This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework. In comparison to traditional structures that made of a single cellular phase, the results demonstrate the improved performance when multiple cellular phases are used.


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    Titel :

    Optimal Design of Cellular Material Systems for Crashworthiness


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Tovar, Andres (Autor:in) / Detwiler, Duane (Autor:in) / Liu, Kai (Autor:in) / Xu, ZongYing (Autor:in)

    Kongress:

    SAE 2016 World Congress and Exhibition ; 2016



    Erscheinungsdatum :

    2016-04-05




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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