Airfoil shape parameterization for optimum Navier–Stokes design with genetic algorithm

The effect of airfoil shape parameterization on optimum design and its influence on the convergence of the optimization process are investigated. A new method for airfoil shape parameterization is presented which takes into consideration the characteristics of viscous transonic flow particularly around the trailing edge. The method is then applied to airfoil shape optimization at high Reynolds number turbulent flow conditions using a Genetic Algorithm. An unstructured grid Navier–Stokes flow solver with a two-equation K − ε turbulence model is used to evaluate the fitness function. The aerodynamic characteristics of the optimum airfoil obtained from the proposed parametric method are compared with those from alternative methods. It is concluded that the new method is capable of finding efficient and optimum airfoils in fewer number of generations.