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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

DAISY: A Rapid Approach to Evaluating Marine Energy Converter Sound (Final Technical Report)

This project’s objective was to improve the quality of acoustic information about marine energy converters that could be collected from groups of drifting hydrophones, while reducing the costs of deployment and data analysis. This was achieved through technology development addressing four focus areas: (1) minimizing flow-noise and self-noise, (2) integrating metadata streams into a single data acquisition system, (3) developing post-processing routines to facilitate rapid data review, and (4) enabling objective identification of marine energy converter sound against a backdrop of ambient noise using time-delay-of-arrival localization.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

AI-Ready Data Pilot Project Report

The proliferation of artificial intelligence in scientific research has created an urgent need to define "AI-ready data" for researchers and, more importantly, provide resources to help them produce AI-ready data. At Pacific Northwest National Laboratory, we conducted a pilot study with three data scientists evaluating three CSV datasets from different scientific domains, followed by semi-structured interviews capturing assessment practices. Our findings reveal that AI-readiness evaluation is intuition-based, with practitioners asking "How fast can I go from raw data to my machine learning pipeline?" Data scientists consistently prioritized workflow efficiency, human interpretability, and quality stewardship signals. From these insights, we developed a practical evaluation framework comprising data requirements, metadata standards, and validation tests that provides actionable criteria for producing and curating AI-ready datasets, addressing the gap between theoretical understanding and practical implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Closure Report for Corrective Action Unit 116: Area 25 Test Cell C Facility, Nevada National Security Site, Nevada with ROTC-1

CR loaded to this OSTI record. Just adding new file which includes CR plus new ROTC 1 and update the metadata to the following: This Closure Report (CR) presents information supporting closure of Corrective Action Unit (CAU) 116, Area 25 Test Cell C Facility. This CR complies with the requirements of the Federal Facility Agreement and Consent Order (FFACO) that was agreed to by the State of Nevada; the U.S. Department of Energy (DOE), Environmental Management; the U.S. Department of Defense; and DOE, Legacy Management (FFACO, 1996 [as amended March 2010]). CAU 116 consists of the following two Corrective Action Sites (CASs), located in Area 25 of the Nevada National Security Site: (1) CAS 25-23-20, Nuclear Furnace Piping and (2) CAS 25-41-05, Test Cell C Facility. CAS 25-41-05 consisted of Building 3210 and the attached concrete shield wall. CAS 25-23-20 consisted of the nuclear furnace piping and tanks. Closure activities began in January 2007 and were completed in August 2011. Activities were conducted according to Revision 1 of the Streamlined Approach for Environmental Restoration Plan for CAU 116 (U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office [NNSA/NSO], 2008). This CR provides documentation supporting the completed corrective actions and provides data confirming that closure objectives for CAU 116 were met. Site characterization data and process knowledge indicated that surface areas were radiologically contaminated above release limits and that regulated and/or hazardous wastes were present in the facility. The Record of Technical Change 1 updated the use restriction information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

FAIR Data Meets FAIR Software

Modern scientific research is increasingly defined by the interplay between data, software, and the workflows that connect them. Yet while the FAIR (Findable, Accessible, Interoperable, Reusable) principles have become foundational for scientific data stewardship, the same level of structure and expectation has only recently begun to extend to research software. This talk covers why and how FAIR principles are being applied to data and software to support data reuse. It outlines the gaps in current sharing norms, the growing federal emphasis on persistent identifiers and public access, and the opportunities created when datasets, computational workflows, code, and models are linked through rich, standardized metadata. Practical implementation pathways for the EIC and JLab communities are described, including datacards for structured dataset documentation and provenance-aware workflows. By aligning data lifecycle management with FAIR-aligned software practices, the scientific community can advance toward autonomous knowledge graphs, generative workflows, and high-quality, AI-ready scientific datasets.

McSpadden, Diana [Thomas Jefferson National Accele↗
DOE OSTI2026

(U)Vendor Sanitization Requirements – SIEMENS Control

This document defines the software requirements for the sanitization of the IPC and or the controller. The system is intended to manage part programs and associated data (e.g. simulations, probing data) by capturing metadata, securely sanitizing files, logging operations, backing up data to a defined path, deploying a user defined program to a controller, and restoring part programs and associated data when required.

42 ENGINEERING↗
DOE OSTI2026

GridCoPilot for Thermal Events: An LLM-Based Platform for Power Grid Reliability Analysis

Large Language Models show promise for translating natural language into database queries, but deploying such systems in safety-critical domains requires high reliability. We present an application of GridCoPilot to thermal event analysis (heatwaves and coldwaves) that affect power grid reliability. Our approach uses a LangChain SQL Agent to translate natural language queries into auditable SQL statements, with deterministic visualization routines that parse the structured query results. We introduce structural framing as a design principle, we integrate a NERC-region-level event library with county-level meteorology and decompose the combined data into three relational tables (event metadata, county-level event details, and a county-to-NERC subregion mapping), using prompt-guided joins to direct the model toward correct multi-table queries. For two core analytical patterns (identifying worst events by region and by region-year), the system achieved 100% SQL accuracy across all 16 NERC subregions and both event types (64 queries total). These results validate the approach for target use cases, though performance on diverse natural language formulations requires further investigation. We discuss design trade-offs, failure modes including JSON output truncation, and pathways for extending this approach to other hazard domains.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A Field and Laboratory Study to Characterize Fault Prevalence in Residential Comfort Systems

This report describes a project whose goal was to determine the prevalence of residential comfort system faults. The focus is on air conditioners and heat pumps, and on key faults that can occur during installation and have significant impacts on performance: (1) incorrect refrigerant charge level (undercharge or overcharge); (2) indoor coil airflow rate; (3) liquid line restrictions; (4) non-condensable gas in the refrigerant; and (5) duct leakage. In addition to quantifying fault prevalence, we collected metadata that could be studied to determine whether there are correlations that suggest drivers of fault prevalence, such as regional variations in practice, economic factors, climatic impacts, and others.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Benchmarking DAOS Filesystem on Aurora

We benchmark the DAOS filesystem on Argonne's Aurora supercomputer (127 nodes, 4,064 targets) using fio, IOR, mdtest, and IO500 to characterize I/O and metadata performance across the DFS API and DFuse+POSIX. Single-client fio shows POSIX bandwidth saturating at 1–2 MiB I/O sizes, with write-heavy workloads outperforming reads. Multi-node IOR shows DFS bandwidth scaling well up to ~32 tasks/node, with write latency growing faster than read latency. An 8-node IO500 evaluation shows DFS achieving ~5x higher bandwidth and ~190x higher IOPS than POSIX. Results indicate DAOS is well-suited to read-heavy workloads like AI training data loading, given appropriately sized transfers and concurrency.

George, Rebecca [College of William and Mary, Will↗
DOE OSTI2026

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
DOE OSTI2023

Lidar / Processed Data

Wind energy research Note that the processed lidar data has the same metadata as the processed buoy data. These were once considered one dataset, but now the lidar data has been separated to form its own dataset.

17 WIND ENERGY↗
DOE OSTI2018

National Hydropower Plant Dataset, Version 2 (FY18Q3)

The National Hydropower Plant Dataset, Version 2 (FY18Q3) is a geospatially comprehensive point-level dataset containing locations and key characteristics of U.S. hydropower plants that are currently either in the hydropower development pipeline (pre-operational), operational, withdrawn, or retired. These data are provided in GIS and tabular formats with corresponding metadata for each. In addition, we include access to download 2 versions of the National Hydropower Map, which was produced with these data (i.e. Map 1 displays the geospatial distribution and characteristics of all operational hydropower plants; Map 2 displays the geospatial distribution and characteristics of operational hydropower plants with pumped storage and mixed capabilities only). This dataset is a subset of ORNL's Existing Hydropower Assets data series, updated quarterly as part of ORNL's National Hydropower Asset Assessment Program.

13 HYDRO ENERGY↗
DOE OSTI2021

Data From: Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO2 and N-2, Journal of Geophysical Research-Biogeosciences

This data package contains pumping data (.txt), parameter matrices, and R code (.R, .RData) to perform bootstrapping for parameter selection for the bioclogging model development. The pumping data were collected from the Russian River Riverbank Filtration site located in Sonoma County, California from 2010-2017 from three riverbank collection wells located alongside the study site. The pumping data is directly correlated with water table oscillations, so the code performs these correlations and simulates stochastic versions of water table oscillations. See Metadata Description.pdf for full details on dataset production. This dataset must be used with the R programming language. This dataset and R code is associated with the publication "Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO2 and N-2"This research was supported by the Jane Lewis Fellowship from the University of California, Berkeley, the Sonoma County Water Agency (SCWA), the Roy G. Post Foundation Scholarship, the U.S. Department of Energy, Office of Science Graduate Student Research (SCGSR) Program, U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award DE-AC02-05CH11231, and the UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.

54 ENVIRONMENTAL SCIENCES↗