Shape optimization of a blunt body in reacting hypersonic flow in chemical non-equilibrium for reducing both drag and heat transfer

A large design concern for high-speed vehicles such as next generation launch vehicles or reusable spacecraft is the drag and heat transfer experienced at hypersonic velocities. In this paper, the optimized shapes for both minimum drag and minimum peak heat flux for an axisymmetric blunt body are developed using computational fluid dynamics (CFD) software in conjunction with a genetic algorithm (GA). For flow field calculations, the commercial flow solver ANSYS FLUENT is employed to solve the unsteady compressible Reynolds Averaged Navier-Stokes (RANS) equations in conjunction with the Shear-Stress-Transport (SST) k-ω turbulence model. Park’s six species finite rate chemistry model is employed to incorporate the effects of air dissociation at high temperatures. The computational results using this model compare favorably with the experimental results for a DLR model validating the computational model used in this study. The axisymmetric hypersonic blunt body shape is optimized using a multi-objective genetic algorithm (MOGA) to minimize both the drag and heat transfer. The MOGA creates a Pareto-optimal front for the optimized shapes obtained by weighting the two objectives of minimizing the drag as well as heat transfer. The computational results for the optimized shapes show a significant decrease in both the drag and heat transfer and exhibit the expected changes in the body profile.