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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Upper-air soundings collected during the CROCUS Urban Canyons 2024 campaign in Chicago, Illinois USA

Funded by the Department of Energy’s Office of Science, Biological and Environmental Research program, Community Research on Climate and Urban Science (CROCUS) studies urban climate change and the impact it has on communities, with particular focus on disinvested, under-resourced communities. This information leads to new insights on urban climate challenges and informs future actions for mitigating and adapting to climate change at the street, neighborhood and regional levels.As part of the CROCUS effort, the Urban Canyons 2024 project was undertaken to study conditions at unprecedented detail over various neighborhoods in Chicago, Illinois. This dataset consists of upper air soundings that were collected as part of this effort. Soundings were launched during two intensive observing periods, IOP1 occurred on 22-23 July 2024, while IOP2 occurred on 27-28 July 2024. For IOP1, soundings were launched at coordinated times from three sites, Shedd Aquarium in Downtown Chicago, Abizu Campus High School in Humboldt Park, and Gary Comer Youth Center in West Woodlawn. For IOP2, the Gary Comer site was replaced by a neighborhood site in West Woodlawn, Chicago. The Abizu Campos site was operated by Valparaiso University and used iMET-4 rawinsondes, the other sites were operated by the University of Illinois Urbana-Champaign and used GRAW DFM-19 sondes.This dataset contains netCDF files containing quality-controlled temperature, dewpoint, geopotential height, pressure, and vector wind measurements at 1 second intervals following launch. These files are readable by the open-source netCDF software libraries available in many software packages (i.e., python, R, fortran, C++, etc.). The dataset also contains quicklook plots of each launch on a skew-T log-p thermodynamic diagram. These are in png format viewable by most web browsers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Gap-filled methane and carbon dioxide fluxes across two ecosystem states at the US-OWC AmeriFlux site (2015−2016, 2020−2022)

This dataset contains gap-filled measurements of methane flux (FCH4), net ecosystem CO2 exchange (NEE) partitioned into gross primary productivity (GPP) and ecosystem respiration (RE), as well as latent heat flux (LE) from a Great Lakes coastal freshwater wetland at the US-OWC AmeriFlux site. The dataset covers the peak growing seasons (June−September) of 2015−2016, dominated by Typha spp., and 2020−2022, characterized by floating-leaved species (lotus and water lily). These data were generated to investigate how rising water levels and vegetation shifts influence CH4 and CO2 fluxes across two distinct ecosystem states in this wetland. The dataset, provided in CSV format, includes half-hourly gap-filled flux data from June to September for 2015, 2016, 2020, 2021, and 2022. The gap-filled data refers to measurements where missing values due to instrument issues or quality control were filled using artificial neural networks (ANNs).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Foliar element determination from field survey in association with the National Ecological Observatory Network Airborne Observation Platform survey, East River, Colorado 2018

The purpose of this dataset is to support research aimed at understanding the coupling between hydrologic and biogeochemical processes at watershed scale, particularly the relationship between aboveground vegetation characteristics and subsurface soil properties. These data are intended to inform and calibrate models of catchment-scale biogeochemical fluxes, including rock-derived nutrient cycling, and they were procured to address the following questions: (1) What is the distribution of vegetation characteristics across the study catchments? (2) Are foliar concentrations of rock-derived nutrients related to underlying lithology and soil availability, or are these signals masked by biotic nutrient cycling and retention processes?This data package contains foliar elemental data collected during the 2018 National Ecological Observatory Networks (NEON) Airborne Observation Platform (AOP) imaging spectroscopy and lidar surveys in Gunnison County, Colorado. Folair samples were collected across the East River, Washington Gulch, Slate River, and Coal Creek watersheds and contain a mixture of vegetation including meadow, shrub, and tree foliar samples. The samples were processed using aqua regia digestion and analyzed for elemental determination on inductively coupled plasma optical emission spectrometry (ICP-OES).The data package includes: (1) raw foliar elemental data files in CSV and PDF formats, (2) quality control certificates in PDF format, and (3) an aggregated CSV file containing all elemental measurements compiled across samples. No specialized software is required to access or use these files.

2018 National Ecological Observatory Network Campa↗
DOE OSTI2025

Meteorological Variables and Energy Fluxes at the Pumphouse Site, Crested Butte, CO 2017-2019

This data contains output from the pumphouse eddy covariance tower that includes shortwave radiation, longwave radiation, net radiation, air temperature, relative humidity, as well as sensible, latent, and ground heat fluxes. Also included is calculated evapotranspiration from the latent heat flux and the latent heat of vaporization. All data are on a daily timestep and displayed in Mountain Time. The data has been processed, and Quality Assurance / Quality Control (QA/QC) was done, but any daily gaps in the data have not been filled in. This research was funded by the Department of Energy and performed as part of the Watershed Function Scientific Focus Area. This research aimed to constrain evapotranspiration in a high-elevation catchment.The dataset includes one comma-separated values (CSV) data file (EddyCovariance_MeteorlogicalVariables_CrestedButtePumphouse.csv). Additionally, three metadata CSV files are included: (1) location metadata file (locations.csv), which contains location metadata and coordinates; (2) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Monthly Mean In Situ Surface Flux Observations Paired with Satellite-Derived and Reanalysis-Based Flux Data for the Great Lakes Region, 2001–2020

Surface radiative and turbulent heat fluxes over the Great Lakes strongly influence regional hydrological and meteorological processes, and their accurate representation is critical for numerical weather prediction and coupled atmosphere–lake modeling. However, direct flux observations are spatially sparse across the region, so gridded reanalysis and satellite-derived products are often used for climatological analyses and model evaluation despite differences in their flux representations. This dataset provides processed, quality-controlled, monthly mean surface flux observations from the Great Lakes Evaporation Network (GLEN), AmeriFlux, and the National Data Buoy Center, paired with spatiotemporally matched flux estimates from two reanalysis products, the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) and the Modern Era Reanalysis for Research and Applications, version 2 (MERRA-2), and two satellite-derived products, the Clouds and Earth's Radiant Energy Systems Energy Balanced and Filled (CERES-EBAF) and the Cloud, Albedo and Surface Radiation dataset from AVHRR data - Edition 3 (CLARA-A3). The dataset includes sixteen observational stations with variable temporal coverage within 2001–2020. For each station, a CSV file contains monthly time series of available flux variables, including surface downwelling shortwave radiation (SW), surface downwelling longwave radiation (LW), sensible heat (SH) flux, and latent heat flux (LH), alongside matched gridded product values where available. Columns in the CSV file correspond to different variables sourced from each dataset, with column titles structured as "{dataset}_{variable}". Columns with relevant metadata are also provided in each CSV file, including station latitude and longitude, monthly timestamps, and the name of the sourced observational data. These files are structured for direct use in common analysis tools, including Microsoft Excel, Python pandas, and Python matplotlib. This dataset supports climatological analysis of the Great Lakes regional surface energy budget, evaluation of satellite-derived and reanalysis-based flux products, and development or validation of flux representations in numerical weather prediction and coupled atmosphere–lake models.

Great Lakes↗
DOE OSTI2026

Global compilation of soil methane uptake measurements from 1984 to 2018

This data package contains a global compilation of soil methane uptake measurements collected from published field studies between 1989 and 2022. The dataset was developed to support machine learning (ML) estimation of the global terrestrial methane soil sink and includes monthly methane uptake rates, measurement dates, site coordinates, and associated ecosystem information from different ecosystems. Data were compiled from 164 peer-reviewed publications across approximately 260 study sites, resulting in ~12,000 monthly observations after quality control screening and removal of manipulated experimental treatments. The database was further processed to generate site-averaged methane uptake estimates for comparison between process-based (PB) and ML models.

earth science↗
DOE OSTI2024

Towards a study protocol: A data-driven workflow to identify error sources in direct ink write mechatronics

Abstract Using Direct Ink Write (DIW) technology in a rapid and large-scale production requires reliable quality control for printed parts. Data streams generated during printing, such as print mechatronics, are massive and diverse which impedes extracting insights. In our study protocol approach, we developed a data-driven workflow to understand the behavior of sensor-measured X- and Y- axes positional errors with process parameters, such as print velocity and velocity control. We uncovered patterns showing that instantaneous changes in the velocity, when the build platform accelerates and decelerates, largely influence the positional errors, especially in the X- axis due to the hardware architecture. Since DIW systems share similar mechatronic inputs and outputs, our study protocol approach is broadly applicable and scalable across multiple systems. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2025

Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes

Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob ⁠, as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.

Duan, Chenglong [Rice Univ., Houston, TX (United S↗
DOE OSTI2024

Strategies for mitigating residual magnetic field effect on pre-production PIP-II SSR2 cryomodule performance

This paper outlines the strategy aimed at mitigating the adverse effects of residual magnetic fields on the performance of pre-production SSR2 superconducting cavities within the context of the PIP-II project at Fermilab. Residual magnetic fields can significantly impact cavity performance, leading to reduced quality factor. To address this challenge, our strategy integrates various approaches including magnetic shielding, careful selection of materials, quality controls aimed at measuring magnetic permeability, magnetic hygiene to reduce residual magnetic field at the installation phase. Additionally, experimental studies are being planned to analyze the behavior of the cavities under different magnetic field conditions, and the effectiveness of advanced demagnetization procedures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Scale-Up of Electrode Coating and Flow-Field for Commercial Hydrogen Peroxide Electrolyzer: Cooperative Research and Development Final Report, CRADA Number CRD-17-00687

Hydrogen peroxide is currently produced at central chemical plants via the anthraquinone oxidation process. This process produces environmental pollutants that are costly to remediate, requires hazardous long distance shipping of highly concentrated peroxide (50% or 70%), and necessitates extra handling costs related to storage and dilution. Peroxygen Systems, Inc. (PSi) is developing breakthrough technology for on-site hydrogen peroxide production. PSi’s on-site on-demand electrolyzer can reduce the cost of producing hydrogen peroxide by 50%, while also completely eliminating the cost and safety issues associated with shipping and handling of high concentration hydrogen peroxide. The challenge for PSi is scaling. To support the next step toward commercialization (customer pilot tests), scaling the prototype into larger single cells and 20-40 cell stacks is required. In addition to internal hardware and flow-field design efforts at PSi, NREL will address three critical problems for this scale-up effort: (1) demonstrating a large scale roll-to-roll (R2R) process to coat uniform electrode materials for 100 cm2 and 500 cm2 stack testing, (2) demonstrating an in-line diagnostic to achieve better electrode quality control, and (3) performing in situ cell/stack testing to better understand and optimize the performance of the flow field design.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2026

Inkjet Printing to Scale Perovskite and Silicon Tandem Solar Cell: Cooperative Research and Development Final Report, CRADA Number CRD-17-00690

The proposed project seeks to develop a method for inkjet printing of the active layer in perovskite solar cells for application in stand-alone products or added to conventional silicon solar cells in a mechanically-stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of novel uses for printing technologies and development of predictive quality control techniques.

14 SOLAR ENERGY↗
DOE OSTI2024

BERT Non-Destructively Probes the Microstructure of Dissimilar Welds [Poster]

Energy-resolved neutron imaging (ERNI) utilizes contrast provided by diffraction. Microstructure with >100µm grains as in cast, annealed or welded materials is difficult to characterize by X-ray or electron-based methods $\Rightarrow$ Well-suited for neutron Bragg-edge radiography. BERT was applied to dissimilar welds of Inconel on steel produced by additive manufacturing. Viewing the sample at time-of-flight/energy/wavelength where a single grain orientation dominates the attenuation allows to map grain orientations. Similarly to electron-backscatter diffraction (EBSD) but on cm length scales and through-thickness. Combined with texture measurements on the HIPPO instrument, identifying major grain orientations, 2D and 3D grain orientation maps are feasible. Results can guide development of thermo-mechanical treatment avoiding or introducing such microstructures, characterize dissimilar welds, interpretation of acoustic signals for quality control, guide destructive examination with X-rays/electrons, or provide data for codes predicting such microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evaluating the Nation's Pipeline Infrastructure with NETL's Advanced Infrastructure Integrity Model (AIIM)

This poster is a part of BIL-EDX4CCS Task 36: Advanced Infrastructure Integrity Modeling to Evaluate Existing Energy Infrastructure Reusability and Risk, the goal of which is to produce a smart tool that will assess existing energy infrastructure reusability and risk using the Advanced Infrastructure Integrity Model (AIIM). This model forecasts lifespan and potential risk using a multitude of factors such as incidents reports, structural characteristics, and the surrounding environment. The project aims to provide scientific insights for a better understanding of carbon storage (CS), potential to support CS stakeholder needs, national decarbonization, and mitigating climate change. AIIM will utilize an energy infrastructure database as its input, developed by acquiring publicly available data as well as NETL derived products. These resources include incidents, geohazards, and infrastructure variables. Soil data in the form of rasters and pipeline incident reports were processed and a script was developed to count the number of times features such as roads, railroads, and rivers intersected with pipeline segments which were then converted to points. Distance to oil and natural gas wells, petroleum ports, intermodal freight facilities, and geologic structures were also calculated. After data preparation and quality control was completed, the data was integrated into the pipeline points. Once models are complete, a smart tool will be created in the form of an online dashboard.

Malay, Caleb↗
DOE OSTI2024

Income Verification Strategies for Income-Based Solar Programs

The Inflation Reduction Act has created substantial new programs that support adoption of solar power by low-income households, including the $7 billion Solar For All program and the Low-Income Communities Bonus Credit Program, which increases the investment tax credit for certain types of deployment. In addition, a growing number of states are using solar programs to reduce energy burdens and create energy justice opportunities for low-income households and disadvantaged communities. Verifying the income of participating customers is an important component of these programs. Program managers are seeking strategies to verify a large number of subscribing customers in an accurate, timely, and cost-efficient manner. To help inform program managers, Berkeley Lab investigated how a number of energy and non-energy programs manage income verification. The most common approach is to require proof through tax documents, pay stubs, or other formal income documentation, which can pose an impediment to enrolling eligible customers and create a paperwork burden for administrators. In order to reduce the burden for both the applicant and the program manager, some programs use alternative methods. We identify three common alternative verification methods: -Categorical eligibility: Customers enrolled in other, similar income-verified assistance programs are automatically eligible for enrollment in other income-qualified programs. -Geographic eligibility: Eligibility is based on the customer’s location within a specified area, typically a low-income or disadvantaged community or census tract, and; -“Self-attestation”: The participant claims eligibility with or without further documentation. We describe these options, their pros and cons, give examples of how they are used, and explore how some low-income programs address administrative issues, audits, or other quality control measures. Finally, we explore the risk of mistaken verifications (finding a participant eligible when they are not) in the different strategies. While this memo was initiated by a request relating to income-based community solar programs, the methods are applicable to any program with income eligibility requirements in the energy or non-energy sector. Funding was provided for this research by the Solar Energy Technologies Office of the US Department of Energy, through the National Community Solar Partnership.

14 SOLAR ENERGY↗
DOE OSTI2024

Evaluation of Radiography for TRISO Buffer Layer Density Measurement

Tristructural isotropic (TRISO) fuel particles consist of a central uranium-bearing kernel and a series of coating layers designed to retain fission products and to ensure fuel performance. Several parameters such as thickness and density must be measured for these coating layers to show that they conform with fuel specifications. Current methods for measuring the density of pyrolytic carbon and silicon carbide layers (liquid gradient density column) and the buffer layer (mercury porosimetry) generate Resource Conservation and Recovery Act (RCRA) radiological-mixed waste. In addition, measurement of buffer and inner pyrolytic carbon layer densities require hot sampling or interrupted coating runs and the mercury porosimetry method used for buffer density measurement only measures the mean buffer density, not the interparticle distribution. A new approach has been evaluated to measure the density of coating layers in TRISO particles based on the dependence of x-ray attenuation in radiographs on material density. This method does not generate RCRA mixed waste, measures density on a particle-by-particle basis, and in principle is capable of measuring the density of all coating layers in a single process. Initial results using thinned TRISO particle sections to evaluate radiography measurement of density as a quality control characterization method are reported herein. In this work, the primary focus is on measurement of the density of the buffer layer; however, with appropriate calibration the method should be applicable to other coating layers. Improvements to the initial method and a full demonstration of the method on the remaining coating layers may be pursued as a future effort.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

LYNM PE1 Shot A Meteorology Team Technical Report

Weather support for Shot A was done by NOAA’s Air Resources Laboratory (ARL) / Special Operations and Research Division (SORD) and Lawrence Livermore National Laboratory (LLNL). Weather support activities included wind and precipitation forecasting, maintaining and monitoring PE1 meteorology towers MT02-11, maintaining and monitoring the ARL/SORD tower on Aqueduct Mesa (A12AI, also called MT01), maintaining and monitoring the Blackbrush energy flux tower, radiosonde preparation and launch, providing weather conditions on shot day for go/no-go criteria, and quality control and submission of the datasets. ARL/SORD additionally maintains and monitors the meteorological tower network (Mesonet) and sodar (at Desert Rock) for NNSS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluation of XCT for Matrix Density Measurement of Particle Fuel Forms

Particle fuel forms generally consist of a dispersion of fuel, such as tristructural isotropic (TRISO) particles, within a refractory matrix (e.g., graphite or silicon carbide). The density of matrix materials for particle fuel forms is of interest for modeling fuel form strength and thermal properties and may be specified as a quality control parameter, depending on reactor design. Some of the uncertainty associated with traditional, manual approaches can be eliminated by performing x-ray computed tomography (XCT) on the fuel forms and applying image processing methods to generate a precise count of the number of particles. This also removes the need to include determination of particle count within each individual fuel form during fabrication. Unfortunately, reconstruction artifacts from high-Z uranium-bearing kernels prevent accurate measurement of individual particle volumes using this approach, so the use of mean particle mass and volume are still necessary for computation of average fuel form matrix density. This method of using XCT to count particles in individual fuel form for determination of average matrix density was applied to three archived compacts from the Advanced Gas Reactor Fuel Development and Qualification (AGR)-1 campaign, four archived compacts with uranium carbide/uranium oxide (UCO) TRISO from the AGR-2 campaign, and three archived UO 2 -TRISO compacts from the AGR-2 campaign. The resulting density values were compared with those previously reported, showing slight changes due to uncertainties in the previously used number of particles in each of these cylindrical, graphite matrix compacts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Modularization of EDGE Workflows Using Nextflow: Improving the Efficiency and Maintainability of Bioinformatics Software

EDGE is a bioinformatics platform developed in 2016 by researchers at Los Alamos National Laboratory (LANL) to facilitate the analysis of next-generation sequencing data by researchers with varying levels of experience in bioinformatics (Li et al., 2017). Users with single-end, paired-end or long-read sequencing data can provide their reads as input to EDGE and select the combination of workflows to run that are most useful for their research (e.g., quality control of reads, genome assembly, or the taxonomic classification of input reads). Table 1 summarizes the modules available in EDGE. EDGE is available as a web platform at https://edgebioinformatics.org, as installable source code maintained on GitHub under a GPLv3 license, and as a publicly hosted Docker image.

59 BASIC BIOLOGICAL SCIENCES↗