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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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1 Resources
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Admiralty Inlet Hub-Height Turbulence Measurements from June 2012
This data is from measurements at Admiralty Head, in Admiralty Inlet. The measurements were made using an IMU equipped ADV mounted on a mooring, the 'Tidal Turbulence Mooring' or 'TTM'. The inertial measurements from the IMU allows for removal of mooring motion in post processing....
Kilcher, L. National Renewable Energy Laboratory
Jun 18, 2012
7 Resources
0 Stars
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7 Resources
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UNH TDP Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary
This data was collected between October 12 and December 15 of 2021 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). This data set includes over 29 days of grid connected turbine operation during this 65 day time f...
Wosnik, M. et al National Renewable Energy Laboratory
Dec 21, 2021
30 Resources
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30 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
0 Stars
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18 Resources
0 Stars
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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
0 Stars
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26 Resources
0 Stars
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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
0 Stars
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6 Resources
0 Stars
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