Offshore wind energy is expanding rapidly as governments aim for net-zero emissions, with monopiles and jackets being the primary foundation methods for offshore wind turbines (OWTs). Supply chains, heavier turbines and deeper waters influence the efficiency of jacket foundations. This research considers a jacket-founded OWT. The development of OWTs has sparked its expansion to building sites with a proclivity to earthquakes. Such loading involves soil-structure interaction of which more needs to be known to improve accurate computational modelling.

Current practice of Siemens Gamesa Renewable Energy (SGRE) is to perform aeroelastic simulations in their computational tool BHawC. The Foundation Designer delivers a foundation Superelement to maintain secrecy. The equation of motion for the jacket foundation can then be solved linearly with a reduced amount of unknowns. However, prevalence of nonlinearity in soil raises the question to what degree a linear model adequately captures the response.

This study investigates the impact of soil nonlinearity on OWT dynamic behavior under seismic loads by comparing linear and nonlinear soil models. The analysis involves performing seismic simulations using multiple earthquakes. Another distinction is made through soil models with different characteristics. Nonlinearity is introduced to the soil stiffness and energy dissipation mechanism under cyclic loading. The investigated variations are a linear (elastic), geometrically nonlinear (nonlinear elastic) or both geometrically and physically nonlinear soil model (nonlinear plastic).

The numerical model consists of a Rotor Nacelle Assembly (RNA), tower, transition piece, jacket, piles and soil springs. Beam elements are used for the tower, jacket and piles. The transition piece is simulated by stiffening the top jacket braces. The RNA is modelled using a lumped mass with rotational inertia. It is vertically eccentric to the tower top and connected with a rigid link. The earthquake is applied uniform over depth and only horizontal movements are considered.

The findings underscore a difference in results between the linear and nonlinear models. The evaluated results from simulations consist of forces, displacements and dynamic characteristics of the structure. Also noted should be that the computational time of the linear model is significantly lower. The results found in models can differ greatly due to the loading spectrum with highly varying frequency peaks. Another factor is softening of the stiffness. The frequency domain of the elastic model results consists of narrow peaks at the system's natural frequencies. The peaks for the nonlinear elastic model are wider due to softening of the stiffness. For the structure used in this research, softening introduces coupled modes with greater displacements along the height of the structure. This makes it possible for the evaluated results to have higher values, even with less energy put into the system. The plastic models' peaks are of a width in between the elastic and nonlinear elastic model due to the combined use of isotropic hardening and nonlinear stiffness. When the model falls back on its initial stiffness upon unloading, the eigenfrequencies related to that stiffness become more pronounced. To match the occupancy of wider frequency peaks, loading and unloading should both happen nonlinearly. This can be achieved by using kinematic hardening instead of isotropic hardening. Plasticity generally reduces peak displacement and sectional moment values and nonlinear stiffness broadens the response frequency spectrum. Careful consideration of cyclic material behaviour, eigenfrequencies and loading characteristics are essential for a realistic model.

Technology improvements and growing maturity of the offshore wind industry have resulted in significant cost reductions and rise in demand. More can be achieved by focusing on improving the understanding of key design areas of an offshore wind turbine (OWT). Since fatigue is one of the main design criteria for offshore structures and little is known about fatigue cumulative development in time under operating conditions, it formed the basis of this thesis. However, fatigue is a complex phenomenon that is dependent on numerous interlinked parameters, such as damping, loading type, and stiffness of support structure (SUS). For the purpose, data analysis was performed on measurements which were gathered over a period of four years from a monopile-supported OWT site. The measurement data included information about the environmental and operational conditions of the OWT; and strain, acceleration and inclinometer readings from its SUS. Use of different data acquisition systems during the measurement campaign inherently required significant efforts to synchronise and preprocess raw data to appropriate state for data analysis. Time-dependent lag was identified via computation of cross-correlation sequences between data segment pairings, and the lag was successfully corrected. With the use of a standardized rainflow cycle counting algorithm, strain-derived moment time series were converted to constant amplitude events, which could be used to derive damage equivalent bending moments, M-N curves and fatigue damage accumulation frequency spectra. Short-term damage equivalent bending moment (STEL) was revealed to have a linear dependency with turbulence intensity when the OWT was in the run-up operational state. Additionally, the fatigue damage was demonstrated to be higher for downstream turbines due to wake effects. Also, fatigue life consumption of OWT SUS increases above rated wind speed conditions despite decrease in load magnitude due to increase in SUS response frequency. The latter was confirmed with fatigue damage accumulation frequency spectra, which revealed that the importance of high frequency band (1 – 5 Hz) increases in conjunction with wind speed at above rated wind speed conditions. However, most of the overall fatigue damage is accumulated at the low frequency band, which associated with wind and wave loading, first SUS bending modes, 1P and 3P rotor harmonics.