Aerodynamic Shape Optimization of Natural-Laminar-Flow Wing Using Surrogate-Based Approach

Aerodynamic shape optimization of a swept natural-laminar-flow wing in the transonic regime is still challenging. The difficulty is associated with reliable prediction of laminar–turbulence transition and reasonable compromise of viscous and wave drags. This paper proposes to use efficient global optimization based on surrogate models to address this problem. The Reynolds-averaged Navier–Stokes flow solver features automatic transition prediction via a full eN method, in which dual N factors are used for Tollmien–Schlichting and crossflow instabilities, respectively. The optimizer is based on the kriging surrogate model and parallel infill-sampling method. The baseline natural-laminar-flow wing for short- and medium-range transport aircraft is designed at a cruise Mach number 0.75. Then, drag minimization with up to 42 design variables is carried out, and significant drag reduction (8.79%) has been achieved. A close examination of the optimal wing shows that the drag reduction mainly comes from shock-wave weakening on the upper surface and laminar flow extending via suppression of crossflow instability on the lower surface. Robustness of the optimal wing is investigated, and multipoint optimization is further exercised to improve the robustness to the Mach number variation. It is demonstrated that surrogate-based optimization is feasible and effective for aerodynamic shape optimization of transonic natural-laminar-flow wings.