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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Marine Corps Base Camp Lejeune MARDIS Database

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.The Defense Coastal/Estuarine Research Program (DCERP) Monitoring and Research Data Information System (MARDIS) database is the long-term repository for all DCERP monitoring and research data. Metadata provide supporting information about monitoring and research data that include, but are not limited to, a description of the location where the data were collected, the field and laboratory methods used to collect and analyze the data, and the spatial extent and temporal frequency of the data collected. In MARDIS, metadata fields have been combined with the actual sampling data fields; therefore, DCERP metadata are not a separate element, table, or document, but instead they are an integral component of each data record.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrated Hourly Meteorological Database of 20 Meteorological Stations (1981-2022) for Watershed Function SFA Hydrological Modeling

This dataset contains (a) a script “R_met_integrated_for_modeling.R”, and (b) associated input CSV files: 3 CSV files per location to create a 5-variable integrated meteorological dataset file (air temperature, precipitation, wind speed, relative humidity, and solar radiation) for 19 meteorological stations and 1 location within Trail Creek from the modeling team within the East River Community Observatory as part of the Watershed Function Scientific Focus Area (SFA). As meteorological forcings varied across the watershed, a high-frequency database is needed to ensure consistency in the data analysis and modeling. We evaluated several data sources, including gridded meteorological products and field data from meteorological stations. We determined that our modeling efforts required multiple data sources to meet all their needs. As output, this dataset contains (c) a single CSV data file (*_1981-2022.csv) for each location (20 CSV output files total) containing hourly time series data for 1981 to 2022 and (d) five PNG files of time series and density plots for each variable per location (100 PNG files). Detailed location metadata is contained within the Integrated_Met_Database_Locations.csv file for each point location included within this dataset, obtained from Varadharajan et al., 2023 doi:10.15485/1660962. This dataset also includes (e) a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and (f) a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. Review the (g) ReadMe_Integrated_Met_Database.pdf file for additional details on the script, methods, and structure of the dataset.The script integrates Northwest Alliance for Computational Science and Engineering’s PRISM gridded data product, National Oceanic and Atmospheric Administration’s NCEP-NCAR Reanalysis 1 gridded data product (through the `RCNEP` R package, Kemp et al., doi:10.32614/CRAN.package.RNCEP), and analytical-based calculations. Further, this script downscales the input data into hourly frequency, which is necessary for the modeling efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Growing field of materials informatics: databases and artificial intelligence

The paradigm of molecular discovery in the chemical and pharmaceutical industry has followed a repetitive succession of screening and synthesis, involving the analysis of individual molecules that were both natural and produced. This ability to generate and screen libraries of compounds has found an echo in solid-state physics with the demand to explore and produce new materials for testing. In response to this demand, a golden age of materials discovery is being developed, with progress on important areas of both basic science and device applications. The confluence of theoretical and simulation methods, together with the availability of computation resources, has established the “materials genome” approach that is used by a growing number of research groups around the world with the goal of innovating on materials through systematic discovery. Here, an overview of this group of methodologies in tackling the ever-increasing complexity of computational materials science simulations is provided. Computational simulation is highlighted as a major component of rational design and synthesis of new materials with targeted properties, describing progress on databases and large data treatment. Tools for new materials discovery, including progress on the deployment of new data repositories, the implementation of high-throughput simulation approaches, and the development of artificial intelligence algorithms, are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A representation-independent electronic charge density database for crystalline materials

In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With increasing utilization of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Water Atlas Features Database

Water availability was mapped across the United States and considers multiple sources of fresh water including fresh surface and groundwater, wastewater and brackish groundwater. This dataset includes cost estimates to access, treat and convey each unique source of water. This submission contains a zip file with the Water Atlas Features Database (as an ArcGIS geodatabase).

Availability↗
DOE OSTI2021

Carbon Ore Resources Database (CORD)

The Carbon Ore Resources Database (CORD) is a working collection of 399 data files associated with carbon ore resources in the United States. The collection includes spatial/non-spatial, filtered, processed, and secondary data files with original data acquisition efforts focused on domestic coal resources. The current version 1.0 is on NETL ArcGIS Enterprise.

Carbon Ore↗
DOE OSTI2015

BAAD: a Biomass And Allometry Database for woody plants

Quantifying the amount of mass or energy invested in plant tissues is of fundamental interest across a range of disciplines, including ecology, forestry, ecosystem science, and climate change science (Niklas, 1994; Chave et al. 2005; Falster et al. 2011). The allocation of net primary production into different plant components is an important process affecting the lifetime of carbon in ecosystems, and resource use and productivity by plants (Cannell & Dewar, 1994; Litton et al. 2007; Poorter et al. 2012). While many studies in have destructively harvested woody plants in the name of science, most of these data have only been made available in the form of summary tables or figures included in publications. Until now, the raw data has resided piecemeal on the hard drives of individual scientists spread around the world. Several studies have gathered together the fitted (allometric) equations for separate datasets (Ter-Mikaelian & Korzukhin, 1997; Jenkins et al. 2003; Zianis et al. 2005; Henry et al. 2013), but none have previously attempted to organize and share the raw individual plant data underpinning these equations on a large scale. Gathered together, such data would represent an important resource for the community, meeting a widely recognised need for rich, open data resources to solve ecological problems (Costello et al. 2013; Fady et al. 2014; Harfoot & Roberts, 2014; Costello et al. 2013). We (D.S. Falster and R.A. Duursma, with the help of D.R. Barneche, R.G. FitzJohn and A. Vårhammar) set out to create such a resource, by asking authors directly whether they would be willing to make their raw data files freely available. The response was overwhelming: nearly everyone we contacted was interested to contribute their raw data. Moreover, we were invited to incorporate another compilation led by M. Ishihara and focussing on Japanese literature. As a result, we present BAAD: a Biomass And Allometry Database for woody plants, comprising data collected in 174 different published and unpublished studies.

Falster, Daniel↗
DOE OSTI2014

Thermodynamic database development: Al-Am-Ga-Pu-U

The goal of this study is about the thermodynamic re-assessment of the Plutonium- Uranium (Pu-U) system as a first step leading to the development of a plutonium-based thermodynamic database (i.e., Pu with Al, Am, Ga, Mo, U…) with resulting phase diagrams and associated thermodynamic data. Indeed, phase stability trends and phase diagrams of multi-component nuclear materials are crucial for predicting properties and performance under normal, hypothetical or even accidental conditions. This work is based on a coupling between ab initio energetics, phenomenological thermodynamics models - based on the CALPHAD (CALculation of PHAse Diagrams) approach - and the use of the Thermo-Calc software, together with experimental data (whenever available). The present report summarizes results obtained (quarter period: 10/07/2013-01/07/2014) under the auspices of an agreement between CEA/DAM and NNSA/DP on cooperation in fundamental science supporting stockpile stewardship (P182).

36 MATERIALS SCIENCE↗
DOE OSTI2014

Review of Graph Databases for Big Data Dynamic Entity Scoring

Modeling data as a graph enables users to quickly analyze networked phenomenon, such as social network-based marketing data (e.g., linking entities in social media based on their friends and their "likes", their friend-of-a-friend's "likes", etc.) and scientific data, such as in biology to assess a gene's proximity in a graph to particular disease phenotype. Numerous purpose-built graph databases (DBs) called “NoSQL” or “Not Only SQL” DBs are emerging to support this type of graph analysis. These DBs differ from traditional relational DBs in that they are optimized to improve storage and query performance across large, complex graphs. This document reviews the state of the art in graph DBs and identifies potential DBs that show promise for dynamic entity-scoring algorithms. Dynamic entity scoring is a new area of research that allows analysis of data within graphs using undirected methods to weigh the edges of the graph based on the proximity or ambient influence of near-by nodes. The EntityScore (eScore) methodology developed at Lawrence Livermore National Laboratory (LLNL) is one application of these emerging graph-analysis algorithms to help analysts identify and prioritize entities, based on complex, analyst-defined weighting criteria. Our review examines a wide range of different, well-known graph DBs in use since at least 2010 and identifies unique advantages and disadvantages that may impact eScore-specific requirements. Specifically, we review data structures employed, query features employed, load times, query calculation times, memory usage and several other important attributes reported in the literature. We limited our considerations for eScore to Blueprints-compliant graph DBs (https://github.com/tinkerpop/blueprints/) because they provide a standard, java application programming interface (API) based on the property graph model.

42 ENGINEERING↗
DOE OSTI2014

Summary Report of the Workshop on The Experimental Nuclear Reaction Data Database

The Workshop on the Experimental Nuclear Reaction Data Database (EXFOR) was held at IAEA Headquarters in Vienna from 6 to 10 October 2014. The workshop was organized to discuss various aspects of the EXFOR compilation process including compilation rules, different techniques for nuclear reaction data measurements, software developments, etc. A summary of the presentations and discussions that took place during the workshop is reported here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Analysis of a global database containing tritium in precipitation

The International Atomic Energy Agency (IAEA) directed the collection of tritium in water samples from the mid-1950s to 2009. The Global Network of Isotopes in Precipitation (GNIP) data examined the airborne movement of isotope releases to the environment, with an objective of collecting spatial data on the isotope content of precipitation across the globe. The initial motivation was to monitor atmospheric thermonuclear test fallout through tritium, deuterium, and oxygen isotope concentrations, but after the 1970s the focus changed to being an observation network of stable hydrogen and oxygen isotope data for hydrologic studies. The GNIP database provides a wealth of tritium data collections over a long period of time. The work performed here primarily examined data features in the past 30 years (after much of the effects of above-ground nuclear testing in the late 1950s to early 1960s decayed away), revealing potentially unknown tritium sources. The available data at GNIP were reorganized to allow for evaluation of trends in the data both temporally and spatially. Several interesting cases were revealed, including relatively high measured concentrations in the Atlantic and Indian Oceans, Russia, Norway, as well as an increase in background concentration at a collector in South Korea after 2004. Recent data from stations in the southeastern United States nearest to the Savannah River Site do not indicate any high values. Meteorological impacts have not been considered in this study. Further research to assess the likely source location of interesting cases using transport simulations and/or literature searches is warranted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

High Fluency Low Flux Embrittlement Models of LWR Reactor Pressure Vessel Embrittlement and a Supporting Database from the UCSB ATR-2 Irradiation Experiment

Reactor pressure vessel embrittlement may limit the lifetime of light water reactors (LWR). Embrittlement is primarily caused by formation of nano-scale precipitates, which cause hardening and a subsequent increase in the ductile-to-brittle transition temperature of the steel. While the effect of Cu has historically been the largest research focus of RPV embrittlement, there is increasing evidence that Mn, Ni and Si are likely to have a large effect at higher fluence, where Mn-Ni-Si precipitates can form, even in the absence of Cu. Therefore, extending RPV lifetimes will require a thorough understanding of both precipitation and embrittlement at higher fluences than have ever been observed in a power reactor. To address this issue, test reactors that irradiate materials at higher neutron fluxes than power reactors are used. These experiments at high neutron flux can reach extended life neutron fluences in only months or several years. The drawback of these test irradiations is that they add additional complexity to interpreting the data, as the irradiation flux also plays a role into both precipitate formation and irradiation hardening and embrittlement. This report focuses on developing a database of both microstructure and mechanical property data to better understand the effect of flux. In addition, a previously developed model that enables the comparison of data taken over a range of neutron flux is discussed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

A Global Survey of Deep Underground Facilities; Examples of Geotechnical and Engineering Capabilities, Achievements, Challenges (Mines, Shafts, Tunnels, Boreholes, Sites and Underground Facilities for Nuclear Waste and Physics R&D): A Guide to Interactive Global Map Layers, Table Database, References and Notes

These associated tables, references, notes, and report present a synthesis of some notable geotechnical and engineering information used to create four interactive layer maps for selected: 1) deep mines and shafts; 2) existing, considered or planned radioactive waste management deep underground studies or disposal facilities 3) deep large diameter boreholes, and 4) physics underground laboratories and facilities from around the world. These data are intended to facilitate user access to basic information and references regarding “deep underground” facilities, history, activities, and plans. In general, the interactive maps and database provide each facility’s approximate site location, geology, and engineered features (e.g.: access, geometry, depth, diameter, year of operations, groundwater, lithology, host unit name and age, basin; operator, management organization, geographic data, nearby cultural features, other). Although the survey is not comprehensive, it is representative of many of the significant existing and historical underground facilities discussed in the literature addressing radioactive waste management and deep mined geologic disposal safety systems. The global survey is intended to support and to inform: 1) interested parties and decision makers; 2) radioactive waste disposal and siting option evaluations, and 3) safety case development applicable to any mined geologic disposal facility as a demonstration of historical and current engineering and geotechnical capabilities available for use in deep underground facility siting, planning, construction, operations and monitoring.

58 GEOSCIENCES↗
DOE OSTI2015

Analysis of Global Horizontal Irradiance in Version 3 of the National Solar Radiation Database

We report an analysis that compares global horizontal irradiance (GHI) estimates from version 3 of the National Solar Radiation Database (NSRDB v3) with surface measurements of GHI at a wide variety of locations over the period spanning from 2005 to 2012. The NSRDB v3 estimate of GHI are derived from the Physical Solar Model (PSM) which employs physics-based models to estimate GHI from measurements of reflected visible and infrared irradiance collected by Geostationary Operational Environment Satellites (GOES) and several other data sources. Because the ground measurements themselves are uncertain our analysis does not establish the absolute accuracy for PSM GHI. However by examining the comparison for trends and for consistency across a large number of sites, we may establish a level of confidence in PSM GHI and identify conditions which indicate opportunities to improve PSM. We focus our evaluation on annual and monthly insolation because these quantities directly relate to prediction of energy production from solar power systems. We find that generally, PSM GHI exhibits a bias towards overestimating insolation, on the order of 5% when all sky conditions are considered, and somewhat less (-3%) when only clear sky conditions are considered. The biases persist across multiple years and are evident at many locations. In our opinion the bias originates with PSM and we view as less credible that the bias stems from calibration drift or soiling of ground instruments. We observe that PSM GHI may significantly underestimate monthly insolation in locations subject to broad snow cover. We found examples of days where PSM GHI apparently misidentified snow cover as clouds, resulting in significant underestimates of GHI during these days and hence leading to substantial understatement of monthly insolation. Analysis of PSM GHI in adjacent pixels shows that the level of agreement between PSM GHI and ground data can vary substantially over distances on the order of 2 km. We conclude that the variance most likely originates from dramatic contrasts in the ground's appearance over these distances.

14 SOLAR ENERGY↗
DOE OSTI2018

SP-1 results for UOC Database Project, 2018

Project personnel at Los Alamos National Laboratory provided analysis support for an IAEA SP-1 task proposal aimed at analysis of materials sampled at various points during the Uranium ore refinement. This effort was proposed as a part of FY18 Uranium Ore Concentrate Sourcing Database project activities. Samples related to this effort are categorized as a set of solid samples and a set of liquid samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

User Guide for the Public Industrial CO 2 Capture Retrofit Database Models

The United States (U.S.) Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has produced three carbon capture retrofit databases (CCRDs), which contain a collection of units selected from the power generation and industrial sources (IND) sectors located in the United States that are either in operating or standby status. The power generation category is subdivided into the post-combustion (PC) CCRD – containing coal-fired and atmospheric fluidized bed (AFB) units – and the natural gas combined cycle (NGCC) CCRD – containing natural gas-fired combined cycle and combined cycle single shaft units. The IND CCRD contains facilities from the ammonia, cement, ethanol, hydrogen, and natural gas processing industries. This report is intended to provide a general guide to the IND CCRD. Efforts have been made to ensure similarities between each of the CCRDs. However, as the sources of CO2 vary, differences will exist – most notably in the IND CCRD.

03 NATURAL GAS↗