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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 703 records · Page 39

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NASA NTRSDate not supplied

Improving Earth Science Dataset Search with Publication

The NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) archives a large number of Earth observational datasets. Thousands of the publications are created each year based on these datasets. The content of these publications can be used for discovery of the datasets based on the characteristics of applicational research. We leverage the content of these publications to retrieve the information about phenomena and domains where measurements from the datasets were utilized through linking these publications and dataset in Knowledge Graph. We retrieve phenomena and domain information using SWEET ontology and produce the set of keywords that are linked to the datasets. Further, we evaluate this link strength according to the frequency of dataset usage in the papers mentioning these keywords. We demonstrate how this linkage can improve dataset search by comparing the search results obtained from Common Metadata Repository (CMR) search and the publications based data.

Kristina Stoyanova↗

DOE OSTI2024

RectifHyd Version 2.0: Historical and counterfactual-climatological hydropower monthly generation totals for CONUS plants, 1980 – 2019

This dataset will contain the following files: - RectifHydV2.zip – the RectifHydV2 dataset, split into two files: o RectifHydV2_Actual_MWh.csv: Estimated actual monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 o RectifHydV2_Counterfactual_MWh.csv: Counterfactual (climate-only) monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 - RectifHydV2_code.zip: Full data processing pipeline, coded using R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/rectifhydv2 - RectifHydV2_inputs.zip: Complete set of input data used to create RectifHydV2, organized for direct entry into “/data/” directory of the RectifHydV2 reproducible data pipeline - RectifHydV2_misc.zip: - RectifHydV2_dailyRelease.csv

13 HYDRO ENERGY↗

DOE OSTI2025

PAVC: The foundation for a Pan-Arctic Vegetation Cover database

Field-measured Arctic vegetation cover data is essential for creating accurate, high-quality vegetation structure and composition maps. Extrapolating field data into high-resolution cover maps provides detailed, function-specific information for use in Earth System Models, vegetation classifications, and monitoring vegetation change over time and space. However, field campaigns that collect plant cover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we synthesized and harmonized field-based fractional cover data from various data stores to create a high-quality, consistent repository schema for remote sensing-based vegetation cover mapping applications. We developed a reproducible workflow for synthesizing visual estimate and point-intercept fractional cover data. The resultant Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover at both the species and plant functional type levels. The latter includes absolute foliar cover for deciduous shrubs and trees, evergreen shrubs and trees, forbs, graminoids, lichen, bryophytes, and “other” vegetation, as well as absolute cover for litter and top cover for water and bare ground.

Steckler, Morgan R. [Oak Ridge National Laboratory↗

NASA NTRS2019

GeneLab: A Systems Biology Platform for Omics Analysis

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide the latest in terms of professional state-of-the-art bioinformatics platform for the space biology and radiation community to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare to existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all dataset. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era or on the International Space Station. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗

DOE OSTI2020

Degradation of Commercial Lithium-Ion Cells as a Function of Chemistry and Cycling Conditions

Energy storage systems with Li-ion batteries are increasingly deployed to maintain a robust and resilient grid and facilitate the integration of renewable energy resources. However, appropriate selection of cells for different applications is difficult due to limited public data comparing the most commonly used off-the-shelf Li-ion chemistries under the same operating conditions. This article details a multi-year cycling study of commercial LiFePO 4 (LFP), LiNi x Co y Al 1–x–y O 2 (NCA), and LiNi x Mn y Co 1–x–y O 2 (NMC) cells, varying the discharge rate, depth of discharge (DOD), and environment temperature. The capacity and discharge energy retention, as well as the round-trip efficiency, were compared. Even when operated within manufacturer specifications, the range of cycling conditions had a profound effect on cell degradation, with time to reach 80% capacity varying by thousands of hours and cycle counts among cells of each chemistry. The degradation of cells in this study was compared to that of similar cells in previous studies to identify universal trends and to provide a standard deviation for performance. All cycling files have been made publicly available at batteryarchive.org, a recently developed repository for visualization and comparison of battery data, to facilitate future experimental and modeling efforts.

25 ENERGY STORAGE↗

NASA NTRS1989

Optical archiving for scientific data

Write-once-read-many (WORM) optical disk technology is now practical for use as (1) a near online storage media, (2) long-term storage in a passive repository, and (3) under some circumstances, transporting from and to data generators and data users at remote sites. Optical technology provides several significant advantages over magnetic tapes as a data storage media because it is more compact, provides random access, has a longer lifetime, at least 30 years, and is less sensitive to environmental factors such as temperature and humidity. Two major archival projects using optical technology underway are discussed: the Coastal Zone Color Scanner data and the Dynamics Explorer data. Both projects have used the software for optical archive and retrieval (SOAR) to transfer data in a volume format that can be read transparently by VAX/VMS. Through the use of this software technique, (1) data generators and data users do not have to rewrite extant software and (2) the VAX/VMS Files-11 volume format is in wide use, so it can serve as an interim standard and will be accessible in the long-term.

Lowrey, Barbara E.↗

NASA NTRSDate not supplied

Human Specimen Repository: Sample Collection for the Future [#133-000445]

In early 2014, an executive memo was released directing the improvement of the management of and access to scientific collections funded by government resources. In the spirit of this memo, NASA’s Human Research Program (HRP) funded a project to review existing residual samples in long-term storage for viability, identification, and scientific significance. These samples were to be collected in a centralized location and a detailed inventory was to be conducted to create the Human Sample Repository (HSR). HSR would work to review data from over 27,000 samples, from flight research projects dating back to 1998. The samples themselves would be reviewed, re-labeled, and organized into easy to retrieve, long-term storage. In addition to the older residual samples, HSR would expand to include pristine samples from all consenting crew who have flown on International Space Station (ISS) missions. All samples inventoried and managed by HSR are intended for the same purpose; to support future research projects which will utilize advanced technologies or techniques, by providing one-of-a-kind sample collections that can not be replicated. With this mission in mind, HSR will continue to collect residual samples from HRP funded projects and pristine samples from consenting crew, to further build this unique collection and increase the diversity of flight samples available to the scientific community.

Human Specimen Repository↗

DOE OSTI2024

MSD CoP Webinar: Using Meta-Repositories To Facilitate Open Science in MSD Research

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: In this webinar, we will describe the use of a GitHub meta-repository, for documenting and disseminating the tools and data supporting MSD publications. The goal is to make it easier for others to understand the flow of data and code through your experiment and to be able to reproduce your results and figures with only the information you have provided for them. The webinar will cover the role of open science in the MSD community, the origins and purpose of meta-repositories, and step-by-step instructions and best practices for building a meta-repository starting from the GitHub template (https://github.com/IMMM-SFA/metarepo). We will also discuss how to leverage MSD-LIVE (https://msdlive.org/) in your meta-repository, provide links to numerous examples you can learn from, and discuss the role of meta-repositories in the IM3 project's open science mandates. Presenters : Chris R. Vernon, Casey D. Burleyson, Jennie Rice, and Mengqi Zhao Moderator: Pat M. Reed (MSD CoP Facilitation Team) This webinar was held on: February 22nd, 2024 from 2-3 PM ET

Open Science↗

DOE OSTI2025

nys_psy (NYgrid Model Translation to the Sienna framework) (SWR-25-63)

This repository contains the translation of the NYgrid model, developed by the Anderson Energy Lab at Cornell University, into the Sienna Framework. The baseline model is based on 2019 data. The 2040 version of the model features a unified, correlated dataset of various generation and load profiles spanning 22 years. The methodology used to generate these data is detailed in the following paper The scripts for data generation are available in the ny-clcpa2050 repository. Note: While this test system is designed to simulate the power flow of the New York State transmission system, it does not represent the actual transmission network.

Liu, Vivienne [National Renewable Energy Laborator↗

DOE OSTI2025

mphys-surrogate-model

This repository contains python scripts for building and studying reduced-order-modeling representations of droplet coalescence for eventual use in atmospheric models. The included data are generated from high-fidelity superdroplet methods and are utilized by machine learning pipelines to build data-driven models of droplet size distributions that evolve under coalescence. This repository further includes scripts to determine prediction (uncertainty) intervals on the data-driven model products based on conformal prediction.

Katona, JonasE [Lawrence Livermore National Labora↗

DOE OSTI2021

Can we safely go to 200 °C? An integrated approach to assessing impacts to the engineered barrier system in a high-temperature repository

Abstract. This presentation gives on overview of the complex thermo-hydro-mechanical-chemical (THMC) processes occurring during the disposal of heat-producing high-level radioactive waste in geologic repositories. A specific focus is on the role of compacted bentonite, which is commonly used as an engineered backfill material for emplacement tunnels because of its low permeability, high swelling pressure, and radionuclide retention capacity. Laboratory and field tests integrated with THMC modeling have provided an effective way to deepen our understanding of temperature-related perturbations in the engineered barrier system; however, most of this work has been conducted for maximum temperatures around 100 ∘C. In contrast, some international disposal programs have recently started investigations to understand whether local temperatures in the bentonite of up to 200 ∘C could be tolerated with no significant changes to safety relevant properties. Raising the maximum temperature is attractive for economical and safety reasons but faces the challenge of exposing the bentonite to significant temperature increases. Strong thermal gradients may induce complex moisture transport processes while geochemical processes, such as cementation and perhaps also illitization effects may occur, all of which could strongly affect the bentonite and near-field rock properties. Here, we present initial investigations of repository behavior exposed to strongly elevated temperatures. We will start discussing our current knowledge base for temperature effects in repositories exposed to a maximum temperature of 100 ∘C, based on data and related modeling analysis from a large heater experiment conducted for over 18 years in the Grimsel Test Site in Switzerland. We then show results from coupled THMC simulations of a nuclear waste repository in a clay formation exposed to a maximum temperature of 200 ∘C. We also explore preliminary data from a bench-scale laboratory mock-up experiment, which was designed to represent the strong THMC gradients occurring in a “hot” repository, and we finally touch on a full-scale field heater test to be conducted soon in the Grimsel Test Site underground research laboratory in Switzerland (referred to as HotBENT).

Birkholzer, Jens T. (ORCID:0000000279891912)↗

NASA NTRSDate not supplied

Overview of the Translational Radiation Research and Countermeasures (TRRaC) Project in Space Radiation

The Translational Radiation Research and Countermeasures (TRRaC) Project was initiated by the Space Radiation (SR) Element within NASA’s Human Research Program (HRP) to support the SR mission to understand and characterize the space radiation environment, understand and quantify radiation-associated risks, and mitigate the impacts of radiation-induced adverse health outcomes to enable human space exploration. TRRaC’s mission is to translate radiation research results from experimental studies and epidemiological data to humans and astronauts using bioinformatics and computational modeling. TRRaC will leverage existing datasets such as those available from NASA’s GeneLab repository and human medical radiation exposure registries, along with relevant data generated from ground-based research at molecular, cellular, tissue, and system levels, to: (1) refine the radiation dose rate effectiveness factor, (2) characterize radiation quality effects to improve estimates of the risk of exposure-induced death (REID) from space-relevant radiation exposures, and (3) identify pathways and biomarkers for cancer, cardiovascular disease, and central nervous system changes that are impacted by space radiation exposure.

Parastou Eslami↗

DOE OSTI2023

Atomic protein structure refinement using all-atom graph representations and SE(3)-equivariant graph transformer

Abstract Motivation The state-of-art protein structure prediction methods such as AlphaFold are being widely used to predict structures of uncharacterized proteins in biomedical research. There is a significant need to further improve the quality and nativeness of the predicted structures to enhance their usability. In this work, we develop ATOMRefine, a deep learning-based, end-to-end, all-atom protein structural model refinement method. It uses a SE(3)-equivariant graph transformer network to directly refine protein atomic coordinates in a predicted tertiary structure represented as a molecular graph. Results The method is first trained and tested on the structural models in AlphaFoldDB whose experimental structures are known, and then blindly tested on 69 CASP14 regular targets and 7 CASP14 refinement targets. ATOMRefine improves the quality of both backbone atoms and all-atom conformation of the initial structural models generated by AlphaFold. It also performs better than two state-of-the-art refinement methods in multiple evaluation metrics including an all-atom model quality score—the MolProbity score based on the analysis of all-atom contacts, bond length, atom clashes, torsion angles, and side-chain rotamers. As ATOMRefine can refine a protein structure quickly, it provides a viable, fast solution for improving protein geometry and fixing structural errors of predicted structures through direct coordinate refinement. Availability and implementation The source code of ATOMRefine is available in the GitHub repository (https://github.com/BioinfoMachineLearning/ATOMRefine). All the required data for training and testing are available at https://doi.org/10.5281/zenodo.6944368.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Data and scripts associated with “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments”

This data package is associated with the publication “Moisture content modulates DOM thermodynamic regulation of oxygen consumption in drying streambed sediments” published in Scientific Reports (Garayburu-Caruso et al., 2026). The package contains processed data products and scripts used to quantify how drying and re-inundation of riverbed sediments influence dissolved organic matter (DOM) thermodynamic properties and their relationship with sediment oxygen (O₂) consumption across 33 stream sites in the contiguous United States. The data package contains DOM thermodynamic metrics (e.g., Gibbs free energy of carbon oxidation and thermodynamic efficiency), and O₂ consumption along with watershed-scale climate and land-cover metrics used as explanatory variables in the analyses. Underlying unprocessed and processed ultrahigh-resolution mass spectrometry data, oxygen consumption rates from laboratory moisture-manipulation experiments, within-sample environmental properties, sediment moisture content and contextual field measurements are archived separately at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2428003 (Laan et al., 2024) and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689 (Forbes et al.,2023). A preliminary version of this data package was published in February 2026 at the time of manuscript submission. It was updated in June 2026, at the time of manuscript acceptance, to include the finalized data and additional metadata (readme, data dictionary, and file level metadata). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. At the top level, the data package is organized into five main folders: (1) Data, (2)Figures, (3) Map, (4) GAM_Reulsts, and (5) src. The Data folder contains analysis-ready tabular files with oxygen consumption rates, DOM thermodynamic properties by site and treatment, site-level environmental variables, watershed-scale metrics, and other derived variables referenced in the manuscript. The Figures folder contains static image files associated with the main text and supplemental figures, while the Map folder includes spatial data and map-layer files used to create the sampling-location map. The GAM results folder contains the results for each of the general additive model (GAM).The src folder contains R scripts used to perform data processing, statistical analyses (including clustering, generalized additive models, and threshold analysis), and figure generation. This data package is associated with a GitHub repository found at https://github.com/WHONDRS-Hub/ECA_DOM_Thermodynamics.

Dissolved organic matter↗

DOE OSTI2020

Biodefense Knowledge Management System

After the Amerithrax attacks, the Department of Homeland Security (DHS) recognized the need to link technical scientific information with law enforcement and national security information in the fight against bioterrorism. The Biodefense Knowledge Center (BKC) was formed to provide timely analysis of technical biodefense-related topics to support DHS and its customers in the interagency. The Biodefense Knowledge Management System (BKMS) was created as the backbone for information management within the BKC. It is a scalable, web-based knowledge management system for organizing disparate data sources. By combining information from 35+ data sources, the BKMS provides a searchable repository for technical information including scientific reports, journal articles, news articles, research funding databases, patent databases, and genomic datasets. The current system contains over 58 million documents and 450 million genomic records, and operates at several classification levels.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2020

Science Resource Office Peer Review and Metrics Factsheet [Slides]

The Science Resource Office-Peer Review and Metrics (SRO-PRM) Team hosts and maintains LANL's central repository for Science, Technology, and Engineering (STE) data. The Team tracks, integrates, analyzes, and reports qualitative and quantitative data measuring performance, quality, impact, and productivity. These metrics are indicators of the effectiveness and impact of STE efforts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Short GRB Host Galaxies. I. Photometric and Spectroscopic Catalogs, Host Associations, and Galactocentric Offsets

We present a comprehensive optical and near-infrared census of the fields of 90 short gamma-ray bursts (GRBs) discovered in 2005–2021, constituting all short GRBs for which host galaxy associations are feasible (≈60% of the total Swift short GRB population). We contribute 274 new multi-band imaging observations across 58 distinct GRBs and 26 spectra of their host galaxies. Supplemented by literature and archival survey data, the catalog contains 542 photometric and 42 spectroscopic data sets. The photometric catalog reaches 3σ depths of ≳24–27 mag and ≳23–26 mag for the optical and near-infrared bands, respectively. We identify host galaxies for 84 bursts, in which the most robust associations make up 56% (50/90) of events, while only a small fraction, 6.7%, have inconclusive host associations. Based on new spectroscopy, we determine 18 host spectroscopic redshifts with a range of z ≈ 0.15–1.5 and find that ≈23%–41% of Swift short GRBs originate from z > 1. We also present the galactocentric offset catalog for 84 short GRBs. Taking into account the large range of individual measurement uncertainties, we find a median of projected offset of ≈7.7 kpc, for which the bursts with the most robust associations have a smaller median of ≈4.8 kpc. Our catalog captures more high-redshift and low-luminosity hosts, and more highly offset bursts than previously found, thereby diversifying the population of known short GRB hosts and properties. In terms of locations and host luminosities, the populations of short GRBs with and without detectable extended emission are statistically indistinguishable. This suggests that they arise from the same progenitors, or from multiple progenitors, which form and evolve in similar environments. All of the data products are available on the Broadband Repository for Investigating Gamma-Ray Burst Host Traits website.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1983

Design guide for high pressure oxygen systems

A repository for critical and important detailed design data and information, hitherto unpublished, along with significant data on oxygen reactivity phenomena with metallic and nonmetallic materials in moderate to very high pressure environments is documented. This data and information provide a ready and easy to use reference for the guidance of designers of propulsion, power, and life support systems for use in space flight. The document is also applicable to designs for industrial and civilian uses of high pressure oxygen systems. The information presented herein are derived from data and design practices involving oxygen usage at pressures ranging from about 20 psia to 8000 psia equal with thermal conditions ranging from room temperatures up to 500 F.

Bond, A. C.↗