An Investigation of Structural Optimization in Crashworthiness Design Using a Stochastic Approach
In this paper the Response Surface Methodology (RSM) and the Stochastic Optimization (SO) are compared with regard to their efficiency and applicability in crashworthiness design. Optimization of simple analytic expressions and optimization of a front rail structure are application used in order to assess the respective qualities of both methods. A low detailed vehicle structure is optimized to demonstrate the applicability of the methods in engineering practice. The investigations reveal that RSM is favoured compared to SO for less than 10-15 design variables. A novel zooming method is proposed for SO, which improve its convergence behaviour. A combination of both the RSM and the SO is efficient. Stochastic Optimization can be used in order to determine an appropriate starting design for an RSM optimization, which continues the optimization. Two examples are investigated using this combined method.
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An Investigation of Structural Optimization in Crashworthiness Design Using a Stochastic Approach
In this paper the Response Surface Methodology (RSM) and the Stochastic Optimization (SO) are compared with regard to their efficiency and applicability in crashworthiness design. Optimization of simple analytic expressions and optimization of a front rail structure are application used in order to assess the respective qualities of both methods. A low detailed vehicle structure is optimized to demonstrate the applicability of the methods in engineering practice. The investigations reveal that RSM is favoured compared to SO for less than 10-15 design variables. A novel zooming method is proposed for SO, which improve its convergence behaviour. A combination of both the RSM and the SO is efficient. Stochastic Optimization can be used in order to determine an appropriate starting design for an RSM optimization, which continues the optimization. Two examples are investigated using this combined method.
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