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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Initial Assessment of CTF for Time-at-Temperature Applications

The US nuclear industry is interested in improving the economics of their fleet of light-water reactors (LWRs) by uprating US plants. One option being considered is to regain lost margin from overly conservative fuel safety limits. The current limit requires avoidance of critical heat flux (CHF) and prevents further operation of fuel that experiences a dry-out in boiling water reactors (BWRs) or departure from nucleate boiling (DNB) in pressurized water reactors (PWRs); however, it has been shown that temporary, mild dry-out of the fuel does not necessarily increase the risk of fuel failure during its normal anticipated operating life. Such mild dry-out or DNB events may occur during a plant anticipated operational occurrence (AOO), such as a locked rotor in a PWR or a pump trip in a BWR. The time-at-temperature (TAT) approach to regulating fuel operation aims to demonstrate that the fuel rod’s integrity is not challenged during such a mild transient that leads to CHF in which the fuel operates at an elevated temperature for a brief period of time. However, implementing this approach will require extensive fuel material experimental data, as well as supporting modeling and simulation (M&S) predictions, to ensure that the predicted fuel response during AOOs, with all applicable uncertainty considered, will not threaten the safety of the fuel during the transient or the remainder of its anticipated lifecycle. To address this need, a comprehensive effort is being proposed that includes generating cladding material data under TAT conditions, assessment of available code capabilities for TAT conditions, development of new mechanistic models, and demonstration of the M&S capabilities for AOOs of interest. This will require a joint effort between the Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuels Campaign (AFC) programs, as well as close collaboration with nuclear industry stakeholders. The outcome of this collaboration will result in development and assessment of capabilities that can be used by the nuclear industry to support qualification of a TAT-based fuel failure criteria safety limit. This report focuses on the thermal hydraulics (T/H) modeling capabilities and summarizes currently available data for validating the T/H subchannel code CTF for TAT conditions, as well as preliminary assessment results of the code. The initial assessment also resulted in implementation of an alternative post-CHF heat transfer package, which has been shown to significantly improve accuracy. This report is not a final assessment and does not consider all available validation data; it is intended that a future assessment will more fully validate the code for this application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Analysis of Ground Source Heat Pump ECMs: Implemented Under DOE ESPC IDIQ Contract

Several federal performance and decarbonization objectives are driving the U.S. government to transition to net-zero emissions across the federal building portfolio. The overarching purpose of this Federal Energy Management Program (FEMP)-Geothermal Technologies Office (GTO) work is to support federal facilities in accomplishing the administration’s federal building decarbonization goals. Creating awareness of existing geothermal (or ground-source) heat pump (GHP) systems deployed on federal property, implemented using performance contracts and evaluating the energy and environmental impacts of these systems, this work will assist federal facilities in considering inclusion of GHP technology energy conservation measures (ECMs) in future performance contracting project awards. This report summarizes analyses of data from GHP ECMs installed under the DOE ESPC IDIQ contract across various climate areas and geographic locations, agencies, and building use types. Through the analysis of proposed GHP ECMs and understanding key metrics on implemented GHP systems in a variety of applications, FEMP and GTO can further support federal agencies in meeting decarbonization and net-zero building goals by evaluating and incorporating GHP systems into performance contracts and communicate the benefits of this technology.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utilities Perspective on Protection Challenges with High IBR Penetration

Utilities have seen rapid increase in Solar, Wind, and Battery Energy Storage Resources that interconnect to their electric system through Inverters. Inverter-Based Resources (IBRs) have fault current characteristics that are unlike the fault current response of traditional rotating-machine-based generators, which is well known and repeatable. IBR’s non-traditional fault current behavior is due to the IBR control scheme, which is configured to provide a clean AC output but also protect the inverter’s sensitive power electronics devices from damage, one source of which is overcurrent. This results in low fault current magnitude, low or no negative sequence current injection, the variability of sequence component currents, the variability of voltage with respect to current angles, and the lack of inertia. The control scheme also results in a fault current response that can vary between manufactures and between models of the same manufacturer. High penetration of IBRs can adversely affect the protection schemes applied in areas with high penetration of IBRs. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems. This is mainly because the existing protection elements and practices have been designed based on the fault current response of conventional rotating machines. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This presentation identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. Instead of facing on one issue, we are looking broadly on all the challenges that system protection has experienced with high penetration of IBRs. Based on the IBR response from various utilities during real fault events and gathering perspective from different utility SMEs via questionnaire, the presentation summarizes on gathered data and internal experiences.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Utility Perspective on Protection Challenges with High Penetration of IBRs

Utilities have seen rapid increase in Solar, Wind, and Battery Energy Storage Resources that interconnect to their electric system through Inverters. Inverter-Based Resources (IBRs) have fault current characteristics that are unlike the fault current response of traditional rotating-machine-based generators, which is well known and repeatable. IBR’s non-traditional fault current behavior is due to the IBR control scheme, which is configured to provide a clean AC output but also protect the inverter’s sensitive power electronics devices from damage, one source of which is overcurrent. This results in low fault current magnitude, low or no negative sequence current injection, the variability of sequence component currents, the variability of voltage with respect to current angles, and the lack of inertia. The control scheme also results in a fault current response that can vary between manufactures and between models of the same manufacturer. High penetration of IBRs can adversely affect the protection schemes applied in areas with high penetration of IBRs. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems. This is mainly because the existing protection elements and practices have been designed based on the fault current response of conventional rotating machines. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This report / presentation identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. Instead of facing on one issue, this report looks broadly on all the challenges that system protection has experienced with high penetration of IBRs. Based on the IBR response from various utilities during real fault events and gathering perspective from different utility SMEs via questionnaire, the report summarizes on gathered data and internal experiences.

14 SOLAR ENERGY↗
DOE OSTI2025

Determining Magnetic Field Directions and Omni-directional Fluxes of Particles from STPSat-6 ZPS Plasma Measurements

This report summarizes our recent data derivation efforts on STPSat-6 ZPS plasma measurements, presenting final outcomes. We begin by outlining the methodology developed to determine local magnetic field directions from measured directional intensities of ~20 keV ions, leveraging symmetry in particles’ pitch-angle distributions, and the determined field directions over a storm period are shown with errors analyzed through comparison with NOAA GOES measurements. Next, we further assess the validity of the method and quantify its overall high performance while acknowledging certain caveats. Finally, given local magnetic field directions and ZPS data, we explain how omni-directional fluxes of particles can be derived from ZPS measurements with limited directional coverage, and estimate the related errors under several theoretical scenarios. The methods developed in this study can be applied for processing and augmenting ZPS data for the next, and the insights gained here can also inform instrument design in the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Fungal elemental profiling unleashed through rapid laser-induced breakdown spectroscopy (LIBS)

Elemental profiling of fungal species as a phenotyping tool is an understudied topic and is typically performed to examine plant tissue or non-biological materials. Traditional analytical techniques such as inductively coupled plasma–optical emission spectroscopy (ICP-OES) and inductively coupled plasma–mass spectrometry (ICP-MS) have been used to identify elemental profiles of fungi; however, these techniques can be cumbersome due to the difficulty of preparing samples. Additionally, the instruments used for these techniques can be expensive to procure and operate. Laser-induced breakdown spectroscopy (LIBS) is an alternative elemental analytical technique—one that is sensitive across the periodic table, easy to use on various sample types, and is cost-effective in both procurement and operation. LIBS has not been used on axenic filamentous fungal isolates grown in substrate media. In this work, as a proof of concept, we used LIBS on two genetically distinct fungal species grown on a nutrient-rich and nutrient-poor substrate media to determine whether robust elemental profiles can be detected and whether differences between the fungal isolates can be identified. This data set contains the raw LIBS spectral data for the summarized results described inRush, et. al. 2024

elemental profiling↗
DOE OSTI2024

Utility Perspective on Protection Challenges with High IBR Penetration [Slides]

Utilities have seen rapid increase in Solar, Wind, and Battery Energy Storage Resources that interconnect to their electric system through Inverters. Inverter-Based Resources (IBRs) have fault current characteristics that are unlike the fault current response of traditional rotating-machine-based generators, which is well known and repeatable. IBR’s non-traditional fault current behavior is due to the IBR control scheme, which is configured to provide a clean AC output but also protect the inverter’s sensitive power electronics devices from damage, one source of which is overcurrent. This results in low fault current magnitude, low or no negative sequence current injection, the variability of sequence component currents, the variability of voltage with respect to current angles, and the lack of inertia. The control scheme also results in a fault current response that can vary between manufactures and between models of the same manufacturer. High penetration of IBRs can adversely affect the protection schemes applied in areas with high penetration of IBRs. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems. This is mainly because the existing protection elements and practices have been designed based on the fault current response of conventional rotating machines. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This report identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. Instead of facing on one issue, this report looks broadly on all the challenges that system protection has experienced with high penetration of IBRs. Based on the IBR response from various utilities during real fault events and gathering perspective from different utility SMEs via questionnaire, the report summarizes on gathered data and internal experiences.

14 SOLAR ENERGY↗
DOE OSTI2025

Nuclear data sensitivity and uncertainty study of copper-reflected integral experiments [Slides]

This presentation touches on reducing uncertainties in intermediate-energy actinide nuclear data and this continues to be a high priority for many applications. The goal of PARADIGM (PARallel Approach of Differential and InteGral Measurements): accelerate efforts to reduce biases and uncertainties in nuclear data through improvements to the nuclear data pipeline. This presentation includes integral experiments and a summarization of existing copper nuclear data.

Cu63↗
DOE OSTI2025

Shared and Ownership Mobility Technologies in the US: Data Availability and Usage Trends

This report supports the vision for a more sustainable transportation future by summarizing and analyzing the latest data on new mobility technologies, including ridesharing, shared and privately owned bikes, e-bikes, and scooters that have emerged over the past two decades. Having access to accurate and current data that is representative of new mobility systems and individual usage of these systems across different parts of the country is critical for researchers, city and regional planning professionals, and current and potential industry technology developers to better understand and forecast usage trends both nationwide as well as across different existing and potential future markets across the country. Building on the previous study published in 2022, this report incorporates the latest available market and usage data on new mobility technologies and compares usage by Chicago and New York City demographic characteristics. Moreover, this report includes recent developments and insights on privately owned micromobility technologies. Our analysis found that more downtown areas in Chicago show high per capita usage for all three modes than in the previous study, likely due to the full launch of shared e-scooter systems citywide in 2022. Notably, the majority of high shared mobility usage is concentrated in high-income, densely populated downtown areas in Chicago, which also have good public transit access. In contrast, TNC and bikeshare usage hotspots in central Manhattan are more widely distributed, though also appear to be shaped by the geography of the public transit system. Analysis of privately owned micromobility shows that the greatest energy savings occurred when e-bikes replaced single-occupancy vehicle (SOV) trips (i.e., gasoline-powered cars driven alone). Based on the literature review and analysis results, we also make recommendations for supporting the development of both shared and privately owned micromobility programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A flexible class of priors for orthonormal matrices with basis function-specific structure

Statistical modeling of high-dimensional matrix-valued data motivates the use of a low-rank representation that simultaneously summarizes key characteristics of the data and enables dimension reduction. Low-rank representations commonly factor the original data into the product of orthonormal basis functions and weights, where each basis function represents an independent feature of the data. However, the basis functions in these factorizations are typically computed using algorithmic methods that cannot quantify uncertainty or account for basis function correlation structure a priori. While there exist Bayesian methods that allow for a common correlation structure across basis functions, empirical examples motivate the need for basis function-specific dependence structure. We propose a prior distribution for orthonormal matrices that can explicitly model basis function-specific structure. The prior is used within a general probabilistic model for singular value decomposition to conduct posterior inference on the basis functions while accounting for measurement error and fixed effects. We discuss how the prior specification can be used for various scenarios and demonstrate favorable model properties through synthetic data examples. Finally, we apply our method to two-meter air temperature data from the Pacific Northwest, enhancing our understanding of the Earth system’s internal variability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data Center Cybersecurity, Supply Chain Risk Management, and Emerging Regulation Cohort Summary: Takeaways and Action Plans

This report summarizes the outcomes of the Data Center Cohort under the Department of Energy’s Technical Assistance for Digital Assurance (TADA) initiative, aimed at enhancing grid resilience through cybersecurity, supply chain risk management (SCRM), and Cyber-Informed Engineering (CIE). The cohort engaged 17 organizations across utilities, data center operators, vendors, and technology providers in three sessions combining presentations, discussions, and exercises. Key topics included AI-driven load behavior, cybersecurity vulnerabilities in UPS/BESS and cooling systems, governance gaps at utility–data center boundaries, and supply chain integrity. Five cross-cutting themes emerged: interconnection architecture vulnerabilities, fragmented governance, AI-driven stability risks, lack of regulatory frameworks, and long-term supply chain concerns. Actionable recommendations were developed, including implementing DMZ segmentation, formalizing vendor access agreements, designing AI workload limits, and advancing standards through NERC and state-level programs. These strategies aim to strengthen resilience, clarify responsibilities, and ensure secure integration of data centers into the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Cloverleaf Data Artifacts for ArtIMis LDRD

This report summarizes the use of the open-source CloverLeaf/CloverLeaf3D mini-apps to generate synthetic data sets to train foundation models for the ArtIMis LDRD DI. These data artifacts are intended to be used by LANL collaborators and shared externally with our university and institutional partners. Note that CloverLeaf/CloverLeaf3D is not a LANL simulation code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Foundational Industrial Energy Dataset (FIED): Open-Source Data on Industrial Facilities

The state of data on industrial energy use has co-evolved over several decades with the demands of industrial energy analysis. The most recent development - analysis in support of decarbonizing the industrial sector - has changed the characteristics of industrial data that are useful for analysts and model developers. Although data and its collection processes may be cast from a conventional viewpoint as objective and free from the influence of social dynamics, this provides an incomplete picture of not only the processes by which information is generated, but also the limitations and opportunities of data to be useful for analysis. The foundational industry energy data set (FIED) is a result of the confluence of trends in open data and the demand for higher resolution industrial energy analysis. The general approach to compiling the FIED involves accessing, filtering, and formatting data published by federal organizations on the Internet for public use. Unlike most industrial energy datasets, which are published by the U.S. Energy Information Administration (EIA), the FIED relies on core datasets from the U.S. Environmental Protection Agency (EPA). The FIED addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization - including estimates of energy use, greenhouse gas emissions, and design capacities - for facilities that are identified by latitude and longitude. This enables local-level analysis of existing combustion equipment, as well as regional comparisons with traditional industrial energy data estimates. The report summarizes the general logic behind compiling the FIED. The FIED itself and its Python code are available from OpenEI and GitHub, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A systematic review of machine learning in groundwater monitoring

With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.

AI/ML↗
DOE OSTI2025

Advanced Data Management for the Wastewater Industry

This information sheet discusses the technology pillar Advanced Data Management as a pathway toward improving wastewater infrastructure sustainability and resiliency. To supplement existing literature on current technologies and policies for improving resiliency at wastewater treatment plants (WWTPs), this document aims to accomplish the following: • Summarize key technologies such as Supervisory Control and Data Acquisition (SCADA), digital twins, and smart sensors • Summarize relevant cybersecurity measures and data management tools available for WW utilities • Summarize advances in sensing and monitoring technologies • Serve as a comprehensive (though not exhaustive) repository for data management for wastewater utilities The Advanced Management Technical Information Sheet should be viewed as a general guide to established best practices for the water and wastewater sector when considering implementing energy capture and energy- or process-efficient technologies. Further details are presented in the SWIFt Technology Information Sheet Series for accompanying Technology Pillars.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

ExaFEL: extreme-scale real-time data processing for X-ray free electron laser science

ExaFEL is an HPC-capable X-ray Free Electron Laser (XFEL) data analysis software suite for both Serial Femtosecond Crystallography (SFX) and Single Particle Imaging (SPI) developed in collaboration with the Linac Coherent Lightsource (LCLS), Lawrence Berkeley National Laboratory (LBNL) and Los Alamos National Laboratory. ExaFEL supports real-time data analysis via a cross-facility workflow spanning LCLS and HPC centers such as NERSC and OLCF. Our work therefore constitutes initial path-finding for the US Department of Energy's (DOE) Integrated Research Infrastructure (IRI) program. We present the ExaFEL team's 7 years of experience in developing real-time XFEL data analysis software for the DOE's exascale supercomputers. We present our experiences and lessons learned with the Perlmutter and Frontier supercomputers. Furthermore we outline essential data center services (and the implications for institutional policy) required for real-time data analysis. Finally we summarize our software and performance engineering approaches and our experiences with NERSC's Perlmutter and OLCF's Frontier systems. This work is intended to be a practical blueprint for similar efforts in integrating exascale compute resources into other cross-facility workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Annual Site Environmental Report for Pantex Plant, Calendar Year 2023

The 2023 Annual Site Environmental Report (ASER) summarizes Pantex’s status, data, and efforts for the environmental compliance, protection, and restoration programs. It has been prepared in accordance with DOE O 231.1B, Environment, Safety and Health Reporting, and DOE O 458.1, Radiation Protection of the Public and the Environment. These orders outline the requirements for environmental protection programs at DOE facilities to ensure that programs fully comply with applicable federal, state, and local environmental laws and regulations, executive orders, and DOE policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Analyzing Multifaceted Scientific Data with Topological Analytics (Final Technical Report)

This final technical report describes the activities undertaken through Department of Energy, Office of Science, Advanced Scientific Computing Research Early Career award DE-SC-0019039, “Analyzing Multifaceted Scientific Data with Topological Analytics." This report summarizes contributions made toward the research of visualization, machine learning, and topological data analysis of complex simulation data.

97 MATHEMATICS AND COMPUTING↗