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High quality mesh generation technology coupled with a robust shape deformation technique enables large design space exploration for optimization without the need to remesh the geometry. To demonstrate this, we present a collection of best practices for cleaning complex analytic CAD data that together with a robust grid generation algorithm enable the automatic generation of high quality boundary layer resolved grids that retain their quality when morphed during the optimization process. The case study for this work is the DrivAer model developed by the Institute of Aerodynamics and Fluid Mechanics at the Technische Universität München. The first step in the proposed automated optimization framework is to use a technique called Solid Meshing to heal faults in the provided geometry and recover its original engineering intent.