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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
NASA NTRS1973

Pressure loads and aerodynamic force information for the -89A space shuttle orbiter configuration, volume 2

Experimental aerodynamic investigations were conducted in a low speed wind tunnel on an 0.0405 scale representation of the 89A light weight Space Shuttle Orbiter to obtain pressure loads data in the presence of the ground for orbiter structural strength analysis. The model and the facility are described, and data reduction is outlined. Tables are included for data set/run number collation, data set/component collation, model component description, and pressure tap locations by series number. Tabulated force and pressure source data are presented.

Mennell, R. C.↗
NASA NTRS1976

Shear layer structure of a low speed jet

A series of measurements of near field pressures and turbulent velocity fluctuations were made in a low speed jet with a Reynolds number near 50,000 in order to investigate more quantitatively the character and behavior of the large scale structures and their interactions with each other. The near field measurements were modelled according to the vortex pairing hypothesis to deduce the distribution of pairings along the jet axis and the variances about the mean locations. The hodograph plane description of turbulence was explored in some detail, and a complex correlation quantity was synthesized which has useful properties for turbulence in the presence of mean shear.

Petersen, R. A.↗
NASA NTRS1993

State-of-the-art satellite laser range modeling for geodetic and oceanographic applications

Significant improvements have been made in the modeling and accuracy of Satellite Laser Range (SLR) data since the launch of LAGEOS in 1976. Some of these include: improved models of the static geopotential, solid-Earth and ocean tides, more advanced atmospheric drag models, and the adoption of the J2000 reference system with improved nutation and precession. Site positioning using SLR systems currently yield approximately 2 cm static and 5 mm/y kinematic descriptions of the geocentric location of these sites. Incorporation of a large set of observations from advanced Satellite Laser Ranging (SLR) tracking systems have directly made major contributions to the gravitational fields and in advancing the state-of-the-art in precision orbit determination. SLR is the baseline tracking system for the altimeter bearing TOPEX/Poseidon and ERS-1 satellites and thus, will play an important role in providing the Conventional Terrestrial Reference Frame for instantaneously locating the geocentric position of the ocean surface over time, in providing an unchanging range standard for altimeter range calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. Nevertheless, despite the unprecedented improvements in the accuracy of the models used to support orbit reduction of laser observations, there still remain systematic unmodeled effects which limit the full exploitation of modern SLR data.

Klosko, Steve M.↗
NASA NTRS1994

Automatic procedures for computing complete configuration geometry from individual component descriptions

Procedures are derived for developing a complete airplane surface geometry starting from component descriptions. The procedures involve locating the intersection lines of adjacent components and omitting any regions for which part of one surface lies within the other. The geometry files utilize the wave-drag (Harris) format, and output files are written in Hess format. Two algorithms are used: one, if both intersecting surfaces have airfoil cross sections; the other, if one of the surfaces has circular cross sections. Some sample results in graphical form are included.

Barger, Raymond L.↗
NASA NTRS1995

Determination of tire cross-sectional geometric characteristics from a digitally scanned image

A semi-automated procedure is described for the accurate determination of geometrical characteristics using a scanned image of the tire cross-section. The procedure can be useful for cases when CAD drawings are not available or when a description of the actual cured tire is desired. Curves representing the perimeter of the tire cross-section are determined by an edge tracing scheme, and the plyline and cord-end positions are determined by locations of color intensities. The procedure provides an accurate description of the perimeter of the tire cross-section and the locations of plylines and cord-ends. The position, normals, and curvatures of the cross-sectional surface are included in this description. The locations of the plylines provide the necessary information for determining the ply thicknesses and relative position to a reference surface. Finally, the locations of the cord-ends provide a means to calculate the cord-ends per inch (epi). Menu driven software has been developed to facilitate the procedure using the commercial code, PV-Wave by Visual Numerics, Inc., to display the images. From a single user interface, separate modules are executed for image enhancement, curve fitting the edge trace of the cross-sectional perimeter, and determining the plyline and cord-end locations. The code can run on SUN or SGI workstations and requires the use of a mouse to specify options or identify items on the scanned image.

Danielson, Kent T.↗
NASA NTRS1973

Compendium of meteorological satellites and instrumentation

Pertinent information is presented for 98 launched and planned satellites of the U.S., U.K., U.S.S.R., and France, as well as their over 200 meteorological experiments or instruments. Summary information is provided for both operational and research satellites. Three major sections include: (1) an overview by country, of the various series of meteorological satellite programs; (2) brief descriptions of the satellites and their experiments; and (3) an extensive bibliography. A glossary of acronyms and two indexes for cross-referencing are also included. In addition, various tables and figures presenting satellite operating times, data coverage, location of launch sites, and descriptions of the launch vehicles used to orbit the meteorological satellites are given.

Stoldt, N. W.↗
NASA NTRS2003

Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description of the local convective spectrum which retains vertical structure information. A further cluster analysis of these 'mixes' can identify recurrent convective spectra. These are a first step towards objective identification of convective regimes, and towards answering the question: 'What are the most convectively similar locations in the world?'

Boccippio, Dennis J.↗
DOE OSTI2025

Redox potential in Typha-dominated tidal brackish marsh, PIE LTER, Plum Island Sound, MA, June–December 2022

This dataset includes soil redox potential measurements collected at multiple depths within a tidal brackish wetland in the upper estuary of the Plum Island Ecosystems Long-Term Ecological Research site (PIE LTER), Plum Island Sound, Newbury, Massachusetts. Measurements were taken to evaluate temporal variation in redox potential in relation to hydrological events at three replicate locations. Data were recorded every 5 minutes using a Campbell Scientific Volt116 connected to a CR6 datalogger with SWAP instrument redox probes (ORP-30-4-B) and reference electrodes. Measurements were made at the AmeriFlux site US-PLo at four soil depths (5, 10, 15, and 30 cm). The file redox_soiltemp_2022.csv contains temperature-corrected redox values and soil temperature following Silva-Machado et al. (2024). Metadata files redox_soiltemp_dd.csv and redox_soiltemp_flmd.csv provide detailed descriptions of variables and site locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Redox potential in Typha-dominated tidal brackish marsh, PIE LTER, Plum Island Sound, MA, 2023

This dataset includes soil redox potential measurements collected at multiple depths within a tidal brackish wetland in the upper estuary of the Plum Island Ecosystems Long-Term Ecological Research site (PIE LTER), Plum Island Sound, Newbury, Massachusetts (MA). Measurements were taken to evaluate temporal variation in redox potential in relation to hydrological events at three replicate locations. Data were recorded every 5 minutes using a Campbell Scientific Volt116 connected to a CR6 datalogger with SWAP instrument redox probes (ORP-30-4-B) and reference electrodes. Measurements were made at the AmeriFlux site US-PLo at four soil depths (5, 10, 15, and 30 cm). The file redox_soiltemp_2023.csv contains temperature-corrected redox values and soil temperature following Silva-Machado et al. (2024). Metadata files redox_soiltemp_dd.csv and redox_soiltemp_2023_flmd.csv provide detailed descriptions of variables and site locations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

The Virtual Tablet: Virtual Reality as a Control System

In the field of human-computer interaction, Augmented Reality (AR) and Virtual Reality (VR) have been rapidly growing areas of interest and concerted development effort thanks to both private and public research. At NASA, a number of groups have explored the possibilities afforded by AR and VR technology, among which is the IT Advanced Concepts Lab (ITACL). Within ITACL, the AVR (Augmented/Virtual Reality) Lab focuses on VR technology specifically for its use in command and control. Previous work in the AVR lab includes the Natural User Interface (NUI) project and the Virtual Control Panel (VCP) project, which created virtual three-dimensional interfaces that users could interact with while wearing a VR headset thanks to body- and hand-tracking technology. The Virtual Tablet (VT) project attempts to improve on these previous efforts by incorporating a physical surrogate which is mirrored in the virtual environment, mitigating issues with difficulty of visually determining the interface location and lack of tactile feedback discovered in the development of previous efforts. The physical surrogate takes the form of a handheld sheet of acrylic glass with several infrared-range reflective markers and a sensor package attached. Using the sensor package to track orientation and a motion-capture system to track the marker positions, a model of the surrogate is placed in the virtual environment at a position which corresponds with the real-world location relative to the user's VR Head Mounted Display (HMD). A set of control mechanisms is then projected onto the surface of the surrogate such that to the user, immersed in VR, the control interface appears to be attached to the object they are holding. The VT project was taken from an early stage where the sensor package, motion-capture system, and physical surrogate had been constructed or tested individually but not yet combined or incorporated into the virtual environment. My contribution was to combine the pieces of hardware, write software to incorporate each piece of position or orientation data into a coherent description of the object's location in space, place the virtual analogue accordingly, and project the control interface onto it, resulting in a functioning object which has both a physical and a virtual presence. Additionally, the virtual environment was enhanced with two live video feeds from cameras mounted on the robotic device being used as an example target of the virtual interface. The working VT allows users to naturally interact with a control interface with little to no training and without the issues found in previous efforts.

virtual control interface↗
NASA NTRS1996

Leaf Area Influence on Surface Layer in a Deciduous Forest: Site Description - Part I

A study over a deciduous forest located in middle Massachusetts (USA) has been performed to examine the role of leaves in the forest-atmosphere interaction. Due to the seasonal presence of leaves, a deciduous forest is a 'good laboratory' to study this interaction. In this first part, a description of a 30 m micrometeorological tower as well a qualitative description of some meteorological parameters are presented. The presence of leaves affects the forest in several ways. There is a decrease of upward PAR (Photosynthetically Active Radiation) due to absorption of visible light in the canopy. Water vapor concentration increases, and the CO2 concentration decreases in the surface layer as the canopy starts to be foliated. The physical presence of the leaves is felt in other quantities such as the global albedo and the subcanopy environment.

Sakai, Ricardo K.↗
DOE OSTI2023

El valor de los metadatos para las estaciones de recuperación de recursos del agua

Spanish: Los metadatos hacen referencia a información descriptiva (como ubicación del sensor, unidad de medida, rango de medida, fecha de calibración, fecha de limpieza, si ocurrió algún evento como episodio de lluvia/fallo operativo/vertido tóxico . . .) que es esencial para convertir los grandes volúmenes de datos que se recogen actualmente en las instalaciones de tratamiento de agua y que están sin procesar en información y recursos útiles. Con el avance de la digitalización en el sector del agua, es fundamental evitar los cementerios de datos y, por otro lado, utilizar los datos almacenados para resolver problemas actuales y futuros. Este artículo se centra en el papel crucial que tienen los metadatos para responder a desafíos futuros y posiblemente impredecibles. El objetivo de este documento es presentar el ‘reto de los metadatos’ y destacar la necesidad de tener en cuenta los metadatos cuando se recoge información como parte de las buenas prácticas de digitalización. English: Metadata refers to descriptive information (such as sensor location, measurement unit, measurement range, calibration date, cleaning date, if any event occurred such as rain event/operating failure/toxic spill, . . .) essential to convert large volumes of raw data that are currently collected at water treatment facilities into useful information and resources. With the advance of digitalization in the water sector, it is fundamental to avoid data graveyards and, on the other hand, using collected data to address current and future problems. This paper focuses on the crucial role that metadata has in responding to future and possibly unpredictable challenges. The aim of this document is to present the ‘metadata challenge’ and to highlight the need to consider metadata when collecting information as part of good digitalization practices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

AmeriFlux US-SRS Santa Rita Experimental Range Mesquite Savanna

This is the AmeriFlux version of the carbon flux data for the site US-SRS Santa Rita Experimental Range Mesquite Savanna. Site Description - The study site is located in the Santa Rita Experimental Range, approximately 45 km south of Tucson, Arizona, within the Sonoran Desert. The rangeland has undergone a shift from a semiarid grassland to a savanna due to the encroachment of the woody leguminous tree Prosopis velutina Woot., or velvet mesquite. A pair of adjacent watersheds of similar size ( 1.08 ha and 1.10 ha) was established to investigate the effects of mesquite removal on hydrologic processes. In 1974, diesel oil was applied basally to all trees in one watershed, with reapplication as needed and dead tree removal for wood, whereas the other watershed, where the flux tower is located, has continued in the woody plant encroachment process. In 2016, an herbicide process was applied to the area around the EC flux tower.

Vivoni, Enrique R.↗
DOE OSTI2020

AmeriFlux PE-QFR Quistococha Forest Reserve

This is the AmeriFlux version of the carbon flux data for the site PE-QFR Quistococha Forest Reserve. Site Description - The study site is located at Quistococha on the outskirts of Iquitos, Loreto region, Peru. Quistococha is a natural protected forest reserve and an official scientific research area for IIAP. The EC flux tower (45 m tall) is located at 73o 19’ 08.1’’ W; 3o 50’ 03.9’’ S within a pristine palm swamp peatland that is within the reserve. The major vegetation type is Mauritia flexuosa (moriche palm, or aguaje in Spanish, reaching 35 m height).

Roman, Tyler↗
DOE OSTI2021

AmeriFlux CR-Fsc Filadelfia sugar cane cropland

This is the AmeriFlux version of the carbon flux data for the site CR-Fsc Filadelfia sugar cane cropland. Site Description - The research site is located in a sugar cane cropland generally harvested in December. Sugarcane is irrigated(furrow irrigation) sporadically only during the dry season (January-April).Crop height varies from 0m to 4m.

Johnson, Mark↗