Abstract: By applying the Kriging model and the Pareto optimization method, a multiobject planform parameter design method based on approximation is proposed. The design of experiment is used to choose the configuration parameters and select configuration concept samples. The configuration samples are analyzed using the CFD, and the results are used to create the Kriging approximation model. Application of the Kriging model to parameter optimization can improve design efficiency and guarantee its precision. The Pareto multiobject genetic algorithm is used for parameter optimization, and the planform optimum results can be chosen in the Pareto front. A crankedsweep configuration is selected as a design case. The design results indicate that Kriging approximation model can satisfy the requirement of precision with errors of less than 5%. Three planform optimums are chosen by different preferences in the Pareto front. Through optimization, the supersonic drag coefficient can be reduced by about 6.0%~12.8%, while the transonic lift to drag ratio can be increased by about 0.01%~3.40%. By Pareto of design of experiment, main effect and inter effect analysis, the quantitative relationship between the parameters and aerodynamic characteristics can be achieved. This method can be applied to other aerodynamic configurations including unconventional configurations.

Key words: Pareto principle, design of experiment, Kriging model, aerodynamic configuration, parameter matching