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PoroTomo - Distributed Temperature Sensing (DTS) Measurements made in Brady Observation Well 56-1
This submission is a follow-up to Distributed Temperature Sensing (DTS) measurements made in Brady observation well 56-1 during the PoroTomo field experiment conducted in March,... -
ORPC RivGen Hydrokinetic Turbine Wake Characterization
Field measurements of mean flow and turbulence parameters at the Kvichak river prior to and after the deployment of ORPC's RivGen hydrokinetic turbine. Data description and... -
Distributed Acoustic Sensing (DAS) of Strain at Earth Tide Frequencies: Laboratory Tests
The solid Earth strains in response to the gravitational pull from the Moon, Sun, and other planetary bodies. Measuring the flexure of geologic material in response to these... -
Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging - Test Data and Processing
This dataset contains experimental results from testing the Halona wave energy converter (WEC) in both fixed and floating configurations. This dataset reflects a 1/10th scale... -
Underwater Mapping Results for Seabotix vLBV300 Vehicle with Tritech Gemini 720i Imaging Sonar near Newport, OR
This document presents results from tests to demonstrate underwater mapping capabilities of an underwater vehicle in conditions typically found in marine renewable energy... -
TigerRAY Moored Deployment Data
This respiratory contains TigerRAY moored deployment data for each day in which data was collected between January 10, 2024 and March 3, 2024. For sensors on and inside... -
Admiralty Inlet Advanced Turbulence Measurements: Final Data and Code Archive
Data and code that is not already in a public location that is used in Kilcher, Thomson, Harding, and Nylund (2017) "Turbulence Measurements from Compliant Moorings - Part II:... -
Material Properties for Brady Hot Springs Nevada USA from PoroTomo Project
The PoroTomo team has completed inverse modeling of the three data sets (seismology, geodesy, and hydrology) individually, as described previously. The estimated values of the... -
MBARI WEC 2021 deployment
This dataset includes data from the Monterey Bay Aquarium Research Institute (MBARI) wave energy converter (WEC) and a nearby located Sofar Spotter buoy. The Monterey Bay... -
Small Scale WEC Performance Modeling Data
Small Scale WEC Performance Modeling Data is performance data from downscaled models of common WEC devices and their calculated performance outputs. This data is used by the... -
TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Test Logs and Results
Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full... -
RivGen Controller Performance Raw Data, Igiugig, AK
Contains raw data for operations of Ocean Renewable Power Company (ORPC) RivGen Power System in Igiugig 2015 in Matlab data file format. Two data files capture the data and... -
DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period
This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady... -
HERO WEC 2024 Hydraulic Configuration Deployment Data
The following submission includes raw and processed data from the in water deployment of NREL's Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), in the... -
Utah FORGE: Friction-Permeability-Seismicity Laboratory Experiments with Non-Linear Acoustics
Laboratory experimental data on saw-cut interface of Westerly Granite and Utah Forge granitoid rocks. Experiments include velocity-stepping and fluid pressure stepping... -
2017 Western Passage Tidal Energy Resource Characterization Measurements
These data are from tidal resource characterization measurements collected between April and July 2017 in Western Passage near Eastport, Maine, USA. The dataset contains the... -
Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files...
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