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Showing results 1 - 8 of 8.
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"iterative learning"×

Control-based optimization for tethered tidal kite

This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission. Cobb...
Vermillion, C. et al North Carolina State University
Mar 02, 2020
3 Resources
0 Stars
Publicly accessible

CalWave First Iterative PTO Description

This documents summarizes a preliminary first iterative design of a PTO device developed by CalWave. The document includes controls, hydraulic, and electric architectures from the first iteration of the CalWave PTO design that match requirements set out by the "CalWave Holistic PT...
Kojimoto, N. et al CalWave Power Technologies Inc.
Dec 06, 2021
2 Resources
0 Stars
Awaiting release

TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters

Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement Learning (DRL) control in the wave tank. Unlike model-based controls, DRL control is model-free and can directly max...
Zou, S. et al Michigan Technological University
Mar 07, 2025
7 Resources
0 Stars
Awaiting curation

Fish Detection AI, sonar image-trained detection, counting, tracking 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 ...
Gutstein, S. et al Water Power Technology Office
Aug 25, 2024
6 Resources
0 Stars
Curated

StingRAY Failure Mode, Effects and Criticality Analysis: WEC Risk Registers

Analysis method to systematically identify all potential failure modes and their effects on the Stingray WEC system. This analysis is incorporated early in the development cycle such that the mitigation of the identified failure modes can be achieved cost effectively and efficient...
Rhinefrank, K. Columbia Power Technologies, Inc.
Jul 25, 2016
18 Resources
0 Stars
Publicly accessible

Underwater Target Detection Software Demonstration on the RivGen Turbine

This repository includes data, object detection models, and processing scripts necessary to evaluate the accuracy of the object detection models created for the underwater target detection software demonstration on the RivGen turbine project and to reproduce the performance metric...
Joslin, J. et al MarineSitu
Dec 17, 2024
2 Resources
1 Stars
Curated

CODAS Data from Oliktok Point, Beaufort Sea, Alaska

Cryosphere/Ocean Distributed Acoustic Sensing (CODAS) data collected from the Beaufort Sea, Alaska, using ~37.4 km of dark telecommunications fiber located at Oliktok Point, Alaska. Data were collected with a Silixa iDAS, using 10 m gauge length, 2 m spatial resolution, and 1000 H...
Baker, M. and Abbott, R. Sandia National Laboratories
Aug 08, 2023
23 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
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  • The MHKDR is the submission point for all data collected from research funded by the U.S. Department of Energy's Marine and Hydrokinetic Power Program.
  • Content is available under Creative Commons Attribution 4.0 unless otherwise noted.

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