Abstract

Computational Fluid Dynamics and Finite Element Analysis structural models are developed for generation of large datasets of high-fidelity aerodynamic loading, displacement and stress for the NREL 5 MW wind turbine blade. Based on the datasets, analysis of structural responses of the turbine blade and their possible shifts with respect to a change in the operating conditions, e.g. rotor plane tilting and yawing, are performed. A Bayesian Network model is trained to produce ranges of values and likelihoods of occurrence of abnormal structural response or the most likely damage in the blade from inputs of operating conditions. The numerical analysis showed that yawing and tilting of rotor plane has very strong influence on the performance of a wind turbine. The out-of-plane bending is the dominant mode of the rotor blade while twisting and other complex modes of displacement could be more significant during some operating conditions such as at high tilt and yaw angles. The Bayesian Network is capable of computing probability mass functions of mechanical stress or displacement of the blade given a rotor rotation speed and a type of damage or vice versa, identifying a type of damage given a measured stress distribution level.

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