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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quality Assurance Program Plan for SFR Metallic Fuel Data Qualification

This document contains an evaluation of the applicability of the current Quality Assurance Standards from the American Society of Mechanical Engineers Standard NQA-1 (NQA-1) criteria and identifies and describes the quality assurance process(es) by which attributes of historical, analytical, and other data associated with sodium-cooled fast reactor [SFR] metallic fuel will be evaluated. This process is being instituted to facilitate validation of data to the extent that such data may be used to support future licensing efforts associated with advanced reactor designs. The initial data to be evaluated under this program were generated during the US Integral Fast Reactor program between 1984-1994, where the data include, but are not limited to, research and development data and associated documents, test plans and associated protocols, operations and test data, technical reports, and information associated with past United States Nuclear Regulatory Commission reviews of SFR designs. It is recognized that managing the data generated by large research and development projects presents a significant challenge for retaining data integrity and availability. American Society of Mechanical Engineers Standard NQA-1 (NQA-1) 2008/2009a provides appropriate requirements for this plan.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The six trajectory data sets support aerosol, cloud, planetary boundary layer, and related research (aerosol-cloud interactions, etc.), as well as studies using ARM Aerial Facility (AAF) and tethered balloon system (TBS) measurements. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soil moisture and temperature from 2019 to 2024 along northeast- and southwest-facing hillslopes at the Lower Montane site in the East River Watershed, Colorado

Soil moisture, temperature, and electrical conductivity have been monitored at multiple depths (between 10 and 50 cm) at 4 locations along a northeast-facing slope and 3 locations on the opposite southwest-facing slope at the Lower Montane site in the East River Watershed, Colorado, from Oct 2019 to Oct 2024. The purpose of this data is to inform hydro-biogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). Two locations on the northeast-facing slope were reinstalled in 2020 due to damage from wildlife, and thus data for these sites are provided in two distinct files. Overall, the data are reported in 9 CSV files containing the measurements, and the locations are provided in the Sensor_Location.csv file. There is a total of 10 *.csv data files and 3 *.csv metadata files. Older datasets associated with the northeast-facing slope are provided in another archive (see reference). These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales. Feel free to contact the author with any questions or collaboration interests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

U.S. ESCO Industry Report: Industry Size and Recent Market Trends, 2022- 2024

The latest edition of the U.S. Energy Service Company (ESCO) Industry Report by Lawrence Berkeley National Laboratory (LBNL) finds that the U.S. ESCO industry continues to show strong growth. The report draws from ESCO industry reported revenue data for the 2022-2024 period, detailing the current size and characteristics of the U.S. ESCO industry. Following 20 years of ESCO industry reports, the 2024 report explores significant revenue trends across market segments, geographic regions, ESCO size, financing structures, and business activities. New analysis in this report outlines customer priorities and non-energy benefit drivers of Energy Savings Performance Contract projects, adjusted revenue analysis detailing the impacts of inflation on industry growth, and project challenges by market segment.

Chelminski, Kathryn↗
DOE OSTI2024

Validation of HyRAM+ Version 5.1 Physics Models

The Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) software has seen various improvements and additional physics capabilities since validation against experimental data was last published for HyRAM v3.1. Notably, HyRAM+ now includes four models allowing for the calculation of overpressure resulting from vapor cloud explosions from unconfined jet releases. As with the previous HyRAM validation report, validation data was gathered from available published literature and tested against HyRAM+ capabilities. The validation comparisons include tank blowdown, unignited dispersion jet plume, ignited jet flame, and enclosed accumulation and overpressure. The unconfined overpressure calculations in HyRAM+ v5.1.1 generally show good agreement with many of the experimental data sets for all four unconfined overpressure models, though HyRAM+ overpredicts the experimental data for small and cryogenic hydrogen releases. The comparisons for the other HyRAM+ physics models are largely unchanged from the previously published validation report.

08 HYDROGEN↗
DOE OSTI2026

Extracting the Breakout Distance from the ECOT Trajectories: Gaussian Process Regression Approach

Enhanced Corner Turning (ECOT) experiments provide an important metric of performance of high explosive (HE) formulations. The breakout distance is a single scalar value that characterizes the corner turning efficiency of an HE. Extracting the breakout distance from the raw ECOT results, whether experimental or simulated, is a conceptually straightforward procedure which, however, is non-unique, especially in the presence of noise. More specifically, this procedure involves numerical smoothing and selecting particular values for parameters of this smoothing introduces human bias. In this work, we propose to use the Gaussian process regression to analyze ECOT results. This analysis involves the effective smoothing of the data, thus allowing for accurate extraction of the breakout distance. Most importantly, the parameters of this smoothing can be inferred from the ECOT data itself, rendering the approach effectively parameter-free and thus diminishing the human bias. An additional benefit of the Gaussian process regression, being a statistical inference method, is that not just the value of the breakout distance, but also its confidence interval can be extracted from the data. This report introduces the Gaussian process regression, as applied to ECOT, and demonstrates its usefulness by extracting the breakout distances for a selection of experimental and simulated data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Specimen sizing and remaining life sample calculations for high temperature reactor material surveillance

Advanced high-temperature nuclear reactors rely on structural components that will operate for decades under combined mechanical, thermal, and environmental loading. Materials surveillance programs are a promising strategy for managing the resulting uncertainty in long-term structural integrity by monitoring degradation in service using passively actuated mechanical test articles. Previous reports have developed a simplified, spreadsheetimplementable framework for sizing these test articles and for inferring accumulated creep damage and remaining life from ex-situ test data. This report advances that work toward practical deployment by providing a sample-problem book: a collection of worked, end-toend examples in which the ASME Section III, Division 5 design analysis of a representative high-temperature reactor component is carried through to a sized surveillance article, verified with detailed finite-element analysis, and concluded with a remaining-life assessment based on an assumed ex-situ creep-rate measurement on the retrieved specimen. The report also summarizes ongoing ANL engagement with ASTM Committee E10 on Nuclear Technology and Applications toward drafting a standard covering surveillance procedures for advanced reactors.

Barua, Bipul (ORCID:0000000247184113)↗
DOE OSTI2024

Gas Transfer Across Air‐Water Interfaces in Inland Waters: From Micro‐Eddies to Super‐Statistics

In inland water covering lakes, reservoirs, and ponds, the gas exchange of slightly soluble gases such as carbon dioxide, dimethyl sulfide, methane, or oxygen across a clean and nearly flat air‐water interface is routinely described using a water‐side mean gas transfer velocity $\overline{k_{L}}$, where overline indicates time or ensemble averaging. The micro‐eddy surface renewal model predicts $\overline{k_{L}}$ = α o Sc -1/2 ($v\bar{ϵ}$) 1/4 , where Sc is the molecular Schmidt number, $v$ is the water kinematic viscosity, and $\bar{ϵ}$ is the waterside mean turbulent kinetic energy dissipation rate at or near the interface. While α o = 0.39 - 0.46 has been reported across a number of data sets, others report large scatter or variability around this value range. It is shown here that this scatter can be partly explained by high temporal variability in instantaneous ϵ around $\bar{ϵ}$, a mechanism that was not previously considered. As the coefficient of variation (CV e ) in ϵ increases, α o must be adjusted by a multiplier (1 = CV e 2 ) -3/32 that was derived from a log‐normal model for the probability density function of ϵ. Reported variations in α o with a macro‐scale Reynolds number can also be partly attributed to intermittency effects in ϵ. Such intermittency is characterized by the long‐range (i.e., power‐law decay) spatial auto‐correlation function of ϵ. That α o varies with a macro‐scale Reynolds number does not necessarily violate the micro‐eddy model. Instead, it points to a coordination between the macro‐ and micro‐scales arising from the transfer of energy across scales in the energy cascade.

Batchelor scale↗
DOE OSTI2026

Survey of emerging nuclear data needs for nonproliferation applications with advanced reactors

Nuclear science plays a key role in non-proliferation activities supporting advanced reactor technologies. Nuclear data underpin predictions and interpretations of nuclear material behavior and signatures in reactor fuel production, use, transport, and storage. Advanced reactors provide new challenges compared to the current fleet of thermal fission reactors. This report consolidates reported nuclear data needs from representative workshops, conferences, and publications, identifying six themes for recommended future investments supporting non-proliferation and safeguards applications. While also identified as data needs, major fission product evaluations and (α,n) reactions were omitted as there are ongoing activities producing new data under NA22/Objective O. Each theme is summarized below with example data and association with the nonproliferation mission for advanced fuels and reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Summary of Graphite Data Stored within NDMAS

The Graphite Technology Development Project provides data to support the design of graphite core components within specific reactor service conditions of the next generation of high-temperature, gas-cooled nuclear reactors. Physical, mechanical, and thermal properties of nuclear grade graphite were characterized for specimens that were unirradiated, irradiated, and irradiated under various stress conditions. The material properties include diameter, length, mass, density, compressive strength, tensile strength, flexural strength, modulus, resistivity, thermal diffusivity, and thermal expansion coefficient. Baseline graphite specimens are unirradiated from different grades (2114, IG-110, NBG-17, NBG-18, and PCEA) and different types used in different characterization tests (compressive, flexural, tensile, one-inch cylinder, and quarter-inch cylinder). The Advanced Graphite Creep (AGC) irradiation specimens are from a much larger number of grades and cylinder types (creep, piggyback, and pencil). For baseline graphite, characterization data for 7,756 specimens extracted from thirteen graphite billets were captured to the NDMAS database. For AGC experiments, four irradiation campaigns have been completed: AGC-1, AGC-2, AGC-3, and AGC-4. The ongoing HDG-1 (High-Dose Graphite) experiment, which began irradiation with Cycle 168B on August 26, 2020, includes specimens previously irradiated in AGC-2 in addition to the specimens originally destined for AGC-5.. Besides the characterization data, the AGC data includes irradiation monitoring and physics data representing the irradiation conditions of AGC specimens. Currently, all data for AGC-1, AGC-2, and AGC-3 have been captured to the NDMAS database. Only AGC-4 pre-irradiation and irradiation monitoring data have been captured, and HDG-1 pre-irradiation data are in process of being captured for unirradiated specimens. To date, a total of 38,149 material property records have been captured into NDMAS database for baseline and AGC specimens. All characterization data are qualified for use according to their perspective data verification reports. For the AGC irradiation campaigns, a total of 41,502 qualified physics calculation records were added for AGC-1, AGC-2, and AGC-3. Finally, a total of 173,698,505 AGC irradiation monitoring data records (thermocouple temperature, gas flow rate, gas pressure, gas moisture, applied load, and specimen displacement) have been captured to NDMAS; the majority of those records (~94%) are qualified data records.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗
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↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Constraining gravity with a new precision 𝐸 𝐺 estimator using Planck + SDSS BOSS data

The 𝐸 𝐺 statistic is a discriminating probe of gravity developed to test the prediction of general relativity (GR) for the relation between gravitational potential and clustering on the largest scales in the observable Universe. We present a novel high-precision estimator for the 𝐸 𝐺 statistic using CMB lensing and galaxy clustering correlations that carefully matches the effective redshifts across the different measurement components to minimize corrections. A suite of detailed tests is performed to characterize the estimator’s accuracy, its sensitivity to assumptions and analysis choices, and the non-Gaussianity of the estimator’s uncertainty is characterized. After finalization of the estimator, it is applied to Planck CMB lensing and SDSS CMASS and LOWZ galaxy data. We report the first harmonic space measurement of 𝐸 𝐺 using the LOWZ sample and CMB lensing and also updated constraints using the final CMASS sample and the latest Planck CMB lensing map. We find $\hat{𝐸}$$^{Planck+CMASS}_{𝐺}$ = 0.3⁢6$^{+0.06}_{−0.05}$⁢(68.27%) and $\hat{𝐸}$$^{Planck+LOWZ}_{𝐺}$ = 0.4⁢0$^{+0.11}_{−0.09}$⁢(68.27%), with additional subdominant systematic error budget estimates of 2% and 3%, respectively. Using Ω m,0 constraints from Planck and SDSS BAO observations, Λ⁢CDM-GR predicts 𝐸$^{GR}_ {𝐺}$⁡(𝑧 =0.555) = 0.401 ± 0.005 and 𝐸$^{GR}_{𝐺}$⁡(𝑧 =0.316) = 0.452 ± 0.005 at the effective redshifts of the CMASS and LOWZ based measurements. We report the measurement to be in good statistical agreement with the Λ⁢CDM-GR prediction and report that the measurement is also consistent with the more general GR prediction of scale independence for 𝐸 𝐺 . Furthermore, this work provides a carefully constructed and calibrated statistic with which 𝐸 𝐺 measurements can be confidently and accurately obtained with upcoming survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

U.S. Agrivoltaics Irradiance Database

This is a foundational data set for research and deployment of agrivoltaics, which is the co-location of agriculture and solar power plants on the same land. This irradiance and shading dataset can be utilized to determine the suitability of agrivoltaics configurations for a given region and crop-type. The data is hourly, 4x4 km resolution across the contiguous United States and Hawaii. It is calculated from the National Solar Radiation Database sites, using the System Advisor Model (SAM) to simulate the shading patterns for 10 common agrivoltaics configurations. Sunlight availability data is reported for 10 locations on the ground between adjacent rows of solar panels, as well as averaged across areas of interest such as the average irradiance in the edge-to-edge open area or across 3-6 planting beds. Other available metrics include the input meteorological data from the NSRDB (e.g. global horizontal irradiance, wind speed, etc.) and estimates for comparing energy and agricultural characteristic across the 10 configurations, including power output per acre or per kW installed capacity and farmable land area per acre.

14 SOLAR ENERGY↗
DOE OSTI2025

Fermi-LAT Captures a Late-2024 Gamma-Ray Outburst near Two Newly Identified Gamma-Ray-emitting Galactic Supernova Remnants, without Evidence of Physical Association

We report the gamma-ray study of two neighboring in the sky Galactic supernova remnants (SNRs), namely, 3C 434.1 (or G094.0+01.0) and G093.7–00.2. In the vicinity of the two SNRs, a late-2024 gamma-ray outburst—not physically connected to the SNRs—was detected with the Fermi Large Area Telescope (LAT). Employing 16.5 yr of Fermi-LAT data, we report the first firm detection of the gamma-ray counterpart of 3C 434.1 at a 7.2σ significance and a likely detection of an enhanced gamma-ray emission signal at a 4.5σ level from G093.7–00.2. The late-2024 gamma-ray outburst is detected at a ∼12σ significance level over a duration of 3 days. For all three objects, a comprehensive morphological and spectral analysis of the corresponding gamma-ray data was conducted. The prevalent scenario for the nature of the gamma-ray emission of both SNRs is attributed to their surrounding environment. Both are likely interacting with nearby dense material, resulting in hadronically induced gamma-ray emission. We deduce that the outburst source is most likely a blazar in flare, linked to the compact, flat-spectrum radio source TXS 2138+527 (also known as NVSS J213953+530016). Further, the spectral analysis of the gamma-ray source conducted within the 100 MeV–800 GeV energy range using the complete LAT data sets, which yielded a soft averaged spectral shape, supports the hypothesis of a flat spectrum radio quasar (FSRQ) origin for the source; with a most likely leptonically induced scenario for the observed gamma-ray outburst as inferred from the obtained hard spectral shape when utilizing short time intervals focusing on the outburst.

Michailidis, Miltiadis [Stanford Univ., CA (United↗
DOE OSTI2024

Insight into premixed diethoxymethane flames: Laminar burning velocities, temperatures, and emissions behaviour

Diethoxymethane ((CH 3 CH 2 O) 2 CH 2 , DEM) is a promising carbon-neutral fuel. DEM is a diether or acetal with a molecular structure similar to oxymethylene ethers (CH 3 O–(CH 2 O)n–CH 3 , OME n ). Thus, DEM can be expected to have a similar combustion behavior to OMEs, reducing harmful emissions such as NO x and particulate matter (PM) in internal combustion engines. From both experimental and kinetic modeling, fundamental studies on DEM are scarce in the literature. More studies are required to gain a detailed insight into the oxidation kinetics of DEM. Laminar burning velocity (LBV) is a critical property that allows a detailed assessment of the potential application of DEM in combustion devices. Unfortunately, the literature on the LBV of DEM is limited. Therefore, in this study we have investigated the LBV of DEM using two reactors for the first time, namely a heat flux burner and a combustion chamber. The experimental data is reported for equivalence ratio between 0.7 and 1.7, initial temperatures of 368–423 K, and initial pressure of 1–5 bar. In addition, we developed a detailed kinetic model extending our recent work of Shrestha et al. (Combust. Flame. 246 (2022) 112,426) to characterize the combustion behavior of DEM utilizing the new experimental data from this work and the literature data. Our model performs remarkably well in capturing the newly measured LBV experimental data over various experimental conditions. We found that DEM and dimethoxy methane (DMM) have similar values of LBVs (within ±1.5 cm/s) for a given condition, which indicates that intermediate chemistry governs the flame chemistry. Despite DEM being a larger molecule that is expected to have slightly lower LBVs than DMM, its effect on the measured values of LBVs is negligible. Finally, we experimentally measured NO x formation in DEM flame for the first time. The stochiometric flame has the highest NO x formation. The proposed model predicted the equivalence ratio dependence of NO x nicely. However, it overestimates the NO x formation for stoichiometric DEM/air mixtures by ~30 %. The model suggests that the thermal NO formation route is favored at lean and stochiometric conditions. In contrast, the prompt NO formation route is enhanced for rich mixtures.

10 SYNTHETIC FUELS↗
DOE OSTI2024

U.S. Average Corn Ethanol Production Baseline for 45Q Life Cycle Analysis Version 1.0 (2018-2022)

U.S. Average Benchmark life cycle inventory documentation for ethanol production for calendar years 2018 - 2022. The documentation includes a technical report describing data sources and statistical methods used and an Excel file showing calculations. The calculations performed are used in the 45Q benchmark json-ld dataset, compatible with the NETL CO2U LCA Guidance Toolkit. Summary impact results will be included in the NETL CO2U LCA Documentation Spreadsheet within the Toolkit. To access the model referenced in the report, please visit https://www.netl.doe.gov/energy-analysis/details?id=55ab21f1-9238-4b63-9a7a-ae1a4cfa7b05.

09 BIOMASS FUELS↗