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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

LON 94101 Provides a Unique Record of C-Class Asteroid Regolith Diversity

LON 94101 and its pairing mate LON 94102 are two of the largest CM finds, with a collective mass of 3.8kg.Over the years we noticed that every section of these meteorites appeared significantly different. These stones are highly brecciated and display an unprecedented range of CM lithologies [1-3, and numerous other papers]. They thus record direct information regarding the physical and petrologic characteristics of the CM parent asteroid(s) at the greatest scale observable from meteorites. Still unanswered questions are what the typical clast size was for each lithology, and what the full range of CM textures in LON 94101 could be. We were also interested in learning whether there were xenoliths in these breccias, these being apparently unknown for CM chondrites. Detailed characterization of an especially large sample is required to address these issues. This abstract reports results of the initial characterization of one large sample of LON 94101.

Michael Zolensky↗
NASA NTRS2011

STS-130 Launch-on-Need (LON) Assessment

A viewgraph presentation covering an STS-130 Launch on Need assessment is shown. The contents include: 1) LON Status GREEN II STS-132 is processing as the LON for STS-131; 2) TSM Bonnet Closure Timing; 3) LC-39A High Pressure Gas Storage Facility (HPGF) Net Damage; and 4) STS-130 Ice Detection Camera FOD concern.

Jezierski, Eduardo↗
NASA NTRS2011

Xenoliths in the CM2 Carbonaceous Chondrite LON 94101: Implications for Complex Mixing on the Asteroidal Parent Body

Xenoliths are foreign clasts that oc-cur in various classes of meteorites, e.g. [1,2,3]. A re-cent study reveals the presence of several distinct classes of xenoliths in regolith-bearing meteorites, in-cluding in over 20 different carbonaceous chondrites [4]. The most common types of xenoliths are fine-grained hydrous clasts, often referred to as C1 or CI clasts in the literature, although their mineralogy is actually more similar to hydrous micrometeorites [5,6]. Xenoliths in meteorites present an opportunity to study material not yet classified or available as separate meteorites, and can provide additional information on processes in the dynamic early history of the Solar Sys-tem. Here we have performed chemical and mineralogi-cal analyses of xenoliths in the CM2 carbonaceous chondrite LON 94101, using scanning electron micro-scopy (SEM) and transmission electron microscopy (TEM).

Lindgren, P.↗
NASA NTRS2002

Photoionization of the Fe lons: Structure of the K-Edge

X-ray absorption and emission features arising from the inner-shell transitions in iron are of practical importance in astrophysics due to the Fe cosmic abundance and to the absence of traits from other elements in the nearby spectrum. As a result, the strengths and energies of such features can constrain the ionization stage, elemental abundance, and column density of the gas in the vicinity of the exotic cosmic objects, e.g. active galactic nuclei (AGN) and galactic black hole candidates. Although the observational technology in X-ray astronomy is still evolving and currently lacks high spectroscopic resolution, the astrophysical models have been based on atomic calculations that predict a sudden and high step-like increase of the cross section at the K-shell threshold (see for instance. New Breit-Pauli R-matrix calculations of the photoionization cross section of the ground states of Fe XVII in the region near the K threshold are presented. They strongly support the view that the previously assumed sharp edge behaviour is not correct. The latter has been caused by the neglect of spectator Auger channels in the decay of the resonances converging to the K threshold. These decay channels include the dominant KLL channels and give rise to constant widths (independent of n). As a consequence, these series display damped Lorentzian components that rapidly blend to impose continuity at threshold, thus reformatting the previously held picture of the edge. Apparent broadened iron edges detected in the spectra of AGN and galactic black hole candidates seem to indicate that these quantum effects may be at least partially responsible for the observed broadening.

Palmeri, P.↗
NASA NTRSDate not supplied

Lithological Diversity of a C-Complex Asteroid Recorded in LON 94101

CMs are the most common carbonaceous chondrite type, providing a wealth of information about the formation and aqueous alteration of primitive asteroids. Owing to their brecciated nature and possible rubble pile heritage, CMs host many lithologies. Indeed, recent results from Hayabusa2 and OSIRIS-REx have revealed a plethora of boulder types on the surface of C-complex asteroids, from which most carbonaceous chondrites are likely derived, attesting to the complex history individual asteroids have experienced. Deciphering the relationships between lithologies, particularly when drawing upon multiple meteorites remains challenging, as C-complex asteroids are very common, and multiple asteroids could be providing similar materials.

R Findlay↗
NASA NTRSDate not supplied

Future Lunar Geophysical Mission Opportunities Including the Lunar Geophysical Network and CLPS

In the next few years, several opportunities are underway to take new geophysical observations of the Moon including geodetic and seismic. NASA’s novel Commercial Lunar Payload Services (CLPS) program seeks to acquire delivery services from 14 US companies. Nine funded task orders have been selected with payloads from multiple disciplines. Here we review the upcoming geophysical CLPS payloads and their measurement objectives then we provide a review of the Lunar Geophysical Network mission in development for New Frontiers 5. The Lunar Geophysical Network (LGN) mission is proposed to land on the Moon in the early 2030’s and deploy packages at four locations to enable continuous geophysical measurements for a minimum of 6 and a goal of 10 years. Returning to the lunar surface with a long-lived geophysical network is a key next step to advance lunar and planetary science. LGN will greatly expand our primarily Apollo-based knowledge of the deep lunar interior by identifying and characterizing mantle melt layers, as well as core size and state. To meet the mission objectives, the instrument suite provides complementary seismic, geodetic, heat flow, and electromagnetic (EM) observations. We discuss the network landing site requirements and provide example sites that meet these requirements. Landing sites include the P-5 region within the Procellarum KREEP Terrane (PKT; (lat:15˚; lon:-35˚), Schickard basin (lat:-44.3˚; lon:-55.1˚), Crisium basin (lat:18.5˚; lon:61.8˚), and the farside Korolev basin (lat:-2.4˚; lon:-159.3˚) (Figure 1). Network optimization considers the best locations to observe seismic core phases, e.g., ScS and PKP. Ray path density and proximity to young fault scarps are also analyzed to provide increased opportunities for seismic observations. Geodetic constraints from laser ranging require the LGN to have at least three nearside stations at maximum limb distances. Heat flow and EM measurements should be obtained away from terrane boundaries and from magnetic anomalies at locations representative of global trends. In our recent paper, an in-depth case study is provided for Mare Crisium. We also discuss the consequences for scientific return of less-than-optimal locations or number of stations.

Moons↗
NASA NTRSDate not supplied

Future Lunar Geophysical Mission Opportunities Including the Lunar Geophysical Network, Artemis and CLPS

In the next few years, several opportunities are underway to take new geophysical observations of the Moon including geodetic and seismic. NASA’s novel Commercial Lunar Payload Services (CLPS) program seeks to acquire delivery services from 14 US companies. Nine funded task orders have been selected with payloads from multiple disciplines. Here we review the upcoming geophysical CLPS payloads and their measurement objectives then we provide a review of the Lunar Geophysical Network mission in development for New Frontiers 5. The Lunar Geophysical Network (LGN) mission is proposed to land on the Moon in the early 2030’s and deploy packages at four locations to enable continuous geophysical measurements for a minimum of 6 and a goal of 10 years. Returning to the lunar surface with a long-lived geophysical network is a key next step to advance lunar and planetary science. LGN will greatly expand our primarily Apollo-based knowledge of the deep lunar interior by identifying and characterizing mantle melt layers, as well as core size and state. To meet the mission objectives, the instrument suite provides complementary seismic, geodetic, heat flow, and electromagnetic (EM) observations. We discuss the network landing site requirements and provide example sites that meet these requirements. Landing sites include the P-5 region within the Procellarum KREEP Terrane (PKT; (lat:15˚; lon:-35˚), Schickard basin (lat:-44.3˚; lon:-55.1˚), Crisium basin (lat:18.5˚; lon:61.8˚), and the farside Korolev basin (lat:-2.4˚; lon:-159.3˚) (Figure 1). Network optimization considers the best locations to observe seismic core phases, e.g., ScS and PKP. Ray path density and proximity to young fault scarps are also analyzed to provide increased opportunities for seismic observations. Geodetic constraints from laser ranging require the LGN to have at least three nearside stations at maximum limb distances. Heat flow and EM measurements should be obtained away from terrane boundaries and from magnetic anomalies at locations representative of global trends. In our recent paper, an in-depth case study is provided for Mare Crisium. We also discuss the consequences for scientific return of less-than-optimal locations or number of stations.

Moons↗
NASA NTRS1984

Observing system simulation experiments related to space-borne Lidar wind profiling. Part 1: Forecast impacts of highly idealized observing systems

Simulation experiments comparing the relative importance of an idealized LIDAR wind profiling system with idealized temperature and pressure sounding systems on 12 h forecasts are studied for three "nature' fields representing the true evolving atmospheric states. The three fields are obtained respectively from: (1) a long integration of the GLAS 4th Order Model (4 deg lat x 5 deg lon x 9 levels), (2) a continuous sequence of NMC operational analysis and, (3) a long integration of the ECMWF high resolution (1.875 deg 1 lat x 1.875 deg lon x 15 layers) operational forecast model. These fields are interpolated to the grid of the GLAS model and used for simulating the observed global analysed fields of winds, temperature, moisture and surface pressure. The same interpolated fields are also used for verification of forecast impact. The effects of clouds, aerosol concentrations, and instrument accuracies on the simulated observation will be discussed.

Halem, M.↗
NASA NTRS1999

Parallel Grid Manipulations in Earth Science Calculations

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center is moving its data assimilation system to massively parallel computing platforms. This parallel implementation of GEOS DAS will be used in the DAO's normal activities, which include reanalysis of data, and operational support for flight missions. Key components of GEOS DAS, including the gridpoint-based general circulation model and a data analysis system, are currently being parallelized. The parallelization of GEOS DAS is also one of the HPCC Grand Challenge Projects. The GEOS-DAS software employs several distinct grids. Some examples are: an observation grid- an unstructured grid of points at which observed or measured physical quantities from instruments or satellites are associated- a highly-structured latitude-longitude grid of points spanning the earth at given latitude-longitude coordinates at which prognostic quantities are determined, and a computational lat-lon grid in which the pole has been moved to a different location to avoid computational instabilities. Each of these grids has a different structure and number of constituent points. In spite of that, there are numerous interactions between the grids, e.g., values on one grid must be interpolated to another, or, in other cases, grids need to be redistributed on the underlying parallel platform. The DAO has designed a parallel integrated library for grid manipulations (PILGRIM) to support the needed grid interactions with maximum efficiency. It offers a flexible interface to generate new grids, define transformations between grids and apply them. Basic communication is currently MPI, however the interfaces defined here could conceivably be implemented with other message-passing libraries, e.g., Cray SHMEM, or with shared-memory constructs. The library is written in Fortran 90. First performance results indicate that even difficult problems, such as above-mentioned pole rotation- a sparse interpolation with little data locality between the physical lat-lon grid and a pole rotated computational grid- can be solved efficiently and at the GFlop/s rates needed to solve tomorrow's high resolution earth science models. In the subsequent presentation we will discuss the design and implementation of PILGRIM as well as a number of the problems it is required to solve. Some conclusions will be drawn about the potential performance of the overall earth science models on the supercomputer platforms foreseen for these problems.

Sawyer, W.↗
NASA NTRS2010

Hubble Space Telescope Crew Rescue Analysis

In the aftermath of the 2003 Columbia accident, NASA removed the Hubble Space Telescope (HST) Servicing Mission 4 (SM4) from the Space Shuttle manifest. Reasons cited included concerns that the risk of flying the mission would be too high. The HST SM4 was subsequently reinstated and flown as Space Transportation System (STS)-125 because of improvements in the ascent debris environment, the development of techniques for astronauts to perform on orbit repairs to damaged thermal protection, and the development of a strategy to provide a viable crew rescue capability. However, leading up to the launch of STS-125, the viability of the HST crew rescue capability was a recurring topic. For STS-125, there was a limited amount of time available to perform a crew rescue due to limited consumables (power, oxygen, etc.) available on the Orbiter. The success of crew rescue depended upon several factors, including when a problem was identified; when and what actions, such as powering down, were begun to conserve consumables; and where the Launch on Need (LON) vehicle was in its ground processing cycle. Crew rescue success also needed to be weighed against preserving the Orbiter s ability to have a landing option in case there was a problem with the LON vehicle. This paper focuses on quantifying the HST mission loss of crew rescue capability using Shuttle historical data and various power down strategies. Results from this effort supported NASA s decision to proceed with STS-125, which was successfully completed on May 24th 2009.

Hamlin, Teri L.↗
NASA NTRS2007

Some algorithms for polygons on a sphere.

A limited search for polygon algorithms for use in a new military training simulation that interfaces with several others produced only planar algorithms. To avoid having to implement several different sophisticated map projections to guarantee compatibility with all the other simulations, we opted to develop algorithms that work directly on a sphere. The first is an algorithm to compute the area of a polygon whose edges are segments of great circles. Since our model represents certain object locations as mathematical points, the second topic is whether a specified point is inside a specified polygon. Possibly pathological cases are identified and eliminated. When we realized that most political boundaries are actually rhumb lines, use of the Mercator projection equations seemed unavoidable. We then reasoned that if all the edges were short enough, lat-lon lines, great circle segments, and rhumb lines would be close enough to being identical that we could use whichever was most convenient. Thence, we looked at the relationship between the maximum distances between great circle segments and rhumb lines and between lat-lon lines and rhumb lines as functions of length, azimuth, and latitude. The final algorithm finds the area overlapped by two polygons. Again, potentially pathological cases are identified and eliminated.

Duquette, William H.↗
NASA NTRSDate not supplied

Anomalous and Ungrouped Carbonaceous Chondrites in the US Antarctic Meteorite Collection and their Potential Relevance to Ryugu and Bennu

With two different carbonaceous asteroid sample return missions in full swing, attention has focused on what connections can be made between the asteroid samples and the wide range of carbonaceous chondrite meteorites in worldwide collections. The US Antarctic meteorite collection contains nearly 1000 carbonaceous chondrites of various types including many in well-established groups as well as ungrouped, unusual or anomalous groups [1]. Some of the latter have been included in, or are possibly related to, recently proposed new carbonaceous chondrite classifications – CA and CY chondrites [2,3]. In addition to these, there are numerous ungrouped samples that have properties intermediate between established groups (like CM and CO; [4]), distinct from any other groups [5], or have anomalous properties that might be attributable to parent body processes such as heating, fluid interaction, or impacts [6]. Some CM anomalous or ungrouped chondrites share spectral features with Ryugu, which has a small hydration peak arguably due to hydrated minerals left after either impact heating or shock in carbonaceous chondrites [7]. PCA 91008, PCA 02012, GRO 95566, and LEW 85311 are all CMs that have experienced heating or metamorphism that may be due to impacts, solar radiation, or radiogenic decay [6]. These samples all have low H contents, C/H (bulk), and low 17O [6,8] and may hold clues to understanding the mineralogy of Ryugu, or interpretations of its spectral properties. WIS 91600, on the other hand, appears to be related to several other highly altered CM [6], and shares properties with the newly proposed CY chondrites [6]. An understanding of this grouplet will also aid in the interpretation of Bennu samples which have strong hydration features. In addition, ungrouped carbonaceous chondrites may provide valuable insights into the aqueous alteration potentially recorded in Bennu and Ryugu samples; such as the relatively moderate aqueous alteration recognized and dated at 4-5 myr after CAIs in MAC 88107 (C2-ungrouped) by [9] to the extensive aqueous alteration apparent in MIL 090292 (C1-ungrouped) [10]. Finally, LON 94101/94102 is a brecciated CM chondrite with numerous lithologies. Its appearance is similar to some of the brecciated lithologies visible at the surface of Bennu and Ryugu [11]. Although CM chondrites with multiple lithologies are common (e.g., [12]), the lithologies are often difficult to resolve at the hand specimen scale and only after some detailed e-beam characterization are the subtle lithologic differences evident (e.g., [13]). LON 94102 contains visibly distinct clasts at the hand specimen scale, relatively rare for CM breccias. The largest CM chondrites by mass from the U.S. Antarctic meteorite collection may provide insights into the extent of brecciation and heterogeneity within more typical CM chondrite-like source asteroids. For example, recent curation CT scans [14] show possible clasts within in a subsplit of ALH 83100 (CM1/2) which is the largest CM chondrite or CM chondrite pairing group in the U.S. Antarctic collection with an original mass of 3.019 kg. Similar work on additional subsplits or meteorites may aid our understanding of heterogeneity within CM chondrites from Antarctica. Initial classification of CM chondrites in U.S. Antarctic meteorite collection includes preliminary pairing when petrographically similar CM chondrites that have been previously found in the same field area. The two largest CM chondrite preliminary pairing groups by mass are the ALH 83102 (CM2) pairing group with an original mass of 2.554 kg and the EET 96005 (CM2) pairing group with an original mass of 1.125 kg. However, preliminary pairing groups assigned at classification—intrinsically— do not include stones that are petrographically distinct. Rigorous pairing group studies of CM chondrites from specific field sites are needed to investigate if there is unrecognized heterogeneity in CM chondrites from Antarctica that may represent common asteroid impactors (pre-atmospheric entry asteroids/meteoroids). Detailed pairing studies have the potential to recognize initial stones with multiple lithologies and investigate if there are stones that only sample one of those respective lithologies in the collection. These groups of heated CMs, extensively hydrated CMs, intermediate between CM and CO chondrites, and brecciated samples are all potentially relevant to Bennu and Ryugu samples, where heating, hydration, and brecciation have all come into play. These bodies might also be comprised of material intermediate to CM and CO chondrites, or at least distinct from the well-established CC groups. These small and unusual groups of carbonaceous chondrites may help to unlock new information about early solar system processes and aid in the understanding of the evolution of these carbonaceous asteroids.

meteorites↗
DOE OSTI2025

Improved Understanding of Multicentury Greenland Ice Sheet Response to Strong Warming in the Coupled CESM2‐CISM2 With Regional Grid Refinement

The simulation of ice sheet‐climate interactions, such as surface mass balance fluxes, is sensitive to model grid resolution. Here we simulate the multi‐century evolution of the Greenland Ice Sheet (GrIS) and its interaction with the climate using the Community Earth System Model version 2.2 (CESM2.2) including an interactive GrIS component (the Community Ice Sheet Model v2.1 [CISM2.1]) under an idealized warming scenario (atmospheric CO 2 increases by 1% yr -1 until quadrupling the pre‐industrial level and then is held fixed). A variable‐resolution (VR) grid with 1/4° regional refinement over the broader Arctic and 1° resolution elsewhere is applied to the atmosphere and land components, and the results are compared with conventional 1° lat‐lon grid simulations to investigate the impact of grid refinement. Compared with the 1° runs, the VR run features a slower rate of surface melt, especially over the western and northern GrIS, where the ice surface slopes gently toward the periphery. This difference pattern originates primarily from higher snow albedo and, thus, weaker albedo feedback in the VR run. The VR grid better captures the CISM ice sheet topography by reducing elevation discrepancies between CAM and CISM and is, therefore, less reliant on the downscaling algorithm, which is known to underestimate albedo gradients. The sea level rise contribution from the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350, approximately 40% and 20% less than that of the 1° runs, respectively.

Earth System Model↗
DOE OSTI2026

Back-to-back dijet production in DIS at arbitrary Bjorken x: TMD gluon distributions to twist-3 accuracy

We derive the gluon transverse-momentum-dependent (TMD) operator structure of back-to-back\\\\r\\\\nquark–antiquark dijet production in deep inelastic scattering at arbitrary Bjorken-x to twist-3 ac\\\\r\\\\ncuracy. Working at leading order in the strong coupling and in the kinematic regime where the\\\\r\\\\ntransverse momentum imbalance of the jets is much smaller than their individual transverse mo\\\\r\\\\nmenta, we perform a systematic gradient expansion of the quark propagator in a background gluon\\\\r\\\\nfield. This expansion organizes multiple interactions with the target in terms of longitudinal Wilson\\\\r\\\\nlines and gauge-invariant field-strength insertions, yielding a TMD description valid beyond the\\\\r\\\\nstrict high-energy eikonal (x → 0) approximation. We obtain explicit cross sections for longitudi\\\\r\\\\nnally and transversely polarized virtual photons, identifying all contributing gluon TMD operators\\\\r\\\\nup to twist-3, including structures involving F+−, Fij, and three-gluon correlators. The full lon\\\\r\\\\ngitudinal phase eixP+z− associated with Bjorken-x is retained throughout. In the small-x limit,\\\\r\\\\nour results reproduce the known sub-eikonal expressions obtained in the Color Glass Condensate\\\\r\\\\nframework, establishing a direct connection between the general-x TMD expansion and high-energy\\\\r\\\\nfactorization. We further reduce the operator basis using equations of motion, minimizing the num\\\\r\\\\nber of independent nonperturbative matrix elements entering the cross section. This work provides\\\\r\\\\na systematic foundation for extending TMD analyses of dijet production beyond leading twist, es\\\\r\\\\ntablishing a unified operator framework valid at arbitrary Bjorken-x that smoothly interpolates\\\\r\\\\nbetween moderate- and small-x descriptions of gluon TMDs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Luteolibacter sp. strain Populi

Luteolibacter sp. strain Populi is bacterium from the phylum Verrucomicrobiota, isolated from the rhizosphere of a black cottonwood tree, Populus trichocarpa, from the Cascade mountains in Washington. Its 6.6 Mb chromosome was completely sequenced using Oxford Nanopore long-reads and is predicted to encode 5301 proteins and 60 RNAs. The bacteria was isolated from the rhizosphere of a mature Populus trichocarpa from the Tieton riverwatershed of Washington state, USA (Lat: 46°42’9” N, Lon: 120°25 39’36” W). A rhizosphere sample (fine roots and adhering soil) was used to obtain a microbial fraction by centrifugation on Histodenz (12) and stained with 5µM Syto59 (Thermo Fisher Scientific Inc). A Cytopeia Influx cell sorter (BD, Franklin Lakes, NJ) was used to sort and array single cells (100 per plate) based on forward-side scatter and fluorescence intensity on asparagine-glucose nutrient agar (ATCC medium 184). The Luteolibacter sp. Populi genome sequence has been deposited in GenBank under the accession number CP161812. A draft genome annotated with Prokka and DRAM is available in this Narrative as Luteolibacter_sp_Prokka.240711.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Characteristics of the IBEX Ribbon and Their Implications for a Source Region Outside the Heliopause

This paper presents a comprehensive exploration of the Interstellar Boundary Explorer energetic neutral atom (ENA) ribbon, focusing on its spatial and temporal variations over 14 yr. Methodological advancements, including a refined map modeling procedure and a new ribbon separation technique with appropriate error propagation, enable a detailed investigation of the ribbon’s features. Utilizing statistically robust metrics, this study reveals details of the ribbon across energy and time. Key findings include energy- and time-dependent variations in flux, angular radius, ribbon profile width, and higher moments. By applying these metrics, we reveal new complexity to the evolution of the ribbon over time, highlighting the nuanced relationship between it and the solar wind. Furthermore, the study examines for the first time the ribbon as it passes through the starboard/heliotail region (Lon EC 120°–180°), revealing properties distinct from other portions of the ribbon. The analysis uncovers an anticorrelation between ribbon width and flux, which provides quantitative support for a multisource ribbon created by a combination of solar wind neutrals that generate a spatiall narrow ribbon component and heliosheath neutrals giving rise to a broad component. Finally, differences in the temporal evolution of the ENA flux at different energies provide additional support that the location of the ribbon source region is beyond the heliopause.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

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. 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↗
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. 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Mongird, Kendall [Pacific Northwest National Labor↗