Surrogate-based aerodynamic shape optimization of hypersonic flows considering transonic performance

Abstract

Aerodynamic shape optimization of a hypersonic transport aircraft over a wide Mach-number range is challenging. The difficulty is not only associated with the large computational cost of high-fidelity CFD (computational fluid dynamics) simulations but also linked to the reasonable compromise between aerodynamic performances of aircraft at different speed ranges. This article proposes to use efficient global optimization based on surrogate models to address this type of problems. A RANS (Reynolds averaged Navier-Stokes) flow solver is adopted to evaluate objective and constraint functions; Kriging surrogate model combined with a parallel infill-sampling method and a multi-round strategy are employed to find the global optimum. First, a profile optimization with baseline airfoil of NACA64A-204 is conducted to achieve high lift-to-drag ratio (L/D) at both hypersonic (Ma=6.0) and transonic (Ma=0.8) regimes with up to 18 design variables, and significant improvement has been observed. Then, multi-objective wing optimizations of maximizing both hypersonic and transonic L/Ds with up to 54 design variables are performed and multiple optimizations with various sets of weight coefficients are investigated. The optimized wings are further evaluated and compared with the baseline wing at the flow regimes from subsonic to hypersonic speeds. Results show that by using the optimized profile, hypersonic and transonic L/Ds of a typical wing configuration are increased by 13.85% and 7.32%, respectively. After 3-D optimizations, the L/Ds at hypersonic and transonic design points are further improved by 4.47% and 3.19%, respectively, and a better performance over a wide Mach-number range is obtained. It is shown that a multi-round surrogated-based optimization is feasible and effective for aerodynamic shape optimization of hypersonic transport aircrafts over a wide Mach-number range.