Honeycomb structures are widely used in energy absorption, and more recently auxetic honeycombs have been studied in order to improve absorption capabilities of such structures. The hexagonal re-entrant (HR) honeycomb is foreseen to be a promising structure under impact velocities. An experimental analysis of the re-entrant honeycomb under impact velocity has led to a finite elements model validation at scale one, i.e. scale of current car crash cushions. A new objective function based on the European Standard has been developed in order to improve crash cushions capabilities while avoiding peak deceleration by using a meta-heuristic optimization algorithm. The global optimization process has been performed using Inverse-PageRank-PSO algorithm. The algorithm has led to an optimal geometrical configuration of HR honeycomb improving the performance of current road safety devices. The optimal structure presents a quasi-linear absorption curve, as recommended by European standards.


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    Titel :

    Artificially smart optimization of crash cushion device sustained by experimental and numerical study of re-entrant auxetic honeycomb


    Beteiligte:
    Tondut, J. (Autor:in) / Di Cesare, N. (Autor:in) / Ronel, S. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2024-01-02


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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