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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DE-FE0029488 - North Dakota Integrated Carbon Capture and Storage Complex Feasibility Study Public Data

Data from award DE-FE0029488 - North Dakota Integrated Carbon Capture and Storage Complex Feasibility Study performed by the Energy & Environmental Research Center including the following: - 2D Seismic {Input data, sgy files, maps, logs, and descriptors} - Core Petrophysics {Core analysis of plugs from the two stratigraphic test wells (Flemmer-1 [API 33-057-00039] and BNI-1 [API 33-065-00018])} - North Dakota Oil and Gas File No 37380 Files - North Dakota Oil and Gas File No 37672 Files - Well Testing Data {Summary of well testing methods and results from the stratigraphic test wells (Flemmer-1 and BNI-1)} Additional References: https://www.netl.doe.gov/sites/default/files/2017-12/Wesley-Peck-_Mastering-the-Subsurface_CarbonSAFE-Phase-II_August-2017-final.pdf Peck, W.D., Ayash, S.C., Klapperich, R.J., Gorecki, C.D. (2019) The North Dakota integrated carbon storage complex feasibility study, International Journal of Greenhouse Gas Control, Volume 84, 2019, Pages 47-53, https://doi.org/10.1016/j.ijggc.2019.03.001

Carbon Storage↗
DOE OSTI2019

Toward unrestricted use of public genomic data

Despite some notable progress in data sharing policies and practices, restrictions are still often placed on the open and unconditional use of various genomic data after they have received official approval for release to the public domain or to public databases. These restrictions, which often conflict with the terms and conditions of the funding bodies who supported the release of those data for the benefit of the scientific community and society, are perpetuated by the lack of clear guiding rules for data usage. Existing guidelines for data released to the public domain recognize but fail to resolve tensions between the importance of free and unconditional use of these data and the “right” of the data producers to the first publication. This self-contradiction has resulted in a loophole that allows different interpretations and a continuous debate between data producers and data users on the use of public data. We argue that the publicly available data should be treated as open data, a shared resource with unrestricted use for analysis, interpretation, and publication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

CHARACTERIZING THE VARIABILITY OF STARS WITH EARLY-RELEASE KEPLER DATA

We present a variability analysis of the early-release first quarter of data publicly released by the Kepler project. Using the stellar parameters from the Kepler Input Catalog, we have separated the sample into 129,000 dwarfs and 17,000 giants and further sub-divided the luminosity classes into temperature bins corresponding approximately to the spectral classes A, F, G, K, and M. Utilizing the inherent sampling and time baseline of the public data set (30 minute sampling and 33.5 day baseline), we have explored the variability of the stellar sample. The overall variability rate of the dwarfs is 25% for the entire sample, but can reach 100% for the brightest groups of stars in the sample. G dwarfs are found to be the most stable with a dispersion floor of {sigma} {approx} 0.04 mmag. At the precision of Kepler, >95% of the giant stars are variable with a noise floor of {approx}0.1 mmag, 0.3 mmag, and 10 mmag for the G giants, K giants, and M giants, respectively. The photometric dispersion of the giants is consistent with acoustic variations of the photosphere; the photometrically derived predicted radial velocity distribution for the K giants is in agreement with the measured radial velocity distribution. We have also briefly explored the variability fraction as a function of data set baseline (1-33 days), at the native 30 minute sampling of the public Kepler data. To within the limitations of the data, we find that the overall variability fractions increase as the data set baseline is increased from 1 day to 33 days, in particular for the most variable stars. The lower mass M dwarf, K dwarf, and G dwarf stars increase their variability more significantly than the higher mass F dwarf and A dwarf stars as the time baseline is increased, indicating that the variability of the lower mass stars is mostly characterized by timescales of weeks while the variability of the higher mass stars is mostly characterized by timescales of days. A study of the distribution of the variability as a function of galactic latitude suggests that sources closer to the galactic plane are more variable. This may be the result of sampling differing populations (i.e., ages) as a function of latitude or may be the result of higher background contamination that is inflating the variability fractions at lower latitudes. A comparison of the M dwarf statistics to the variability of 29 known bright M dwarfs indicates that the M dwarfs are primarily variable on timescales of weeks or longer presumably dominated by spots and binarity. On shorter timescales of hours, which are relevant for planetary transit detection, the stars are significantly less variable, with {approx}80% having 12 hr dispersions of 0.5 mmag or less.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Raw data for publication: Cao et al. 2023. GCB-Bioenergy (accepted for publication).

Raw data for publication: Viet Dang Cao, Baskaran Kannan, Guangbin Luo, Hui Liu, John Shanklin, and Fredy Altpeter. 2023. Triacylglycerol, total fatty acid and biomass accumulation of metabolically engineered energycane grown under field conditions. GCB-Bioenergy (accepted for publication).

Bioenergy, energycane, lipids, biodiesel, biofuel,↗
DOE OSTI2016

The Materials Data Facility: Data Services to Advance Materials Science Research

With increasingly strict data management requirements from funding agencies and institutions, expanding focus on the challenges of research replicability, and growing data sizes and heterogeneity, new data needs are emerging in the materials community. The materials data facility (MDF) operates two cloudhosted services, data publication and data discovery, with features to promote open data sharing, self-service data publication and curation, and encourage data reuse, layered with powerful data discovery tools. The data publication service simplifies the process of copying data to a secure storage location, assigning data a citable persistent identifier, and recording custom (e.g., material, technique, or instrument specific)and automatically-extractedmetadata in a registrywhile the data discovery service will provide advanced search capabilities (e.g., faceting, free text range querying, and full text search) against the registered data and metadata. TheMDF services empower individual researchers, research projects, and institutions to (I) publish research datasets, regardless of size, from local storage, institutional data stores, or cloud storage, without involvement of thirdparty publishers; (II) build, share, and enforce extensible domain-specific custom metadata schemas; (III) interact with published data and metadata via representational state transfer (REST) application program interfaces (APIs) to facilitate automation, analysis, and feedback; and (IV) access a data discovery model that allows researchers to search, interrogate, and eventually build on existing published data. We describe MDF’s design, current status, and future plans.

data management↗
DOE OSTI2013

Analysis Approach and Data Package for Mayak Public Doses: Data Supporting the Calculation of Representative Doses to Members of the Public from Airborne Releases of 131 I at the Mayak Production Association from 1948 through 1972

Historical activities at facilities producing nuclear materials for weapons released radioactivity into the air and water. Past studies in the United States have evaluated the release, atmospheric transport and environmental accumulation of 131 I from the nuclear facilities at Hanford in Washington State and the resulting dose to members of the public (Farris et al. 1994). A multi-year dose reconstruction effort (Mokrov et al. 2004) is also being conducted to produce representative dose estimates for members of the public living near Mayak, Russia, from atmospheric releases of 131 I at the facilities of the Mayak Production Association. The approach to calculating individual doses to members of the public from historical releases of airborne 131 I has the following general steps: • Construct estimates of releases 131 I to the air from production facilities. • Model the transport of 131 I in the air and subsequent deposition on the ground and vegetation. • Model the accumulation of 131 I in soil, water and food products (environmental media). • Calculate the dose for an individual by matching the appropriate lifestyle and consumption data for the individual to the concentrations of 131 I in environmental media at their residence location. A number of computer codes were developed to facilitate the study of airborne 131 I emissions at Hanford. Of particular interest is DESCARTES code that modeled accumulation of 131 I in environmental media (Miley et al. 1994). In addition, the CIDER computer code estimated annual doses to individuals (Eslinger et al. 1994) using the equations and parameters specific to Hanford (Snyder et al. 1994). Several of the computer codes developed to model 131 I releases from Hanford are general enough to be used for other facilities. Additional codes have been developed, including the new individual dose code CiderF (Eslinger and Napier 2013), and applied to historical releases of 131 I from Mayak. This document provides a data package that identifies computer code runs and associated input and output files prepared for the purpose of calculating doses to members of the public from atmospheric releases of 131 I at the Mayak Production Association for the time period 1948 through 1972.

Mayak↗
DOE OSTI2016

A Semi-Automated Workflow Solution for Data Set Publication

In order to address the need for published data, considerable effort has gone into formalizing the process of data publication. From funding agencies to publishers, data publication has rapidly become a requirement. Digital Object Identifiers (DOI) and data citations have enhanced the integration and availability of data. The challenge facing data publishers now is to deal with the increased number of publishable data products and most importantly the difficulties of publishing diverse data products into an online archive. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), a NASA-funded data center, faces these challenges as it deals with data products created by individual investigators. This paper summarizes the challenges of curating data and provides a summary of a workflow solution that ORNL DAAC researcher and technical staffs have created to deal with publication of the diverse data products. Finally, the workflow solution presented here is generic and can be applied to data from any scientific domain and data located at any data center.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

The Dark Energy Survey Data Release I

We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single-epoch images, co-added images, co-added source catalogs, and associated products and services assembled over the first 3 yr of DES science operations. DES DR1 is based on optical/near-infrared imaging from 345 distinct nights (2013 August to 2016 February) by the Dark Energy Camera mounted on the 4 m Blanco telescope at the Cerro Tololo InterAmerican Observatory in Chile. We release data from the DES wide-area survey covering similar to 5000 deg(2) of the southern Galactic cap in five broad photometric bands, grizY. DES DR1 has a median delivered point-spread function of g = 1.12, r = 0.96, i = 0.88, z = 0.84, and Y = 0.'' 90 FWHM, a photometric precision of <1% in all bands, and an astrometric precision of 151 mas. The median co-added catalog depth for a 1.'' 95 diameter aperture at signal-to-noise ratio (S/N) = 10 is g = 24.33, r = 24.08, i = 23.44, z = 22.69, and Y = 21.44 mag. DES DR1 includes nearly 400 million distinct astronomical objects detected in similar to 10,000 co-add tiles of size 0.534 deg(2) produced from similar to 39,000 individual exposures. Benchmark galaxy and stellar samples contain similar to 310 million and similar to 80 million objects, respectively, following a basic object quality selection. These data are accessible through a range of interfaces, including query web clients, image cutout servers, jupyter notebooks, and an interactive co-add image visualization tool. DES DR1 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

Abbott, T. M. C.↗
DOE OSTI2024

A modeling pipeline to relate municipal wastewater surveillance and regional public health data

As COVID-19 becomes endemic, public health departments require improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging. We have developed a generalized methodology to improve the predictive power of wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but all model estimates of prevalence significantly improved correlation compared to doing no correction. We also investigate the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We do this in a rolling manner for corrected wastewater data and for other prevalence indicators, and statistically compare the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We find that wastewater trends often lead other COVID-19 indicators in predicting new surges.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Outcome of the First Electron Microscopy Validation Task Force Meeting

This Meeting Review describes the proceedings and conclusions from the inaugural meeting of the Electron Microscopy Validation Task Force organized by the Unified Data Resource for 3DEM (http://www. emdatabank.org) and held at Rutgers University in New Brunswick, NJ on September 28 and 29, 2010. At the workshop, a group of scientists involved in collecting electron microscopy data, using the data to determine three-dimensional electron microscopy (3DEM) density maps, and building molecular models into the maps explored how to assess maps, models, and other data that are deposited into the Electron Microscopy Data Bank and Protein Data Bank public data archives. The specific recommendations resulting from the workshop aim to increase the impact of 3DEM in biology and medicine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Use of Cultivation Data from the Algae Testbed Public Private Partnership as Utilized in NREL's Algae State of Technology Assessments

The Algae Testbed Public Private Partnership (ATP3) conducted algal growth experiments over the course of 16 months termed the Unified Field Studies (UFS). These experiments were conducted at 5 different geographic locations in Arizona (ASU), California (CP), Florida (FA), Georgia (GT), and Hawaii (CELL). The UFS sought to evaluate different algal biomass harvesting strategies using identical ponds, media, and operational conditions through all four seasons across different geographic regions to isolate the effects on productivity attributed to locational climate and seasonal variability, overlaid by the differing harvest strategies. Set up as the baseline against which other experiments would build upon, it must be emphasized that as per the stated, approved experimental goals of the ATP3 UFS, no attempts at growth or lipid accumulation optimization were made; rather, the primary focus of the UFS work was to cultivate algal biomass under deliberate, consistent conditions, time periods, and harvesting protocols, to provide public data on year-round outdoor biomass production that could be directly compared between one site and another (with accompanying climate data for each site). Thus the resulting productivity numbers in effect represent a conservative baseline of non-optimized algal growth one may expect at these sites. Also clearly weather can vary dramatically from season to season and from year to year, and even within a given 'season' where an individual season's data was typically based on 4-6 week operating windows. Thus these numbers also only reflect a short snapshot in time, and must be interpreted carefully in projecting what may be expected over many years or decades (for example, a 30-year facility lifetime as evaluated in techno-economic models).

09 BIOMASS FUELS↗
NASA NTRS2001

Integrated Propulsion Data System Public Web Site

The Integrated Propulsion Data System's (IPDS) focus is to provide technologically-advanced philosophies of doing business at SSC that will enhance the existing operations, engineering and management strategies and provide insight and metrics to assess their daily impacts, especially as related to the Propulsion Test Directorate testing scenarios for the 21st Century.

Hamilton, Kimberly↗
DOE OSTI2017

Jet substructure studies with CMS open data

We utilize public data from the CMS experiment to study the two-prong substructure of jets. The CMS open data are based on 31.8 pb -1 of 7 TeV proton-proton collisions recorded at the Large Hadron Collider in 2010, yielding a sample of 768,687 events containing a high-quality central jet with transverse momentum larger than 85 GeV. Using CMS’s particle flow reconstruction algorithm to obtain jet constituents, we extract the two-prong substructure of the leading jet using soft-drop declustering. We find good agreement between results obtained from the CMS open data and those obtained from parton shower generators, and we also compare to analytic jet substructure calculations performed to modified leading-logarithmic accuracy. Even though the 2010 CMS open data do not include simulated data to help estimate systematic uncertainties, we use track-only observables to validate these substructure studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗