The reliability of structural safety assessments for offshore wind turbines is often compromised by time-dependent corrosion effects and the high computational cost of fluid–structure interaction analysis. This study proposes a data-driven framework for predicting the degradation of offshore wind turbine support structures under time-dependent corrosion. First, the multi-faceted mechanisms of corrosion progression were analyzed to quantitatively evaluate the evolution of structural cross-sectional damage and residual load-bearing capacity. A structural mechanical equivalent method was then proposed and integrated with a high-fidelity fluid–structure coupled model that takes into account corrosion effects, and a corresponding time-dependent structural response database was established. Then, the data extrapolation techniques were applied to unsimulated response samples, enabling comprehensive assessment and accurate forecasting of structural states. Validation under different data sampling strategies shows that the dense strategy achieves the highest accuracy, with stress and deformation errors of 0.31% and 2.23%, the moderate strategy yields errors of 2.47% and 2.58%, while the sparse strategy results in larger errors of 3.31% and 8.71%, but still captures the overall evolution trend. It demonstrates that the proposed approach provides a reliable and efficient predictive tool for service-life assessment and structural response evaluation of offshore wind turbine support structures.
Cao et al. (Tue,) studied this question.