Application of improved Kriging-model-based optimization method in airfoil aerodynamic design

An improved Kriging-model-based optimization design method is presented. Such a method is based on design of experiment of Latin hypercube sampling, Kriging model and a genetic optimization algorithm. By simultaneously adding the sample point with maximum expected improvement (EI) and the optimal point from optimization of the initial samples, a new Kriging model of higher accuracy can be formed gradually. The fitting accuracy of Kriging model based on EI method is investigated and validated through the tests of a one-dimensional function and an aerodynamic problem. Test results show that the developed Kriging model is effective for optimization problems. Finally, a drag reduction optimization design of RAE2822 airfoil is carried out for examining the validity and efficiency of our method. The drag coefficient of RAE2822 airfoil is reduced by 33.6%. It shows that this method can gradually improve the fitting accuracy of the Kriging model, thus greatly improve the aerodynamic performance of the airfoil.