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Utah FORGE 2-2446: Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity Workshop Presentation

This is a presentation on the Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity project by Lawrence Livermore National Laboratory, presented by Dr. Matteo Cusini. The project's objective was to employ a combination of high-fidelity simulations and true...
Cusini, M. and Bunger, A. Lawrence Livermore National Laboratory
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

Utah FORGE 5-2565: Hydrothermal Evolution of Fracture Properties Workshop Presentation

This is a presentation on the Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions project by the U.S. Geological Survey, presented by Dr. David Lockner. The project's objective was to determine how thermal, hydraulic, mechanical, and ch...
Lockner, D. et al United States Geological Survey
Sep 08, 2023
1 Resources
0 Stars
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Utah FORGE 3-2514: A Strain Sensing Array to Characterize Deformation at the FORGE Site Workshop Presentation

This is a presentation on the Strain Sensing Array to Characterize Deformation at the FORGE Site project by Clemson University, presented by Lawrence Murdoch. The project's objective was to evaluate the feasibility of measuring and interpreting tensor strain data to improve the pe...
Murdoch, L. et al Clemson University
Sep 08, 2023
1 Resources
0 Stars
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Utah FORGE 5-2428: Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior Workshop Presentation

This is a presentation on the Fracture Permeability Impact on Seismic Slip Behavior project by Lawrence Livermore National Laboratory, presented by Dr. Kayla A. Kroll. The project's objective is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemic...
Kroll, K. et al Lawrence Livermore National Laboratory
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

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
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