Aerodynamic Shape Optimization of a Missile Using a Multiobjective Genetic Algorithm

Abstract

The aim of this paper is to demonstrate the effects of the shape optimization on the missile performance at supersonic speeds. The N1G missile model shape variation, which decreased its aerodynamic drag and increased its aerodynamic lift at supersonic flow under determined constraints, was numerically investigated. Missile geometry was selected from a literature study for optimization in terms of aerodynamics. Missile aerodynamic coefficient prediction was performed to verify and compare with existing experimental results at supersonic Mach numbers using SST k-omega, realizable k-epsilon, and Spalart-Allmaras turbulence models. In the optimization process, the missile body and fin design parameters need to be estimated to design optimum missile geometry. Lift and drag coefficients were considered objective function. Input and output parameters were collected to obtain design points. Multiobjective Genetic Algorithm (MOGA) was used to optimize missile geometry. The front part of the body, the main body, and tailfins were improved to find an optimum missile model at supersonic speeds. The optimization results showed that a lift-to-drag coefficient ratio, which determines the performance of a missile, was improved about 11-17 percent at supersonic Mach numbers.