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Stanford Thermal Earth Model for the Conterminous United States

Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....

Aljubran, M. and Horne, R. Stanford University

Mar 14, 2024
9 Resources
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INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...

Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)

May 04, 2021
8 Resources
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Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate...

Williams, J. Energy and Geoscience Institute at the University of Utah

Sep 17, 2024
1 Resources
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GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...

Buster, G. et al Upflow

Jun 30, 2021
11 Resources
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Tularosa Basin Play Fairway: Weights of Evidence Models

These models are related to weights of evidence play fairway anlaysis of the Tularosa Basin, New Mexico and Texas. They were created through Spatial Data Modeler: ArcMAP 9.3 geoprocessing tools for spatial data modeling using weights of evidence, logistic regression, fuzzy logic a...

Brandt, A. University of Utah

Dec 01, 2015
2 Resources
0 Stars
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BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset

The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...

Tripp, C. et al National Renewable Energy Laboratory

Dec 30, 2022
9 Resources
1 Stars
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BUTTER Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...

Tripp, C. et al National Renewable Energy Laboratory

May 20, 2022
4 Resources
0 Stars
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Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events

This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...

Williams, J. et al Global Technology Connection, Inc.

Jan 21, 2025
3 Resources
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Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies

This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system c...

BushNational Renewable Energy Laboratory

Aug 01, 2020
2 Resources
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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...

Mordensky, S. et al United States Geological Survey

Feb 07, 2023
7 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
1 Resources
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Sup3rWind Data (CONUS)

This data contains paired European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit (WTK) images for 2007 and 2010 over two regions in the US, with domain sizes ~800x800 (latitudes from 25.89 to 41.58, and long...

Sinha, S. et al National Renewable Energy Laboratory (NREL)

Jul 16, 2024
6 Resources
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Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data

Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...

Reinisch, E. University of Wisconsin

Jul 28, 2016
1 Resources
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Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...

Moraga, J. et al Colorado School of Mines

Sep 01, 2020
16 Resources
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...

Ahmmed, B. Stanford University

Apr 04, 2022
3 Resources
0 Stars
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Geothermal Power Capacity Online by State (as of April 2011)

The Geothermal Energy Association (GEA) provides data about geothermal power plants in the U.S. This data summarizes total geothermal power capacity online (MW) as of April, 2011. The information is available via the GEA website (http://geo-energy.org/plants.aspx). The Excel file ...

Hallett, K. and Association, G. National Renewable Energy Laboratory

Jul 30, 2014
2 Resources
0 Stars
In curation

Organic Photovoltaic (OPV) Database

A database of quantum mechanical calculations on organic photovoltaic candidate molecules. Related Publications: Peter C. St. John, Caleb Phillips, Travis W. Kemper, A. Nolan Wilson, Michael F. Crowley, Mark R. Nimlos, Ross E. Larsen. (2018) Message-passing neural networ...

St. JohnNational Renewable Energy Laboratory

Apr 10, 2024
8 Resources
0 Stars
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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...

Jin, W. et al Idaho National Laboratory

Apr 15, 2022
4 Resources
0 Stars
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Machine Learning Model Geotiffs Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...

Faulds, J. et al Nevada Bureau of Mines and Geology

Jun 01, 2021
1 Resources
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Play Fairway Analysis CA-NV-OR: Figures on 2km Grids

Various data sets displayed on a 2km grid for the Play Fairway Analysis CA-NV-OR area.

M, C. University of California

Sep 15, 2015
16 Resources
0 Stars
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Description of the NSW Australia Electricity Network

Information about the New South Wales (NSW) electricity network is available. The information was taken from a line diagram of the NSW (Australia) Electricity network circa 2002 containing electrical bus and transmission line properties for use in load flow analysis. The results o...

Neale, D. and Management, M. National Renewable Energy Laboratory

Jan 01, 2002
1 Resources
0 Stars
In curation

Community Geothermal: Planning and Design of a Heating and Cooling System in Framingham, Massachusetts

These reports, plans, and drawings review the achievements of Home Energy Efficiency Team (HEET) and its partners to plan and design a network of interconnected ground-source heat pump systems, or geothermal network, in an area encompassing multiple environmental justice (EJ) neig...

Varela Gutierrez, I. et al Home Energy Efficiency Team (HEET)

Sep 01, 2024
6 Resources
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Genome-wide Transcription Factor DNA Binding Sites and Gene Regulatory Networks in Clostridium thermocellum

Clostridium thermocellum is a thermophilic bacterium recognized for its natural ability to effectively deconstruct cellulosic biomass. While there is a large body of studies on the genetic engineering of this bacterium and its physiology to-date, there is limited knowledge in the ...

Chou. . et al National Renewable Energy Laboratory

Apr 19, 2021
2 Resources
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Snake River Plain FORGE: Well Data for WO-2

Well data for the WO-2 well located in eastern Snake River Plain, Idaho. This data collection includes lithology reports, borehole logs, temperature at depth data, neutron density and gamma data, and rock strength parameters for the WO-2 well. This collection of data has been ass...

Podgorney, R. Idaho National Laboratory

Jul 29, 1991
9 Resources
0 Stars
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Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption

The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) ...

Ayyanar, R. et al Arizona State University

Feb 01, 2025
12 Resources
0 Stars
In curation

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