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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Patch-level chamber-based CH4 and CO2 flux measurements in freshwater and salt marshes of coastal Louisiana

This dataset contains chamber-based carbon dioxide and methane flux measurements from ecohydrological patches in two coastal wetlands in Louisiana (within the footprint of AmeriFlux sites US-LA2 and US-LA3). Measurements span four patches, two per wetland. At the freshwater marsh (US-LA2), patches were dominated by Sagittaria lancifolia or co-dominated by Sagittaria lancifolia and Typha latifolia. At the salt marsh site (US-LA3), patches were dominated by Spartina alterniflora or Juncus roemerianus. Flux measurements included (i) wetland surface-level measurements encompassing the entire soil-water-vegetation column and (ii) soil-water surface chamber measurements that excluded emergent vegetation. At US-LA3, open-water pools were common and were also measured as a patch type. With this data we aimed to assess differences in gas flux pathways within ecohydrological patches across different wetland types. Files can be read in any program or code typical of processing .csv file types. "PatchChambers_LA2LA3.csv" covers flux data from patch level chambers which includes bulk CO2/CH4 flux encompassing water, soil, and vegetation within each chamber. "Water_Soil_SurfaceChamber_LA2LA3.csv" has CO2/CH4 flux data from chambers measuring only the water-soil surface without the effects of vegetation. Metadata can be found in the similarly named files for each data sheet ("xxxx_md.csv").

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

SPRUCE Bud Cold Hardiness of Trees and Shrubs in Experimental Plots, Marcell Experimental Forest, Minnesota, 2021-2025

This dataset contains bud cold hardiness measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site (Hanson et al, 2017) within the Marcell Experimental Forest in northern Minnesota, USA. Cold hardiness was quantified as the temperature at which low temperature exotherms (LTEs) were identified (i.e., the temperature at which supercooled water within a bud freezes) measured by differential thermal analysis (DTA). Buds were sampled at semi-regular intervals from September 2021 through May 2025 (2021-09-25 to 2025-05-21) across four seasons (2021-2022 through 2024-2025) for four co-occurring boreal peatland tree and shrub species: Picea mariana (PIMA), Larix laricina (LALA), Rhododendron groenlandicum (RHGR), and Chamaedaphne calyculata (CHCA). Samples were collected across the experiment's warming gradient (ambient to +9 degrees Celsius (C)) and pooled by species within each enclosure. These data were used to assess the species- and season-specific effects of experimental warming on cold hardiness and cold damage risk in boreal peatland vegetation (Campos-Arguedas et al, accepted). This dataset contains one data file in comma-separate values (*.csv) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Chamaedaphne calyculata↗
DOE OSTI2025

American-Made Solar Prize: Edgeli Enables DER Integration (CRADA 615) (Final Report)

The purpose of this project was to demonstrate how granular time series data and automated data transformation, and impact assessment tools could speed interconnection approvals for distributed energy resource projects of various types and sizes. Types included community solar, rooftop solar, and EV charging projects. Using software routines to automate the transformation of data (e.g. GIS) to a network database and power flow model then applying scenarios to create hourly (8760) hosting capacity values and voltage and thermal impacts for specific projects, we were able to demonstrate the feasibility of quickly assembling and analyzing key utility data sets for interconnection purposes. The outcomes of this effort will become the foundation for future work that will enhance and encapsulate the software components developed as part of this project, into web services (e.g. APIs) that can be integrated into queue management systems and automate interconnection screening processes.

14 SOLAR ENERGY↗
DOE OSTI2026

Estimating Return on Investment for Energy Technical Assistance Programs

The U.S. Department of Energy's Office of State and Community Energy Programs engaged the National Laboratory of the Rockies to assess the return on investment (ROI) of technical assistance (TA) programs that support state, local, and Tribal energy planning. Although TA delivers value through capacity building, stakeholder engagement, and knowledge transfer, these benefits are often intangible and challenging to monetize. This study reviews existing ROI frameworks and synthesizes the most relevant elements into a hybrid approach tailored to energy TA programs. The proposed framework integrates monetary and non-monetary outcomes through early logic model development, baseline data collection, and the use of proxies for intangible benefits. As a case study, this paper applies this approach to the Communities Local Energy Action Program (Communities LEAP), demonstrating how ROI can inform program design, data strategy, and performance assessment. Findings underscore that ROI should be applied selectively and planned from the outset to ensure data alignment and attribution accuracy. The framework offers TA practitioners a structured approach that can be leveraged for future programs to evaluate and communicate the multifaceted value of TA investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A new data-driven map predicts substantial undocumented peatland areas in Amazonia

Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km 2 ) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km 2 (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Assessment of 180,182, 183,184,186 W Photonuclear Data

When electron beams from accelerators are stopped in thick targets made of materials with a high atomic number (or high-Z targets), they produce photons through braking radiation (commonly known as bremsstrahlung). The efficiency of photon production increases with the atomic number (Z). Tungsten is commonly chosen as a bremsstrahlung converter in both research and medical linear accelerators due to its high Z, large bremsstrahlung cross section, high melting point, and excellent thermal conductivity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A Data-Driven Framework for Predicting the Sorting and Screening Performance of an Integrated Biomass Feedstock Preprocessing System

The characteristics of mechanically sorted and screened lignocellulosic biomass, such as the mass contents of corn stover anatomical fractions (leaves, husks, stalks, cobs, etc.), can be used to calculate the intermediate feedstock quality attributes “yield” and “purity” that indicate the conversion efficiency of biocrude. No prior study has investigated the correlations from the characteristics of raw biomass and preprocessing unit operation parameters to those intermediate feedstock quality attributes. This work presents a data-driven framework for assessing and predicting the intermediate feedstock quality attributes in an integrated biomass feedstock preprocessing system. Our study used corn stover as a typical type of herbaceous biomass because of its abundance in the U.S. It began with data acquisition of moisture content, particle size distribution, and anatomical fractions of the materials after each unit operation in the system. The objective of this preprocessing system is to minimize husks and leaves and maximizing cobs and stalks by mechanically separating the materials into three streams via disc screen and air separator. Prototype neural network models were then developed to evaluate the feasibility of predicting process outcomes based on measurable parameters. It is found that incorporating physical constraints into these prediction models significantly enhances the accuracy of the predicted yield and purity against the ground truth data. The experimental data and model predictions indicate that decreasing throughput increases purity, while higher throughput results in lower purity. Finally, an optimization problem was introduced to search optimal combinations of feed material properties and preprocessing unit operation parameters, as the intermediate feedstock quality attributes – yield and purity, appeared to be competing factors. The study also suggests the continual need to improve the data-driven framework’s predictability by incorporating more accurate physical models to describe the dynamics in the preprocessing units such as the air separator.

09 - BIOMASS FUELS↗
DOE OSTI2024

Updated Filter Leak Frequencies for Use in Risk Assessments

Quantitative risk assessment (QRA) is highly dependent on data, leading to more robust models as new and updated data is acquired. The Hydrogen Plus Other Alternative Fuels Risk Assessment (HyRAM+) QRA capabilities include calculations of individual risk from leaks in a gaseous hydrogen facility due to the potential effects of jet fires and explosions. Leak frequencies are acquired through statistical analysis of published data from a variety of sources and industries. The filter leak frequencies in previous versions of the HyRAM+ software are substantially greater than the leak frequencies of other components, leading to QRA results for gaseous hydrogen in which filters consistently dominate the overall risk. Data that were previously used to derive the filter leak frequencies were reevaluated for applicability and additional data points were added to update the filter leak frequencies. The new frequencies are more comparable to leak frequencies for other components.

08 HYDROGEN↗
DOE OSTI2026

M3SF-25LL010302052 - Radionuclide Interaction with Hydrothermally Altered Repository Materials

This progress report (Level 3 Milestone Number M3SF-25LL010302052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline Host Rock Properties & Processes - LLNL Number SF-25LL01030205. Observed changes in radionuclide sorption after bentonite/clay heating have implications for radionuclide diffusive transport through engineered barriers and must be considered when designing waste disposal repositories. Recent research performed at Los Alamos National Laboratory (LANL) has provided key insights regarding the hydrothermal alteration behavior of bentonite backfill in the presence of repository materials (steel, concrete, etc.). We are examining how this mineral alteration affects retardation behavior of a suite of radionuclides of interest to repository performance assessment. Sorption experiments and data analysis for 233 U were initiated in FY24 following earlier experiments performed on 243 Am, 90 Sr, 137 Cs. In FY25, we completed the 233 U study and initiated and completed a study of 237 Np sorption. Below, we summarize the results and potential impacts of hydrothermal alteration on radionuclide retardation and assess the importance of this process to radionuclide migration from a GHRDC. We also use statistical tools (i.e. PCA) to help us determine the major drivers in affecting changes in measured Kd values induced by hydrothermal alteration. These experiments also allow us to test the predictive ability of our component additivity approach to surface complexation and ion exchange. Our guiding hypothesis is that a robust surface complexation/ion exchange model and associated database can effectively predict changes in radionuclide sorption behavior resulting from the hydrothermal alteration of mineralogy in a repository near field. In November 2024 the paper “Selenium interaction with iron minerals: Quantitative comparison of sorption and coprecipitation impacts on mobility” was published in Applied Geochemistry. A short update of results to date is presented below. In FY25, we also actively supported the DITUSC project, which is part of the EURADII initiative, as associate partners. We are executing the Migration2025 conference and support associated the NEA-TDB and Thermochimie workshops that will provide critical international engagements and develop consensus and synergy in thermodynamics as it relates to supporting the US nuclear waste repository program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Silicon Carbide Composite Cladding Qualification

This report examines the process to qualify a new fuel-cladding type focusing on the data requirements and types of irradiation testing necessary to meet the regulatory burden and related guidance applicable to fuel qualification of accident-tolerant fuel. The report considers the use of accelerated fuel qualification techniques and lead-test specimen programs that may shorten the timeline for qualifying fuel for use in a nuclear reactor at the desired burnup. The assessment framework particularly emphasizes the identification of key fuel manufacturing parameters, the specification of a fuel performance envelope to inform testing requirements, the use of evaluation models in the fuel qualification process, and the assessment of the experimental data used to develop and validate the empirical models and empirical safety criteria.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Active Learning Meets Foundation Models: Fast Remote Sensing Data Annotation for Object Detection

Object detection in remote sensing demands extensive, high-quality annotations—a process that is both labor-intensive and time-consuming. In this work, we introduce a real-time active learning and semi-automated labeling framework that leverages foundation models to streamline dataset annotation for object detection in remote sensing imagery. For example, by integrating a Segment Anything Model (SAM), our approach generates mask-based bounding boxes that serve as the basis for dual sampling: (a) uncertainty estimation to pinpoint challenging samples, and (b) diversity assessment to ensure broad data coverage. Furthermore, our Dynamic Box Switching Module (DBS) addresses the well-known cold start problem for object detection models by replacing its suboptimal initial predictions with SAM-derived masks, thereby enhancing early-stage localization accuracy. Extensive evaluations on multiple remote sensing datasets plus a real-world user study, demonstrate that our framework not only reduces annotation effort, but also significantly boosts detection performance compared to traditional active learning sampling methods. The code for training and the user interface will be made available.

Burges, Marvin [ORNL] (ORCID:0000000312690769)↗
DOE OSTI2024

Field Evaluation of the High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art - Summary of Measurement and Verification (M&V) Results from Summer 2023

The National Renewable Energy Laboratory (NREL) is performing a measurement and verification (M&V) assessment of the Conservant High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art in San Diego, California. The HEDS was selected for evaluation by the U.S. Department of Energy (DOE) High Impact Technology Catalyst (HIT) evaluation program in 2022. This report documents recently completed analysis of data collected as an initial assessment of the HEDS system performance. Data was collected for the summer M&V during several weeks in August and September 2023 while operating the Timken Museum's HVAC system in several operating modes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Operating Experience Data Analysis for Digital Instrumentation and Control System Reliability and Risk Assessment in Nuclear Power Plants

The implementation of advanced digital instrumentation and control (DI&C) systems in U.S. nuclear power plants (NPPs) can bring significant advancements in reliability, monitoring, and control capabilities. However, these systems also introduce new challenges, particularly in assessing risks such as common-cause failures (CCFs) and establishing robust reliability estimates for DI&C components. Addressing these challenges is critical for ensuring the safe and efficient operation of NPPs. Recently, Idaho National Laboratory was tasked by the U.S. Nuclear Regulatory Commission (NRC) to conduct a DI&C reliability study using operating experience data from the nuclear industry. The two operating experience data sources for the study are the Institute of Nuclear Power Operations’ Industry Reporting and Information System (IRIS) and the NRC’s Licensee Event Report database which is hosted at Idaho National Laboratory at https://lersearch.inl.gov/LERSearchCriteria.aspx. This report provides a comprehensive examination of DI&C systems, including their architecture, operational advantages, and associated challenges. It reviews existing industry DI&C studies and failure mode taxonomies, along with reliability data from various industries. Through a detailed analysis of these databases, the study provides insights into DI&C system performance. Considerations should be given to incorporate DI&C failure data into the NRC's Integrated Data Collection and Coding System and updating the Reliability and Availability Data System to support ongoing DI&C reliability studies. Recommendations are also provided for modeling DI&C reliability and CCF in probabilistic risk assessment, thereby supporting risk-informed decision-making and enhancing the reliability and safety of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Walker Branch Watershed: Daily Stream Metabolism and Organic Carbon Spiraling Metrics in the West Fork of Walker Branch, Tennessee, USA, 2004-2010

This dataset contains daily metabolism estimates of gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP), in addition to organic carbon spiraling length (SOC) and mineralization velocity (VfOC) estimates at the West Fork of Walker Branch, a small headwater stream, in the Walker Branch Watershed, Tennessee, USA. Observations were made from 2004-2010 (2004-01-01 to 2010-12-31). These data were generated to assess seasonal and interannual variability in metabolism and organic carbon spiraling and to explore potential driver variables, as analyses of intra- and interannual variability in metabolism and organic carbon spiraling are currently limited, leaving knowledge gaps in the driving mechanisms of and future changes to stream metabolism and carbon processing under climate change. Additionally, measurements of discharge (Q), stream width, stream- and canopy-level photosynthetically active radiation (PAR), water temperature, and precipitation from this time frame are included. This dataset contains one data file in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Cloud-Based Demonstration of the Eastern Interconnection Situational Awareness Monitoring System (ESAMS)

This report describes a cloud-based implementation and field demonstration of the Eastern Interconnection Situational Awareness and Monitoring System (ESAMS). ESAMS was developed to support the detection and source localization of forced oscillations using synchrophasor measurements from tie-lines connecting areas served by different reliability coordinators (RCs), so that RCs could better coordinate their response to wide-area events. A previous effort had identified deployment barriers associated with hosting shared situational awareness tools at a single RC. To address these barriers, ESAMS was migrated to Amazon Web Services and evaluated in a six-month field demonstration. ISO New England (ISO-NE) and PJM streamed data to the platform using AWS Direct Connect and a site-to-site VPN, respectively. The resulting multi-utility measurement footprint enabled regional source localization across major portions of the U.S. Eastern Interconnection and supported routine identification of oscillation events. During the final three months of the trial, 24 events above 2 MW/MVAR were detected. The largest detected oscillation approached a 25 MW peak-to-peak amplitude, and the longest persisted intermittently for more than 11 hours. The demonstration also assessed operational considerations—including data transfer volumes, end-to-end latency, and cloud computing costs—and found that network and compute requirements were modest relative to typical cloud capabilities while providing performance comparable to prior on-premises deployments. Overall, the results indicate that cloud hosting can provide a practical path to shared interconnection-wide oscillation monitoring. The cloud ESAMS demonstration establishes a foundation for broader utility participation and for building future wide-area analytics that leverage measurements across organizational boundaries.

Follum, James D.↗
DOE OSTI2024

Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts.

Drought↗
DOE OSTI2025

Enhanced Component Performance Study: Emergency Diesel Generators 1998-2024

This report presents an enhanced performance evaluation of the emergency power system (EPS) and high-pressure core spray (HPCS) emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS) data from 1998 through 2024 and (2) maintenance unavailability performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2024. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in Nuclear Regulatory Commission (NRC) probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. The EDG failure modes considered are fail to start (FTS), fail to load and run (FTLR), and fail to run after one hour of operation (FTR>1H). Engineering analyses were performed with respect to time-period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed include subcomponent, failure cause, detection method, recovery, manufacturer, and EDG rating. The following increasing trends were identified for EDGs for the most recent 10-year period: • EPS and HPCS EDG frequency of start demands (demands per reactor year) • EPS and HPCS EDG frequency of FTLR demands • EPS and HPCS EDG frequency of run>1H hours. The following decreasing trends were identified for EDGs for the most recent 10-year period: • EPS EDG FTR>1H failure rate • EPS EDG unreliability • EPS and HPCS EDG frequency of FTR>1H events (failures per reactor year).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗