Abstract
Offshore wind turbines (OWTs) have emerged as a reliable source of renewable energy, witnessing massive deployment across the world. While there is a wide range of support foundations for these structures, the monopile and jacket are most utilised so far; their deployment is largely informed by water depths and turbine ratings. However, the recommended water depth ranges are often violated, leading to cross-deployment of the two foundation types. This study firstly investigates the dynamic implication of this practice to incorporate the findings into future analysis and design of these structures. Detailed finite element (FE) models of Monopile and Jacket supported offshore wind turbines are developed in the commercial software, ANSYS. Nonlinear Soil springs are used to simulate the soil-structure interactions (SSI) and the group effects of the jacket piles are considered by using the relevant modification factors. Modal analyses of the fixed and flexible-base cases are carried out, and natural frequencies are chosen as the comparison parameters throughout the study. Secondly, this study constructs a few-parameters SSI model for the two FE models developed above, which aims to use fewer variables in the FE model updating process without compromising its simulation quality. Maximum lateral soil resistance and soil depths are related using polynomial equations, this replaces the standard nonlinear soil spring model. The numerical results show that for the same turbine rating and total height, Jacket supported OWTs generally have higher first-order natural frequencies than Monopile supported OWTs, while the reverse is true for the second-order vibration modes, for both fixed and flexible foundations. This contributes to future design considerations of OWTs. On the other hand, with only two parameters, the proposed SSI model has achieved the same accuracy as that using the standard model with seven parameters. It has the potential to become a new SSI model, especially for the identification of soil properties through the model updating process.