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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Towards Cross-Facility Workflows Orchestration through Distributed Automation

Modern science relies on end-to-end workflows that incorporate experimental instruments and utilize edge, cloud, or high-performance computing and storage resources. These components are geographically dispersed across various user facilities and interconnected through high-speed networks. In this paper, we present Zambeze, an automated distributed framework designed to facilitate this new class of cross-facility workflows. Utilizing swarm intelligence principles, Zambeze orchestrates science campaigns by managing distributed autonomous agents. These agents can offer a suite of services, including computing, storage, and data management. We demonstrate the feasibility of Zambeze through a real-world application involving electron microscopy, enhanced with Artificial Intelligence capabilities.

Skluzacek, Tyler↗
DOE OSTI2025

Existing Hydropower Assets (EHA) Capacity Factor Plant Database, 2005-2024

Existing Hydropower Asset (EHA) Annual Capacity Factor is a geospatial point-level dataset containing annual capacity factors over the years (2005-2024) and key characteristics of operational U.S. hydropower plants with 1 megawatt or greater of nameplate capacity. EIA form 860 and EHA are the primary sources of the derived data. Pumped storage and hybrid plants are excluded.

Johnson, Megan [ORNL] (ORCID:0000000290141741)↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2023

The UCLA Cosmochemistry Database

Abstract The UCLA Cosmochemistry Database was initiated as part of a data-rescue and -storage project aimed at archiving a variety of cosmochemical data acquired at University of California, Los Angeles (UCLA). The data collection includes elemental compositions of extraterrestrial materials analyzed by UCLA cosmochemists over the last five decades. The analytical techniques include atomic absorption spectrometry (AAS) and neutron activation analysis (NAA) at UCLA. The data collection is stored on the Astromaterials Data System (Astromat). We provide both interactive tables and downloadable datasheets for users to access all data. The UCLA Cosmochemistry Database archives cosmochemical data that are essential tools for increasing our understanding of the nature and origin of extraterrestrial materials. Future studies can reference the data collection in the examination, analysis, and classification of newly acquired extraterrestrial samples.

Science & Technology - Other Topics↗
DOE OSTI2025

Navigating Integration: Key Challenges for Data Centers, Nuclear Stakeholders, and Utility Operators

The rapid expansion of data centers, driven by the exponential growth in data-processing and storage needs, presents significant challenges and opportunities for various stakeholders, including data center developers, nuclear energy providers, and utility companies. Data centers are projected to consume 6.7–12% of United States (U.S.) electricity by 2028, driven by artificial intelligence (AI) and cloud-computing demands. Nuclear energy offers reliability and dispatchable baseload power, but data centers need power now while nuclear still needs time to address siting, fast power ramping, and regulatory hurdles. Utilities must keep pace with the unprecedented acceleration of large load interconnection requests and urgently adapt to high-density loads while maintaining grid stability, reliability, and accelerating interconnection timelines. This report dives into these challenges and proposes key collaboration strategies to streamline data center integration that aligns with recent federal initiatives like America’s AI Action Plan and related executive orders that emphasize the importance of data center growth, nuclear energy expansion, and maintaining a competitive edge in the global AI race.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

Hydrogen adsorption and transport in clay-rich geomaterials: Implications for large-volume underground hydrogen storage

Depleted oil and gas reservoirs, characterized by impermeable clay-rich caprocks, are promising sites for large-scale underground hydrogen storage (UHS), which is a key strategy to support hydrogen-based energy systems. However, experimental data on hydrogen storage in clay-rich geomaterials remain scarce. In this work, we experimentally investigated hydrogen adsorption and migration in clay-rich geomaterials in the presence of nitrogen and water under controlled temperatures. Experimental observations showed that hydrogen was adsorbed in dry illite. A dual-porosity transport model was developed to interpret hydrogen transport between large-pore and small-pore domains in illite. The large-pore domain is the space between clay particles (i.e., inter-particle space), whereas the small-pore domain is the nanoscale pore space between clay mineral layers (i.e., inter-layer or intra-particle space). In contrast, nitrogen showed no evidence of adsorption in dry illite because it cannot move into the small-pore domain due to the relatively large kinetic diameter, referred to as the molecular sieving effect. Here, we found that 0.7–1.3 nm is the length scale regulating this molecular sieving effect, matching the interlayer spacing in illite, suggesting that nitrogen is a promising cushion gas in UHS, which aims to maintain adequate pressure in the reservoir for economic operations. In wetted illite, hydrogen was not adsorbed into the interlayer space due to the occupation of adsorption sites by interlayer water, which highlights the critical role of the clay hydration state in controlling hydrogen-clay interactions. Additionally, hydrogen adsorption experiments on crushed shale indicated that the shale surface possessed adsorption sites more favorable for hydrogen than for nitrogen. Through these experiments, we provide new insights into hydrogen storage mechanisms in clay-rich geomaterials and offer valuable laboratory data for evaluating the performance of large-scale UHS systems.

Adsorption↗
DOE OSTI2024

Spatial Seal Database for Prospective Storage Resources in the USA

The goal of the Spatial Seal Database for Prospective Storage Resources in the USA is to provide relevant information and spatial extents of caprock and seal rocks. A lack of aggregated information is readily available that focuses on the caprock and seal units within sedimentary basins. The EPA class VI permit requires an assessment of the confining zone as part of submitting a permit. The data catalog of seal unit names and relevant properties with the seal spatial extent database aims to help provided important data for carbon storage based assessments. The data catalog and database are designed to show what seal data is available in a sedimentary basin and guide stakeholders to the original data source for those datasets.

Pantaleone, Scott↗
DOE OSTI2025

GeoGridFusion (Open-Source Geospatial Toolkit for Solar Data Integration​) [SWR-25-19]

GeoGridFusion facilitates the usage and storage of gridded geospatial satellite data by users outside of the National Renewable Lab (NREL), particularly those without access to high-performance computing (HPC) resources. This tool builds on work done by the PVDegradationTools project for DuraMAT, with the goal of making our advancements from this project widely accessible. This repo contains utilities to allow for the storage of user downloaded geospatial weather data by providing a local datastore for storage and spatial queries, supporting large-scale analyses without the need for HPC resources.

Ford, Tobin [National Renewable Energy Laboratory ↗
DOE OSTI2024

Smart CO2 Transport-Route Planning Tool: Providing Data and Insights for Accelerating Carbon Transport & Storage Deployment

Overview presentation given at the 2024 FECM / NETL Carbon Management Research Project Review Meeting on NETL's Bipartisan Infrastructure Law-funded Smart CO2 Transport-Route Planning Tool and associated geodatabase. This machine learning informed, data-driven public resource was designed to inform regulators, industry, and researchers plan and develop safe and efficient transport routes across the country.

Romeo, Lucy↗
DOE OSTI2026

FIRM: federated image reconstruction using multimodal tomographic data

Here, we propose a federated algorithm for reconstructing images using multimodal tomographic data sourced from dispersed locations, addressing the challenges of traditional unimodal approaches that are prone to noise and reduced image quality, as well as the limitations of centralized multimodal approaches that require extensive data transfer, leading to significant communication overhead, storage demands, and potential data privacy concerns. Our approach formulates a joint inverse optimization problem incorporating multimodality constraints and solves it in a federated framework through local gradient computations complemented by lightweight central operations, thereby ensuring data decentralization. Leveraging the connection between our federated algorithm and the quadratic penalty method, we introduce an adaptive step-size rule with guaranteed sublinear convergence. Numerical results demonstrate superior computational efficiency and improved image reconstruction quality compared to existing approaches.

federated algorithm↗
DOE OSTI2026

ndi

The Nuclear Data Interface (NDI) is an application programming interface (API) that allows access to standard nuclear data parameters while hiding the underlying details of the data libraries and their storage. It allows access to multigroup transport data (neutron and gamma), thermonuclear burn data, dosimetry data, production/depletion chain data, radiochemistry data, and secondary neutron multiplicity data. The name NDI refers to both the code and data formats supported by the code.

Saller, Thomas↗
DOE OSTI2026

Integrated Energy-Water Data for Cross-Sector Resilience

This white paper focuses on the “energy-for-water” domain, addressing the urgent need for integrated, empirical data to support regional management, benchmarking, and research on improving efficiency and developing technologies for water and wastewater management systems. The costs and energy required for the supply, treatment, and distribution of water and wastewater lack a standard data collection mechanism and centralized database or storage infrastructure, limiting data-driven decision-making across interdependent infrastructure systems.

42 ENGINEERING↗
DOE OSTI2024

WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

Tetteh, Daniel A.↗
DOE OSTI2025

Fate of Listeria monocytogenes Serotypes on Frozen Mixed Vegetables During Consumer‐Simulated Thawing and Storage

ABSTRACT Recent outbreaks and recalls associated with frozen vegetables in the United States and Europe have been linked to Listeria monocytogenes . This study aims to understand the extent to which frozen vegetables support the growth of L. monocytogenes once thawed and held at different temperatures. Six L. monocytogenes strains, two of each from serotypes 1/2a, 1/2b, and 4b, were individually inoculated onto frozen vegetables and stored at −18°C for 7 days. After 7 days, the vegetables were thawed and stored at 5°C or 10°C for up to 14 days or at 25°C for up to 7 days. L. monocytogenes was enumerated from the thawed vegetables throughout the storage period. Population data were fitted to the primary Baranyi model to estimate growth rates and lag phase durations; the secondary Ratkowsky square root model was used to model the relationship of the growth rates with storage temperature. Five of the L. monocytogenes strains survived and grew on the thawed vegetables (population increases of > 1 log CFU/g) stored at 5°C, and all six of the strains proliferated at 10°C and 25°C (population increases of > 3 log CFU/g after 14 days and > 4 log CFU/g after 7 days, respectively). A secondary model was successfully generated based on the growth rates of the six L. monocytogenes strains on the thawed vegetables ( r 2 = 0.8888, RMSE = 0.2057). Results from this study fill a data gap associated with L. monocytogenes survival on thawed vegetables and can be used to determine safe handling and storage practices for these products to protect public health.

Salazar, Joelle K. [Division of Food Processing Sc↗
DOE OSTI2025

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗