Abstract
This paper presents an optimized design of airfoil cross section using two different meta-heuristic schemes with micro-population. Geometrical coordinates of airfoil section are obtained for achieving the desired target pressure distribution and minimum lift-to-drag ratio. The flow solution for a given angle of attack and free-stream velocity is obtained by using XFOIL and with coupled panel–boundary layer (viscous–inviscid interaction) method. Two optimization schemes namely micro-genetic algorithms and micro-differential evolution with five basic airfoil configurations are employed to achieve required objectives with certain constraints in each case. In minimizing the computation time and effort, a surrogate model based on three-layer perceptron neural network is developed and the results are also reported. The optimized section is analysed finally using computational fluid dynamics solution to know the correctness of the optimized data.
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