Parametric Geometry Modeling for Robust and Efficient Aerodynamic Shape Optimization

Kurzfassung

This paper presents a parametric geometry modeling approach based on subdivision surfaces for robust and computationally efficient aerodynamic shape optimization in the preliminary design phase. In contrast to conventional computer-aided design systems, which rely on high-precision Non-Uniform Rational B-Splines representations tuned for detailed design, our method uses polygon meshes to provide intuitive, explicit, and watertight surfaces with second-order continuity. The approach enables high-fidelity gradient-based optimization by obtaining exact geometric sensitivities through algorithmic differentiation, thereby eliminating the need for finite-difference approximations or surrogate models. It offers superior robustness in handling complex topologies and large parameter variations, while its license-free structure is tailored for automation and compatibility with high-performance computers. The intrinsic surface parameterization allows smooth mesh deformation, enabling the reuse of converged computational fluid dynamics solutions and reducing computational cost. The methodology is validated using the German Aerospace Center F25 aircraft configuration, including airfoil and full-aircraft Reynolds-Averaged Navier-Stokes simulations. Results confirm smooth flow solutions and accurate geometric sensitivities, with the workflow showing scalability for high-dimensional design spaces under constraints.