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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Full Inversion of Solar Relativistic Electron Events Measured by the Helios Spacecraft

The Parker Solar Probe and the incoming Solar Orbiter mission will provide measurements of solar energetic particle (SEP) events at close heliocentric distances from the Sun. Up to present, the largest data set of SEP events in the inner heliosphere are the observations by the two Helios spacecraft. Aims.We re-visit a sample of 15 solar relativistic electron events measured by the Helios mission with the goal of better characterizing the injection histories of solar energetic particles and their interplanetary transport conditions at heliocentric distances <1AU. Methods. The measurements provided by the E6 instrument on board Helios provide us with the electron directional distributionsin eight di erent sectors that we use to infer the detailed evolution of the electron pitch-angle distributions. The results of a Monte Carlo interplanetary transport model, combined with a full inversion procedure, were used to fit the observed directional intensities in the 300–800 keV nominal energy channel. Unlike previous studies, we have considered both the energy and angular responses of the detector. This method allowed us to infer the electron release time profile at the source and determine the electron interplanetary transport conditions. Results. We discuss the duration of the release time profiles and the values of the radial mean free path, and compare them with thevalues reported previously in the literature using earlier approaches. Five of the events show short injection histories (<30 min) at the Sun and ten events show long-lasting (>30 min) injections. The values of mean free path range from 0.02AU to 0.27AU.Conclusions. The inferred injection histories match with the radio and soft X-ray emissions found in literature.We find no dependence of the radial mean free path on the radial distance. In addition, we find no apparent relation between the strength of interplanetary scattering and the size of the solar particle release.

Pacheco, D.↗
NASA NTRS2013

Detection of Evolved Carbon Dioxide in the Rocknest Eolian Bedform by the Sample Analysis at Mars(SAM) Instrument at the Mars Curiosity Landing Site

The Sample Analysis at Mars (SAM) instrument detected four releases of carbon dioxide (CO2) that ranged from 100 to 700 C from the Rocknest eolian bedform material (Fig. 1). Candidate sources of CO2 include adsorbed CO2, carbonate(s), combusted organics that are either derived from terrestrial contamination and/or of martian origin, occluded or trapped CO2, and other sources that have yet to be determined. The Phoenix Lander s Thermal Evolved Gas Analyzer (TEGA) detected two CO2 releases (400-600, 700-840 C) [1,2]. The low temperature release was attributed to Fe- and/or Mg carbonates [1,2], per-chlorate interactions with carbonates [3], nanophase carbonates [4] and/or combusted organics [1]. The high temperature CO2 release was attributed to a calcium bearing carbonate [1,2]. No evidence of a high temperature CO2 release similar to the Phoenix material was detected in the Rocknest materials by SAM. The objectives of this work are to evaluate the temperature and total contribution of each Rocknest CO2 release and their possible sources. Four CO2 releases from the Rocknest material were detected by SAM. Potential sources of CO2 are adsorbed CO2, (peak 1) and Fe/Mg carbonates (peak 4). Only a fraction of peaks 2 and 3 (0.01 C wt.%) may be partially attributed to combustion of organic contamination. Meteoritic organics mixed in the Rocknest bedform could be present, but the peak 2 and 3 C concentration (approx.0.21 C wt. %) is likely too high to be attributed solely to meteoritic organic C. Other inorganic sources of C such as interactions of perchlorates and carbonates and sources yet to be identified will be evaluated to account for CO2 released from the thermal decomposition of Rocknest material.

Sutter, B.↗
DOE OSTI2025

Legacy Survey of Space and Time Data Preview 1: 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 object_forced_source dataset type. These are forced measurements in visit and difference images, at the coordinates of all objects. This release contains 636 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

GeoThermalCloud: A Machine Learning Tool for Discovery, Exploration, and Development of Hidden Geothermal Resources

In this 25 minute presentation, we showcase our open source “GeoThermalCloud” tool for identifying hidden geothermal resources using a publicly available dataset for southwestern New Mexico. The presenters include Bulbul Ahmmed and Luke Frash. All of the visuals use source material from LA-UR approved publications and this work falls under the Earth Sciences DUSA. The code shown in this video is already released with LANL approval in open source format on GitHub and DockerHub. The audio in this video includes only material on the topics of geothermal energy and machine learning applied to geothermal energy. The primary machine learning method used is LANL’s Non-negative Matrix Factorization “NMFk” method. Modeling work also mentions LANL’s Geothermal Design Tool “GeoDT” which is another approved open source code that has been released by LANL. This work was performed for DOE Geothermal Technologies Office (DE-EE-3.1.8.1). The host for the released video is intended to be YouTube or a suitable perpetual data repository such as GDR.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Radiological Dispersal Device (RDD) Recovery Guidance: After Action Report from Pilots - Responding to Feedback from Pilots Reviewing RDD Recovery Guidance

The goal of this After Action report is to utilize feedback from the pilot participants to improve the guidance for responding to radiological dispersal device (RDD) events, which can include deliberate acts to release radioactive materials into the environment using explosives or other means or accidental releases (e.g., release from a medical isotope source). This longer-term recovery guidance is an extension of the initial response guidance that was released in a 2017 interagency report called RDD Response Guidance: Planning for the First 100 Minutes. Recovery teams reviewed the longer-term recovery guidance during pilot sessions that were held in Harris County, Texas (March 8-10, 2022) and Seattle, Washington (May 2-3, 2022). The pilot teams reviewed the RDD Recovery Guidance Presentation, which contains a summary of the more detailed RDD Recovery Guidance draft document. The feedback from both pilots was grouped and binned into unique themes (e.g., “checkpoint challenges”) that align with the recovery missions and tactics that they reviewed. PNNL authors of the recovery guidance then prepared responses that describe how they recommend addressing the feedback for each theme. The responses typically included recommendation plans for improving the guidance document, but also described when no changes are needed because the guidance already contains the suggested improvement. These pilot recommendations will be brought to the interagency team to finalize plans for updating and improving recovery guidance materials.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1995

The 1991 October 24 flare: A challenge for standard models

The M9.8 solar flare of 1991 October 24 22:30 UT presents several interesting characteristics: (1) energy release starts high in the corona; (2) the primary chromospheric ribbons are initially well separated and do not move apart at an observable rate; (3) no evidence is found for an erupting filament or other driver. To explain this flare, we consider several canonical flare models, including a filament eruption, a confined filament eruption, current interruption, and interacting loops. We conclude that none of these scenarios unequivocally explains this flare. Two possibilities which cannot be ruled out are (1) the eruption of a filament unobservable in H-alpha which starts high in the corona and produces no ribbon motions smaller than our detection threshold and no perceptible expansion of the coronal X-ray source, and (2) energy release due to spontaneous, propagating reconnection which allows the system to essentially brighten in place.

Beaujardiere, J.-F. De LA↗
DOE OSTI2026

rustpix

rustpix is a high-performance, open-source Rust library with first-class Python bindings (via PyO3) for processing pixel-detector data in neutron imaging. It targets time-stamping detectors such as Timepix3 (TPX3) at ORNL's Spallation Neutron Source (VENUS beamline), where each detected neutron deposits charge across a cluster of pixels within a very high-rate event stream (96M+ hits/sec). rustpix parses TPX3 event data in parallel using memory-mapped I/O, offers four interchangeable clustering algorithms (ABS adjacency-based search, DBSCAN, graph/union-find connected components, and a parallel grid method), and extracts weighted, super-resolved centroids to produce neutron-event lists. A streaming architecture lets it process files larger than available memory. rustpix is distributed as a pip-installable Python package (with NumPy integration), Rust crates, a command-line tool, and an interactive GUI; it writes HDF5, Apache Arrow, and CSV; and it is designed to extend to TPX4 and other detector types. Released as open-source under the MIT License.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2020

Survey and Assessment of Computational Capabilities for Advanced (Non-LWR) Reactor Mechanistic Source Term Analysis.

A vital part of the licensing process for advanced (non-LWR) nuclear reactor developers in the United States is the assessment of the reactor’s source term, i.e., the potential release of radionuclides from the reactor system to the environment during normal operations and accident sequences. In comparison to source term assessments which follow a bounding approach with conservative assumptions, a mechanistic approach to modeling radionuclide transport, which realistically accounts for transport and retention phenomena, is expected to be used for advanced reactor systems. As the designs of advanced reactors increase in maturity and progress towards licensing, there is a need to advance modeling and simulation capabilities in analyzing the mechanistic source term (MST) of a prospective reactor concept. In the present work, a survey is provided of existing computational capabilities for the modeling of advanced reactors MSTs. The following reactors are considered: high temperature gas reactors (HTGR); molten salt reactors (MSR) which include salt-fueled reactors and fluoride salt-cooled high temperature reactors (FHR); and sodium- and lead-cooled fast reactors (SFR, LFR). A review of relevant codes which may be useful in providing information to MST analyses is also completed, including codes that have been used for source term analyses of LWRs, as well as those being developed for other aspects of advanced reactor system modeling such as reactor physics, thermal hydraulics, and chemistry. A discussion of MST modeling capabilities for each reactor type is provided with additional focus on important phenomena and functional requirements. Additionally, a comprehensive survey is provided of tools for consequence modeling such as atmospheric transport and dispersion (ATD).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Legacy Survey of Space and Time Data Preview 2: ss_source dataset type

We present Rubin Data Preview 2 (DP2), the second data preview from the NDF-DOE Vera C. Rubin Observatory. Data Preview 2 (DP2) comprises coadds, detection catalogs, and ancillary data products; and when fully released will also include single-epoch images and difference images. DP2 is derived from observations acquired by the LSST Science Camera (LSSTCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile, primarily during the on-sky commissioning campaign between 2025-04-16 and 2025-09-21, supplemented by observations taken between 2025-10-25 and 2026-01-06 that overlap the commissioning footprint. The DP2 footprint comprises the Science Validation wide-area survey, five Deep Drilling Fields, and a number of targeted small-field regions, including Trifid and Lagoon, Prawn, M49, and New Horizons, all observed as part of the Rubin First Look campaign. Each field was imaged in up to six broad photometric bands, ugrizy, and coadded to produce deep imaging covering an estimated 3,000 deg2. The addition of single-visit-only areas expands the total DP2 footprint to an estimated 15,000 deg2, with coverage in at least one filter. The median per-visit PSF FWHM across the wide-area survey ranges from 1.17 arcsec in the z band to 1.26 arcsec in g and r bands. The deepest field, reaches estimated coadded 5σ depths of u=26 mag, g=26.8 mag, r=26.3 mag, i=26.1 mag, z=25.3 mag, y=23.9 mag. Based on a roughly five-month primary observing baseline and covering only part of the eventual LSST footprint, DP2's area, depth, and multiband coverage nonetheless support a broad range of early science investigations ahead of LSST Data Release This dataset is a subset of the full data release consisting of the ss_source dataset type. These are instantaneous physical parameters for moving objects at the time of every observation. This release contains 1 dataset of this type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sterile neutrinos and the global reactor antineutrino dataset

We present results from global fits to the available reactor antineutrino dataset, as of Fall 2019, to determine the global preference for a fourth, sterile neutrino. We have separately considered experiments that measure the integrated inverse-beta decay (IBD) rate from those that measure the energy spectrum of IBD events at one or more locations. The evidence that we infer from rate measurements varies between ≲ 3σ and negligible depending on the reactor antineutrino flux model employed. Moreover, we find that spectral ratios ostensibly imply ≳ 3σ evidence, consistent with previous work, though these measurements are known to be plagued by issues related to statistical interpretation; these results should therefore be viewed cautiously. The software used is the newly developed GLoBESfit tool set which is based on the publicly available GLoBES framework and will be released as open-source software.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Modelica-based modeling and simulation of district cooling systems: A case study

While equation-based object-oriented modeling language Modelica can evaluate practical energy improvements for district cooling systems, few have adopted Modelica for this type of large-scale thermo-fluid system. Further, to our best knowledge, district cooling modeling studies have yet to include hydraulics in piping networks alongside plant models featuring realistic mechanical systems and controls. These are critical details to include when looking to make energy and control improvements in many physical system installations. To fill these gaps, this study released new open-source district cooling models at the Modelica Buildings Library and leveraged these models for a real-world case study at the University of Colorado Boulder. Here, the site includes six buildings connected to a central chiller plant featuring a waterside economizer. Several energy saving strategies are pursued based on the validated model, including control setpoint optimization, equipment modification, and pump setpoint adjustments. Results indicate that a combination of the studied measures can save the campus annually 84.6 MWh of energy, 8.9% of electricity costs, 58.0 metric tons of carbon dioxide emissions, while the waterside economizer cuts down chillers’ run times by 201 days/year, reducing maintenance costs and extending chiller life.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Post-irradiation examination of AGR-3/4 TRISO fuel compacts using three-dimensional X-ray computed tomography

The AGR-3/4 irradiation tests combined the third and fourth planned irradiation experiments in the US Department of Energy’s Advanced Gas Reactor (AGR) testing campaign of tri-structural isotropic (TRISO) fuel compacts. In this article, we present post-irradiation examination (PIE) using X-ray computed tomography (XCT) of two unirradiated and two irradiated compacts from the AGR-3/4 irradiation tests. The irradiated compacts studied (compact 7–1 and compact 12–4) represent the upper and lower limit of burnup within the AGR-3/4 irradiation experiment. This article presents a detailed quantitative analysis on the post-irradiation structure of TRISO fuel compacts. Various quantitative parameters including shape, size, and packing of kernels, and their spatial distribution, were utilized to gain insights into the structural changes caused by irradiation. The equivalent diameter and sphericity were found to increase and decrease, respectively, in irradiated compact 7–1 due to its higher burnup. Nearest neighbor distance between fuel kernels decreased after irradiation, suggesting irradiation-induced shrinkage of graphitic matrix. Furthermore, each compact in AGR-3/4 irradiation tests contained 20 designed-to-fail (DTF) fuel particles that were meant to act as a source of fission product release to the experiment test train. Furthermore, in the present work, all DTF fuel particles in the four compacts studied were identified, and it was found that they exhibited larger kernel swelling in compact 12–4 and smaller kernel swelling in compact 7–1, compared to the driver particles.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Pseudomonas sp. Strain 273 Incorporates Organofluorine into the Lipid Bilayer during Growth with Fluorinated Alkanes

Anthropogenic organofluorine compounds are recalcitrant, globally distributed, and a human health concern. Although rare, natural processes synthesize fluorinated compounds, and some bacteria have evolved mechanisms to metabolize organofluorine compounds. Pseudomonas sp. strain 273 grows with 1-fluorodecane (FD) and 1,10-difluorodecane (DFD) as carbon sources, but inorganic fluoride release was not stoichiometric. Metabolome studies revealed that this bacterium produces fluorinated anabolites and phospholipids. Mass spectrometric fatty acid profiling detected fluorinated long-chain (i.e., C 12 –C 19 ) fatty acids in strain 273 cells grown with FD or DFD, and lipidomic profiling determined that 7.5 ± 0.2 and 82.0 ± 1.0% of the total phospholipids in strain 273 grown with FD or DFD, respectively, were fluorinated. The detection of the fluorinated metabolites and macromolecules represents a heretofore unrecognized sink for organofluorine, an observation with consequences for the environmental fate and transport of fluorinated aliphatic compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Potential Chemical Impacts of Subsurface CO 2 : An Integrated Experimental and Numerical Assessment for a Case Study of the Ogallala Aquifer

Leakage from geologic CO 2 sequestration (GCS) reservoirs to overlying underground sources of drinking water (USDW) is a tangible risk. This study is an integrated assessment that combines column experiments and reactive transport simulations of sediments sampled from the Ogallala aquifer above an active commercial-scale GCS site (the Farnsworth Unit in northern Texas). Experimental and simulation results suggest that carbonate mineral (calcite and dolomite) dissolution is the most significant reaction following CO 2 intrusion, and is also the dominant source of trace metal release. Cation exchange is another key mechanism controlling trace metal release by cation interference. Most of the trace metals, including Ba, Sr, As, Pb, and Zn, show a short-term release and quickly drop to the baseline values, suggesting low risk to the overlying USDW quality. Other trace metals, such as Mn and U, exhibit a tangible increase of their concentrations in the beginning, and drop to a higher level compared to the baseline, which may become a potential concern of long-term USDW quality change with CO2introduction. This study provides a comprehensive example of combining laboratory experiments and simulations for assessment of CO 2 -sediment interactions with combined release mechanisms in shallow groundwater aquifers. Data presented here provides useful insights for quantitative risk assessment and effective public education regarding CO 2 geological sequestration, and trace metal reactive transport studies in shallow groundwater aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Towards automating structural discovery in scanning transmission electron microscopy *

Abstract Scanning transmission electron microscopy is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric domain walls, extended defects, or second phase inclusions. Selecting regions to image for structural and chemical discovery via atomically resolved imaging has traditionally proceeded via human operators making semi-informed judgements on sampling locations and parameters. Recent efforts at automation for structural and physical discovery have pointed towards the use of ‘active learning’ methods that utilize Bayesian optimization with surrogate models to quickly find relevant regions of interest. Yet despite the potential importance of this direction, there is a general lack of certainty in selecting relevant control algorithms and how to balance a priori knowledge of the material system with knowledge derived during experimentation. Here we address this gap by developing the automated experiment workflows with several combinations to both illustrate the effects of these choices and demonstrate the tradeoffs associated with each in terms of accuracy, robustness, and susceptibility to hyperparameters for structural discovery. We discuss possible methods to build descriptors using the raw image data and deep learning based semantic segmentation, as well as the implementation of variational autoencoder based representation. Furthermore, each workflow is applied to a range of feature sizes including NiO pillars within a La:SrMnO 3 matrix, ferroelectric domains in BiFeO 3 , and topological defects in graphene. The code developed in this manuscript is open sourced and will be released at github.com/nccreang/AE_Workflows .

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

components for the MuMMI software release

The Department of Energy and the National Cancer Institute have developed new software for conducting multi-scale simulations of complex systems. This software, called the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), couples simulations on three spatial scales to study slow, large-scale reorganizations of biomolecular systems with the speed of continuum and coarse-grained models while revealing selected interactions at full atomic precision. In these simulations, coarse-to-fine model conversions are used to spawn relevant fine-scale simulations along chosen order parameters, and fine-to-coarse feedback is used to iteratively improve the accuracy and multi-scale consistency of coarse-scale and continuum simulations. The complete MuMMI framework will be reviewed and released as open-source software by Lawrence Livermore National Laboratory. This review covers a subset of the MuMMI components that were developed exclusively at the Los Alamos National Laboratory.

Neale, Christopher↗
DOE OSTI2023

STPPHAWKES

SAND2024-08541O STTPHAWKES software solution is a Bayesian estimation approach to a Hawkes process model that treats missing data as a latent variable in the estimation. The open-source software will be released to the R CRAN repository and Sandia National Labs’ Github. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rowe, Stephen↗
DOE OSTI2025

Simulated Microstructures for Laser Powder Bed Fusion Additive Manufacturing Using Myna, AdditiveFOAM, and ExaCA

This dataset provides sample datasets containing voxelized, three-dimensional representations of simulated grain structures and crystallographic orientations that can result from laser powder bed fusion additive manufacturing. The six microstructure files each contain approximately 1 cubic millimeter of material (1 mm x 1 mm cross-section over 26 simulated layers of deposition). Some of the microstructures have columnar grains that extend across nearly the entire simulation domain, while others have more equiaxed or truncated columnar grains. The process conditions to generate these microstructures were from the Peregrine v2023-10 dataset (10.13139/ORNLNCCS/2008021). The codes used are publicly available and released under open-source licenses. Myna (https://github.com/ORNL-MDF/Myna) was used for configuration of the cases from the Peregrine v2023-10 HDF5 dataset and to run the simulation workflow. AdditiveFOAM (https://github.com/ORNL/AdditiveFOAM) was used to simulate the melt pool and generate solidification conditions. And ExaCA (https://github.com/LLNL/ExaCA ) was used to simulate the three-dimensional microstructures.

36 MATERIALS SCIENCE↗