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Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
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12 Resources
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Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement Workshop Presentation
This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the U...
Kelley, M. and Bunger, A. Battelle Memorial Institute
Sep 08, 2023
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1 Resources
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Summary of Cement Formulations Tested by BNL for Self-Healing Ability Tests Conditions and Data
A table of cement formulations tested by Brookhaven National Laboratory in 2016-2017 in the frame of the "Self-healing and Re-Adhering Cements with Improved Toughness at Casing and Formation Interfaces for Geothermal Wells" project.
Sugama, T. Brookhaven National Laboratory
Sep 27, 2017
2 Resources
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2 Resources
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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
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3 Resources
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G2Aero Database of Airfoils Curated Airfoils
This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes.
We constructed the a...
Doronina, O. et al National Renewable Energy Lab NREL
Sep 24, 2024
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3 Resources
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UAE6 Wind Tunnel Tests Data UAE6 Sequence X Raw Data
**Overview**
Sequence X: Elevated RPM (F)
This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged
from 5 m/s to 12 m/s, and yaw angles of ±30° were obtained. The blade pitch angle was 3°. The
rotor rotated at 90 RPM. Blade pressure measur...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 29, 2018
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1 Resources
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Open-source technology database on Energy Storage
This database provides energy storage technologies, products, demonstration projects and analyses. Also, an Energy Map is created listing other sources of data, and an overview of the future potential estimations is provided. The data is machine-readable and open-source, working f...
Dorp, B. and Storage, E. National Renewable Energy Laboratory
Oct 10, 2014
2 Resources
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DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
4 Resources
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4 Resources
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Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes model...
Buster, G. et al National Renewable Energy Lab (NREL)
Oct 16, 2024
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Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
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3 Resources
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Brady Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
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3 Resources
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Buildings Performance Database
The Buildings Performance Database (BPD) unlocks the power of building energy performance data. The platform enables users to perform statistical analysis on an anonymous dataset of tens of thousands of commercial and residential buildings from across the country. Users can compar...
Contact, B. and (EERE), O. Office of Energy Efficiency & Renewable Energy
Nov 25, 2014
2 Resources
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2 Resources
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USGS Water Data for the Nation
The U.S. Geological Survey maintains national data bases of water-use information. The data are collected and compiled every five years for each State, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.
County, state, and national water-use estimates may be downl...
Hopkins, C. and Team, W. United States Geological Survey
Aug 06, 2020
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2 Resources
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UAE6 Wind Tunnel Tests Data UAE6 Sequence 5 Raw Data
**Overview**
Sequence 5: Sweep Wind Speed (F,P)
This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed was
ramped from 5 m/s to 25 m/s by the wind tunnel operator. This was repeated with a decreasing
ramp. The yaw angle was maintained at 0°. The ...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 11, 2018
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Hawaii Play Fairway Analysis: Recharge Data for the Islands of Kauai, Lanai and Molokai, Hawaii
Recharge data for the islands of Kauai, Lanai and Molokai in shapefile format. These data are from the following sources:
Whittier, R.B and A.I. El-Kadi. 2014. Human Health and Environmental Risk Ranking of On-Site Sewage Disposal systems for the Hawaiian Islands of Kauai, Molo...
Lautze, N. University of Hawaii
Jan 01, 2015
12 Resources
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12 Resources
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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
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4 Resources
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U.S. Wind Siting Regulation and Zoning Ordinances
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...
Lopez, A. et al National Renewable Energy Laboratory
Jun 30, 2022
5 Resources
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5 Resources
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Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
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3 Resources
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UAE6 Wind Tunnel Tests Data UAE6 Sequence V Raw Data
**Overview**
Sequence V: Tip Plate (F)
This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged
from 5 m/s to 25 m/s, and the yaw angle was held at 0°. The blade pitch angle was 3°. The rotor
rotated at 72 RPM. Blade pressure measurements w...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 28, 2018
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UAE6 Wind Tunnel Tests Data UAE6 Sequence W Raw Data
**Overview**
Sequence W: Extended Blade (F)
This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged
from 5 m/s to 21 m/s, and the yaw angle was held at 0°. The blade pitch angle was 3°. The rotor
rotated at 72 RPM. Blade pressure measureme...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 11, 2018
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UAE6 Wind Tunnel Tests Data UAE6 Sequence M Raw Data
**Overview**
Sequence M: Transition Fixed (P)
Test sequence M used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from
5 m/s to 15 m/s. Yaw angles ranged from 0° to 90°. The blade tip pitch was 3°. The rotor rotated
at 72 RPM. Blade pressure measurement...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 28, 2018
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Virtual Flow Solver Geophysics: A 3D Incompressible Navier-Stokes Solver
Virtual Flow Solver Geophysics (VFS-Geophysics) is a three-dimensional (3D) incompressible Navier-Stokes solver based on the Curvilinear Immersed Boundary (CURVIB) method. The CURVIB is a sharp interface type of immersed boundary (IB) method that enables the simulation of fluid f...
Khosronejad, A. et al Stony Brook University
Jul 17, 2023
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2 Resources
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Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32
Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, f...
DeWolf, S. and Murdoch, L. Clemson University
Sep 15, 2022
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8 Resources
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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
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9 Resources
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Stimulation at Desert Peak Modeling with the Coupled THM Code FEHM
Numerical modeling of the 2011 shear stimulation at the Desert Peak Well 27-15 using a coupled thermal-hydrological-mechanical simulator. This submission contains the finite element heat and mass transfer (FEHM) executable code for a 64-bit PC Windows-7 machine, and the input and ...
Kelkar, S. et al Los Alamos National Laboratory
Apr 30, 2013
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