Publications

Mesh generation for high-fidelity computational fluid dynamics simulations and aerodynamic shape optimization is a time-consuming task. Complex geometries can be accurately modeled using overset meshes, whereby multiple high-quality structured meshes corresponding to different aircraft components overlap to model the full aircraft configuration. However, from the standpoint of geometry manipulation, most methods operate on the entire geometry rather than on separate components, which diminishes the advantages of overset meshes. To address this issue, a geometry module is introduced that operates on individual components and automatically computes their intersections to update overset meshes during optimization. Reverse-mode automatic differentiation is applied to compute partial derivatives across this geometry module so that it fits into an optimization framework that uses a hybrid adjoint method (known as ADjoint) to efficiently compute gradients for a large number of design variables. By using these automatically updated meshes and the corresponding derivatives, the aerodynamic shape of the DLR-F6 geometry is optimized while allowing changes in the wing–fuselage intersection. Sixteen design variables control the fuselage shape, and 128 design variables determine the wing surface. Under transonic flight conditions, the optimization reduces drag by 15 counts (5%) as compared with the baseline design.