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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Estimated impacts of forest restoration scenarios on smoke exposures among outdoor agricultural workers in California

Abstract As wildfires continue to worsen across western United States, forest managers are increasingly employing prescribed burns as a way to reduce excess fuels and future wildfire risk. While the ecological benefits of these fuel treatments are clear, little is known about the smoke exposure tradeoffs of using prescribed burns to mitigate wildfires, particularly among at-risk populations. Outdoor agricultural workers are a population at increased risk of smoke exposure because of their time spent outside and the physical demands of their work. Here, we assess the smoke exposure impacts among outdoor agricultural workers resulting from the implementation of six forest management scenarios proposed for a landscape in the Central Sierra, California. We leverage emissions estimates from LANDIS-II to model daily PM 2.5 concentrations with the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and link those to agricultural employment data from the Bureau of Labor Statistics. We find a u-shaped result, in that moderate amounts of prescribed burning result in the greatest reduction in total smoke exposure among outdoor agricultural workers, particularly during months of peak agricultural activity due to wildfire-specific smoke reductions. The reduction in total smoke exposure, relative to scenarios with the least amount of management, decreases as more prescribed burning is applied to the landscape due to the contributions of the fuel treatments themselves to overall smoke burden. The results of this analysis may contribute to preparedness efforts aimed at reducing smoke exposures among outdoor agricultural workers, while also informing forest management planning for this specific landscape.

Environmental Sciences & Ecology↗
DOE OSTI2020

New precise half-life measurement for the superallowed β+ emitter Ar34

We have measured the half-life of 34 Ar, the parent of a superallowed 0 + → 0 + β transition, to be 0.84646(35) s. With a precision of 0.04%, this result is an essential ingredient needed to complete a third pair of mirror superallowed transitions, 34 Ar → 34 Cl and 34 Cl → 34 S, the ratio of whose ft values would provide the most sensitive test yet of the isospin-symmetry-breaking corrections used to obtain V ud . In a sequence repeated thousands of times, we implanted a very pure 34 Ar beam into tape for 0.7 s, and then rapidly transported the collected source to a shielded 4π proportional gas counter, which detected the decay positrons from the combined decays of 34 Ar and its daughter 34 Cl. The data were analyzed as a linked parent-daughter pair. Our new result replaces one we published 13 years ago.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Cryo-EM analysis of S. aureus TarL, a polymerase in wall teichoic acid biogenesis central to virulence and antibiotic resistance

Wall teichoic acid (WTA), a covalent adduct of Gram-positive bacterial cell wall peptidoglycan, contributes directly to virulence and antibiotic resistance in pathogenic species. Polymerization of the Staphylococcus aureus WTA ribitol-phosphate chain is catalyzed by TarL, a member of the largely uncharacterized TagF-like family of membrane-associated enzymes. We report the cryo–electron microscopy structure of TarL, showing a tetramer that forms an extensive membrane-binding platform of monotopic helices. TarL is composed of an amino-terminal immunoglobulin-like domain and a carboxyl-terminal glycosyltransferase-B domain for ribitol-phosphate polymerization. The active site of the latter is complexed to donor substrate cytidine diphosphate–ribitol, providing mechanistic insights into the catalyzed phosphotransfer reaction. Furthermore, the active site is surrounded by electropositive residues that serve to retain the lipid-linked acceptor for polymerization. Our data advance general insight into the architecture and membrane association of the still poorly characterized monotopic membrane protein class and present molecular details of ribitol-phosphate polymerization that may aid in the design of new antimicrobials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

pnnl/Rooftop-Unit-LCI-Template

A content repository for the life cycle inventory (LCI) rooftop unit (RTU) data collection template, a data collection template for the linked openLCA model Life Cycle Assessment (LCA) for automated Environmental Product Declaration (EPD) results generation.

Unger, Scott [Pacific Northwest National Laborator↗
DOE OSTI2022

FTICR-MS Data from Multi-continent River Water and Sediment and from Coastal River Fresh and Saline Sediment Associated with: “Dissolved Organic Matter Functional Trait Relationships are Conserved Across Rivers”

This data package is associated with the publication “Dissolved Organic Matter Functional Trait Relationships are Conserved Across Rivers” submitted to PNAS (Stegen et al., 2023). The study aims to understand large-scale spatial structure of the dissolved organic matter (DOM) thermodynamic traits and inter-trait relationships by investigating (1) river water and sediments collected along 97 rivers spanning 3 continents and (2) coastal sediment collected from fresh and saline locations in Pacific and Gulf/Atlantic rivers. Sediment extracts and water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This dataset is comprised of three folders (1) Coastal, (2) WHONDR_S19S, and (3) Data_Dictionaries. Coastal contains (1) a subfolder with processed FTICR-MS data as csv files and sample collection metadata, (2) a subfolder with R scripts used to process the data and create associated figures, (3) a subfolder with the raw, unprocessed FTICR-MS data as .xml files, and (4) a readme file with more information about the dataset and instructions for using Formularity (https://omics.pnl.gov/software/formularity). WHONDRS_S19S contains (1) a csv file with processed FTICR data, (2) a csv with sample collection metadata, (3) a csv with sample geospatial data, (4) a csv with simulated lambda model outputs, (5) a subfolder with R scripts used to process the data and create associated figures, and (6) a readme file with more information regarding WHONDRS raw FTICR data and processing scripts. Data_Dictionaries contains data dictionaries for each csv file in the data package. The 97 global river corridors were part of a WHONDRS (https://whondrs.pnnl.gov) study. The raw, unprocessed FTICR-MS data with additional data can be found at doi:10.15485/1729719 for sediments and doi:10.15485/1603775 for water. This data package contains the processed data used in the associated manuscript. The coastal data has not been previously published, and this data package contains both the raw and processed data. Version 3 of this data package published February 2023 includes updates to the title of the manuscript, additional data and data dictionary and updated scripts linked to new analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Storage Futures Study: Distributed Solar and Storage Outlook: Methodology and Scenarios

This report is one in a series of NREL’s Storage Futures Study (SFS) publications. The SFS is a multiyear research project that explores the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. The research findings and supporting data will be published as a series of reports, with each report being released on its completion. The table below lists the specific research topics planned for examination under the SFS and the associated publication formats. This report, the fourth in the SFS series, provides a set of scenarios for cost-effectiveness and customer adoption for a range of scenarios that include future technology costs and valuation of backup power. The SFS series provides data and analysis in support of the U.S. Department of Energy’s Energy Storage Grand Challenge, a comprehensive program to accelerate the development, commercialization, and utilization of next-generation energy storage technologies and sustain American global leadership in energy storage. The Energy Storage Grand Challenge employs a use case framework to ensure storage technologies can cost-effectively meet specific needs, and it incorporates a broad range of technologies in several categories: electrochemical, electromechanical, thermal, flexible generation, flexible buildings, and power electronics. More information, any supporting data associated with this report, links to other reports in the series, and other information about the broader study are available at https://www.nrel.gov/analysis/storage-futures.html.

25 ENERGY STORAGE↗
DOE OSTI2022

Distributed Grid Control of Flexible Loads and DERs for Optimized Provision of Synthetic Regulating Reserves

Over the course of this project, we have successfully de-risked our distributed microgrid control architecture by tightly integrating its associated control algorithms into a unified software library, installing the software library on several industrial-grade target hardware platforms, and validating the performance of the resulting microgrid controller in a real-life microgrid. Upon completion of the project, we demonstrated that our distributed control architecture is resilient against (i) failures in control devices, (ii) unreliable communication links, (iii) delays in transmitted data, and (iv) imperfect knowledge of the number of (and state of) generation and load assets in the microgrid. In this final report, we present results from all the milestones that were accomplished over the course of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

IMPACT: Design of Integrated Multiphysics Producible Additive Components for Turbomachinery

The overall objective of the IMPACT program was to enable a dramatic reduction in design maturation time for an additive hot-section turbomachinery component through the following: • A fast crack-risk producibility surrogate model generated from machine learning applied to additive process simulation data generated via exascale computing, • Linking this surrogate model to multi-physics topology optimization (TO) to enable the creation of producible, near-optimal structural/thermal designs for additive hot-section components, • Maturing this toolset to reduce hot-section component design-for-manufacturing iterations by a large fraction, and eventually, • Using these tools to develop more efficient gas turbines in much shorter design cycle times.

42 ENGINEERING↗
DOE OSTI2025

GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics

Data package for Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon This data is published under a CC0 license. The authors encourage data reuse and request attribution by referencing the below citations for the data packages and associated manuscript. Please cite as: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. GLBRC Soil Yearlong Incubation 13C-SIP-Lipidomics. [Data Set] PNNL DataHub. doi: Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. MSV000097435: GLBRC soil yearlong incubation 13C-SIP-Lipidomics [Data Set] MassIVE. doi:10.25345/C57659T3K Rempfert KR, Bell SL, Kasanke CP, Kyle JE, Hofmockel KS. 2025. Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon. In Prep This data package consists of compound-specific 13C SIP-lipidomics data from a yearlong tracer incubation experiment designed to investigate microbial lipid persistence in switchgrass bioenergy crop soils. In order to explore how lipid structure may modulate the persistence of C in soil lipids, we leveraged soils from two sites (Michigan - sandy texture, Wisconsin - silty texture) operated by the U.S. Department of Energy-funded Great Lakes Bioenergy Research Center (GLBRC). These sites had comparable climates, identical management practices, but contrasting soil textures, allowing us to assess the variability of lipid accrual or degradation in soils as well as provide insight regarding the degree to which edaphic properties may regulate the retention of soil lipids. Untargeted lipidomics analyses were performed to identify 13C-labeled lipids in the soil microbiome after long-term incubation. Soils were supplemented with 100 micrograms glucose per gram dry soil (99 atom % 13C or natural abundance for paired control) and incubated; samples were collected two months and one year after glucose addition. Lipid extracts (MPLEx) were analyzed by LC-MS/MS and identified using LIQUID. Calculation of isotopic enrichment of lipids was performed by targeted approach using TarMet to quantify lipid isotopologues and IsoCorrectoR to correct for natural abundance isotopes. Contents: Data package contents reported here are the first version and contain downstream analysis files for the raw LC-MS mass spectrometry files (.mzXML) deposited at the MassIVE database repository under accession MSV000097435 (80 experimental runs; 5.85 GB) | MassIVE DOI: 10.25345/C57659T3K. Support files include the additional data download 'Read Me' file containing data descriptor information. Reported data download contents are structured for compliance with project data sharing guidelines, community standards initiatives, and sponsor stakeholder policies supporting FAIR data principles. Data processing software, analysis tools, and data workflows are listed below corresponding to the host repository long-term location. Available Data Downloads (0.3 GB): "GLBRC soil yearlong incubation 13C-SIP-Lipidomics_readme.txt" - 'Read Me' data package content file (txt) "GLBRC_DataPackage_analysis files" - Data processing files (Rmd) and saved intermediate data processing outputs (rds, csv, xlsx) "GLBRC_13C_lipidomics_dataset.xlsx" - processed data in tabular format (xlsx) Linked Software: LIQUID LC-MS Analysis Software | 10.5281/zenodo.6459462 Lipid Mini-On Software Tools | 10.5281/zenodo.1492803 pmartR Omics Statistical Software | 10.5281/zenodo.6108667 xcms (v4.3.3) TarMet (v1.1.1) IsoCorrectoR (1.24.0) Funding Acknowledgments: This research was supported by an Early Career Research Program award funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (OBER) Genomic Science program under FWP 68292, FWP 07880 and EMSL Exploratory Research Project 51095. A portion of this work was performed in the William R. Wiley Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by OBER and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated by Battelle for the DOE under Contract DE-AC05-76RLO1830.

Rempfert, Kaitlin R [Pacific Northwest National La↗
DOE OSTI2022

Temporal link encoding

Temporal link encoding, including: identifying a data type of a data value to be transmitted; determining that the data type is included in one or more data types for temporal encoding; and transmitting the data value using temporal encoding.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Nanoscale morphology of functional materials determines their chemical and physical properties. However, despite increasing use of transmission electron microscopy (TEM) to directly image nanomorphology, it remains challenging to quantify the information embedded in TEM data sets, and to use nanomorphology to link synthesis and processing conditions to properties. We develop an automated, descriptor-free analysis workflow for TEM data that utilizes convolutional neural networks and unsupervised learning to quantify and classify nanomorphology, and thereby reveal synthesis–nanomorphology relationships in three different systems. While TEM records nanomorphology readily in two-dimensional (2D) images or three-dimensional (3D) tomograms, we advance the analysis of these images by identifying and applying a universal shape fingerprint function to characterize nanomorphology. After dimensionality reduction through principal component analysis, this function then serves as the input for morphology grouping through unsupervised learning. We demonstrate the wide applicability of our workflow to both 2D and 3D TEM data sets, and to both inorganic and organic nanomaterials, including tetrahedral gold nanoparticles mixed with irregularly shaped impurities, hybrid polymer-patched gold nanoprisms, and polyamide membranes with irregular and heterogeneous 3D crumple structures. In each of these systems, unsupervised nanomorphology grouping identifies both the diversity and the similarity of the nanomaterial across different synthesis conditions, revealing how synthetic parameters guide nanomorphology development. Our work opens possibilities for enhancing synthesis of nanomaterials through artificial intelligence and for understanding and controlling complex nanomorphology, both for 2D systems and in the far less explored case of 3D structures, such as those with embedded voids or hidden interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Data driven discovery and quantification of hyperspectral leaf reflectance phenotypes across a maize diversity panel

Abstract Estimates of plant traits derived from hyperspectral reflectance data have the potential to efficiently substitute for traits, which are time or labor intensive to manually score. Typical workflows for estimating plant traits from hyperspectral reflectance data employ supervised classification models that can require substantial ground truth datasets for training. We explore the potential of an unsupervised approach, autoencoders, to extract meaningful traits from plant hyperspectral reflectance data using measurements of the reflectance of 2151 individual wavelengths of light from the leaves of maize ( Zea mays ) plants harvested from 1658 field plots in a replicated field trial. A subset of autoencoder‐derived variables exhibited significant repeatability, indicating that a substantial proportion of the total variance in these variables was explained by difference between maize genotypes, while other autoencoder variables appear to capture variation resulting from changes in leaf reflectance between different batches of data collection. Several of the repeatable latent variables were significantly correlated with other traits scored from the same maize field experiment, including one autoencoder‐derived latent variable (LV8) that predicted plant chlorophyll content modestly better than a supervised model trained on the same data. In at least one case, genome‐wide association study hits for variation in autoencoder‐derived variables were proximal to genes with known or plausible links to leaf phenotypes expected to alter hyperspectral reflectance. In aggregate, these results suggest that an unsupervised, autoencoder‐based approach can identify meaningful and genetically controlled variation in high‐dimensional, high‐throughput phenotyping data and link identified variables back to known plant traits of interest.

Tross, Michael C.↗
DOE OSTI2023

Stem psychrometer and flux data from US-CdM

Cleaned midday and predawn water potential data from 14 stem psychrometers installed within the footprint of the US-CdM flux tower, from May-October 2021. These data were collected in order to link environmental drivers, vegetation responses to seasonal water stress, and ecosystem fluxes of carbon and water at a pinyon-juniper woodland in southeastern Utah.Data include a comma separated values file containing all water potential data used in the published paper. Data were first published in Kannenberg et al. 2023 Agricultural and Forest Meteorology (doi: 10.1016/j.agrformet.2022.109269). Flux data are publicly available from the AmeriFlux portal (doi: 10.17190/AMF/1865477). This data file and the AmeriFlux data are all that is necessary to replicate the analyses in Kannenberg et al. 2023 Agricultural and Forest Meteorology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data

Building energy code compliance is the crucial link between the actual energy savings and the efficiency prescribed in energy codes. A research project aiming to identify opportunities to reduce energy consumption in new single-family residential construction by increasing compliance with the building energy code was conducted in several states of the United States. The study was comprised of three phases: (1) a baseline study to document typical practice and identify opportunities for improvement based on empirical data gathered from the field; (2) an education and training phase targeting the opportunities identified; and (3) a post-study to assess whether a reduction in average state-wide energy use could be achieved following the education and training phase. We proposed a novel methodology based on large-scale building energy simulation inferred by limited field data to assess the performance of a large population of homes. This paper presents the methodology, findings, and results of this study. The state-wide average energy consumption decreased at Phase III from Phase I for five of the seven states involved in the analysis. The measure-level savings potential analysis shows an overall reduction. Overall, the training and education phase plays a recognizable role in improving compliance with building energy codes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

WholeTraveler Anonymized Data Phase 2

Phase 2 of the WholeTraveler study consisted of a global positioning system (GPS) data collection. Phase 2 started immediately after the completion of the Phase 1 survey for any respondent who opted into Phase 2. The raw locational data collected have been processed into identified "trips" and some of those trips into identified "trip chains." Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗