Aerodynamic optimization of hypersonic blunted waveriders based on symbolic regression

Abstract

The previous waverider optimization was mainly focused on the original configuration with sharp leading edge. In actual application, the leading edge must be blunted for hypersonic flight, which can change the aerodynamic performance significantly. Thus, the optimum waverider with sharp leading edge doesn't mean that it's still optimum after bluntness. To solve the problem, this paper first investigates the influence mechanism of leading edge bluntness on the aerodynamic performance of the waveriders in detail. And the novel methodology of symbolic regression is employed to establish an analytical pressure increment model for the original waverider caused by the bluntness effects. Then an efficient aerodynamic model for the blunted waverider is constructed by combining traditional approximate methods and the pressure increment model, which is further incorporated into the Genetic Algorithm optimization framework. Results show that the resulting blunted optimized waveriders have distinctly different shapes and better aerodynamic performance compared to previous optimization that considers only sharp leading edge. And as the bluntness radius or the design lift increases, the improvement of lift-to-drag ratio (L/D) turns larger. Finally, when the center of pressure is constrained during the optimization, the blunted optimized waverider exhibits both better trim characteristic and higher L/D.