Project

The candidate will be responsible for exploiting the recent advances in performance-based approaches and machine learning (ML) to develop a fully probabilistic performance-based assessment method for floating offshore wind turbines (FOWT) foundation design. To ensure safety in the design, the performance of FOWT foundations subjected to aero- and hydrodynamic loadings should be quantified. The method will take into account stochastic metocean conditions and variability of soil properties. Explainable Artificial Intelligence (XAI) techniques will be utilised to model the fragility function of FOWT foundations over a range of loading intensities. The project will focus on developing a performance-based framework to predict the response of FOWT foundations under extreme environmental loads. The performance-based design model will capture the uncertainties present in the data as well as in the XAI-driven physics-based model.