Aerodynamic and stealth synthesis design optimization of UAV based on double-stage metamodel

In this paper, an aerodynamic and stealth synthesis design optimization method is presented based on double-stage metamodel (DSM). DSM integrates advantages of both interpolation and regression metamodel and expresses higher fidelity than traditional metamodels. Navier-Stokes equations numerical solution method and sparse matrix method are applied to analysis aerodynamic and stealth performance parameters. And then DSM models of both simulation models are constructed and the characteristics of DSM are validated. In the end, based on adaptive metamodel-based design optimization strategy, the fly-wing UAV aerodynamic and stealth synthesis optimal design using DSM and multi-objective genetic algorithm is presented. The design target is to minimize the drag coefficient and heading radar cross section while meeting performance and geometric constraints. Satisfying results are obtained and practicality of the design method is verified.