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Tidal Resource Data from Sequim Bay Inlet, WA, August 2020
Data from a Nortek Signature1000 deployed on a lander for 14 days in Aug 2020 in the entrance to Sequim Bay, WA. Raw data were processed using the DOLfYN python package and standardized using the ME Data Pipeline python package, tsdat version 0.2.12. Processed data were partitione...
McVey, J. and Cavagnaro, R. Pacific Northwest National Laboratory
Aug 13, 2020
17 Resources
1 Stars
Publicly accessible
17 Resources
1 Stars
Publicly accessible
PacWave Site Observations
This data submission contains raw and near-real-time updated data from FLOATr (Fixed Location Ocean and Atmosphere Tracking) buoys and Sofar Spotter wave buoys at sites in the PacWave open-ocean testing facility operated by Oregon State University, located off the coast of Newport...
Hembrough, B. et al Oregon State University
Jan 01, 2020
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow
This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A t...
Bharath, A. et al National Renewable Energy Laboratory
Dec 16, 2022
17 Resources
0 Stars
Publicly accessible
17 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
30 Resources
0 Stars
Publicly accessible
Fish Detection AI, Optic and Sonar-trained Object Detection Models
The Fish Detection AI project aims to improve the efficiency of fish monitoring around marine energy facilities to comply with regulatory requirements. Despite advancements in computer vision, there is limited focus on sonar images, identifying small fish with unlabeled data, and ...
Slater, K. et al Water Power Technology Office
Jun 25, 2014
12 Resources
0 Stars
Curated
12 Resources
0 Stars
Curated