Aerodynamic optimization method based on adaptive surrogate model

In order to reduce the computation cycle and improve the search efficiency, the Surrogate Model method with simple structure and low cost of calculation is applied in the aerodynamic optimization design. The combination of effective interpolation and sampling methods (adaptive sampling) has been proved to be an effective reduction of the model establishing time. An aerodynamic optimization method based on the adaptive surrogate model is proposed in this paper. Based on the research of the adaptive surrogate model, the Kriging adaptive surrogate model and the support vector regression adaptive surrogate model are established. The models have higher predictive ability than the general surrogate model with same sample points. When applying to the airfoil optimization design, these two adaptive surrogate models perform well and satisfied aerodynamic optimal results are obtained, indicating that these two adaptive agent models are not only simple and practical, but also significantly improve the computational efficiency of aerodynamic analysis.