Multi Objective Optimization of Transonic Airfoil Using Cst Methodology with General and Evolved Supercritical Class Function

CST method is a powerful parameterization method because of its simplicity, robustness, and its ability to be generalized into various possible shapes of aerodynamic bodies. The geometry from CST itself is mainly determined by the formula of class and shape function. Application of CST to transonic airfoil optimization is still rare and more studies are needed. This work studies the application of CST and modified CST to the transonic airfoil multi-objective optimization problem. Various scheme for optimization such as free lower and upper bound and reuse of the information from existing airfoil are performed in this work. An Euler solver with NSGA-II algorithm is employed to find the Pareto front with maximizing lift and minimizing drag coefficient as the objectives. Furthermore, robust optimization with the L/D ratio as the objective is also performed. Results show that reusing the information of existing airfoil could help to reduce the possible shape of airfoil, and thus makes the optimization scheme more effective. Moreover, the evolved class function also perform fairly well compared to the standard class function. It is also found that the mean and standard deviation of L/D ratio are two highly conflicting objectives.