This paper presents an approach to reduce the computational effort of shape optimizations for crashworthiness design. The work presented here focuses on the reduction of computational effort associated with Robust Design Optimization (RDO) of
large industrial models. For the robust design study, the computational effort is determined by the following two aspects: (i) time for the computation of crash and (ii) the
number of robustness evaluations required for each design. To reduce the computational effort in aspect one, a sub-structuring method is presented where only the sub-region of a computationally expensive model is considered in the optimization. For the second aspect, a modified double loop approach is presented where only the designs in the Region Of Interest (ROI), a subset of the total design space, are considered for robustness analysis. For the designs outside the ROI, assumed robustness values can be used or, better, surrogate models (physical or mathematical) are used for these values. At present the Equivalent Static Loads Method (ESLM) (Park (2011) and Kim et al. (2010)) is under investigation for the latter approach. First the three approaches, the sub-structuring and the two simplified robustness evaluation methods, are implemented and validated separately for shape optimization problems based on simpler test cases (reduced number of design variables and design complexity). These approaches will be integrated into one optimization loop to solve a large scale industrial optimization problem in the future.
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This paper presents an approach to reduce the computational effort of shape optimizations for crashworthiness design. The work presented here focuses on the reduction of computational effort associated with Robust Design Optimization (RDO) of
large industrial models. For the robust design study, the computational effort is determined by the following two aspects: (i) time for the computation of crash and (ii) the
number of robustness evaluations required for each design. To reduce the computat...
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