Investigation on the sensitivity of flexible foundation models of an offshore wind turbine under earthquake loadings

This paper presents an investigation on the sensitivity of flexible foundation models of offshore wind turbines subjected to earthquake loadings. A novel seismic analysis framework (SAF) is developed and implemented in an open source aero-hydro-elastic analysis tool, “FAST”, for accurately modelling the effects of seismic loadings on offshore wind turbines. SAF has been validated through comparisons against experimentally validated numerical tools, GH Bladed and NREL Seismic. The behaviours of three flexible foundation models, namely, the apparent fixity (AF), coupled springs (CS) and distributed springs (DS) methods, subjected to earthquake loadings have been examined in relation to a fixed foundation. A total of 224 fully coupled nonlinear simulations of the foundation models are performed using a dataset of 28 earthquake records which are scaled using the target spectrum matching technique to represent the actual seismic effects of the selected sites. The results reveal that the AF model appropriately reflects realistic situations in comparison to the CS model. In addition, the amplitudes of vibration induced by the earthquake loadings are larger for flexible foundations compared to the rigid foundation. The main contribution to the out-of-plane bending moment of the support structure at the mudline comes from the wind loading for all the foundation models. This study has also found that the 2nd flap mode of blade is activated by the earthquake loadings for the AF and DS models but not for the rigid and CS models. As a result, the peak blade-root bending moment is found to be more sensitive to pseudo spectral acceleration (PSA) for the AF and DS models. Furthermore, the peak tower-top displacement and mudline bending moment increase linearly with PSA for all the examined models. This study contributes to the evaluation of the wind turbine responses subjected to earthquakes or combined multi-hazard loadings in the operational state. © 2019 Elsevier Lt