Research on the Rapid Aerodynamic Shape Optimization of Canards of Gliding Guided Projectile

Abstract

In order to improve the accuracy of calculation, it is often necessary to calculate the aerodynamic parameters of the projectile iteratively through computational fluid dynamics simulation, so the optimization efficiency is low. In this paper, a rapid aerodynamic shape ptimization method based on multi-fidelity surrogate model is proposed, which improves the calculation efficiency greatly under the condition of ensuring the calculation accuracy. Taking the canard shape optimization of gliding guided projectile as an example, the multi-fidelity surrogate is trained by two kinds of reliability samples to replace the computational fluid dynamics simulation process to calculate the aerodynamic parameters. According to the design requirements of maximum gliding lift-to-drag ratio, matching stability and maneuverability, the genetic algorithm is used to search for the optimal design of canard aerodynamic shape. Compared with the initial scheme, the lift-to-drag ratio of the optimized scheme are improved significantly. Compared with the results of numerical simulation, the average error of the method for the lift-to-drag ratio prediction is 1.94%, the accuracy is higher, and the amount of calculation is greatly reduced, which verifies the feasibility and effectiveness of the method.

Keywords

• |gliding guided projectile|aerodynamic shape|co-kriging surrogate model|cfd|genetic algorithm|optimal design