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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 OSTI2020

GBCGE Subsurface Database Explorer and APIs

This submission defines a DOI for the Great Basin Center for Geothermal Energy's (GBCGE) Subsurface Database Explorer web application and underlying data services, and acknowledges the INGENIOUS project as a major source of funding for data compilation and quality assurance. The GBCGE Subsurface Database Explorer is an interactive web mapping application that provides public access to the GBCGE Subsurface Database, and its collection of datasets pertinent to geothermal exploration, oil and gas exploration, critical mineral exploration, and other subsurface characterization for the Great Basin Region, western US. This is a living database, and will be continuously updated with new data and datasets as funding and motivations allow. The underlying database views that populate the web application are on an automated refresh schedule. Data sources and acknowledgements: We thank our partners with the Nevada Division of Minerals (NDOM), the Southern Methodist University (SMU), and Great Basin State Geological Surveys for their active efforts in data curation, schema design, and quality assurance. We also thank contributors among the USGS, Oregon Institute of Technology, State Divisions of Water Resources, State Divisions of Oil, Gas, and Minerals, and State Geological Surveys for open data availability and direct contributions made under the National Geothermal Data System (NGDS).

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

United States Nuclear Data Program Annual Report for FY2021

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2021 (FY21) summarizes the work of USNDP for the period of October 1, 2020 through September 30, 2021, with respect to the Work Plan for FY21 that was prepared in 2019. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the nuclear data program is described in the staffing table and in Appendix A. This leverage amounts to about 3.24 FTE scientific, to be compared with 25.095 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

United States Nuclear Data Program Annual Report for FY 23

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2023 (FY23) summarizes the work of USNDP for the period of October 1, 2022 through September 30, 2023, with respect to the Work Plan for FY23 that was prepared in 2022. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the nuclear data program is described in the staffing table and in Appendix A. This leverage amounts to about 17.4 FTE scientific, to be compared with 23.8 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

United States Nuclear Data Program Annual Report for Fiscal Year 2024

The US Nuclear Data Program (USNDP) Annual Report for Fiscal Year 2024 (FY24) summarizes the work of USNDP for the period of October 1, 2023 through September 30, 2024, with respect to the Work Plan for FY24 that was prepared in 2022. The Work Plan and Final Report for USNDP are prepared for the DOE Office of Science, Office of Nuclear Physics. The support for the nuclear data activity from sources outside the nuclear data program is described in the staffing table and in Appendix A. This leverage amounts to about 14.8 FTE scientific, to be compared with 13.9 FTEs at USNDP units funded by the DOE Office of Science, Office of Nuclear Physics. Since it is often difficult to separate accomplishments funded by various sources, some of the work reported in the present report was accomplished with nuclear data program support leveraged by other funding.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A study on the clustering properties of radio-selected sources in the Lockman Hole region at 325 MHz

Studying the spatial distribution of extragalactic source populations is vital in understanding the matter distribution in the Universe. It also enables understanding the cosmological evolution of dark matter density fields and the relationship between dark matter and luminous matter. Clustering studies are also required for EoR foreground studies since it affects the relevant angular scales. This paper investigates the angular and spatial clustering properties and the bias parameter of radio-selected sources in the Lockman Hole field at 325 MHz. The data probes sources with fluxes ≳0.3 mJy within a radius of 1.8° around the phase centre of a 6° × 6° mosaic. Based on their radio luminosity, the sources are classified into Active Galactic Nuclei (AGNs) and Star-Forming Galaxies (SFGs). Clustering and bias parameters are determined for the combined populations and the classified sources. The spatial correlation length and the bias of AGNs are greater than SFGs- indicating that more massive haloes host the former. This study is the first reported estimate of the clustering property of sources at 325 MHz, intermediate between the pre-existing studies at high and low-frequency bands. It also probes a well-studied deep field at an unexplored frequency with moderate depth and area. Clustering studies require such observations along different lines of sight, with various fields and data sets across frequencies to avoid cosmic variance and systematics. Thus, an extragalactic deep field has been studied in this work to contribute to this knowledge.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Detecting and Analyzing Power System Disturbances in PMU Data with the Open-Source Archive Walker Tool

As the number of Phasor Measurement Units (PMUs) deployed in power systems increases, so do the archives of synchrophasor measurements stored by utilities. Significant value can be extracted from these archives by using them to support studies such as frequency response analysis, small-signal stability analysis, and power plant model validation. To better enable utilities to perform these studies, the open-source Archive Walker tool was developed. This tool examines PMU data for grid disturbances and periods of interest. Once identified, the data can be further analyzed inside Archive Walker or exported to specialty tools. In this paper, the various disturbance detectors available in Archive Walker are described, and its interactions with other openly-available tools are highlighted.

Follum, James D.↗
DOE OSTI2022

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Source Characterization of the Declared North Korean Nuclear Tests From Regional Distance Coda Wave Spectral Ratios

Abstract Seismic observations of underground nuclear explosions provide crucial data on source yield and depth that cannot easily be estimated from other geophysical methods. However, it is difficult to obtain reliable yield estimates for test sites for which we do not have direct seismic calibration experiments. To obtain source information from uncalibrated sites and paths, local and regional seismic records of six, proximal, declared underground nuclear explosions in North Korea are used to compute spectral ratios of narrow‐band waveform envelopes of body‐wave coda that remove path and site effects to reveal precise, relative source moment. The yields of these explosions are obtained from the observed source ratios by simultaneously fitting the classical source model of Mueller and Murphy (1971), https://doi.org/10.1785/bssa0610061675 to all event pairs. The source model provides an impressive fit to the observations considering that the P phase coda derived source spectral ratios did not require a prior knowledge of the source or regionally calibrated corrections to be applied to the data. However, the observed corner frequencies from S wave coda spectral ratios are lower than the source model predictions, but are well fit by models calculated using the corner frequency consistent with the Fisk conjecture. The results presented here provide novel constraints on the spectral distributions of the energy radiated by the sources of the DPRK test series, and allows for an independent evaluation of existing estimated source model parameters.

58 GEOSCIENCES↗
DOE OSTI2025

SITCOMTN-163: Source Selection for Abell 360 in LSSTComCam Data Preview 1

We cover the source selection done for the Abell 360 LSSTComCam cluster study focusing on color and photo-z cuts. Identification of cluster members via the red sequence and photo-z offers a science focused validation of photometry with LSSTComCam. We are able to cross-match with DESI spectroscopic redshifts to offer an independent validation suite on photo-z estimates. We make various color and photo-z cuts to generate N(z)s and shear profiles. We find that both cuts are quite robust to various choices made and can produce a shear profile for Abell 360. Both methods should be applicable to generating a consistent mass estimate for the cluster.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Legacy Survey of Space and Time Data Preview 1: dia_object_forced_source dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the dia_object_forced_source dataset type. These are forced measurements in visit and difference images, at the coordinates of all DIA objects. This release contains 597 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Machine Learning for Automated Extraction of Building Geometry

As data science comes to buildings, the promise of using machine learning and novel sources of data has received much attention. Advances in machine learning and computer vision algorithms, combined with increased access to unstructured data (e.g., images and text), have created an opportunity for automated extraction of building characteristics – cost-effectively, and at scale. Acquisition of features such as footprint are time consuming and costly to acquire with today’s manual methods, but can be streamlined through intelligent software-based solutions applied to satellite images. When combined with aerial RGB and thermal images, full 3D geometries and thermal maps can be constructed to determine additional characteristics such as window to wall ratio, height, number of stories and envelope thermal characteristics. In this paper we present three contributions to accelerate these high potential opportunities: (1) a methodical analysis of how these features can be integrated into today’s simulation and data driven software tools to enhance efficiency measure identification and owner/operator decision making; (2) development and accuracy testing of open source deep neural network methods to extract building footprints from satellite imagery, including the curation and application of openly available GIS datasets for training and continued development by others; and (3) an open framework for drone-based image capture and creation of 3D building geometries. This work represents an important bridge between high-level studies that span diverse application areas and those that detail point solutions yet cannot be easily replicated or extended.

Touzani, Samir↗
DOE OSTI2025

Source apportionment of aerosols at the White River IMPROVE site near the SAIL site

This data set contains source apportionment results at the White River IMPROVE site (39.1536, -106.8209), which is about 30 km north of the Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign site. The IMPROVE network (Malm et al. 1994) collected 24-hour aerosol filter samples every three days over several decades at this site. Chemical concentrations in the PM2.5 fraction of 19 elements (Al, As, Br, Ca, Cl, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Si, Ti, V, and Zn), along with nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and calculated coarse mass concentrations (PM10−PM2.5 mass concentrations), from 2014 to 2023, were used as input for the PMF analysis. PMF was performed using EPA PMF 5.0 (Norris et al. 2014). A five-factor solution was chosen as the optimal solution. These factors were identified as coarse dust, fine dust, biomass burning, sulfate-dominated, and nitrate-dominated sources. This data set is useful for understanding aerosol sources and their long-term variability near this region.

biomass burning↗
DOE OSTI2023

Data Remapping Between One-Dimensional Meshes

In this report, we describe two approaches to the problem of remapping data from a source mesh (on which data is available) onto a target mesh. We consider two separate methods to solve the problem: Pointwise and Conservative remap, and determine why one is more advantageous when considering different physics applications and elements. We utilize C++ functionalities to derive our findings along with the C++ ”Chronos” library for timing measurements of our studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Independent malware detection architecture

A system and method (referred to as the system) detect malware by training a rule-based model, a functional based model, and a deep learning-based model from a memory snapshot of a malware free operating state of a monitored device. The system extracts a feature set from a second memory snapshot captured from an operating state of the monitored device and processes the feature set by the rule-based model, the functional-based model, and the deep learning-based model. The system identifies identifying instances of malware on the monitored device without processing data identifying an operating system of the monitored device, data associated with a prior identification of the malware, data identifying a source of the malware, data identifying a location of the malware on the monitored device, or any operating system specific data contained within the monitored device.

Smith, Jared M.↗
DOE OSTI2023

Pilot decision space for sonic boom impact resolution

A system for predicting pressure waves in a sonic boom footprint calculates alternative footprints and pressure waves along a flight path based on speed and altitude modifiers. The available, adjustable parameters are bounded within a flight envelope and along an approved flight corridor. The system receives and incorporates data from external sources, such as weather data, that impacts sonic boom pressure wave predictions and aircraft performance characteristics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

NREL OpenPATH: An Open-Source, Extensible Platform for Instrumenting Travel Behavior Data

NREL OpenPATH is an open-source, extensible platform that allows communities to instrument their own travel behavior data. The platform consists of a smartphone app, server and analysis pipeline, and enables collection of opt-in, multi-modal, end-to-end travel diaries. It makes the aggregate statistics available via a public dashboard, and allows deployers to download and visualize trip and trajectory data through the admin dashboard. It also allows for customization of the initial demographic survey and the trip-level qualitative information collected. Our goal is to provide an easy-to-use tool that can democratize travel behavior data collection by empower communities of all sizes to recruit participants and obtain a holistic picture of their travel patterns. The platform has been used by close to 40 partners, to collect data from thousands of participants. Upon signing a simple MOU, it is currently available for free to universities, non-profits and public agencies in the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Time-Integrated Neutrino Source Searches with 10 Years of IceCube Data

This Letter presents the results from pointlike neutrino source searches using ten years of IceCube data collected between April 6, 2008 and July 10, 2018. We evaluate the significance of an astrophysical signal from a pointlike source looking for an excess of clustered neutrino events with energies typically above ~1 TeV among the background of atmospheric muons and neutrinos. We perform a full-sky scan, a search within a selected source catalog, a catalog population study, and three stacked Galactic catalog searches. The most significant point in the northern hemisphere from scanning the sky is coincident with the Seyfert II galaxy NGC 1068, which was included in the source catalog search. The excess at the coordinates of NGC 1068 is inconsistent with background expectations at the level of 2.9σ after accounting for statistical trials from the entire catalog. The combination of this result along with excesses observed at the coordinates of three other sources, including TXS 0506+056, suggests that, collectively, correlations with sources in the northern catalog are inconsistent with background at 3.3σ significance. The southern catalog is consistent with background. Finally these results, all based on searches for a cumulative neutrino signal integrated over the 10 years of available data, motivate further study of these and similar sources, including time-dependent analyses, multimessenger correlations, and the possibility of stronger evidence with coming upgrades to the detector.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Derivation of at-birth neutron energy distribution of americium-beryllium source based on ISO8529 spectral data

In many practical applications, the accuracy of neutron transport calculations depends on an estimate of the energy distribution provided in the source definition. While the energy distribution of neutrons emitted by spontaneous fission sources is well-defined, the spectra of neutrons produced in (α,n) reactions in compound mixtures, such as americium-beryllium (AmBe), depend on the microstructural properties of the source material, which may vary. Although the energy of neutrons produced in nuclear reactions can be calculated from first principles, such computations require detailed knowledge of the key characteristics of the source material, which are often unknown. Here, this study focuses on deriving the at-birth neutron energy distribution for an AmBe source by applying reverse transport calculations to the externally measured high-precision spectrum recommended in the latest revision of the international standard. The derived at-birth spectrum was validated through indirect energy-sensitive neutron emission rate measurements of AmBe sources calibrated at national primary metrology institutions. The resulting at-birth neutron energy distribution serves as essential input data for radiation transport modeling, providing a validated spectrum for broader experimental and computational applications.

AmBe↗