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TEAMER: Tidal Energy Resource Characterization and Model Validation via the Assessment of Distributed Current Measurements from microFloat Swarms, Data and Post-Access Report
This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for pro...
Harrison, T. et al University of Washington (NNMREC) Applied Physics Lab
Aug 20, 2020
20 Resources
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20 Resources
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AlphaBuilding Synthetic Buildings Operation Dataset
This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with...
Li, H. et al Lawrence Berkeley National Laboratory
Dec 21, 2020
5 Resources
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5 Resources
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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
27 Resources
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27 Resources
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Soda Lake Geothermal: Raw 3D and 3C Seismic-Reflection Data from 2010 Survey
This dataset contains seismic-reflection records created in 2010 around the Soda Lake geothermal field near Fallon, Nevada. The data was collected by the power plant operator at the time, Magma Energy (CYRQ Energy in 2024). This was a petroleum-industry-quality three-dimensional ...
N. Louie, J. et al University of Nevada Reno
Sep 01, 2010
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5 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
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6 Resources
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