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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Plastic Parallel Pathways Platform- 4P Model

The U.S. generates 42 million metric tons of plastic waste each year - the most of any country - of which less than 9% is recycled. This represents an estimated loss of $2.3 billion and 3.4 EJ embodied energy per year. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. Various recycling and waste management options are available for plastics, such as conversion into energy (incineration, pyrolysis, gasification), conversion to lower- or higher-grade plastics (mechanical recycling, chemical or enzymatic depolymerization processes, dissolution) or up-cycling to feedstock chemicals (photo/electro/catalytic methods, pyrolysis, gasification). While many previous publications have investigated a subset of these options, there is currently no modelling platform that can quantitatively assess and compare the economic and environmental impacts of all these different plastic management pathways and their respective products simultaneously. To directly compare the benefits and disadvantages of plastic-to-x technologies, we propose a novel analysis framework: the Plastic Parallel Pathways Platform (4P). 4P will model a systems analysis framework for capturing plastic material flows processed via different waste management scenarios. The total economic cost and greenhouse gas emissions (as well as additional economic, energetic, and environmental metrics indicators) of a given scenario will be calculated enabling comparison to other scenarios, thereby informing decisions on plastic recycling pathways.

circular economy↗
DOE OSTI2022

Platinum Group Metal Catalysts: Supply Chain Deep Dive Assessment

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. This report focuses on the supply chain for catalysts, specifically platinum group metal (PGM) catalysts, used for decarbonizing energy technologies. Catalysts are substances that increase the rate, conversion, and selectivity of chemical reactions and are used in a variety of applications such as chemical manufacturing, petroleum refining, and catalytic converters. Catalysts containing PGMs (“PGM catalysts”) are particularly useful in widespread industrial applications, including the production of high-volume chemicals such as ammonia, acetic acid, nitric acid, and the refining of crude oil into petroleum products. The PGM metals possess extraordinary properties such as being active oxidation and hydrogenation catalysts; excellent electrical conductors and electrodes; and outstanding adsorbers of oxygen and hydrogen. Within the energy industrial base, PGM catalysts improve the energy and materials efficiency of petroleum refining and chemical industry processes and reduce energy consumption in manufacturing. In addition to their use in catalytic converters, PGM catalysts are important to maximizing the efficiency of emerging decarbonization technologies, specifically in proton exchange membrane (PEM) electrolyzers for green hydrogen production from water and PEM fuel cells for transportation and stationary energy storage. Green hydrogen is expected to play a significant role in decarbonization scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

GODEEEP-hydro: Historical and projected power system ready hydropower data for the United States

Hydropower is a critical electricity resource in the United States which, in addition to low-cost electricity generation, provides valuable ancillary grid services, and supports the integration of nondispatchable weather-dependent resources (e.g., wind and solar). Despite its value to the grid, there are very few comprehensive datasets available from which to study both historical and future impacts of climate, weather driven energy droughts, and integration of other weather driven generation. In this paper, we present a hydropower generation dataset covering 1,452 hydroelectric plants in the contiguous U.S. The dataset contains monthly and weekly hydropower generation estimates for both historical (1982–2019) and future (2020–2099) periods which includes 4 future climate scenarios. In addition, this dataset provides weekly and monthly constraints such as minimum and maximum power which are particularly useful in power system models which are used to study grid reliability, transmission planning and capacity expansion.

13 HYDRO ENERGY↗
DOE OSTI2026

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗
DOE OSTI2022

Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transiciones a Energia 100% Renovable (PR100): Actualizacion de Progreso de Seis Meses [Slides]

Puerto Rico se ha comprometido a satisfacer sus necesidades de electricidad con un 100% de energia renovable para 2050, junto con el cumplimiento de objetivos intermedios del 40% para 2025, el 60% para 2040, la eliminacion gradual de la generacion a base de carbon para 2028, y una mejora del 30% en la eficiencia energetica para 2040, segun lo establecido en la Ley de Politica Publica Energetica de Puerto Rico (Ley 17). Desde los huracanes Irma y Maria en septiembre de 2017, DOE y sus laboratorios nacionales han proporcionado a las partes interesadas del sistema energetico de Puerto Rico herramientas, adiestramiento y apoyo de modelaje para permitir la planificacion y el funcionamiento de la red electrica con mas resiliencia frente a nuevas interrupciones. El 2 de febrero de 2022, DOE, FEMA y seis laboratorios nacionales lanzaron el Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transicion a la Energia 100% Renovable (PR100), de dos anos de duracion, para llevar a cabo un analisis exhaustivo de las vias impulsadas por las partes interesadas para el futuro energetico de Puerto Rico. El analisis energetico, solido y objetivo, comprende cinco actividades, con enfasis en la confiabilidad del sistema electrico, la resiliencia y la planificacion de la generacion. Esta presentacion se realizo en un seminario web publico el 21 de julio del 2022, proporcionando un resumen general del progreso en los primeros seis meses del Estudio, incluyendo la presentacion de cuatro escenarios iniciales definidos mediante un rol activo de las partes interesadas. This is the Spanish translation of NREL/PR-6A20-83431.

14 SOLAR ENERGY↗
DOE OSTI2020

Multi-orbital-phase and Multiband Characterization of Exoplanetary Atmospheres with Reflected Light Spectra

Direct imaging of widely separated exoplanets from space will obtain their reflected light spectra and measure atmospheric properties. Previous calculations have shown that a change in the orbital phase would cause a spectral signal, but whether this signal may be used to characterize the atmosphere has not been shown. We simulate starshade-enabled observations of the planet 47 UMa b, using the present most realistic simulator Starshade Imaging Simulation Toolkit for Exoplanet Reconnaissance to estimate the uncertainties due to residual starlight, solar glint, and exozodiacal light. We then use the Bayesian retrieval algorithm ExoReL{sup R} to determine the constraints on the atmospheric properties from observations using a Roman- or Habitable Exoplanet Observatory (HabEx)-like telescope, comparing the strategies to observe at multiple orbital phases or in multiple wavelength bands. With a ∼20% bandwidth in 600–800 nm on a Roman-like telescope, the retrieval finds a degenerate scenario with a lower gas abundance and a deeper or absent cloud than the truth. Repeating the observation at a different orbital phase or at a second 20% wavelength band in 800–1000 nm, with the same integration time and thus degraded signal-to-noise ratio (S/N), would effectively eliminate this degenerate solution. Single observation with a HabEx-like telescope would yield high-precision constraints on the gas abundances and cloud properties, without the degenerate scenario. These results are also generally applicable to high-contrast spectroscopy with a coronagraph with a similar wavelength coverage and S/N, and can help design the wavelength bandwidth and the observation plan of exoplanet direct-imaging experiments in the future.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1981

Computer simulator for a mobile telephone system

A software simulator was developed to assist NASA in the design of the land mobile satellite service. Structured programming techniques were used by developing the algorithm using an ALCOL-like pseudo language and then encoding the algorithm into FORTRAN 4. The basic input data to the system is a sine wave signal although future plans call for actual sampled voice as the input signal. The simulator is capable of studying all the possible combinations of types and modes of calls through the use of five communication scenarios: single hop systems; double hop, signal gateway system; double hop, double gateway system; mobile to wireline system; and wireline to mobile system. The transmitter, fading channel, and interference source simulation are also discussed.

Schilling, D. L.↗
NASA NTRS1988

Project Longshot

Project Longshot presents a preliminary design for an unmanned probe to Alpha Centauri with a planned launch early in the 21st century. A 100-year estimated travel time was baselined for the mission on Space Report, Pioneering the Space Frontier. One of the elements of the Commission's solar and space physics plan is 'a long-life, high-velocity spacecraft to be sent out of the Solar System on a trajectory to the nearest star'. Adequate lead time is included in the scenario to allow the development of several enabling technologies and to ensure that the required space operations infrastructure will be in place.

Source record↗
NASA NTRS1997

An Overview of the Revised Mobile Satellite Handbook. 'Propagation Effects for Land Mobile Satellite Systems: Overview of Experimental and Modeling Results'

A review of the planned revised mobile satellite propagation handbook is presented. The revised manual will have a broadened scope such that it contains propagation information related to personal-mobile, airmobile, and marine-mobile scenarios; subject areas; previously not covered in the former document. It will also review new experiments, revised and new empirical and theoretical models developed since the previous publication. It is expected that many of the chapters will have been made accessible on the World Wide Web (http://propagation jpl.nasa.gov) by the time of the presentation of this paper. A formal document is expected to be published during the fall of 1997. As a sample of the contents of the revised handbook, the Extended Empirical Roadside Shadowing Model is described in detail.

Goldhirsh, Julius↗
NASA NTRS2013

Probabilistic Modeling of the Renal Stone Formation Module

The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.

kidney stones↗
NASA NTRSDate not supplied

Integral Equation Model of the Martian Surface layer for the Detection of Buried Ice Deposits in Support of the international Ice Mapping Mission Synthetic Aperture Radar

This work implemented a 3-D Electromagnetic Scattering model to gain a better understanding in the observations of L- and P-band radar returns from the multi-layered Martian upper surface layer. The model is based on the Integral Equation Model (IEM) developed by Adrian Fung. Our model implementation treats the upper surface (regolith) layer as an inhomogeneous medium with irregular boundaries for a range of Martian surface and shallow subsurface scenarios. The model is well suited to study the near subsurface (upper 10 meters of surface sediments) ice detection capability of the L-band (32 cm wavelength) Synthetic Aperture Radar (SAR) planned for the international Mars Ice Mapping (I-MIM) mission launching later in the 2020s.

surface roughness, Integral Equation Model (IEM)↗
NASA NTRSDate not supplied

Computational Nondestructive Evaluation Case Studies at NASA

The state of the art of numerical simulation of nondestructive evaluations (NDE) has begun to transition from research to application. The simulation software, both commercial and custom, has reached a level of maturity where it can be readily deployed to solve real world problems. The next area of research that is beginning to emerge is determining when and how to NDE simulation should be applied. At NASA Langley Research Center, NDE simulations have already been utilized for several aerospace projects to facilitate or enhance understanding of the inspection optimization and interpretation of results. Researchers at NASA have identified several different scenarios where it is appropriate to utilized NDE simulations. In this presentation, we will describe these scenarios, give examples of each instance, and demonstrate how NDE simulations were applied to solve problems with an emphasis on the mechanics of integrating with other workgroups. These examples will include inspection planning for multi-layer pressure vessels as well as on-orbit inspections.

Peter D. Juarez↗
DOE OSTI2022

Nuclear's Role in the U.S. Electricity System: A Multi-Model Inter-Comparison Analysis

Multiple capacity expansion models (CEMs) for the U.S. power system represent the balance of options among generation, transmission, and storage assets that can satisfy electric loads, operating and planning reserves, and policy requirements. These models are typically set up to find the least-cost portfolio of assets that meet specified requirements, and model decisions can include both investments in new, and retirement of existing, resources. The scenarios explored by CEMs can help inform strategies for meeting future electricity and energy needs under a range of future conditions. However, projections can differ between models, sometimes dramatically, for a seemingly similar scenario. Differences in model coverage, structure, and input assumptions contribute to the range of model outcomes. Understanding what drives the biggest differences in model outputs improves model insights and provides context for interpreting results. This summary presents analysis that was performed through a forum of analysts who own, update, and apply CEMs, as well as nuclear experts from national laboratories, industry, and the research community. The following sections describe methods, results, and findings from an original, innovative inter-model comparison that provides insights into what drives the greatest differences in nuclear retirement and deployment projections across models and a range of technology, market, and policy conditions.

capacity expansion model↗
DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility 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 This data is made available under a CCBY4.0 License 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 (ORCID:0000000328077088)↗
NASA NTRS1986

Conceptual planning for Space Station life sciences human research project

The Life Sciences Research Facility dedicated laboratory is currently undergoing system definition within the NASA Space Station program. Attention is presently given to the Humam Research Project portion of the Facility, in view of representative experimentation requirement scenarios and with the intention of accommodating the Facility within the Initial Operational Capability configuration of the Space Station. Such basic engineering questions as orbital and ground logistics operations and hardware maintenance/servicing requirements are addressed. Biospherics, calcium homeostasis, endocrinology, exercise physiology, hematology, immunology, muscle physiology, neurosciences, radiation effects, and reproduction and development, are among the fields of inquiry encompassed by the Facility.

Primeaux, Gary R.↗
NASA NTRS2021

Novel Ways to use the International Spacer Station as an Exploration Analog: International Progress in Planning "ISS4Mars"

In October 2020, International Space Station (ISS) Partner Agencies held a set of international workshops to solicit and develop creative and forward-looking ideas for using the ISS as an analog for preparation for Mars missions during its 3rd decade of operations. The workshops brought together participants from nine international space agencies or organizations, with stakeholders consisting of research managers, discipline experts, technology developers, flight physicians, flight operators, and astronauts. Breakout meetings and brainstorming sessions were conducted focusing on the following topics: Critical hazards and countermeasures for the transit to Mars; gravity transitions and early surface operations; environmental control and life support systems; food systems; human microbiome, microbial monitoring, and planetary protection; medical operations for Mars missions; isolation and confinement; autonomous systems and crew-centered autonomy; and communications delay effects on operations. In many cases the scenarios and approaches identified were compelling but challenging to implement under the current utilization structure used to manage the ISS for experiments. Following the series of workshops, a team of utilization leaders across the ISS partnership worked to compile the workshop recommendations and extract a set of use-cases with their prerequisites and constraints. The work considered the following aspects: what can be effectively done on ISS; which new technologies, approaches and scenarios are feasible; what alternatives could be considered; and what steps should be taken to enable integrated testing and future use of ISS as an analog for Mars missions. The final report will be published so that the use cases can be considered in each agency’s strategic planning processes. This paper will cover the process of international assessment in detail and how this process has influenced and broadened the vision of ISS utilization beyond single experiments to integrated studies and testing for future Mars missions. This approach to international collaboration informs both the next decade of international exploration research on the ISS and advancement of its utilization as an analog for deep space missions. For many of the participating partners, it also helps to frame the strategy for human research in Artemis as we begin planning for human missions to the moon. We conclude with a summary of the progress on the actions in the report and the additional implementation discussions that have occurred across the partnership.

Julie A Robinson↗
NASA NTRS2003

A Dynamic Risk Model for Evaluation of Space Shuttle Abort Scenarios

The Space Shuttle is an advanced manned launch system with a respectable history of service and a demonstrated level of safety. Recent studies have shown that the Space Shuttle has a relatively low probability of having a failure that is instantaneously catastrophic during nominal flight as compared with many US and international launch systems. However, since the Space Shuttle is a manned. system, a number of mission abort contingencies exist to primarily ensure the safety of the crew during off-nominal situations and to attempt to maintain the integrity of the Orbiter. As the Space Shuttle ascends to orbit it transverses various intact abort regions evaluated and planned before the flight to ensure that the Space Shuttle Orbiter, along with its crew, may be returned intact either to the original launch site, a transoceanic landing site, or returned from a substandard orbit. An intact abort may be initiated due to a number of system failures but the highest likelihood and most challenging abort scenarios are initiated by a premature shutdown of a Space Shuttle Main Engine (SSME). The potential consequences of such a shutdown vary as a function of a number of mission parameters but all of them may be related to mission time for a specific mission profile. This paper focuses on the Dynamic Abort Risk Evaluation (DARE) model process, applications, and its capability to evaluate the risk of Loss Of Vehicle (LOV) due to the complex systems interactions that occur during Space Shuttle intact abort scenarios. In addition, the paper will examine which of the Space Shuttle subsystems are critical to ensuring a successful return of the Space Shuttle Orbiter and crew from such a situation.

Henderson, Edward M.↗
DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility 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 This data is made available under a CCBY4.0 License 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 (ORCID:0000000328077088)↗