Date of Award

Summer 8-18-2023

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)

Department

Mechanical Engineering

Advisor

Andrew J Goupee

Second Committee Member

Richard W Kimball

Third Committee Member

Lauren Ross

Abstract

This thesis presents a tuned OpenFAST hydrodynamics model of three iterations of the VolturnUS semisubmersible floating offshore wind turbine (FOWT) floating platform. The three floating platforms under consideration share similar geometric features, including three legs, rectangular bottom beams, and cylindrical pontoons, but range in size from 6 MW to 15 MW. The proposed tuning method focuses on improving the second-order hydrodynamic motions of the FOWT hull in OpenFAST using a potential flow solution and viscous drag from the Morison equation. Additional settings in OpenFAST such as wave stretching and calculation of the wave kinematics at the instantaneous location of the hull were used.

A parametric study was completed on the VolturnUS 11 MW hull for a 50-year return period wave case to determine the combination of tuning parameters that provided the best overall second-order response when compared to experimental data. A baseline potential flow simulation model and a potential flow model with a global quadratic drag matrix based on free-decay data (referred to as the quadratic drag model) were also developed for comparison to the tuned model. The tuning parameters determined from the parametric study were then applied to other sea states for the VolturnUS 11 MW hull and the 6 MW and 15 MW hulls. The proposed tuning method was found to largely provide a better response than the quadratic drag and baseline models when compared to the experimental data load cases for the VolturnUS 11 MW hull. The response comparison for the 6 MW and 15 MW hulls was found to be less conclusive, with the quadratic drag model providing similar or better results than the tuned model for some metrics and worse results for others when compared to experimental data.

Available for download on Thursday, October 09, 2025

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