In this study, the results of two optimized and base blades of a horizontal axis wind turbine with aerodynamic point of view and analyze the stresses and strains are compared. The aerodynamic forces are obtained by solving the viscous flow and the optimization is done by genetic algorithm and neural network. By applying the aerodynamic loads, the stress and strain are analyzed. In order to optimization, the chord length and the twist angle of the blade at various radiuses have been calculated by BEM. The Navier Stokes equations are solved to simulate both two and three dimensional flows. The Results which are obtained from 2D Computational Fluid Dynamics (CFD) have been utilized to train a Neural Network (NN). In the process of airfoil optimization, Genetic Algorithm (GA) is coupled with trained NN to attain the best airfoil shape at each angle of the attack. First, the results of both optimized and base wing are compared then the aerodynamic forces on the blades were applied for stress analysis. The results of the analysis of the stress - strain showed that optimized wing improves the wing performance.

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