Informing asset life extension: probabilistic fatigue life reassessment of offshore wind turbine structural components using a Bayesian network

Substantiating the safe operation of a wind turbine beyond its original design life requires a reassessment of the fatigue life of its structural components. It is common practice to use the same partial safety factors in the fatigue reassessment as were applied in the original design. However, using the same partial safety factors for through-life fatigue assessments may lead to overly conservative estimations, which could result in assets being removed from service prematurely. This paper proposes a methodology for conducting a probabilistic fatigue life assessment of wind turbine structural components through implementation of a Bayesian network (BN). The BN has been trained on inputs from offshore wind turbine design codes and standards to calculate the fatigue design life of a steel tower. The results from the fatigue calculations for the tower sections determined the P50 and P95 values for damage equal to 0.42 and 0.51 respectively, while the fatigue assessment of the tower flange connections resulted in P50 and P95 value of 0.63 and 0.81. The paper also presents the results of applying Sobol variance analysis to the BN, which shows how the variance in the output parameters can be decomposed to determine the largest contributors to uncertainty in the tower damage assessment.