Select No. 1 - Acid Baking vs. Heap Leaching

An essential step for recovering rare earth and critical minerals from coal mine waste is one that achieves adequate dissolution of the target elements into a pregnant leachate solution. The simplest technical approach was thought to be heap-leaching that could proceed using mild acid dosing or naturally generated acid from biological activity. For this reason, the University of Kentucky at Lexington (UKY) undertook two efforts to evaluate feasibility, including a laboratory column leaching evaluation and a pilot heap-leaching demonstration. Later, the UK evaluated a pyrometallurgical approach using roasting combined with acid baking and tank leaching at elevated temperatures to improve extraction efficiencies. This report surveys the previously reported leaching yields and calculates the gross value of rare earth oxides as a basket in the pregnant leachate solution.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Bipartisan Infrastructure Law (BIL) – Illinois Rare Earth Novel Extraction and Supply (IRENES)

This report presents the physical and chemical characterization of breaker and sorter reject materials sourced from the Prairie State Generation facility, as part of the Illinois Rare Earth Novel Extraction and Supply (IRENES) project. Key analyses include particle size distribution, density, angle of repose, proximate and ultimate composition, mineralogy, and elemental content. Breaker reject material was found to be coarser and higher in ash content (~80%) with lower calorific value, while sorter reject showed finer distribution, lower ash (~68%), and higher carbon and energy content. XRD and XRF analyses confirmed the presence of REE-bearing minerals and relevant oxides, supporting process design and beneficiation strategy development for critical mineral recovery.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Ultra-Low Disorder Graphene Quantum Dot-Based Spin Qubits for Cyber Secure Fossil Energy Infrastructure (Final Technical Report)

The overarching goal of the proposed project is to demonstrate the feasibility of creating ultralow local disorder graphene quantum dots (GQDs)-based high-speed, high-fidelity spin quantum bits (qubits) for extremely cyber-secure coal energy plants of the future. Despite their inherent benefits, the coherence times in the state-of-the-art GQD qubits are still low primarily due to the local disorder in GQD devices generated during lithographic fabrication of GQDs. Hence, the focus of this research is to prepare ultralow disorder GQDs (e.g., edge roughness ~0.5nm) and evaluate the low temperature (~mK) charge/spin transport characteristics of the engineered GQD qubit platform. To achieve minimal disorder in GQD qubits, we employ a novel approach that combines nanotomy (novel GQD fabrication technique developed by the PI) and scanning probe microscopy-atomic oxidation lithography (SPM-AOL).

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Improved digital construction binder solution utilizing calcium aluminate additive for Infrastructure Scale Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Kerneos Inc., a Division of Imerys USA, Inc. to develop an improved digital construction binder using calcium aluminate additives produced by Kerneos along with locally available concrete materials. When the two-stage (2K) binder formulation was added to commercially available Portland Limestone Cement and sand to form a digital construction mortar, its strength exceeded a number of commercially available digital construction binders both at early and later ages. At the same time, the developed formulation showed precise control of setting time after addition and showed very low shrinkage making it a strong, reliable, and easily customizable alternative to fixed proprietary digital construction binders.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Improved digital construction binder solution utilizing calcium aluminate additive for Infrastructure Scale Additive Manufacturing

Oak Ridge National Laboratory (ORNL) worked with Kerneos Inc., a Division of Imerys USA, Inc. to develop an improved digital construction binder using calcium aluminate additives produced by Kerneos along with locally available concrete materials. When the two-stage (2K) binder formulation was added to commercially available Portland Limestone Cement and sand to form a digital construction mortar, its strength exceeded a number of commercially available digital construction binders both at early and later ages. At the same time, the developed formulation showed precise control of setting time after addition and showed very low shrinkage making it a strong, reliable, and easily customizable alternative to fixed proprietary digital construction binders.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Western Smart Regional EV Adoption and Infrastructure at Scale- WestSmartEV@Scale (Budget Period 2 – Milestone Report – TNC EV Study)

WestSmartEV@Scale is a comprehensive research project addressing key opportunities to decarbonize transportation throughout the Rocky Mountain West. Building upon the framework established in the original WestSmart project, unique subprojects are scoped targeting transportation emissions across light-, medium-, and heavy-duty vehicles with consideration of equity and access. This report summarizes the progress to date on Subproject 6, TNC EV Study (Urban Mobility). It is comprised of three sections: • Outreach and participant recruitment; • Survey data collection and analysis; and • BEV driver driving and charging behavior data collection and analysis.

33 ADVANCED PROPULSION SYSTEMS↗