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 table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.

This is an exercise in optimizing the flow through a shrouded axial turbine to have the least resistance and to have optimal output and torque and energy. In this study, different variations of the original geometry of the current turbine designed by Hydrokinetic Energy Corp. (HEC) were evaluated for energy efficiency using Computational Fluid Dynamics (CFD). The objective was accomplished by a parametric study of the key geometric parameters for the shroud, the diffuser, and the hub. Project is part of the TEAMER RFTS 3 (request for technical support) program.

Measurements in the wake of a high-solidity cross-flow turbine in a laboratory flume obtained using Acoustic Doppler Velocimetry and Particle Image Velocimetry for the purposes of characterizing the turbine wake and comparing the methods.

Performance data of a 1-meter diameter cross-flow tidal turbine consisting of three NACA 0018 blades with two support struts with high deflection hydrofoils. Data was collected at the University of New Hampshire Jere A. Chase Ocean Engineering Lab within the tow tank. Three turbine parameters were varied: the blade materials, blade shape, and support strut position. A detailed description of the testing set-up and data files contained within the compressed "Turbine_Performance_Data.zip" file is in the "ReadMe.txt" file. Review of the original dataset "_Ver1" found that one of the tests had issues with one of the two redundant sensors. Resources were updated by replacing the dataset with measurements from the redundant sensor and are provided as version 2 "_Ver2".

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 TCST - Iterative learning for kite path optimization.pdf This paper presents an iterative learning control-based approach for optimizing the flight path geometry of a tethered MHK system. Tethered MHK systems, which replace the tower and turbine of a conventional system with a tether and a lifting body, capture energy by driving a generator with the tension in the tether. By spooling out tether during the high tension portions of cross-current flight and spooling in during low tension portions, net positive energy is generated over one cycle. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. Additionally, we present a realistic system model, along with lower-level path-following and power take-off (PTO) controllers. We then demonstrate the efficacy of our algorithm on this model in both uniform and realistic flow environments. Siddiqui ACC - Optimal spooling control of kites in variable flow.pdf This work focuses on the development of an adaptive control strategy that fuses Gaussian process modeling and receding horizon control to ideally manage the tradeoff between exploration (i.e., maintaining an adequate map of the resource) and exploitation (i.e., carrying out a mission, which consists in this work of harvesting the resource). The use of a receding horizon formulation aids in the consideration of limited mobility, which is characteristic of dynamical systems. In this work, we focus on an airborne wind energy (AWE) system as a case study, where the system can vary its elevation angle (tether angle relative to the ground, which trades off higher efficiency with higher-altitude operation) and flight path parameters in order to maximize power output in a wind environment that is changing in space and time. We demonstrate the effectiveness of the proposed approach through a data-driven study on a rigid wing-based AWE system. Reed ACC - Spatial optimization of kite paths.pdf This paper presents a technique for maximizing the power production of a tethered marine energy-harvesting kite performing cross-current figure-eight flight in a 3D spatiotemporally varying flow environment. To generate a net positive power output, the kite employs a cyclic spooling method, where the kite is spooled out while flying in high-tension crosscurrent figure-eight flight, then spooled in radially towards the base-station under low tension.