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Texas Tech Building Wake Field Experiment, Reese Technology Center / Averaged Data

**Overview** This dataset contains sonic anemometer measurements around a building the size of a typical suburb home located at Texas Tech's Reese Technology Center. These data are intended to validate computer models. **Data Details** Stations 1-22 are sonic anemometers at a h...
Nelson, M. and Pol, S. Wind Energy Technologies Office (WETO)
May 06, 2021
1 Resources
0 Stars
Publicly accessible

Utah FORGE Report on the Thermal Properties of Wells 16A(78)-32 & 58-32 Granite

This is a report from Metarock Laboratories on the thermal properties of Utah FORGE wells 16A(78)-32 & 58-32 granite. The report includes pictures of core samples, core details for the samples (where the sample was taken and the size of the sample), sample thermal expansion test r...
Laboratories, M. et al Energy and Geoscience Institute at the University of Utah
May 04, 2021
1 Resources
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Utah FORGE: Results of Direct Shear Tests on Saturated Joints in Sierra White Granite

This dataset includes an Excel file with the results of direct shear tests to investigate the mechanical and geophysical response of saturated joints. Tests were conducted on induced tension-fractured Sierra White granite joints in a custom water pressurized chamber. The preparati...
Han, K. et al Purdue University
Dec 31, 2022
2 Resources
0 Stars
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Verdant Power Gen5 KHPS and TriFrame System Content Models

This submission includes the Component Content Model for Verdant Power TriFrame and the System Content Model for Verdant Power TriFrame + 3 Gen5 KHPS Turbines. The TriFrame is the foundation component of the system, which consists of a TriFrame + 3 Gen5 KHPS Turbines (TF+3T).
Corren, D. et al Verdant Power Inc.
Jul 05, 2018
2 Resources
0 Stars
Publicly accessible

Surface Meteorological Station UND 10m, (2) Sonics 3m 10m, (2) T/RH 3m 10m (1) Licor 3m, Physics site-1 Reviewed Data

**Overview** Surface wind, temperature, and turbulence measurements based on three-dimensional (3D) sonic anemometer and temperature/relative humidity (T/RH) data. **Data Details** T/RH events history is available in the attached Excel file: *PS01-TRH-3m *PS01-TRH-10m *PS02...
Otarola-Bustos, S. and Fernando, J. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
0 Stars
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Surface Meteorological Station UND 10m, (2) Sonics 3m 10m, (2) T/RH 3m 10m, Physics site-11 Reviewed Data

**Overview** Surface wind, temperature, and turbulence measurements based on three-dimensional (3D) sonic anemometer and temperature/relative humidity (T/RH) data. **Data Details** T/RH events history is available in the attached Excel file: *PS01-TRH-3m *PS01-TRH-10m *PS02...
Otarola-Bustos, S. and Fernando, J. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
0 Stars
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Surface Meteorological Station UND 17m, (3) Sonics 3m 10m 17m, (2) T/RH 3m 17m, Physics site-2 Reviewed Data

**Overview** Surface wind, temperature, and turbulence measurements based on three-dimensional (3D) sonic anemometer and temperature/relative humidity (T/RH) data. **Data Details** T/RH events history is available in the attached Excel file: *PS01-TRH-3m *PS01-TRH-10m *PS02...
Otarola-Bustos, S. and Fernando, J. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
0 Stars
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Surface Meteorological Station UND 21m, (3) Sonics 3m 10m 21m, (2) T/RH 3m 21m, Physics site-6 Reviewed Data

**Overview** Surface wind, temperature, and turbulence measurements based on three-dimensional (3D) sonic anemometer and temperature/relative humidity (T/RH) data. **Data Details** T/RH events history is available in the attached Excel file: *PS01-TRH-3m *PS01-TRH-10m *PS02...
Otarola-Bustos, S. and Fernando, J. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
0 Stars
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Distributed Acoustic Sensing (DAS) for Periodic Hydraulic Tests: Laboratory Data

These data were collected in the laboratory located at California State University Long Beach. They consist of DAS data collected from a fiber optic cable placed in a tank of water, subjected to oscillating head. These tests are described in the article linked below.
Coleman, T. California State University
Feb 27, 2015
5 Resources
0 Stars
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EGS Collab Experiment 1: Accelerometer orientations

Document describing the methodology used to determine the accelerometers' three-component orientations at the first EGS Collab testbed using Continuous Active-Source Seismic Monitoring (CASSM) data and hodogram analysis. Original submission: gdr.openei.org/submissions/1166
Hopp, C. et al Lawrence Berkeley National Laboratory
Aug 19, 2020
2 Resources
0 Stars
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Water chemistry data and calculations for Fracture Sustainability Tests

Measured cation, anion, and silica are presented as well as calculations evaluating mass balance performed for 4 fracture sustainability tests under EGS conditions: Stripa granite, Metamudstone, Rhyolitic Ashflow Tuff, and Silicified Rhyolitic Tuff. Calculations of charge balance ...
Kneafsey, T. et al Lawrence Berkeley National Laboratory
Sep 30, 2020
2 Resources
0 Stars
Publicly accessible

Purdue University: Results of B-Value Tests for Rock Saturation

This dataset includes an Excel file with the results of B-value tests to determine the magnitude of the back pressure required for full saturation of Sierra White granite samples. Test were conducted on cylindrical rock specimens of Sierra White granite in a custom water pressuriz...
Han, K. et al Purdue University
Jun 20, 2022
2 Resources
0 Stars
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Utah FORGE Phase 3 Native State Model: 2022 Update

This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. Thi...
Podgorney, R. and Liu, R. Idaho National Laboratory
Jul 29, 2022
1 Resources
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Chemistry of the thermal water samples of the Camas Prairie area in Idaho, USA

This dataset includes chemistry of geothermal water samples of the Camas Prairie area in Idaho. The samples included in this dataset were collected over the period of 2016-2019. Collection/analysis of new water samples and compilation of existing water chemistry database were cond...
Neupane, G. et al Idaho National Laboratory
Sep 30, 2020
1 Resources
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Machine Learning Model Geotiffs Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...
Faulds, J. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
1 Resources
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Utah FORGE 2-2404: Determination of Reservoir-Scale Stress State Presentation Slides

This PowerPoint summarizes the integration of multiple approaches and data to constrain wellbore stress models at Utah FORGE. This stress determination used faulting theory, breakouts, and drilling-induced cracks detected in image logs. Wellbore stress profiles were established f...
Ghassemi, A. et al The University of Oklahoma
Jul 31, 2022
1 Resources
0 Stars
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UAE6 Wind Tunnel Tests Data UAE6 Sequence 4 Raw Data

**Overview** Sequence 4: Static Pressure Calibration (P) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 30° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. B...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 28, 2018
1 Resources
0 Stars
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UAE6 Wind Tunnel Tests Data UAE6 Sequence 6 Raw Data

**Overview** Sequence 6: Shroud Wake Measure (P) This test sequence used a downwind, rigid turbine with a 3.4° cone angle. The wind speeds for this sequence corresponded to subcritical [7 m/s], transitional [15 m/s], and supercritical [20 m/s] Reynolds number regimes for the ci...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 28, 2018
1 Resources
0 Stars
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Lidar HilFlowS LLNL ZephIR300 MOP Processed Data

**Overview** The ZephIR300 is a continuous wave LIDAR with a range of 10 m to 300 m. During HilFlowS the ZephIR300 was programmed to measure from 10 m to 150 m. In addition, the ZephIR300 provided a measurement at 1 m height using an onboard meteorological sensor. The ZephIR300 ...
Wharton, S. and , . Wind Energy Technologies Office (WETO)
Jul 07, 2019
1 Resources
0 Stars
Publicly accessible

Lidar HilFlowS LLNL ZephIR300 WOP Processed Data

**Overview** The ZephIR300 is a continuous wave LIDAR with a range of 10 m to 300 m. During HilFlowS the ZephIR300 was programmed to measure from 10 m to 150 m. In addition, the ZephIR300 provided a measurement at 1 m height using an onboard meteorological sensor. The ZephIR300 ...
Wharton, S. and , . Wind Energy Technologies Office (WETO)
Jul 07, 2019
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.hrrr.01.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.hrrr.01.fcst.02

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.hrrr.02.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.hrrr.02.fcst.02

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
0 Stars
Publicly accessible

wfip2.model/retro.rap.01.fcst.01

**Overview** The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
0 Stars
Publicly accessible
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