As offshore wind power continues to develop, with increased capacity and ability to function in deeper waters, jacket-type offshore wind turbines (OWTs) are becoming increasingly challenged by complex environmental loads and significant structural vibration issues. This study focuses on a 10 MW jacket foundation OWT and proposes an optimization approach for tuned mass damper (TMD) parameters based on the artificial bee colony (ABC) algorithm. A fully coupled model of the OWT and TMD system is developed, and the TMD parameters are optimized through frequency-domain analysis and time-domain simulations. The vibration control performance of the optimized TMD is then evaluated under combined wind, wave, and seismic excitations. The results show that the passive TMD achieves substantially greater vibration suppression under seismic loading compared to combined wind and wave conditions. In addition, the optimized TMD reduces the standard deviations of tower-top displacement and tower-base bending moment by more than 50%, significantly enhancing the dynamic response of the structure and contributing to an extended fatigue life.

To advance global sustainability and meet climate targets, the development of reliable renewable energy infrastructure is paramount. Offshore wind energy is a key factor in achieving this goal, and ensuring its operational efficiency requires a deep understanding of the sources of uncertainty faced by offshore wind turbines (OWTs). This study proposes and implements an integrated framework for sensitivity analysis (SA) to investigate the key sources of uncertainty influencing the dynamic response of an OWT. This framework is based on the XGBoost surrogate model and Sobol’s method, aiming to efficiently and accurately quantify the impact of various uncertain parameters. A key methodological novelty lies in the integrated use of Sobol’s method and SHapley Additive exPlanations (SHAP), which provides a unique cross-validating mechanism for the sensitivity results. This study demonstrates the strongly condition-dependent nature of the OWT’s sensitivity characteristics by analyzing design load cases. The results indicate that wind speed is the dominant factor influencing the structural response under normal operating conditions. In contrast, under extreme shutdown conditions, the response of the OWT is primarily governed by the physical and material properties of the structure. In addition, the high consistency between the results of SHAP technology and the SA results obtained by Sobol’s method confirms the reliability of the proposed framework. The identified key sources of uncertainty provide direct practical insights for design optimization and reliability assessment of OWTs.

The characteristics and energies of infragravity waves (IGWs) are investigated based on field observations. IGWs are closely related to short waves, and the wave spectrum integration method was adopted to separate sea and swell waves. By comparing the performance of the separation frequency in the spectral shape and the correlation between the IGWs and short waves, it was found that the dynamic separation frequency was more reasonable than the commonly used fixed separation frequencies (0.125 and 0.14 Hz). Infragravity waves exhibited a stronger correlation with swell than with wind waves, with a correlation coefficient exceeding 0.8. Therefore, swell wave heights were used instead of short-wave heights for the energy evaluation of the IGWs. The spectral domain method was adopted to separate the incident and reflected IGWs, and, combined with the bound infragravity waves (BIG), was used to obtain the wave height of each IGW component. The wave heights of the BIG and swell exhibited a significant quadratic relationship. The correlation between the free infragravity waves (FIG) and swell was weaker than that of the BIG. An empirical expression between the wave heights of total incident IGWs and the swell waves was obtained, and the exponent α related to swell wave heights was approximately 1.0.