Multi-objective Airfoil Design Using Variable-Fidelity CFD Simulations and Response Surface Surrogates
Slawomir Marcin Koziel, Leifur Leifsson · 2014
In this work, a computationally efficient procedure for multi-objective design optimization of transonic airfoil shapes is presented. The proposed approach utilizes the multi-objective evolutionary algorithm (MOEA) that works with a fast surrogate model of an airfoil under design, obtained with kriging interpolation of low-fidelity CFD airfoil simulations. The initial Pareto front generated by multi-objective optimization of the surrogate using MOEA can be iteratively refined by local enhancements of the surrogate model. The latter are realized with space mapping response correction based on limited number of high-fidelity CFD training points allocated along the initial Pareto front. The proposed method allows us to obtain—at a low computational cost—a set of airfoil geometries representing trade-offs between the lift and drag coefficients. Our approach is illustrated using an example design of a transonic airfoil.