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Author ORCID Identifier

https://orcid.org/0000-0001-6033-2654

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Mechanical Engineering

Year Degree Awarded

2020

Month Degree Awarded

September

First Advisor

Matthew A. Lackner

Subject Categories

Aerodynamics and Fluid Mechanics | Computer-Aided Engineering and Design | Systems Engineering and Multidisciplinary Design Optimization

Abstract

Floating offshore wind turbines are an immature technology with relatively high costs and risk associated with deployment. Of the few floating wind turbine prototypes and demonstration projects deployed in real metocean conditions, all have used standard turbines design for onshore or offshore fixed bottom conditions. This neglects the unique unsteady aerodynamics brought on by floating support structure motion. While the floating platform has been designed and optimized for a given rotor, the global system is suboptimal due to the rotor operating in conditions outside of which it was design for. If the potential offered by floating wind turbines is to be realized, offering access to deep water near-shore, costs need to continue to be reduced. This dissertation is the first known design study that considers the optimization of wind turbine rotors specifically for floating conditions.

Two design optimization methodologies are presented using different analysis fidelity levels. A relatively computationally efficient, state-state blade element moment optimization of floating wind turbine blades is presented that will be useful for future systems level optimization studies. A higher fidelity methodology is then presented, using time-domain aeroelastic simulations to fully capture the unsteady aerodynamics and dynamic couplings between the rotor and platform motion throughout the optimization process. The principal finding of these studies is that low induction rotors are a promising technology pathway for future FOWT systems, reducing the severity of cyclical loading due to platform motion.

Available for download on Monday, March 01, 2021

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