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Original Articles

Robust design assessment of automotive crash box structures through model order reduction

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Pages 256-269 | Received 16 Jul 2021, Accepted 02 May 2022, Published online: 15 May 2022
 

Abstract

The research work is focused on a comprehensive study of crashworthiness parameters associated with widely used crash box components of passenger cars. The finite-element models representing the automotive crash box structure were procured from full-car digital models issued by NHTSA. From the full car model, the crash box geometry is extracted for the crash analysis and further design optimizations. The crashworthiness parameters such as energy absorption, crush force efficiency, specific energy absorption is studied in detail with analytical and finite-element solutions for each variant and are further enhanced using multi-objective design optimization through RSM-based DOE methods. For guiding engineers in real- time design exploration and other parametric assessments, a reduced-order model for each of the variants was developed by using the sPGD (sparse Proper Generalised Decomposition) method. The developed reduced order models of the crash boxes were able to accurately capture the non-linearities associated with them and delivered accuracy of 90%. On undergoing robust design assessment with crash box designs, taking into account of all variants, an average of 34.33% in energy absorption capacity was achieved. The heavier crash box variants which had good SEA capacity are performed for successful mass reduction of 18.91% without affecting their crash performance. For the explicit crash simulations, the virtual performance solution finite-element solver from the ESI group is utilized.

Acknowledgments

The author acknowledges the support given by ESI group India, for providing the academic license and technical support for their packages of Visual Performance Solution and Visual Environment for this research work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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