内凹三角形负泊松比结构耐撞性多目标优化设计

doi:10.13229/j.cnki.jdxbgxb20181027

摘要/Abstract

摘要：

为设计出具有良好耐撞性的车辆碰撞吸能结构，以内凹三角形负泊松比多胞结构为研究对象，通过显式动力有限元软件 LS?DYNA建立了此吸能结构的轴向冲击有限元模型。结合最优拉丁超立方设计方法，构建了此吸能结构的峰值冲击力PCF和比吸能SEA关于长胞壁尺寸a与胞壁厚度b的多项式代理模型，采用第二代非劣排序遗传算法（NSGA?II）进行多目标优化设计，并基于适应度函数C获取一妥协解。优化结果表明：胞壁厚度比长胞壁尺寸对此吸能结构耐撞性影响更显著，通过合理匹配壁厚和长胞壁长度，能有效降低峰值冲击力，提高比吸能。

关键词: 车辆工程, 碰撞吸能, 负泊松比, 轴向冲击, 多目标优化

Abstract:

To design vehicle collision energy-absorbing structures with excellent crashworthiness, the concave triangle cell structure with negative Poisson's ratio was studied. The axial impact finite element model of the structure was established by explicit dynamic finite element software LS-DYNA. Combined with the optimal Latin hypercube design method, the polynomial surrogate model of the peak crush force (PCF) and the specific energy absorption (SEA) for horizontal size and thickness of the cell wall were constructed, respectively. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was adopted to perform the multi-objective optimization design, and a compromise solution was obtained based on the fitness function C. The results show that the wall thickness has more obvious effect on crashworthiness of the energy-absorbing structure than horizontal cell wall size. The PCF can be effectively reduced and SEA can be improved by reasonable matching wall thickness and horizontal cell wall size．

Key words: vehicle engineering, collision energy absorption, negative Poisson′s ratio, axial impact, multi-objective optimization

中图分类号:

U465.9

马芳武,梁鸿宇,赵颖,杨猛,蒲永锋. 内凹三角形负泊松比结构耐撞性多目标优化设计[J]. 吉林大学学报(工学版), 2020, 50(1): 29-35.

Fang-wu MA,Hong-yu LIANG,Ying ZHAO,Meng YANG,Yong-feng PU. Multi⁃objective crashworthiness optimization design of concave triangles cell structure with negative Poisson′s ratio[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 29-35.

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样本点	相对密度Δρ	PCF/kN	SEA/（kJ?kg^–1）
（3，1.5）	0.163 3	2.844 71	3.516
（4,2.25）	0.230 2	5.553 31	7.095
（5,3）	0.287 3	8.470 96	10.626
（6,1.25）	0.142 0	2.670 49	3.418
（7,2）	0.209 6	5.931 79	7.115
（8,2.75）	0.267 3	9.053 34	10.451
（9,1）	0.122 5	3.599 93	2.455
（10,1.75）	0.190 7	5.387 62	4.072
（11,2.5）	0.248 2	10.4531	8.650

模型	a/mm	b/mm	PCF/kN	SEA/（kJ?kg^–1）
初始模型	8.0	2.750	9.053 3	9.912
优化模型	5.4	2.845	8.151 7	10.233
验证模型	5.4	2.845	8.152 0	10.363