Fatigue Reliability Analysis of Offshore Wind Turbines Under Combined Wind–Wave Excitation via Direct Probability Integral Method

As offshore wind turbines develop into deepwater operations, accurately quantifying the impact of stochastic excitation in complex sea environments on offshore wind turbines and conducting structural fatigue reliability analysis has become challenging. In this paper, based on long-term wind–wave reanalysis data from the South China Sea, a novel direct probability integral method (DPIM) is developed for the stochastic response and fatigue reliability analysis of the key components for the floating offshore wind turbine structures, under combined wind–wave excitation. A 5 MW floating offshore wind turbine is considered as the research object, and a comprehensive analysis of the wind turbine system is performed to assess the short-term fatigue damage at the tower base and blade root. The proposed method’s accuracy and efficiency are validated by comparing the results to those obtained from Monte Carlo simulations (MCS) and a subset simulation (SSM). Additionally, a sensitivity analysis is conducted to evaluate the impact of different environmental parameters on fatigue damage, providing valuable insights for the design and operation of FOWTs in varying sea conditions. Furthermore, the results indicate that the fatigue life of floating offshore wind turbine (FOWT) structures under combined wind–wave excitation meets the design requirements. Notably, the fatigue reliability of the wind turbine under aligned wind–wave conditions is lower compared to misaligned wind–wave conditions.

Authors

Institutions

Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-03-05
DOI
https://doi.org/10.3390/jmse13030506
Citations
5
Primary Topic
Wind and Air Flow Studies
Type
article
Field-Weighted Citation Impact
4.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fatigue Reliability Analysis of Offshore Wind Turbines Under Combined Wind–Wave Excitation via Direct Probability Integral Method

Zhuojia Fu, Hanshu Chen, Xiaoting Liu, Jau M. Ding et al.
5 citations
Journal of Marine Science and Engineering
Wind and Air Flow Studies
4.00
article

Fatigue Reliability Analysis of Offshore Wind Turbines Under Combined Wind–Wave Excitation via Direct Probability Integral Method

Zhuojia Fu, Hanshu Chen, Xiaoting Liu, Jau M. Ding, Youssef F. Rashed
article en
5 citations

Abstract

As offshore wind turbines develop into deepwater operations, accurately quantifying the impact of stochastic excitation in complex sea environments on offshore wind turbines and conducting structural fatigue reliability analysis has become challenging. In this paper, based on long-term wind–wave reanalysis data from the South China Sea, a novel direct probability integral method (DPIM) is developed for the stochastic response and fatigue reliability analysis of the key components for the floating offshore wind turbine structures, under combined wind–wave excitation. A 5 MW floating offshore wind turbine is considered as the research object, and a comprehensive analysis of the wind turbine system is performed to assess the short-term fatigue damage at the tower base and blade root. The proposed method’s accuracy and efficiency are validated by comparing the results to those obtained from Monte Carlo simulations (MCS) and a subset simulation (SSM). Additionally, a sensitivity analysis is conducted to evaluate the impact of different environmental parameters on fatigue damage, providing valuable insights for the design and operation of FOWTs in varying sea conditions. Furthermore, the results indicate that the fatigue life of floating offshore wind turbine (FOWT) structures under combined wind–wave excitation meets the design requirements. Notably, the fatigue reliability of the wind turbine under aligned wind–wave conditions is lower compared to misaligned wind–wave conditions.

Journal of Marine Science and EngineeringVol. 13(3)
Cairo University (EG), China Three Gorges Corporation (China) (CN), Hohai University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 7%
Wind and Air Flow Studies
4.00
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.