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Colorado Heat Flow Data from IHFC
This layer contains the heat flow sites and data of the State of Colorado compiled from the International Heat Flow Commission (IHFC) of the International Association of Seismology and Physics of the Earth's Interior (IASPEI) global heat flow database. The data include different i...
E., R. Flint Geothermal, LLC
Feb 01, 2012
1 Resources
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1 Resources
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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
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1 Resources
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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
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1 Resources
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AeroDyn V15.04: Design Tool for Wind and MHK Turbines
AeroDyn is a time-domain wind and MHK turbine aerodynamics module that can be coupled into the FAST version 8 multi-physics engineering tool to enable aero-elastic simulation of horizontal-axis wind turbines. AeroDyn V15.04 has been updated to include a cavitation check for MHK tu...
Murray, R. et al National Renewable Energy Laboratory
Apr 28, 2017
1 Resources
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1 Resources
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Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Lu, G. et al University of Pittsburgh
Aug 30, 2024
2 Resources
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2 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-10 Reviewed Data
**Overview**
This dataset provides fast response wind and virtual sonic temperature data.
**Data Details**
Each meteorological (met) station has one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (within a degree) has been veri...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
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1 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-10 Raw Data
**Overview**
This dataset provides fast response wind and virtual sonic temperature data.
**Data Details**
Each meteorological (met) station has one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (within a degree) has been veri...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
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Publicly accessible
1 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-4 Raw Data
**Overview**
This dataset provides fast response wind and virtual sonic temperature data.
**Data Details**
Each meteorological (met) station has one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (within a degree) has been veri...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
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Publicly accessible
1 Resources
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Publicly accessible
Surface Meteorological Station PNNL 10m Sonic, Physics site-4 Reviewed Data
**Overview**
This dataset provides fast response wind and virtual sonic temperature data.
**Data Details**
Each meteorological (met) station has one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (within a degree) has been veri...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
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1 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-5 Derived Data
**Overview**
This set provides estimation of the turbulent fluxes obtained with EddyPro v6.2.0 software (15-min averaging).
**Data Details**
Each meteorological station had one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (w...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Apr 01, 2016
1 Resources
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1 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-5 Raw Data
**Overview**
This dataset provides fast response wind and virtual sonic temperature data.
**Data Details**
Each meteorological (met) station has one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (within a degree) has been veri...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
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Publicly accessible
Surface Meteorological Station PNNL 10m Sonic, Physics site-5 Reviewed Data
**Overview**
This dataset provides fast response wind and virtual sonic temperature data.
**Data Details**
Each meteorological (met) station has one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (within a degree) has been veri...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
0 Stars
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1 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-4 Derived Data
**Overview**
This set provides estimation of the turbulent fluxes obtained with EddyPro v6.2.0 software (15-min averaging).
**Data Details**
Each meteorological station had one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (w...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
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Surface Meteorological Station PNNL 10m Sonic, Physics site-10 Derived Data
**Overview**
This set provides estimation of the turbulent fluxes obtained with EddyPro v6.2.0 software (15-min averaging).
**Data Details**
Each meteorological station had one sonic anemometer (Gill R3-50, omnidirectional) mounted on top of a 10-m tower. Sensor verticality (w...
Pekour, M. and Berg, L. Wind Energy Technologies Office (WETO)
Mar 31, 2016
1 Resources
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1 Resources
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Stanford Thermal Earth Model for the Conterminous United States
Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Aljubran, M. and Horne, R. Stanford University
Mar 14, 2024
9 Resources
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9 Resources
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RivGen Current Flow Measurements, Igiugig, AK
Measurements of flow velocity, distribution and turbulence conducted by University of Washington Applied Physics Laboratory, Igiugig, Alaska, Summer 2014
Thomson, J. et al Ocean Renewable Power Company
Nov 03, 2014
1 Resources
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1 Resources
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Surface Meteorological Station PNNL 3m Tower, Physics site-8 Raw Data
**Overview**
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
**Data Details**
A PNNL computer is used as the base station to download the meteorological data acquired by th...
Morris, V. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
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1 Resources
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Surface Meteorological Station PNNL 3m Tower, Physics site-7 Raw Data
**Overview**
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
**Data Details**
A PNNL computer is used as the base station to download the meteorological data acquired by th...
Morris, V. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
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1 Resources
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Surface Meteorological Station PNNL 3m Tower, Physics site-7 Reviewed Data
**Overview**
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
**Data Details**
A PNNL computer is used as the base station to download the meteorological data acquired by the...
Berg, L. Wind Energy Technologies Office (WETO)
Feb 17, 2016
1 Resources
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1 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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6 Resources
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Surface Meteorological Station PNNL 3m Tower, Physics site-8 Reviewed Data
**Overview**
In support of the Wind Forecasting Improvement Project, Pacific Northwest National Laboratory (PNNL) deployed surface meteorological stations in Oregon.
**Data Details**
A PNNL computer is used as the base station to download the meteorological data acquired by the...
Berg, L. Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
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1 Resources
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Northwest National Marine Renewable Energy Center, OR Final Technical Report & Appendices
In 2008, the US Department of Energy (DOE) Wind and Water Power Program issued a funding opportunity announcement to establish university-led National Marine Renewable Energy Centers. Oregon State University and the University of Washington combined their capabilities in wave and ...
Hellin, D. Northwest National Marine Renewable Energy Center
Jun 30, 2016
2 Resources
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2 Resources
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
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3 Resources
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Surface Meteorological Station UND 10m, (2) Sonics 3m 10m, (2) T/RH 3m 10m, Physics site-11 Raw Data
**Overview**
The data included features wind, temperature, and turbulence measurements.
**Data Details**
Each met station (met.z18, met.z19, met.z21, and met.z23) consists of multiple levels of three-dimensional ultrasonic anemometers, RM Young 81000 (sampling frequency = 20 ...
Fernando, J. et al Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
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Surface Meteorological Station UND 17m, (3) Sonics 3m 10m 17m, (2) T/RH 3m 17m, Physics site-2 Raw Data
**Overview**
The data included features wind, temperature, and turbulence measurements.
**Data Details**
Each met station (met.z18, met.z19, met.z21, and met.z23) consists of multiple levels of three-dimensional ultrasonic anemometers, RM Young 81000 (sampling frequency = 20 ...
Fernando, J. et al Wind Energy Technologies Office (WETO)
Feb 14, 2016
1 Resources
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1 Resources
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