Developing A Framework for Gradient-Based Aerodynamic Optimization Using Parametric CAD

Improving aircraft performance often requires modifying the aerodynamic shape of an aircraft, and this motivates the use of shape optimization techniques. Predominantly, computer-aided design (CAD)-free methods applied to the discretized geometry, such as free-form deformation, offer considerable flexibility. These methods also facilitate the computation of design derivatives, which are often required for large-scale optimization problems. However, these methods have some limitations when addressing system-level problems, such as challenges with geometric intersections and less intuitive design parameterization. To address these challenges, this work presents a new optimization framework that couples a CAD-based geometric representation with gradient-based methods for aerodynamic shape optimization. It integrates Engineering Sketch Pad for geometry parameterization and SU2 for computational fluid dynamics analysis, coupled through OpenMDAO for gradient-based optimization. Its performance and accuracy are first demonstrated through a benchmark problem that minimizes drag for the transonic RAE 2822 airfoil. A second study focuses on a more challenging design scenario in which the thrust of a notional axisymmetric turbofan engine is maximized. This application case illustrates how a CAD-based parameterization can support more complex aerodynamic design tasks. The results highlight the effectiveness of the framework and its wide applicability for more demanding engineering problems.