Parametric Curve Comparison for Modeling Floating Offshore Wind Turbine Substructures

Journal Article (2023)
Author(s)

Adebayo Ojo (University of Strathclyde)

M. Collu (University of Strathclyde)

A. Coraddu (TU Delft - Ship Design, Production and Operations)

Research Group
Ship Design, Production and Operations
Copyright
© 2023 Adebayo Ojo, Maurizio Collu, A. Coraddu
DOI related publication
https://doi.org/10.3390/en16145371
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 Adebayo Ojo, Maurizio Collu, A. Coraddu
Research Group
Ship Design, Production and Operations
Issue number
14
Volume number
16
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

The drive for the cost reduction of floating offshore wind turbine (FOWT) systems to the levels of fixed bottom foundation turbine systems can be achieved with creative design and analysis techniques of the platform with free-form curves to save numerical simulation time and minimize the mass of steel (cost of steel) required for design. This study aims to compare four parametric free-form curves (cubic spline, B-spline, Non-Uniform Rational B-Spline and cubic Hermite spline) within a design and optimization framework using the pattern search gradient free optimization algorithm to explore and select an optimal design from the design space. The best performance free-form curve within the framework is determined using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The TOPSIS technique shows the B-spline curve as the best performing free-form curve based on the selection criteria, amongst which are design and analysis computational time, estimated mass of platform and local shape control properties. This study shows that free-form curves like B-spline can be used to expedite the design, analysis and optimization of floating platforms and potentially advance the technology beyond the current level of fixed bottom foundations.