The TidGen Power System generates emission-free electricity from tidal currents and connects directly into existing grids using smart grid technology. The power system consists of three major subsystems: shore-side power electronics, mooring system, and turbine generator unit (TGU) device. ProteusDS is a full featured dynamic analysis software capable of simulating vessels, structures, lines, and technologies in harsh marine environments. This simulation software that was used to test the Advanced TidGen Power System. This submission includes the supporting Proteus simulation files.

Adequacy Analysis of Air Quality Monitoring Activities Relevant to California Thermal Enhanced Oil Recovery Fields - Final Report; November 1979

Analysis of Unit Mobility Ratio Well-to-Well Tracer Flow to Determine Reservoir Heterogeneity DOE/SF/11564-1

Dataset contains MHK Hydrofoils Design and Optimization and CFD Analysis Report for the Aquantis 2.5 MW Ocean Current Generation Device, as well as MHK Hydrofoils Wind Tunnel Test Plan and Checkout Test Report.

Aquantis 2.5 MW Ocean Current Generation Device, Tow Tank Dynamic Rig Structural Analysis Results. This is the detailed documentation for scaled device testing in a tow tank, including models, drawings, presentations, cost of energy analysis, and structural analysis. This dataset also includes specific information on drivetrain, roller bearing, blade fabrication, mooring, and rotor characteristics.

Core Labs Analysis on 33-14R Well at Bell Creek

This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python. This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility. Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case. New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.

The subsurface uncertainty at West Virginia University Main Campus is dominated by the uncertainty in the projections of geofluid flowrate in the target formation, the Tuscarora Sandstone. In this paper, three cores from the heterogeneous reservoir, available through West Virginia Geologic and Economic Survey, are analyzed by performing core analysis using CT scanning and permeability measurements via minipermeameter. Additional geological data are collected through cores, published literature, seismic data, and nearby, existing wells to estimate thickness, fracture network configuration and geothermal gradient to minimize the uncertainty of well deliverability. Using these estimated reservoir properties; a 3D conceptual model for the proposed geothermal site is developed. This dataset includes a GRC conference publication along with the data used to produce results explained in the paper including minipermeability measurement data for Preston -119 core and thin section analysis photos and data for Clay-513 core.

Digital Rocks is a data portal for fast storage and retrieval, sharing, organization and analysis of images of varied porous micro-structures. It has the purpose of enhancing research resources for modeling/prediction of porous material properties in the fields of Petroleum, Civil and Environmental Engineering as well as Geology. This platform allows managing, preserving, visualization and basic analysis of available images of porous materials and experiments performed on them, and any accompanying measurements (porosity, capillary pressure, permeability, electrical, NMR and elastic properties, etc.) required for both validation on modeling approaches and the upscaling and building of larger (hydro)geological models.

This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--based on the Excel data files--some of which were described in the reports. The scripts depend on the 'score_site' package, and the score site package depends on a number of standard Python libraries (see the score_site install instructions).

This data set is associated with the Nevada Play Fairway project. Excel file 5-Area Chem contains all the major chemistry for the areas sampled in the project. New analyses are in lines 2-30, while older analyses appear below that. Field Data excel file contains both field notes and data with ninety entries showing sixty areas not sampled either because they were to dry, cold, or unable to locate. Thirty sites were sampled and their sample numbers appear in this file corresponding to those in the 5-Area Chemistry file. Excel file 5-Area Geothermometer contains a summary of geothermometers calculated for the new and historical data sets. Scanned field sheets are attached as a pdf.

[Note: Integrated as part of FoodData Central, April 2019.] USDA's Food and Nutrient Database for Dietary Studies (FNDDS) is a database that is used to convert food and beverages consumed in What We Eat In America (WWEIA), National Health and Nutrition Examination Survey (NHANES) into gram amounts and to determine their nutrient values. Because FNDDS is used to generate the nutrient intake data files for WWEIA, NHANES, it is not required to estimate nutrient intakes from the survey. FNDDS is made available for researchers using WWEIA, NHANES to review the nutrient profiles for specific foods and beverages as well as their associated portions and recipes. Such detailed information makes it possible for researchers to conduct enhanced analysis of dietary intakes. FNDDS can also be used in other dietary studies to code foods/beverages and amounts eaten and to calculate the amounts of nutrients/food components in those items. FNDDS is released every two-years in conjunction with the WWEIA, NHANES dietary data release. The FNDDS is available for free download from the FSRG website.

The link points to a website at NCEDC to download the full moment tensors inversion software The moment tensor analysis conducted in the current project is based on the full moment tensor model described in Minson and Dreger (2008). The software including source, examples and tutorial can be obtained from ftp://ncedc.org/outgoing/dreger (download file pasi-nov282012.tar.gz). Performance criteria, mathematics and test results are provided by Minson and Dreger (2008), Ford et al. (2008, 2009, 2010, 2012) and Saikia (1994). References: Ford, S., D. Dreger and W. Walter (2008). Source Characterization of the August 6, 2007 Crandall Canyon Mine Seismic Event in Central Utah, Seism. Res. Lett., 79, 637-644. Ford, S. R., D. S. Dreger and W. R. Walter (2009). Identifying isotropic events using a regional moment tensor inversion, J. Geophys. Res., 114, B01306, doi:10.1029/2008JB005743. Ford, S. R., D. S. Dreger and W. R. Walter (2010). Network sensitivity solutions for regional moment tensor inversions, Bull. Seism. Soc. Am., 100, p. 1962-1970. Ford, S. R., W. R. Walter, and D. S. Dreger (2012). Event discrimination using regional moment 665 tensors with teleseismic-P constraints, Bull. Seism. Soc. Am. 102, 867-872. Minson, S. and D. Dreger (2008), Stable Inversions for Complete Moment Tensors, Geophys. J. Int., 174, 585-592. Saikia, C.K. (1994), Modified Frequency-Wavenumber Algorithm for Regional Seismograms using Filons Quadrature: Modeling of Lg Waves in Eastern North America. Geophys. J. Int., 118, 142-158.

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

This dataset includes the inputs and results for developing a transportation geo-typology that categorizes every location in the United States in terms of their main drivers of transportation demand and supply. It provides the raw inputs to the census tract level microtypes and county or CBSA level geotypes as well as the final typology labels at both the tract (microtype) and county/CBSA (geotype) levels. Inputs include information on the street network, economic characteristics, topography, commute patterns, and land use. The methodology is published in "Popovich, N., Spurlock, C. A., Needell, Z., Jin, L., Wenzel, T., Sheppard, C., & Asudegi, M. (2021). A methodology to develop a geospatial transportation typology. Journal of transport geography, 93, 103061".

The Geothermal Resource Portfolio Optimization and Reporting Technique (GeoRePORT) was developed with funding from the U.S. Department of Energy Geothermal Technologies Office to assist in identifying and pursuing long-term investment strategies through the development of a resource reporting protocol. GeoRePORT provides scientists and nonscientists a comprehensive and quantitative means of reporting: (1) features intrinsic to geothermal sites (project grade) and (2) maturity of the development (project readiness). Because geothermal feasibility is not determined by any single factor (e.g., temperature, permeability, permitting), a site?s project grade and readiness are evaluated on 12 attributes pertaining to geological, technical, or socio-economic feasibility. In this paper, we present case studies showing how GeoRePORT can be used to compare geological, technical, and socio-economic attributes between geothermal systems. The consistent and objective assessment protocols used in GeoRePORT allow for comparison of project attributes across unique locations and geological settings. GeoRePORT case studies presented here outline the geological, socio-economic, and technical features of four individual geothermal sites: Coso, Chena, Dixie Valley, and White Sands Missile Range. The case studies illustrate the usefulness of GeoRePORT in evaluating project risk and return, identifying gaps in reported data, evaluating R&D impact, and gathering insights on successes and failures as applicable to future projects.

Life Cycle Analysis (LCA) is a comprehensive form of analysis that utilizes the principles of Life Cycle Assessment, Life Cycle Cost Analysis, and various other methods to evaluate the environmental, economic, and social attributes of energy systems ranging from the extraction of raw materials from the ground to the use of the energy carrier to perform work (commonly referred to as the “life cycle” of a product). Results are used to inform research at NETL and evaluate energy options from a National perspective.

Useful information and tools for calculating the Levelized Cost of Energy (LCOE) and MHK Cost Breakdown Structure. Includes a structure for calculating the capital expenditures and operating costs of a marine energy technology or device, reference resource data for both wave and tidal, and LCOE reporting guidance. These tools are meant to be used to help calculate the Levelized Cost of Energy (LCOE) for an MHK or MRE technology or device.

Input data and heave results (unsteady RANS-VOF overset simulations performed in Star-CCM+) for a float with an ellipsoid geometry. Five extreme sea states were considered, as detailed in the conference paper "Application of the Most Likely Extreme Response Method for Wave Energy Converters" by Quon et al. (see resource below). These sea states were extrapolated from conditions near Humboldt Bay, California. Focused waves were generated using the MLER module of the Wave Design Response Toolbox (WDRT) and specified at the inlet boundary conditions. The device was constrained to heave only and a PTO was not modeled.

Life cycle analysis (LCA) is an environmental assessment method for accounting for the environmental burdens from the extraction of raw materials from the earth to production and use of the product to perform a specific function for society. LCA is the analysis technique used by the U.S. DOE Carbon Utilization Program (formerly known as the “Carbon Use and Reuse Program”) to determine if a project will result in lower life cycle greenhouse gas emissions in terms of carbon dioxide equivalents (CO2e) than the current state-of-the-art option on the market. This knowledge is combined with economic and market performance data, technical risk evaluations, and other criteria to evaluate project merit.

Risk Register for the RivGen power system, optimized for performance, durability and survivability, in Microsoft Excel format.

In 2008, the US Department of Energy (DOE) Wind and Water Power Program issued a funding opportunity announcement to establish university-led National Marine Renewable Energy Centers. Oregon State University and the University of Washington combined their capabilities in wave and tidal energy to establish the Northwest National Marine Renewable Energy Center, or NNMREC. NNMREC's scope included research and testing in the following topic areas: - Advanced Wave Forecasting Technologies; - Device and Array Optimization; - Integrated and Standardized Test Facility Development; - Investigate the Compatibility of Marine Energy Technologies with Environment, Fisheries and other Marine Resources; - Increased Reliability and Survivability of Marine Energy Systems; - Collaboration/Optimization with Marine Renewable and Other Renewable Energy Resources. To support the last topic, the National Renewable Energy Laboratory (NREL) was brought onto the team, particularly to assist with testing protocols, grid integration, and testing instrumentation. NNMREC's mission is to facilitate the development of marine energy technology, to inform regulatory and policy decisions, and to close key gaps in scientific understanding with a focus on workforce development. In this, NNMREC achieves DOE's goals and objectives and remains aligned with the research and educational mission of universities. In 2012, DOE provided NNMREC an opportunity to propose an additional effort to begin work on a utility scale, grid connected wave energy test facility. That project, initially referred to as the Pacific Marine Energy Center, is now referred to as the Pacific Marine Energy Center South Energy Test Site (PMEC-SETS) and involves work directly toward establishing the facility, which will be in Newport Oregon, as well as supporting instrumentation for wave energy converter testing. This report contains a breakdown per subtask of the funded project. Under each subtask, the following are presented and discussed where appropriate: the initial objective or hypothesis; an overview of accomplishments and approaches used; any problems encountered or departures from planned methodology over the life of the project; impacts of the problems or rescoping of the project; how accomplishments compared with original project goals; and deliverables under the subtasks. Products and models developed under the award are also included.

Papaya is a JavaScript based CT scan image viewer for the web that is compatible across a range of popular web browsers, including mobile devices and does not require additional software installation to use. This open source CT scan image viewer supports .nii and .nii.gz files. Papaya is developed by the Research Imaging Institute at the University of Texas Health Science Center.

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of petascale size as well as on laptops for smaller data, has become an integral tool in many national laboratories, universities and industry, and has won several awards related to high performance computation.

Attached are the .cas and .dat files for the Reynolds Averaged Navier-Stokes (RANS) simulation of a single lab-scaled DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. In this case study the flow field around and in the wake of the NREL Phase VI wind turbine, modeled is MHK turbine, is simulated using Actuator Disk Model (ADM) (a.k.a Porous Media) by solving RANS equations coupled with a turbulence closure model. It should be highlighted that in this simulation the actual geometry of the rotor blade is not modeled. The effect of turbine rotating blades are modeled using the Actuator Disk Theory (see the stated section of attached M.Sc. thesis for more details).

Attached are the .cas and .dat files for the Reynolds Averaged Navier-Stokes (RANS) simulation of a single full scale DOE RM1 turbine implemented in ANSYS FLUENT CFD-package. In this case study taking advantage of the symmetry of the DOE RM1 geometry, only half of the geometry is modeled using (Single) Rotating Reference Frame model [RRF]. In this model RANS equations, coupled with k-\omega turbulence closure model, are solved in the rotating reference frame. The actual geometry of the turbine blade is included and the turbulent boundary layer along the blade span is simulated using wall-function approach. The rotation of the blade is modeled by applying periodic boundary condition to sets of plane of symmetry. This case study simulates the performance and flow field in both the near and far wake of the device at the desired operating conditions. The results of these simulations showed good agreement to the only publicly available numerical simulation of the device done in the NREL. Please see the attached paper.

Rock Matrix and Fracture Analysis of Flow in Western Tight Gas Sands; December 1987

Rock Matrix and Fracture Analysis of Flow in Western Tight Gas Sands; February 1987

The report included in this submission details the nontechnical barriers to entry for development of geothermal resources in the Salton Sea. The Salton Sea provides an economically viable opportunity for replacing the energy imported by California which makes up 25 percent of Californias total electricity supply. However, geothermal energy in the Salton Sea has been largely undeveloped since the 1980s. This report preforms a techno-economic analysis of Geothermal Energy in the Salton Sea and develops a model to quantify the nontechnical challenges and opportunities associated with new geothermal development in the Salton Sea. Geothermal energy offers an opportunity to generate baseload, renewable energy that can help support the transition to an energy economy with reduced impacts on climate change and replace older, more expensive, nonrenewable, and more resource-impacting energy-generation facilities. The United States has the largest known geothermal resource in the world, with over 31 GW of conventional geothermal potential. However, due to market conditions, an inability to properly quantify both electrical grid benefits and resource stability, and the difficulty of exploring and developing the geothermal resource, few new geothermal projects have come online over the past three decades. The Salton Sea, in Imperial County, California, provides a prime location and opportunity to develop new geothermal resources. The Salton Sea contains a robust, well-mapped, geothermal resource, with opportunities for concurrent development of lithium and other mineral resources. This report describes the history of geothermal development at the Salton Sea and compares geothermal to other renewable energy sources in the area. The report then uses a techno-economic analysis (TEA) model to analyze the relative benefits and costs of various challenges and opportunities and provides recommendations for streamlining geothermal development at the Salton Sea and elsewhere. The challenges and opportunities analyzed in the TEA model were informed by stakeholder interviews and literature reviews. Based upon the identified challenges and opportunities and the results of the TEA model, primary findings are that certain nontechnical barriers such as permitting costs play only a minor role in determining the viability of development of the geothermal resource at the Salton Sea. Other barriers such as permitting timelines, government/agency coordination, and the potential co-location of lithium extraction with a geothermal plant may result in much larger impacts on project viability.

This submission contains 167 deviatoric moment tensor (MT) solutions for the seismicity observed two years prior and three years post start of injection activities at The Geysers Prati 32 EGS Demonstration. Also included is a statistical representation of the properties of 751 fractures derived from the analysis of seismicity observed two years prior and three years post start of injection activities at The Geysers Prati 32 EGS Demonstration Project. The locations of the fractures are taken from microseismic hypocenters, the fracture areas are derived from moment magnitudes via scaling relationships, and the azimuths (sigma 1) and dips (sigma 3) are derived from the results of stress analyses.

Analysis method to systematically identify all potential failure modes and their effects on the Stingray WEC system. This analysis is incorporated early in the development cycle such that the mitigation of the identified failure modes can be achieved cost effectively and efficiently. The FMECA can begin once there is enough detail to functions and failure modes of a given system, and its interfaces with other systems. The FMECA occurs coincidently with the design process and is an iterative process which allows for design changes to overcome deficiencies in the analysis. Risk Registers for major subsystems were completed in compliance with the DOE Risk Management Framework developed by NREL (document included below).

A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled from several sources including, DOE's Wind Exchange Ordinance Database (Linked in the submission), National Conference of State and Legislatures Wind Energy Siting (also linked in the submission), and scholarly legal articles. The citations for each ordinance are included in the spreadsheet. This data is an updated to a previously developed database of wind ordinances found in OEDI Submission 1932: "U.S. Wind Siting Regulation and Zoning Ordinances"

The vast supply of geothermal energy stored throughout the Earth and the exceedingly long time required to dissipate that energy makes the world's geothermal energy supply nearly limitless. As such, this resource holds the potential to provide a large supply of the world's energy demands; however, like all natural resources, it must be utilized in an appropriate manner if it is to be sustainable. Understanding sustainable use of geothermal resources requires thorough characterization efforts aimed at better understanding subsurface properties. The goal of this work is to understand which critical subsurface properties exert the most influence on sustainable geothermal production as a means to provide targeted future resource characterization strategies. Borehole temperature and reservoir pressure data were analyzed to estimate reservoir thermal and hydraulic properties at an active geothermal site. These reservoir properties then served as inputs for an analytical model which simulated net power production over a 30-year period. The analytical model was used to conduct a sensitivity analysis to determine which parameters were most critical in constraining the sustainability of a geothermal reservoir. Modeling results reveal that the number of preferential flow pathways (i.e. fractures) used for heat transport provides the greatest impact on geothermal reservoir sustainability. These results suggest that early and pre-production geothermal reservoir exploration would achieve the greatest benefit from characterization strategies which seek to delineate the number of active flow pathways present in the system.

The files available under this heading are comprised on data taken from a series of bench-scale separations tests. Link to Rare Earth Elements from Coal and Coal Byproducts site 

This is an Excel spreadsheet containing the results of X-ray fluorescence from well 56-32 sludge samples. The instrumentation used was a Olympus Vanta M series handheld XRF analyzer. A glass (SiO2) "blank" was analyzed at the beginning and end of each sample batch to detect contamination within the instrument. The standard 2711A was analyzed at the beginning and end of each sample batch to detect drift in instrument precision over time. Material was analyzed in a plastic cup with a prolene thin film cover for minimal interference.

Berkeley Labs "Utility-Scale Solar", 2022 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developments in 2021, this report explores trends in deployment, technology, capital and operating costs, capacity factors, the levelized cost of solar energy (LCOE), power purchase agreement (PPA) prices, wholesale market value, and interconnection queue data.

This map depicts a population-weighted measure of particulate matter 2.5 (PM 2.5) air quality data for the US for 2016. The measure factors in where population is concentrated within a state or county.Population data is from Esri's Updated Demographics and air quality data is from NASA SEDAC gridded data aggregated to states, counties, congressional districts, and 50km hex bins. Click on the map to view more information such as the trend over time. Click here to view more information on how this layer was created. Citations:van Donkelaar, A., R. V. Martin, M. Brauer, N. C. Hsu, R. A. Kahn, R. C. Levy, A. Lyapustin, A. M. Sayer, and D. M. Winker. 2018. Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, 1998-2016. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4ZK5DQS. Accessed 1 April 2020van Donkelaar, A., R. V. Martin, M. Brauer, N. C. Hsu, R. A. Kahn, R. C. Levy, A. Lyapustin, A. M. Sayer, and D. M. Winker. 2016. Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites. Environmental Science & Technology 50 (7): 3762-3772. https://doi.org/10.1021/acs.est.5b05833.