Crashworthiness analysis of two-layered corrugated sandwich panels under crushing loading

Crashworthiness analysis of two-layered corrugated sandwich panels under crushing loading
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两层波纹夹芯板破碎荷载下的耐撞性分析

DOI:
10.1016/j.tws.2018.09.008
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发表时间:
2018-12
影响因子:
6.4
通讯作者:
Hou Shujuan
Hou Shujuan
中科院分区:
工程技术2区
文献类型:
--
作者:
Shu Chengfu;Zhao Shuyun;Hou Shujuan

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本文首先对不同排列方式的双层波纹芯夹芯板在准静态压缩载荷作用下的吸能特性进行了实验研究。对比两种不同排列方式的夹层板的实验结果,发现对称排列的波纹夹层板具有更好的吸能特性,致密化阶段前位移为6 mm处吸能比规则排列的高出17.17%以上。进行了数值计算,实验结果与数值结果吻合较好。最后,采用有限元模型和响应面法对对称排列的双层波纹夹层板进行了平面碰撞下的参数分析和优化研究。通过参数分析确定优化研究中参数的选择。首先对夹层板的尺寸进行优化,使比能量吸收(SEA)最大化。然后,以SEA最大化和峰值力最小为优化目标,对夹心板形状进行多目标优化,并采用非支配排序遗传算法(NSGA-II)按逐步进化的趋势进行优化,得到由一组最优目标函数向量组成的Pareto前沿。
In this study, the energy absorption characteristic of two-layered corrugated core sandwich panels with different arrangements under quasi-static compression loading were firstly investigated experimentally. Then compared the experimental results of these two different arrangements two-layered sandwich panels, it was found that the symmetric-arranged corrugated sandwich panel has better energy absorption characteristic, which is more than 17.17% at 6 mm displacement before densification stage compare to regularly-arranged. Numerical calculations were carried out and good agreement is achieved between the experimentally results and numerical results. Finally, parameter analysis and optimization study of the symmetric-arranged two-layered corrugated sandwich panel under planar impact was carried out with crashworthiness criteria by using finite element model and response surface method. The selection of parameters in optimization study were determined by parameter analysis. The size of sandwich panel was firstly optimized for maximizing specific energy absorption (SEA). Then the multi-objective optimization of core cell shape with optimal sandwich panel size was optimized by maximizing SEA and minimizing the peak force, a Non-dominated Sorting Genetic Algorithms (NSGA-II) code was used to perform the optimization process in a gradual evolution trend, which led to obtain the Pareto front that consisted of a set of optimal objective function vectors.
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影响因子: 13.1
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