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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Development of a Platform at the Matter in Extreme Conditions End Station for Characterization of Matter Heated by Intense Laser-Accelerated Protons

High intensity short-pulse lasers have made possible the generation of energetic proton beams, unlocking numerous applications in high energy density science. One such application is uniform and isochoric heating of materials to the warm dense matter (WDM) state. We have developed a new experimental platform to simultaneously create and probe warm dense matter at the Matter in Extreme Conditions (MEC) end station at the Linac Coherent Light Source (LCLS). The short pulse optical laser (delivering up to 1 J in 45 fs) and the ultra-bright LCLS x-ray laser with tunable frequency respectively deliver high power required to heat materials to WDM and precision-timed high-resolution x-rays to probe them. The laser-accelerated proton beam driven from a flat 1.5 μm Cu foil was first measured then directed to a secondary sample of Al or polypropylene, typically 300-400 μm away. The time evolution of the sample electron temperature was measured using streaked optical pyrometry, where we observed a peak temperature of 0.9 0.15 eV on the rear surface of an Al sample heated by the proton beam. Here, the simulations using the hybrid-PIC code LSP and the rad-hydro code HELIOS show that a measured proton beam can heat Al to approximately 4 eV and polypropylene to 1 eV if instead focused by a hemispherical Cu target. Through additional LSP simulations, we anticipate creating hotter warm dense matter states (20 eV) by increasing the laser energy to 10 J and keeping the other laser parameters fixed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machinable, high‐conductivity NaSICON through mitigation of humidity effects during solid‐state synthesis

The Na + super ion conductor (NaSICON, Na 1+x Zr 2 Si x P 3-x O 12 ) is a solid electrolyte well-known for fast, selective Na + transport at low temperatures, uniquely enabling sodium-based batteries. Producing high-quality NaSICON from solid-state methods, especially when cost-effective, potentially hygroscopic precursors are used, is not trivial. To understand and eliminate the influence of humidity during processing, a scheme was developed to reproducibly yield a high Na + conductivity (3.75 mS/cm at 25°C, 81.7 mS/cm at 150°C), high density (97%), and machinable NaSICON without the use of binders, sintering aids, or dopants. Controlled humidity studies over 20%–50% RH coupled with thermal, structural, and electrical analysis reveal that calcination temperatures < 1000°C leave NaSICON processing susceptible to water absorption at > 20% RH due to the presence of hygroscopic Na 3 PO 4 and Na 2 CO 3 during shaping, pressing, and sintering. Water absorption results in NaSICON with lower densities, machinability, and Na+ conductivity, due to impaired intergranular Na+ transport. At the other extreme, fully converting precursor to the NaSICON phase at 1230°C before pressing and sintering leads to poor conductivity and density. By calcining at 1000°C, excellent quality NaSICON may be produced under a range of laboratory environments, enabling low-cost production of high-conductivity, machinable NaSICON necessary the ever-growing energy storage market.

NaSICON↗
DOE OSTI2023

Geodynamically corrected Pliocene shoreline elevations in Australia consistent with midrange projections of Antarctic ice loss

The Mid-Pliocene represents the most recent interval in Earth history with climatic conditions similar to those expected in the coming decades. Mid-Pliocene sea level estimates therefore provide important constraints on projections of future ice sheet behavior and sea level change but differ by tens of meters due to local distortion of paleoshorelines caused by mantle dynamics. We combine an Australian sea level marker compilation with geodynamic simulations and probabilistic inversions to quantify and remove these post-Pliocene vertical motions at continental scale. Dynamic topography accounts for most of the observed sea level marker deflection, and correcting for this effect and glacial isostatic adjustment yields a Mid-Pliocene global mean sea level of +16.0 (+10.4 to +21.5) m (50th/16th to 84th percentiles). Recalibration of recent high-end sea level projections using this revised estimate implies a more stable Antarctic Ice Sheet under future warming scenarios, consistent with midrange forecasts of sea level rise that do not incorporate a marine ice cliff instability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ICARUS at the Fermilab Short-Baseline Neutrino program: initial operation

The ICARUS collaboration employed the 760-ton T600 detector in a successful 3-year physics run at the underground LNGS laboratory, performing a sensitive search for LSND-like anomalous $\nu _e$ appearance in the CERN Neutrino to Gran Sasso beam, which contributed to the constraints on the allowed neutrino oscillation parameters to a narrow region around 1 eV$^2$. After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. In 2020 the cryogenic commissioning began with detector cool down, liquid argon filling and recirculation. ICARUS then started its operations collecting the first neutrino events from the booster neutrino beam (BNB) and the Neutrinos at the Main Injector (NuMI) beam off-axis, which were used to test the ICARUS event selection, reconstruction and analysis algorithms. ICARUS successfully completed its commissioning phase in June 2022. The first goal of the ICARUS data taking will be a study to either confirm or refute the claim by Neutrino-4 short-baseline reactor experiment. ICARUS will also perform measurement of neutrino cross sections with the NuMI beam and several Beyond Standard Model searches. After the first year of operations, ICARUS will search for evidence of sterile neutrinos jointly with the Short-Baseline Near Detector, within the Short-Baseline Neutrino program. In this paper, the main activities carried out during the overhauling and installation phases are highlighted. Preliminary technical results from the ICARUS commissioning data with the BNB and NuMI beams are presented both in terms of performance of all ICARUS subsystems and of capability to select and reconstruct neutrino events.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The MEC-U Project at LCLS

Here, we describe the Matter in Extreme Conditions Upgrade (MEC-U) project, co-locating kilojoule long pulse and high repetition rate petawatt lasers with LCLS in a new experimental hall at SLAC National Accelerator Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Utah FORGE: Seismic Event Catalogue from the April, 2022 Stimulation of Well 16A(78)-32

This dataset includes earthquake catalogues for the three stages of the 2022 well 16A(78)-32 stimulation provided by Geo Energie Suisse. Events in these catalogues have been visually inspected. There are additional events of lower signal to noise that were automatically detected. Those events will require additional analysis and processing. Times are recorded in UTC (Coordinate Universal Time), and the coordinate reference system is UTM Zone 12N, NAD83.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Utah FORGE: Updated Seismic Event Catalogue from the April, 2022 Stimulation of Well 16A(78)-32

These are revised catalogs, related to the April, 2022 well 16A(78)-32 stimulation (phases 1,2, & 3), provided by Geo Energie Suisse (GES) that include additional events at the start of Stage 1 and some tidying up of some locations. These catalogs also include events for additional events that were auto-located to provide a larger dataset for statistical analyses, like b-value calculations. The actual auto-locations have been removed to prevent spurious location plots being created. Times are recorded in UTC (Coordinate Universal Time), and the coordinate reference system is UTM Zone 12N, NAD83.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: GES Well 16A(78)-32 and Well 16B(78)-32 Stimulation Seismic Event Catalogs

This dataset contains seismic event catalogs from the hydraulic stimulation of wells 16A(78)-32 and 16B(78)-32 at the Utah FORGE site in April 2024. The data was collected by Geo Energy Suisse (GES) using a variety of seismic monitoring technologies, including 3-component (3C) geophones and distributed acoustic sensing (DAS) systems. These technologies were deployed across several locations, including wells 16A, 16B, and Delano-1, with sensor arrays at multiple depths to capture microseismic activity during the stimulations. The catalogs provide both real-time and manually checked seismic event locations, with detailed parameters such as trigger conditions, velocity models, and data acquisition settings. The dataset includes information on the stimulation stages, event rates, and hydraulic injection conditions for each well, with a report detailing the data acquisition configuration and seismic event location methodologies. Users will need to reference the included report for a complete understanding of the sensor network, data processing techniques, and accuracy considerations.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Hot Droughts and Forest Tree Dynamics in the Amazon - Statistical Models, Scripts, Data, and Outputs

This package contains data, outputs, equations, and R scripts for analyses for manuscript entitled "Hot droughts in the Amazon: A window to a future hypertropical climate" by J. Chambers et al., in particular it contains statistical models and analyses for the INPA BIONTE tree mortality study. The Models folder contains details for all statistical models in PDF files. The Scripts folder contains the R scripts for Bayesian Hierarchical Models (two text files) and SEMs (one text file) are separate and reasonably annotated. All data associated with these scripts are in the data folder. The Data folder contains two of the three CSV files used for the analyses and are called by the R scripts. Two of them are part of published datasets (`BIONTE_mortality-rates.csv` from Lima et al. 2024, DOI:10.15486/ngt/1898910 and `SPEI.csv` from Pastorello et al. 2023 DOI:10.15486/ngt/1958257) and also provided in this package for convenience (please see the corresponding datasets for usage and citation terms). The third dataset (`BIONTE_gapfilled_wd.csv`) contains sensitive information and can be obtained by contacting the manuscript lead author. The Outputs folder contains the two output files that provide extra information about the analyses. The file `figuresFeb2025d.pdf` contains all the figures from the manuscript - captions are in the manuscript. The file `ChambersMS.pdf` contains primary results from Bayesian statistical models, regression analyses, and validation steps applied to the tree mortality data from the INPA experiments. The document includes visual summaries, model diagnostics, and leave-one-out (LOO) validation results. A breakdown of file contents can be found in the README file that is part of this package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Comprehensive GOM Federal Waters Platform, Incident, Metocean, and Geohazard Dataset

The dataset contains integrated data from an array of disparate data sources, all spatially and temporally linked to platforms in the federal waters of the Gulf of Mexico (platform data from BSEE, 2020). Integrated data includes past reported incidents dating back to 1956 (BSEE, BOEM, MMS), metocean data (see Nelson et al. in review for source information), and geohazard data (see Nelson et al. in review for source information). Proprietary well production information was redacted from this dataset, but was used in resulting analytics.

Full System↗
DOE OSTI2022

Historic Submarine Landslides in the Northern Gulf of Mexico

This dataset provides a set of polygons representing the zone of depletion for historic submarine landslides (also referred to as mass transport deposits) within four regions of the US Exclusive Economic Zone in the northern Gulf of Mexico. Landslides were digitized by geologists and spatial scientists at the National Energy Technology Laboratory by visually interpreting landslide boundaries from a seismic-derived, high resolution bathymetric hillshade provided by the Bureau of Ocean and Energy Management (BOEM, 2017). A portion of the landslide features are derived from other spatial sources including the Seismic Water Anomalies dataset by BOEM (2016) as well as from McAdoo et al., 2000 and Twichell et al, 2005. The scale that landslides depletion areas can be interpreted at is limited by the spatial resolution of the gridded bathymetry, which is 12.192 meters (BOEM, 2017). For each landslide feature in the dataset, geometry metrics were calculated including geodesic area (km2) and geodesic perimeter (km) using the North America Albers Equal Area Conic projected coordinate system. The same geometry metrics were calculated for the four inventory regions.

DOE↗
DOE OSTI2023

Gulf of Mexico Risk Analysis Database (GoMRAD)

The Gulf of Mexico Risk Analysis Database is comprehensive Esri geodatabase of vector layers, raster layers, and tables curated for risk analysis within the offshore Gulf of Mexico. Datasets include bathymetry, seafloor characteristics (channels, anomalies, faults, etc.), MetOcean data (wind speed, wave height, etc.), ocean current data, sediment data, and machine learning training regions used in NETL's Ocean & Geohazard Analysis (OGA) tool. This database serves as a compliment to the OGA tool by providing many of the datasets used in the design of the OGA tool, including regions used for machine learning. This database also serves as a valuable resource for risk analysis studies within the offshore Gulf of Mexico. This work was completed under the Advanced Offshore Research Portfolio, FWP Number: 1022476.

BOEM,Bathymetry,Gulf Of Mexico,Machine Learning,Me↗
DOE OSTI2023

Ocean & Geohazard Analysis Tool

The Ocean & Geohazard Analysis (OGA) software tool is designed to summarize insights into key offshore hazards drawing from a diverse set of approaches, including artificial intelligence, machine learning, probabilistic and statistical, and offshore data sources. The offshore hazards that can be analyzed include submarine landslides, extreme wind/wave/current event probabilities, earthquakes, and metocean pathways (CIAM Climatological Isolation and Attraction Model–Climatological Lagrangian Coherent Structures - Submissions - EDX (doe.gov)). Currently, the tool is developed for use in the Gulf of Mexico. The data underlying the offshore hazard analyses can be found here: https://edx.netl.doe.gov/dataset/gulf-of-mexico-risk-analysis-database-gomrad This work was conducted under the Advanced Offshore Research Portfolio, FWP Number 1022409 at National Energy Technology Laboratory, U.S. Dept. of Energy. Disclaimer This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

AIML↗
DOE OSTI2024

Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database

The Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database is an interoperable spatial resource containing critical environmental, operational, and reported stressors tied to publicly available oil and gas pipeline locations across the contiguous U.S. and Alaska. This database contains two layers: 1. Pipeline point locations (‘pipeline_points’) – More than 500,000 points (at every kilometer along pipelines, and end points) to which more than 350 stress-related variables have been appended. 2. Merged pipelines (‘merged_pipelines’) – The original, publicly available pipeline data (see table below) merged together into one feature class.

Carbon Transport↗
DOE OSTI2025

WELLS Interactive Application

The Wellbore Exploration and Location Logistic System (WELLS) Interactive Application is an interactive tool to enable easy exploration and visualization of the living national wellbore database (WELLS Database (https://edx.netl.doe.gov/dataset/wells_database)). The tool and underlying database were created and are maintained by the National Energy Technology Laboratory (NETL), providing visualization of the more than six million public wellbore records from more than 65 authoritative state, federal, and tribal resources. The WELLS Interactive Application serves up wellbore data from oil, gas, underground injection, research, geothermal, geotechnical, groundwater, and other types of wells in a single, standardized, unified system. In addition to the surface location of these wells, the underlying database combines select key attributes for features such as well age, depth, and operating status. The system also provides users with references back to the original sources used in this unified platform. The underlying data can be accessed through the WELLS Database: https://edx.netl.doe.gov/dataset/wells_database Additional Information: The WELLS Interactive Application (formerly titled CO2-Locate) enables visualization and access to the public wellbore records through an intuitive web-based mapping tool. The WELLS Interactive Application was designed to help users visualize, query, analyze, and download wellbore records. Public wellbore points are included as a layer in the Map page, called Public Wells. Additionally, a multivariate hexagon grid summarizing well density from proprietary well data, called Well Density, is included to identify data gaps between the public and proprietary well data. Filtering functionalities in the tool allow these two layers to be spatially filtered by state, county, or basin as well as by status, type, true vertical depth, and spud year. The WELLS Interactive Application also contains a Near Me tool can be used to search and explore wellbore data within a user-defined distance of a specified location on the map, which can also be downloaded. The Query tool allows users to query the selected or filtered wells in the Public Wells layer and export the data. For additional information on these tool functionalities, see the help documentation on the About page of the tool. Notes for Consideration: The Well Density layer provided in this application is derived from proprietary wellbore data, the records of which do not always contain values for key features (status, type, true vertical depth, or spud year). Therefore, data might not be available when layers are queried for all filter combinations. Additionally, visualizing layers and applying filters may take additional time to load (i.e., draw on the map) due to the large size of the data.

ccs↗
DOE OSTI2024

Offshore Advanced Infrastructure Integrity Model (AIIM) Dashboard

The Advanced Infrastructure Integrity Model (AIIM) is a multivariate, multi-machine learning modeling technology applied to evaluate the integrity of offshore energy infrastructure (e.g., pipelines, platforms) in the U.S Gulf Region. Offshore energy infrastructure plays an essential role in ensuring access to safe and secure energy for the United States. According to the U.S. Energy Information Administration (EIA), production in the U.S. Gulf Region accounts for 15% of total crude and 5% of total natural gas from the United States. Many of these structures have been operating for close to or past their design life, while others have the chance of attrition before return on investment. To better understand the potential for reuse or life extension opportunities, an assessment of the infrastructure integrity is critical to inform safe decision making. Assessing structural integrity, AIIM provides key insights that inform infrastructure use and reuse, as well as hazard prevention planning, in support of stakeholders including researchers and industry.

Advanced Infrastructure Integrity Model↗