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Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All expe...

Yu, J. et al Penn State University

Jul 01, 2023
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Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment

Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding...

Roseboom, M. et al Pennsylvania State University

Nov 07, 2023
6 Resources
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Utah FORGE: Phase Native State FALCON Model Files

The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...

Podgorney, R. Idaho National Laboratory

Jun 06, 2019
2 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
3 Resources
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Catalyst Design in Nitrate Removal

Based on the volcano plot developed by Dr. Goldsmith group (Report linked in submission), we utilized DFT (density functional theory) calculations to search for bimetallic materials in the application of catalysts in aqueous nitrate removal. The calculations are conducted via the ...

Wang, D. and Jain, A. Lawrence Berkeley National Laboratory

Dec 01, 2021
7 Resources
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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...

Siler, D. et al United States Geological Survey

Oct 01, 2021
6 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 Lab NREL

Jul 16, 2024
6 Resources
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Programs and Code for Geothermal Exploration Artificial Intelligence

The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...

Moraga, J. Colorado School of Mines

Apr 27, 2021
11 Resources
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Admiralty Inlet Advanced Turbulence Measurements: May 2015

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in May of 2015. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on a 'StableMoor' (Manufacturer: DeepWater Buoyancy) buoy and a Tidal Turbulence Mooring (TTM). Thes...

Kilcher, L. National Renewable Energy Laboratory

May 18, 2015
18 Resources
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Admiralty Inlet Advanced Turbulence Measurements: June 2014

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in June of 2014. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on Tidal Turbulence Mooring's (TTMs). The TTM positions the ADV head above the seafloor to make mid...

Kilcher, L. National Renewable Energy Laboratory

Jun 30, 2014
26 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...

Beckers, K. et al National Renewable Energy Laboratory

Oct 20, 2021
6 Resources
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EGS Collab Experiment 1: Microseismic Monitoring

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...

Schoenball, M. et al Lawrence Berkeley National Laboratory

Jul 29, 2019
46 Resources
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