An efficient fatigue assessment model of offshore wind turbine using a half coupling analysis

Han, Chaoshuai and Mo, Changguan and Tao, Longbin and Ma, Yongliang and Bai, Xu (2022) An efficient fatigue assessment model of offshore wind turbine using a half coupling analysis. Ocean Engineering, 263. 112318. ISSN 0029-8018 (https://doi.org/10.1016/j.oceaneng.2022.112318)

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Abstract

Fatigue failure is an important issue for offshore wind turbine support structures. Especially, fully coupled time domain analysis will lead to high computational burden. Therefore, accurate and efficient fatigue evaluation methods have always been the common goal pursued by the industry and researchers. This paper evaluates fatigue damage under combined wind and wave loading, using a fixed jacket offshore wind turbine as an example. A half coupling model (HCM) with distinct advantage by considering aerodynamic damping and structural damping is developed for dynamic response analysis of offshore wind turbine. The precision and effectiveness of the developed HCM is verified to be reasonable by comparing with numerical simulated results. A linearized Morison equation is proposed to achieve frequency domain analysis of wave response which is embedded as a programming module in ANSYS. Based on the developed model, dynamic response analysis is carried out under wind and wave loading, and then combined stress spectra at the location of different tubular joints (X-joint and K-joint) are obtained. To consider the interaction of wind and wave, a spectral fatigue combination rule based on Han and Ma's method is used to calculate fatigue damage. The developed combination rule is assessed by compared with time domain fatigue result based on rainflow cycle counting. Analysis using the newly developed model and method demonstrates a high accuracy and efficiency for fatigue damage prediction.

ORCID iDs

Han, Chaoshuai, Mo, Changguan, Tao, Longbin ORCID logoORCID: https://orcid.org/0000-0002-8389-7209, Ma, Yongliang and Bai, Xu;
CORE (COnnecting REpositories)