Prediction of dynamic mooring responses of a floating wind turbine using an artificial neural network

Abstract Numerical simulations in coupled aero-hydro-servo-elastic codes are known to be a challenge for design and analysis of offshore wind turbine systems because of the large number of design load cases involved in checking the ultimate and fatigue limit states. To alleviate the simulation burden, machine learning methods can be useful. This article investigates the effect of machine learning methods on predicting the mooring line tension of a spar floating wind turbine. The OC3 Hywind wind turbine with a spar-buoy foundation and three mooring lines is selected and simulated with SIMA. A total of 32 sea states with irregular waves are considered. Artificial neural works with different c…