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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Microbial Biomass in Soils Receiving Varying Levels of Organic Inputs - A Data Compilation

This dataset contains soil microbial biomass data compiled from published laboratory studies and field manipulations of organic inputs to soils. Each study included at least three levels of a given type of organic input applied to a given type of soil. Studies were selected from the literature that had experimentally manipulated organic input rates to soils using unburned, non-synthetic material (e.g. plant litters, manures, and composts). Fifty-five (55) studies, conducted from 1997 to October 2019, were chosen and compiled into a dataset with 358 observations from 96 combinations of a given organic material applied to a given soil in agricultural systems, laboratory incubations, forests, or grasslands. • Studies were selected when biomass measurements used the chloroform fumigation-extraction procedure followed by carbon analysis, or, in two instances, studies estimated microbial biomass using phospholipid fatty acid analysis. • Studies that used fewer than three input rates or characterized microbial biomass via substrate induced respiration were excluded. • The temporal and spatial aspects of the laboratory and field studies were not essential to the analyses (Craig et al., 2021) and were not included with the measurement data. These data were used to assess the relationship between organic input amounts and microbial biomass. Complete reference citations are provided if additional information is needed. The compiled data are provided in two .csv files: (1) soil treatments and microbial biomass data and (2) literature citations. The “Study” field is the cross reference between files. Also provided is the R code for reproducing the results in the related publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Pantropical Tree Sapwood Hydraulic Properties, 1991 - 2014

This data package contains sapwood pressure-volume parameters including osmotic potential at full turgot, turgor loss point, bulk elastic modulus, and others, determined by curve fitting to raw isotherm data (paired measurements of water content and water potential). Raw data were digitized from published figures. Data are from natural tropical and subtropical forests or savannas and span rainfall gradients from deciduous dry tropical forests to everwet tropical forests, and come from the following countries: Argentina, Panama, Brazil, Costa Rica, and Madagascar. Included in the attached zip file are four CSV files. sapwood_PV_recal_headers.csv: description of variables in the two files below sapwood_PV_recal_corrected.csv: bias-corrected sapwood PV data (see Methods in the associated reference) sapwood_PV_recal_uncorrected.csv: uncorrected sapwood PV data (see Methods in the associated reference) sapwood_PV_references.csv: citation, bibliographic reference, and DOI for the published references from which data were extracted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soil organic matter and plant carbon allocated to nitrogen acquisition simulated by the FUN-BioCROP model

This data package contains the model input, results, and validation data from Juice et al (citation below). The FUN-BioCROP model (Fixation and Uptake of Nitrogen- Bioenergy Carbon, Rhizosphere, Organisms, and Protection) advances the field of bioenergy modeling by integrating new empirical paradigms of the role of belowground processes in shaping coupled carbon (C) and nitrogen (N) cycles. It was developed by modifying the FUN-CORPSE model (Fixation and Uptake of Nitrogen- Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment, Sulman et al. 2017 Ecology Letters) for use in bioenergy systems by including mechanistic tillage, organic matter addition, nitrogen fertilization, harvest, and feedstock-specific parameters, and to be driven by DayCent plant productivity and biomass data.

biofuel sustainability↗
DOE OSTI2025

$\bar{\nu}_\mu$ charged-current $\pi^0$ data release

Data release for the NOvA muon antineutrino charged-current (CC) pi^0 cross section presented in arXiv:2511.05807. The signal for this analysis is defined as muon antineutrino CC interactions in the fiducial volume of the NOvA near detector (a 2.7 m × 2.7 m × 9.0 m region) that produce at least one pi^0 in the final state emerging from the nucleus, within the phase space of muon momentum [0.5, 2.5) GeV/c and muon angle [0, 60) degree, as described in arXiv:2511.05807. The released zip file contains two files: NOvA_NumubarCCPi0_DataRelease.root README.txt The ROOT file includes the cross-section results as well as the statistical and systematic covariance matrices for each variable used in this analysis. The README provides a detailed description of the contents of the data release. Official Flux: The flux used in this analysis is available from the NOvA Public Docs: https://publicdocs.fnal.gov/cgi-bin/ShowDocument?docid=8. File structure --- The ROOT file contains the following TDirectories: pi0p - pi^0 momentum distributions pi0dir - pi^0 angular distributions muonp - muon momentum distributions muondir - muon angular distributions Q2 - reconstructed Q^2 distributions Wmass - reconstructed W_mass distributions Each directory contains three histograms: xsec (TH1D): Cross section result cov_stat (TH2D): Statistical covariance matrix cov_syst (TH2D): Systematic covariance matrix Usage notes: - xsec gives the measured differential cross section w.r.t. the corresponding variable. - cov_stat and cov_syst provide the full covariance matrices. - The bin definitions and kinematic phase spaces follow those used in arXiv:2511.05807. Citation --- If you use these data, please cite: NOvA Collaboration, arXiv:2511.05807.

Wu, Wanwei [Pittsburgh U.] (ORCID:0000000326327215↗
DOE OSTI2016

Transportation Secure Data Center

The Transportation Secure Data Center (TSDC) at https//www.nrel.gov/tsdc provides free access to detailed transportation data from travel surveys and studies conducted across the nation. It features millions of data points including second-by-second GPS readings, vehicle characteristics, and demographics for all modes of travel. NREL screens the initial data for quality control, translates each data set into a consistent format, and interprets the data for spatial analysis. NREL processing routines add information on fuel economy and road grades and join data points to the road network. NREL maintains the TSDC in partnership with the U.S. Department of Transportation and the U.S. Department of Energy. Before viewing the data for the first time, you will be required to fill out a short registration form. If you use TSDC data in a publication, please notify NREL at tsdc@nrel.gov and include a citation consistent with the following format: "Transportation Secure Data Center." ([YEAR]). National Renewable Energy Laboratory. Accessed [DATE]: www.nrel.gov/tsdc.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2015

The Open Data Repositorys Data Publisher

Data management and data publication are becoming increasingly important components of researcher's workflows. The complexity of managing data, publishing data online, and archiving data has not decreased significantly even as computing access and power has greatly increased. The Open Data Repository's Data Publisher software strives to make data archiving, management, and publication a standard part of a researcher's workflow using simple, web-based tools and commodity server hardware. The publication engine allows for uploading, searching, and display of data with graphing capabilities and downloadable files. Access is controlled through a robust permissions system that can control publication at the field level and can be granted to the general public or protected so that only registered users at various permission levels receive access. Data Publisher also allows researchers to subscribe to meta-data standards through a plugin system, embargo data publication at their discretion, and collaborate with other researchers through various levels of data sharing. As the software matures, semantic data standards will be implemented to facilitate machine reading of data and each database will provide a REST application programming interface for programmatic access. Additionally, a citation system will allow snapshots of any data set to be archived and cited for publication while the data itself can remain living and continuously evolve beyond the snapshot date. The software runs on a traditional LAMP (Linux, Apache, MySQL, PHP) server and is available on GitHub (http://github.com/opendatarepository) under a GPLv2 open source license. The goal of the Open Data Repository is to lower the cost and training barrier to entry so that any researcher can easily publish their data and ensure it is archived for posterity.

Astrobiology data↗
NASA NTRS1989

Asteroid lightcurve parameters

A light curve data file is presented. Each citation includes the year, all authors, journal or book name, volume, and first and last page numbers. The asteroid list is ordered by asteroid number, followed by asteroid name, the period in hours, amplitude of variation or range of amplitude observed, and a reliability code.

Lagerkvist, C.-I.↗
NASA NTRSDate not supplied

Developing a Vision for Maturing the Heliophysics Infrastructure towards Open Science: The DIARieS Analysis Ecosystem

In the dawn of open science and the upcoming requirements, we speak about the existing state of Heliophysics infrastructure and detail the evolution required to address capability or interconnection shortcomings. Such a daunting barrier calls for an analysis ecosystem with multi-faceted capability. We propose such an ecosystem, called DIARieS, to be built upon five conceptual pillars: Discovery, Implementation, Analysis, Reproducibility, and Sharing of results. The combination of these concepts in a single platform will enable users to more intuitively combine recent advances in technology to create ‘DIARieS’ of their workflows, which can be easily made open to others in the community. The DIARieS ecosystem will also increase our efficiency by streamlining our various workflow processes, including automatic incorporation of the impending requirements of open science. The various components of the ecosystem will simplify software installation and data implementation, including automatically generated citation lists based on the components included. Automatic containerization and version control of the ecosystem will make the custom workflows easily reproducible. Employing widget technology will ease the difficulty of producing publication and commercial quality visualizations and applying common analyses techniques. Incorporating multiple technologies will streamline the various sharing methods common in our work environments today. Overall, the totality of capabilities to be offered by this analysis ecosystem will drastically simplify the application of open science principles to our work in addition to improving our efficiency and ease of collaboration. This talk summarizes a vision of the proposed ecosystem, which is described in more detail in Ringuette et al. (2022: https://doi.org/10.1016/j.asr.2022.05.012).

infrastructure↗
NASA NTRSDate not supplied

Developing a Vision for Maturing the Heliophysics Infrastructure towards Open Science

In the dawn of open science and the upcoming requirements, we speak about the existing state of Heliophysics infrastructure and detail the evolution required to address capability or interconnection shortcomings. Such a daunting barrier calls for an analysis ecosystem with multi-faceted capability. We propose such an ecosystem, called DIARieS, to be built upon five conceptual pillars: Discovery, Implementation, Analysis, Reproducibility, and Sharing of results. The combination of these concepts in a single platform will enable users to more intuitively combine recent advances in technology to create ‘DIARieS’ of their workflows, which can be easily made open to others in the community. The DIARieS ecosystem will also increase our efficiency by streamlining our various workflow processes, including automatic incorporation of the impending requirements of open science. The various components of the ecosystem will simplify software installation and data implementation, including automatically generated citation lists based on the components included. Automatic containerization and version control of the ecosystem will make the custom workflows easily reproducible. Employing widget technology will ease the difficulty of producing publication and commercial quality visualizations and applying common analyses techniques. Incorporating multiple technologies will streamline the various sharing methods common in our work environments today. Overall, the totality of capabilities to be offered by this analysis ecosystem will drastically simplify the application of open science principles to our work in addition to improving our efficiency and ease of collaboration.

Infrastructure↗
NASA NTRS2004

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Icing Sensor Performance During the 2003 Alliance Icing Research Study (AIRS II)

The Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor was deployed onboard the University of North Dakota Citation II aircraft in the Alliance Icing Research Study (AIRS II) from Nov 19 through December 14, 2003. TAMDAR is designed to measure and report winds, temperature, humidity, turbulence and icing from regional commercial aircraft (Daniels et. al., 2004). TAMDAR icing sensor performance is compared to a) in situ validation data from the Citation II sensor suite, b) Current Icing Potential products developed by the National Center for Atmospheric Research (NCAR) and available operationally on the NOAA Aviation Weather Center s Aviation Digital Data Server (ADDS) and c) NASA Advanced Satellite Aviation-weather Products (ASAP) cloud microphysical products.

Murray, John J.↗
DOE OSTI2016

Fleet DNA

Available online at www.nrel.gov/fleetdna, the Fleet DNA clearinghouse of commercial fleet vehicle operating data helps manufacturers and developers optimize vehicle designs and helps fleet managers choose advanced technologies for their fleets. Sponsored by the U.S. Department of Energy, this online tool provides data summaries and visualizations similar to real-world genetics for medium- and heavy-duty commercial fleet vehicles operating in a variety of vocations. If you use Fleet DNA data in a publication, please notify NREL at fleetdna@nrel.gov and include a citation consistent with the following format: “Fleet DNA Project Data.” ([YEAR]). National Renewable Energy Laboratory. Accessed [DATE]: www.nrel.gov/fleetdna.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2004

Airborne In Situ and Ground-based Polarimetric Radar Measurements of Tropical Convection in Support of CRYSTAL-FACE

This report describes the work performed by the University of North Dakota (UND) under NASA Grant NAG5-11509, titled Airborne In Situ and Ground-based Polarimetric Radar Measurements of Tropical Convection in Support of CRYSTAL-FACE. This work focused on the collection of data by two key platforms: the UND Citation II research aircraft and the NASA NPOL radar system. The CRYSTAL-FACE (C-F) mission addresses several key issues from the NASA Earth System Enterprise, including the variability of water in the atmosphere, the forcing provided by tropical cirrus and the response of the Earth system to this forcing. In situ measurements and radar observations of tropical convection, cirrus clouds and their environment are core elements of C-F. One of the primary issues that C-F is addressing is the relationship of tropical cirrus anvils to precipitating deep convection. The in situ measurements from C-F are being used to validate remote sensing of Earth-Atmosphere properties, increase our knowledge of upper tropospheric water vapor and its distribution, and increase our knowledge of tropical cirrus cloud morphology and composition. Radar measurements, especially polarimetric diversity observations available fiom the NASA NPOL radar, are providing essential information about the initiation, modulation, and dissipation of convective cores and the generation of associated anvils in tropical convection. Specifically, NPOL radar measurements contain information about convective intensity and its vertical structure for comparison with thermodynamic and kinematic environmental measurements observed from soundings. Because of the polarimetric diversity of MOL, statistics on bulk microphysical properties can be retrieved and compared to the other characteristics of convection and associated cirrus anvils. In summary, the central objectives of this proposal were to deploy the UND Citation research aircraft as an in situ sensing platform for this mission and to provide collaborative analyses of the recorded data and to deploy the NPOL radar to observe the characteristics of cirrus and parent convection.

Poellot, Michael R.↗
NASA NTRS2003

Cryogenic Information Center

The Cryogenic Information Center (CIC) is a not-for-profit corporation dedicated to preserving and distributing cryogenic information to government, industry, and academia. The heart of the CIC is a uniform source of cryogenic data including analyses, design, materials and processes, and test information traceable back to the Cryogenic Data Center of the former National Bureau of Standards. The electronic database is a national treasure containing over 146,000 specific bibliographic citations of cryogenic literature and thermophysical property data dating back to 1829. A new technical/bibliographic inquiry service can perform searches and technical analyses. The Cryogenic Material Properties (CMP) Program consists of computer codes using empirical equations to determine thermophysical material properties with emphasis on the 4-300K range. CMP's objective is to develop a user-friendly standard material property database using the best available data so government and industry can conduct more accurate analyses. The CIC serves to benefit researchers, engineers, and technologists in cryogenics and cryogenic engineering, whether they are new or experienced in the field.

Mohling, Robert A.↗
NASA NTRS2003

Cryogenic Information Center

The Cryogenic Information Center (CIC) is a not-for-profit corporation dedicated to preserving and distributing cryogenic information to government, industry, and academia. The heart of the CIC is a uniform source of cryogenic data including analyses, design, materials and processes, and test information traceable back to the Cryogenic Data Center of the former National Bureau of Standards. The electronic database is a national treasure containing over 146,000 specific bibliographic citations of cryogenic literature and thermophysical property data dating back to 1829. A new technical/bibliographic inquiry service can perform searches and technical analyses. The Cryogenic Material Properties (CMP) Program consists of computer codes using empirical equations to determine thermophysical material properties with emphasis on the 4-300K range. CMP's objective is to develop a user-friendly standard material property database using the best available data so government and industry can conduct more accurate analyses. The CIC serves to benefit researchers, engineers, and technologists in cryogenics and cryogenic engineering, whether they are new or experienced in the field.

Mohling, Robert A.↗
NASA NTRS1982

Availability of IMP-7 and IMP-8 data for the IMS period

The relation of IMP-7 and IMP-8 data to the International Magnetospheric Study is discussed. Relevant spacecraft and experiment characteristics, and the nature and accessibility of data from each experiment, are identified. Finally the potential value of IMP data in IMS studies is illustrated with a few citations from the IMP Bibliography and with figures from a recent multiple-data-set magnetotail plasma sheet study.

King, J. H.↗
DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Analyzing EOSDIS Dataset Research Outputs using Knowledge Graphs and Large Language Models

Datasets, unlike publications, can be updated over time, with each new version receiving a DOI but not always being linked to previous ones. This complicates tracking citations across a dataset’s lifecycle. We address this by integrating dataset versions and citations into a knowledge graph (KG), which helps trace dataset citations and analyze dataset usage in applied research. To categorize publications from various journals, we fine-tuned NASA IMPACT INDUS Large Language Model (LLM) on a labeled publication set, assigning publications to one of twenty applied research areas. By linking datasets to these research areas, we improved dataset searchability and discovery through these domains.

open-source↗
NASA NTRS1975

Fracture toughness testing data. A bibliography

This bibliography is comprised of approximately 800 reference citations related to the mechanics of failure in aerospace structures. Most of the references are for documents that include fracture toughness testing data and its application or documents on the availability and usefulness of fracture mechanics analysis methodology. The bibliography represents a search of the literature published in the period April 1962 through April 1974 and is largely limited to documents published in the United States.

Carpenter, J. L., Jr.↗