Fatigue damage analysis for a floating offshore wind turbine mooring line using the artificial neural network approach

Abstract

ABSTRACTThe mooring lines used for floating offshore platforms experience wide-banded tension loads, in which fatigue damage can be predicted accurately in time domain. This paper reports the results of a feasibility study on the application of an artificial neural network (ANN) to predict wide-banded fatigue damage in the mooring lines of a floating offshore wind turbine platform (FOWT). The assumed three catenary mooring lines provide station-keeping ability for the FOWT. A commercial software was used to perform dynamic analyses of the mooring line in the time domain for limited load cases. The analysis results were used to train a multi-layered ANN model. To validate the performance of the trained ANN model, mooring dynamic simulations are carried out for a set of newly defined load cases. The new simulation results were compared with the predicted ones using the trained ANN model. It is proven that two results were in excellent agreement in terms of the tension range distributions of a mooring line.