仿生多胞薄壁管耐撞性分析及优化

牛枞; 黄晗; 向枳昕; 闫庆昊; 陈金宝; 许述财

doi:10.11883/bzycj-2021-0527

仿生多胞薄壁管耐撞性分析及优化

doi: 10.11883/bzycj-2021-0527

1.
斯克莱德大学工程学院，苏格兰格拉斯哥 G1 1XQ
2.
南京航空航天大学航天学院，江苏南京 211106
3.
清华大学汽车安全与节能国家重点实验室，北京 100084

基金项目: 国家自然科学基金（11902157）；南京航空航天大学校人才科研启动基金（1011-YAH20001）

详细信息

作者简介:
牛　枞（1992－　），男，博士，cong.niu@strath.ac.uk

通讯作者:
黄　晗（1989－　），男，博士，副研究员，huanghan@nuaa.edu.cn

中图分类号: O383
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- 被引次数: 0
出版历程
- 收稿日期: 2021-12-23
- 修回日期: 2022-06-29
- 网络出版日期: 2022-08-11
- 刊出日期: 2022-10-31

Crashworthiness analysis and optimization on bio-inspired multi-cell thin-walled tubes

1.
College of Engineering, University of Strathclyde, Glasgow G1 1XQ, Scotland, UK
2.
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China
3.
State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

摘要

摘要: 为提高薄壁管结构耐撞性，以雀尾螳螂虾螯为仿生原型，结合仿生学设计方法，设计一种含正弦胞元的多胞薄壁管结构。以初始峰值载荷、比吸能和碰撞力效率为耐撞性指标，通过有限元数值模拟分析了不同碰撞角度（0º、10º、20º和30º）条件下，仿生胞元数对薄壁管耐撞性的影响，通过多目标的复杂比例评估法获取仿生薄壁管的最优胞元数。基于不同碰撞角度权重因子组合，设置了4种单一角度工况和3种多角度工况，采用多目标粒子群优化方法获取了不同工况下薄壁管结构最优胞元高宽比和壁厚。复杂比例评估结果表明，胞元数为4的薄壁管为最优晶胞数仿生薄壁管。优化结果表明，单一角度工况下，最优结构参数高宽比的范围为0.88～1.50，壁厚的范围为0.36～0.60 mm，碰撞角度为0º和10º的最优高宽比明显小于碰撞角度为20º和30º的；多角度工况下，最优高宽比范围为1.01～1.10，壁厚范围为0.49～0.57 mm。
- 多胞薄壁管 /
- 耐撞性 /
- 多目标优化 /
- 仿生设计 /
- 冲击
Abstract: To improve the crashworthiness of thin-walled tube structures, a series of bio-inspired multi-cell thin-walled tubes with sinusoidal cells (abbreviated BSTs) were designed based on the dactyl club microstructure of Odontodactylus scyllarus (O. scyllarus) using bionic design methods. By taking initial peak load, specific energy absorption and crushing force efficiency as crashworthiness indexes, the influences of cell numbers on the crashworthiness of the BSTs under different impact angles (0º, 10º, 20º and 30º) conditions were analyzed under low-velocity impact condition using the nonlinear finite element (FE) method through LS-DYNA. The optimal number of bionic cells was obtained using complex proportion assessment. A complex proportional assessment (COPRAS) method was used to select the optimal number configuration under multiple loading angles. Base on the combination of weight factor values of different impact angles, four single-angle cases (1–4) and three multi-angle cases (5–7) were set. A metamodel-based multi-objective optimization method based on polynomial regression (PR) metamodels and a multi-objective particle optimization (MOPSO) algorithm were employed to optimize the dimensions of the optimal cell number configuration, where the initial peak load, specific energy absorption and crushing force efficiency were taken as objectives and the height-width ratio and thickness were regarded as the design variables. According to the results of the COPRAS method, the BST with four sinusoidal cells was determined to be the best design based on the multi-criteria process. The optimization results of single-angel cases show that, the optimal height-width ratio ranges from 0.88 to 1.50, and the optimal thickness ranges from 0.36 mm to 0.60 mm. The optimal height-width ratios of cases 1–2 are significantly smaller than those of cases 3–4 . The BST with four sinusoidal cells has the maximum optimal thickness of 0.6 mm when the impact angles is 0º. For multi-angel cases, the optimal height-width ratio ranges from 1.01 to 1.10, and the optimal thickness ranges from 0.49 mm to 0.57 mm. The results above are helpful for exploring the lightweight design of new thin-walled tube structures and providing new ideas for their application in energy absorption and crashing field.
- multi-cell thin-walled tube /
- crashworthiness /
- multi-objective optimization /
- bionic design /
- impact

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图 1 虾螯宏微观结构^[19]及仿生多胞管设计

Figure 1. Macro-micro structure of shrimp chela^[19] and bionic design for multi-cell tube

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图 2 不同胞元数目的仿生管截面

Figure 2. Sections of bionic tubes with different cell numbers

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图 3 仿生薄壁管（BST）的有限元模型

Figure 3. A finite element model for bio-inspired sinusoidal cell tubes (BSTs)

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图 4 不同网格尺寸下的碰撞力随位移变化曲线

Figure 4. Crushing force varying with displacement under different mesh size cases

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图 5 试验设备和样件

Figure 5. Testing equipment and specimen

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图 6 碰撞力随时间的变化

Figure 6. Crushing force varying with time

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图 7 不同碰撞角度下薄壁管变形

Figure 7. Deformation of BSTs at different impact angles

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图 8 不同碰撞角度下薄壁管耐撞性指标结果随晶胞数的变化

Figure 8. Crashworthiness indexes of BSTs varying with cell number at different impact angles

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图 9 不同工况下模型预测的耐撞性指标

Figure 9. Predicted crashworthiness indexes under different cases

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图 10 不同工况下优化结果粒子群边界

Figure 10. Particle swarm boundaries of optimization results under different design cases

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表 1 复杂比例评价法计算结果

Table 1. Results calculated by the complex proportional assessment method

N	S_+i	S_−i	Q_i	排序
1	0.0146	0.0061	0.0255	5
2	0.0165	0.0064	0.0269	2
3	0.0164	0.0069	0.0260	3
4	0.0190	0.0075	0.0278	1
5	0.0177	0.0082	0.0259	4
6	0.0171	0.0082	0.0252	6
7	0.0177	0.0088	0.0252	7
8	0.0167	0.0096	0.0237	8
9	0.0161	0.0102	0.0227	9
10	0.0151	0.0111	0.0211	10

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表 2 不同工况的角度权重因子值

Table 2. The values of angle weight for different design cases

工况	w_α1	w_α2	w_α3	w_α4
1 (α=0º)	1.0000	0.0000	0.0000	0.0000
2 (α=10º)	0.0000	1.0000	0.0000	0.0000
3 (α=20º)	0.0000	0.0000	1.0000	0.0000
4 (α=30º)	0.0000	0.0000	0.0000	1.0000
5	0.4668	0.2776	0.1603	0.0953
6	0.2500	0.2500	0.2500	0.2500
7	0.0953	0.1603	0.2776	0.4668

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表 3 模型误差分析

Table 3. Error analysis of model

α/(º)	F_p		E_s		C_f
α/(º)	$ \delta $/%	R_m/kN	$ \delta $/%	R_m/(kJ·kg⁻¹)	$ \delta $/%	R_m
0	0.14	0.016	0.77	0.068	0.78	0.003
10	5.56	0.379	1.35	0.11	4.83	0.07
20	5.85	0.178	5.75	0.431	3.36	0.034
30	9.98	0.339	4.96	0.276	8.15	0.067

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表 4 单一角度工况下的最优结果

Table 4. The optimal results for single-angle cases

工况	α/(º)	η	t /mm	F_p /kN	E_s /(kJ·kg⁻¹)	C_f
1	0	0.88	0.60	14.78	9.03	0.43
2	10	0.71	0.56	6.55	8.30	0.82
3	20	1.23	0.55	6.74	7.28	0.79
4	30	1.50	0.36	2.81	4.35	0.72

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表 5 多角度工况下的最优结果

Table 5. The optimal results for multi-angle cases

工况	α/(º)	η	t /mm	F_p /kN	E_s /(kJ·kg⁻¹)	C_f	$ {F'_{\text{p}}} $/kN	$ {E'_{\text{s}}} $/(kJ·kg⁻¹)	$ {C'_{\text{f}}} $
5	0	1.01	0.57	14.04	8.78	0.42	10.24	8.04	0.61
	10			7.05	8.41	0.81
	20			6.89	7.48	0.77
	30			6.49	4.27	0.72
6	0	1.09	0.54	13.32	8.53	0.41	8.03	7.02	0.68
	10			6.57	8.08	0.81
	20			6.39	7.23	0.78
	30			5.84	4.24	0.72
7	0	1.10	0.49	12.09	8.14	0.39	5.96	5.88	0.72
	10			5.71	7.72	0.81
	20			5.55	6.80	0.77
	30			5.04	4.23	0.72

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