Reliability of offshore wind turbine support structures subjected to extreme wave-induced loads and defects

• Published in: Volume 3: Structures, Safety and Reliability
• Main Authors: Yeter, Baran, Garbatov, Yordan, Guedes Soares, C.
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Society of Mechanical Engineers 2016
• Subjects: Arctic
• Online Access: https://vbn.aau.dk/da/publications/199bfc5a-f236-4f51-bb8b-8995add9e249; https://doi.org/10.1115/OMAE2016-54240; http://www.scopus.com/inward/record.url?scp=84996508758&partnerID=8YFLogxK

The probability of existence of defects, fatigue damage and crack growth in the offshore wind turbine support structures subjected to extreme waves and wind-induced loads is very high and may occur at a faster rate in a low cycle fatigue regime and crack growth, leading to a dramatic reduction in the service life of structures. It is therefore vital to assess the safety and reliability of offshore wind turbine support structures at sea. The aim of the present study is to carry out a low cycle fatigue and crack growth reliability analysis of an offshore wind turbine support structure during the service life. The analysis includes different loading scenarios and accounts for the uncertainties related to the structural geometrical characteristics, the size of the manufacturing and during the service life defects, crack growth, material properties, and model assumed in the numerical analyses. The probability of failure is defined as a serial system of two probabilistic events described by two limit state functions. The first one is related to a crack initiation based on the local strain approach and the second one on the crack growth applying the fracture mechanic approach. The first and second order reliability methods are used to estimate the reliability index and the effect of low cycle fatigue and crack growth on the reliability estimate of the offshore wind turbine support structure. The sensitivity analysis is performed in order to determine the degree of the significance of the random variables and several conclusions are derived.