Optimization of crashworthiness of CFRP thin-walled beams filled with aluminium honeycomb based on surrogate model

耐撞性 结构工程 蜂巢 替代模型 材料科学 撞车 梁(结构) 复合材料 有限元法 工程类 计算机科学 机器学习 程序设计语言
作者
Yong Xiao,Hai Long,Sisi Lu,Dong Liang,Xiaodong Wen,Honglin Hu
出处
期刊:International Journal of Crashworthiness [Taylor & Francis]
卷期号:29 (2): 237-246 被引量:1
标识
DOI:10.1080/13588265.2023.2230643
摘要

AbstractAbstractThe CFRP thin-walled beam filled with aluminum honeycomb is a new design form in the crashworthiness design of automobile energy-absorbing component. It not only meets the requirements of strength, rigidity and lightweight under the normal load, but also ensures absorption of crash energy in a stable failure mode when a crash occurs. In this paper, under two typical conditions of axial impact and lateral impact, structural sample points are established by orthogonal experiment; a highly feasible surrogate model is constructed based on the radial basis function; the initial load peak Fmax and specific energy absorption (SEA) are taken as the main criteria to evaluate the energy absorption performance of the structure; the multi-objective genetic optimization algorithm NSGA-II is used to optimize the energy absorption design of CFRP thin-wall beams filled with aluminum honeycomb. The structure and material parameters of the minibus frame are optimized according to the crash condition to improve the energy absorption performance of the minibus in frontal and side crashes, and on this basis, an effective method to improve the crashworthiness of minibuses is explored.Keywords: Carbon fibre-reinforced plasticaluminium honeycombcrashworthinessthin-walled beamstructural optimization Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is supported by the Chongqing Key Laboratory for Public Transportation Equipment Design and System Integration [CKLPTEDSI-KFKT-202104], Science and Technology Research Program of Chongqing Municipal Education Commission [Grant No. KJQN202100727], Natural Science Foundation of Chongqing [Grant No. CSTB2022NSCQ-BHX0694] and National Natural Science Foundation of China [Grant No. 52175042].
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