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. The aforementioned technique coupled with Pointwise’s anisotropic tetrahedral extrusion algorithm (T-Rex), enables automated, high quality volumetric grid generation.A technology called Arbitrary Shape Deformation (ASD) is then used to smoothly morph the DrivAer volume grid using a small set of shape change parameters. The robustness of this morphing technology enables the achievement of large grid deformations while maintaining cell quality and surface boundary layer thickness and orientation.As mentioned, the proposed design optimization framework eliminates the need to regenerate the grid after every volumetric deformation. This, in turn, minimizes the effect of changes to the characteristics of the grid on the simulation results.


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    Titel :

    Meshing Considerations for Automotive Shape Design Optimization


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Pita, Claudio (Autor:in) / Landon, Mark (Autor:in) / Carrigan, Travis (Autor:in)

    Kongress:

    SAE 2016 World Congress and Exhibition ; 2016



    Erscheinungsdatum :

    05.04.2016




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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