Baran Yeter is a Research Associate at the Department of Naval Architecture, Ocean, and Marine Engineering at the University of Strathclyde. He has been conducting extra activities as a part of the scientific committee of international journals such as Ocean Engineering, Engineering Structures, Wind Energy, and Renewable Energy. He is a member of the Fatigue and Fracture Committee for the International Ship and Offshore Structures Congress (ISSC) as well.
The objective of the present study is to assess the fatigue reliability of a spar-type floating offshore wind turbine based on fracture mechanics. Although floating offshore wind turbines (FOWT) have been historically much more expensive than their fixed bottom peers, the levelised cost of energy of FOWT has decreased dramatically due to increasing wind turbine size, higher capacity factors, innovative designs, and optimal operational strategies. However, there is still much to be done to bring the cost down, especially from the operational and maintenance (O&M) standpoint. In this regard, a damage-tolerant approach is a strong alternative to a safe-life design approach that leads to overdesigning. The present study illustrates a probabilistic framework for structural integrity assessment of a spar-type FOWT, which can be used to design a cost-effective inspection and maintenance planning. The structural integrity assessment is carried out for a fatigue-critical structural detail with an initial crack subjected to variable amplitude loading. The cycle-by-cycle crack growth is simulated using the modified Paris’ law, which allows accounting for the overload-induced retardation on the crack propagation. Furthermore, the factors influencing crack growth are subjected to a great deal of uncertainty. These uncertainties include initial crack size, loading spectrum, load interactions, and material fracture characteristics. To deal with the probabilistic nature of the crack propagation, Monte Carlo Simulation is carried out to estimate the probability of failure. Finally, a sensitivity analysis is performed to determine the degree of significance of the random variables.