In the modern practice of the vehicle crashworthy design development and its impact performance validation, virtual full vehicle crash models have been widely and successfully utilized as the analysis tool by many safety CAE engineers. Recently, a typical full-vehicle front impact model has grown in size up to over 3 million finite elements to enable analysis of highly localized and transient responses of vehicle structure deformation under the impulsive loads. This full vehicle model takes 10~15 computer hours per run even on a fast Massively Parallel Process (MPP) server. The CPU time will increase if the full-vehicle model is applied for analysis of the offset-barrier events in which the test vehicle receives barrier impact loading for a longer duration. Furthermore, for a design optimization task running a large Design of Experiment (DOE) variation matrix, the total turn-around time including CPU hours taken for the DOE model iterations could rise significantly depending on the number of the control parameters and levels of choice.At an early stage of developing a vehicle safety design strategy and direction, a DOE variance study is necessary to provide an adequate size of safety design data for quicker gaining insight and informed decision-making about the effectiveness and unseen risks of the potential safety design options. As this task usually proceeds before a full vehicle model build, a virtual analysis tool, simple but reliable as a full scale model, is required. Hence, this study has developed a simplified vehicle impact model using nonlinear springs and mass elements to enable a single analysis run in a few minutes. To demonstrate the usefulness of the simplified model, a DFSS optimization of the vehicle Small Overlap Rigid Barrier (SORB) impact performance via the simplified model has been conducted and its results are compared with a full vehicle analysis.


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    Titel :

    Design for Six Sigma (DFSS) Optimization of Vehicle IIHS Small Overlap Rigid Barrier (SORB) Impact Performance Using a Simplified Spring-Mass Model


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Hor, Hassan (Autor:in) / Westra, Michael (Autor:in) / Rajagopalan, Rajkumar (Autor:in) / Park, Sae U. (Autor:in) / Kleinhoffer, Stacey (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2022



    Erscheinungsdatum :

    2022-03-29




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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