At present, monopile-supported offshore wind turbines (MOWTs) are widely used in offshore wind farms. The influence of blade flexibility on the dynamic behaviors of MOWTs excited by waves and earthquakes was investigated in this study. Numerical analysis models were established for 5 MW and 10 MW MOWTs, incorporating flexible and rigid blade configurations. The modes and natural frequencies of the full system were compared between these two numerical models, and their dynamic responses were evaluated under wave-only and earthquake-only excitations. It was revealed that the influence of blade flexibility on the first- and second-order modes of the system can be neglected. The dynamic response of these MOWTs under wave excitation can be predicted by the rigid blade model, where the maximum relative difference is less than 5%. However, higher-order modes of the system are significantly affected by the blade flexibility. Under high-frequency excitations, these higher-order modes of the system are remarkably stimulated. Additionally, a large relative difference, exceeding 50%, is detected when the rigid blade model is used to predict the seismic response of the two MOWTs. Consequently, the blade flexibility should be adequately modeled when predicting the dynamic response of OWTs.

Pile running during the installation of offshore large diameter pipe piles poses a significant challenge to construction safety and pile bearing capacity. This paper proposes a deep learning (DL)-based method for predicting pile running occurrences. Utilizing a dataset of pile installation records collected from various construction sites, the DL model was trained and tested. The predictive capacity of the DL model was compared with conventional analytical methods, demonstrating its superior performance in terms of accuracy and robustness. Additionally, the SHAP (SHapley Additive exPlanations) method was employed for the sensitivity analysis of the model’s input variables, and the resultant importance ranking agreed well with the findings of existing studies, thus enhancing the reliability and interpretability of the model’s predictions.

Dynamic state estimation of floating offshore wind turbines (FOWTs) in complex marine environments is a core challenge for digital twin systems. This study proposes a joint estimation framework that integrates windowed dynamic mode decomposition (W-DMD) and an adaptive strong tracking Kalman filter (ASTKF). W-DMD extracts dominant modes under stochastic excitations through a sliding-window strategy and constructs an interpretable reduced-order state-space model. ASTKF is then employed to enhance estimation robustness against environmental uncertainties and noise. The framework is validated through numerical simulations under turbulent wind and wave conditions, demonstrating high estimation accuracy and strong robustness against sudden environmental disturbances. The results indicate that the proposed method provides a computationally efficient and interpretable tool for FOWT digital twins, laying the foundation for predictive maintenance and optimal control.

As offshore wind energy industry advances into deeper water recently, jacket foundations become one of the predominant support structure types for far-sea wind farms. To ensure the safety and reliability of offshore wind turbine (OWT) jacket foundations in the complex environments of far-seas, the investigation of their resistance capabilities to extreme ocean wave is essential. In this study, the OWT jacket foundations in the sea area of Cangnan and Lianjiang are adopted to conduct a typical case study. This study employs a full-scale jacket foundation to carry out some full-scenario, large-scale hydrodynamic numerical simulations considering the combined action of wave and current. It is revealed that for OWT jacket foundations in Cangnan and Lianjiang, China, under an extreme condition with approximately 26 m wave height and 18 s wave period, the peak wave impact and horizontal force on the jacket foundation are approximately 190 kPa and 18,000 kN, respectively. Furthermore, this study discusses the wave profile evolution characteristics around the jacket foundation and the correlation between wave run-up and wave height. These findings provide a good case study and technical reference for the full-scale fine simulation of wave forces on OWT jacket foundations in far-sea areas.

Offshore monopile foundations endure complex loads during service. They bear vertical loads from the superstructure’s self-weight and lateral cyclic loads (e.g., wind, waves), while near-coastal seabeds are usually sloped. To resolve these issues, model pile tests under combined vertical and lateral cyclic loads were carried out to study how slope angle and vertical load affect monopile deformation. A numerical model was validated via comparison with test results and then used to reveal the development of cumulative deformation in offshore sloped monopiles under the above combined loads. The results show that, below 1000 cycles, the cumulative displacement of the pile increases logarithmically with the number of cycles. As the slope angle increases, the cumulative deformation increases. In these tests, the cumulative deformation of the pile increases by 114% compared to the results of the flat site, but it decreases with an increase in vertical load. As such, when a 3 N vertical load is applied to the pile top, its deformation at the flat site decreases by 20%, but its deformation at a 20° slope site decreases by 10%. Finally, a predicted formula is proposed for offshore monopiles with the effect of slope angle, and this formula can provide a preliminary assessment method of cumulative.