Abstract:Firstly, Bezier curve is used to parameterize the suction side of an airfoil to control its thickness profile. Secondly, a surrogate model is established to represent an approximate relationship between the control nodes distributed on the suction side and the performance parameters of airfoil by using uniform experiment design and artificial neural network method. Finally, the optimal thickness profile is obtained based on the multi-objective genetic algorithm(MOGA). Lift-drag ratio F and drag FD of airfoil 791 are served as the optimization objective functions and the control nodes of the Bezier curve are chosen as optimization variables. The result indicates that MOGA is feasible. As a result, the drag is decreased by 4.17%, the lift-drag ratio is increased by 15.33%, and the angle of attack at which a stall appears becomes larger. The optimal location of maximum thickness is more close to the leading edge as near as 0.390 the chord length and the maximum thickness is increased as thick as 0.090 the chord length. When other the objective functions are changed, an optimum airfoil still can be obtained by means of the optimization strategy. Such that the optimization strategy proposed can provide a reference for a study on optimization methods applied in other fluid machines.
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