Analysis reveals improved extreme response estimates in floating offshore wind turbines, suggesting enhanced design reliability using IFORM-based models.
Long-term extreme response prediction is crucial for the design of floating offshore wind turbines (FOWTs) and their supporting structures, and the statistical extrapolation of extreme responses is a widely used approach for the limit states design of FOWTs. To reduce computational demands, the environmental contour methods (ECM) are adopted to predict long-term responses more efficiently. However, the ECMs are derived based on the inverse reliability method by decoupling the structural response from the environmental variables. This decoupling may overlook the response variability, potentially leading to inaccurate assessments of long-term extreme responses. To address this limitation, an extended ECM based on the inverse first-order reliability method (IFORM) is proposed within a four-dimensional model that incorporates short-term extreme response uncertainties. The probability distributions of short-term extreme responses are determined using numerical simulations and the peak-over-threshold (POT) method. And the multivariate distribution of environmental conditions is modeled using the C-vine copula. Taking the 5 MW semi-submersible FOWT as an example, the applicability of the proposed model is demonstrated and discussed by predicting two extreme responses, including tower base pitching moment (TBPM) and mooring tension. Furthermore, the return levels of extreme responses are obtained for both the proposed model and the traditional ECM, providing guidance for parameter selection in future designs.
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Zhao et al. (2025) studied this question.
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