Time-Domain Fatigue Analysis Methodology for Semi-Submersible Hulls of Floating Wind Turbines

24 Pages Posted: 2 Jan 2025

See all articles by Shuaishuai Wang

Shuaishuai Wang

Norwegian University of Science and Technology (NTNU)

Torgeir Moan

Norwegian University of Science and Technology (NTNU)

Zhen Gao

affiliation not provided to SSRN

Abstract

This paper deals with a time-domain fatigue analysis methodology for semi-submersible FWT hulls, using a 10-MW semi-submersible FWT as a case study. It provides a systematic procedure for both short- and long-term fatigue analysis, highlighting the importance of wind and wave loads, as well as the probability distributions of environmental conditions. A fully coupled dynamic analysis of the FWT, employing a multi-body floater, is conducted to compute internal global loads and time-domain stresses on the hull. Short-term fatigue damage is examined across various wind-wave directions, different environmental conditions, and random wind and wave samples, identifying critical loading scenarios. A comprehensive long-term analysis, involving 10182 one-hour time-domain simulations across three wind-wave directions, is conducted for five offshore sites in the North Sea and one offshore site in the China Sea. The fatigue damage in different pontoon locations of the floater at different offshore sites, is estimated and discussed in view of fatigue design check. The comprehensive analysis approach serves as a reference to validate simplified, efficient fatigue analysis procedures in an accompanying paper. Limitations of the present work are identified, pointing to future research directions aimed at mitigating fatigue risks.

Keywords: floating wind turbine, semi-submersible floater, multibody modeling approach, time-domain fatigue analysis methodology, short-term fatigue damage, long-term fatigue damage

Suggested Citation

Wang, Shuaishuai and Moan, Torgeir and Gao, Zhen, Time-Domain Fatigue Analysis Methodology for Semi-Submersible Hulls of Floating Wind Turbines. Available at SSRN: https://ssrn.com/abstract=5080108 or http://dx.doi.org/10.2139/ssrn.5080108

Shuaishuai Wang (Contact Author)

Norwegian University of Science and Technology (NTNU) ( email )

Høgskoleringen 7A
Trondheim, 7033
Norway

Torgeir Moan

Norwegian University of Science and Technology (NTNU) ( email )

Høgskoleringen 7A
Trondheim, 7033
Norway

Zhen Gao

affiliation not provided to SSRN ( email )

No Address Available

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