Application of a lumping method for fatigue design of monopile-based wind turbines using fully coupled and simplified models. (March 2022) - Katsikogiannis, George; Hegseth, John Marius; Bachynski-Polić, Erin E.
Abstract: The study presents different methods for fatigue assessment of monopile-based offshore wind turbines. Their accuracy and computational time is compared to full long-term time domain results. The damage-equivalent lumping method from Katsikogiannis et al. (2021) is further examined using nonlinear fully coupled time domain models as well as simplified, frequency domain, state–space models for three turbines (5 MW, 10 MW, 15 MW). The different dynamic characteristics of these turbines affect the resultant contour lines and lumped load cases for various wave conditions. The lumping method using fully coupled models had an accuracy of 92%–98% for the total fatigue damage along the support structure for all turbines, and decreased the computational time by 90%. The simplified models were able to accurately capture the dynamic characteristics of the turbines in the lumping process, resulting in similar lumped load cases and accuracy, with further reduction of the computational effort (96%). Long-term fatigue assessment in frequency domain generally resulted in discrepancies compared to time domain assessment (40%–80%), mainly due to the linear soil stiffness, sensitivity to damping (especially for parked conditions), and the simplified representation of the control system in the simplified models. Using the simplified models to select the lumped load cases, combined with time domain analyses of the lumped cases, resulted in the best combination of accuracy and computational effort. Highlights: Comparison of fatigue assessment methods for monopile-based offshore wind turbines. Damage-equivalent lumping method using fully coupled and simplified models. 92%–98% accuracy on support structure damage estimates for 5 MW, 10 MW, 15 MW turbines. Combining simplified and fully coupled models reduces the computational cost by 96%.