Aerodynamic Shape Optimization Using Feature based CAD Systems and Adjoint Methods

This paper presents a CAD-based optimization framework using adjoint functions for aerodynamic design. In this work, the SU2 code is used to obtain high-fidelity flow solutions and surface sensitivities using adjoint methods. This work proposes methodologies to exploit CAD models created using standard commercial modelling software like CATIA V5 in the optimization workflow. A formulation to obtain geometric sensitivities is introduced, enabling the calculation of gradients with respect to these CAD variables. The performance and robustness of the optimization framework is assessed using a range of inviscid and viscous problems. The results show the CAD parameterisation can be efficiently used in obtaining reliable optimums, while operating directly on feature based CAD systems.