内爆炸载荷下双向波纹夹芯管的动力响应及抗爆性能预测

唐波; 李子豪; 刘志芳; 李世强

doi:10.11858/gywlxb.20240782

内爆炸载荷下双向波纹夹芯管的动力响应及抗爆性能预测

doi: 10.11858/gywlxb.20240782

唐波^1,,
李子豪¹,
刘志芳^{1, 2},
李世强^{1, 2, 3,*, ,}

1.
太原理工大学机械与运载工程学院应用力学研究所, 山西太原　030024)
2.
材料强度与结构冲击山西省重点实验室, 山西太原　030024
3.
北京理工大学爆炸科学与安全防护全国重点实验室，北京 100081

基金项目: 国家自然科学基金（12072219，12272254）；山西省自然科学研究面上项目（202203021211170）；海安太原理工大学先进制造与智能装备产业研究院开放研发项目（2023HA-TYUTKFYF016）；山西省科技创新人才团队（领军）专项（202204051002006）；爆炸科学与安全防护全国重点实验室（北京理工大学）开放课题（KFJJ24-03M）

详细信息

作者简介:
唐　波（1999－），男，硕士研究生，主要从事轻质结构冲击动力学行为研究. E-mail：tb15881862576@163.com

通讯作者:
李世强（1986－），男，博士，副教授，主要从事结构冲击动力学研究. E-mail：lishiqiang@tyut.edu.cn

中图分类号: O347.1; O521.9
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出版历程
- 收稿日期: 2024-04-03
- 修回日期: 2024-05-08
- 录用日期: 2024-06-04
- 网络出版日期: 2024-11-25
- 刊出日期: 2024-12-05

Blast Resistance and Prediction of Bi-Directional Corrugated Sandwich Tubes under Internal Blast Loading

TANG Bo^1
,,
LI Zihao¹,
LIU Zhifang^{1, 2},
LI Shiqiang^{1, 2, 3,*
, ,}

1.
Institute of Applied Mechanics, College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, Shanxi, China
2.
Shanxi Key Laboratory of Material Strength and Structural Impact, Taiyuan University of Technology, Taiyuan 030024, Shanxi, China
3.
State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, China

摘要

摘要: 受孔雀螳螂虾前鄂抗冲击区结构启发，设计并制备了双向波纹夹芯管结构，采用实验和数值模拟相结合的方法研究了其在内爆炸载荷下的动态响应及能量吸收机制。实验获得了结构的外管中点最大挠度和3种典型变形模式：局部塑性变形、塑性大变形以及撕裂破坏。内外管中点最大挠度和结构最终变形模态的数值模拟结果与实验结果吻合较好。通过数值模拟研究了芯层波纹数、内外管壁厚以及炸药质量对外管中点最大挠度和能量吸收特性的影响，结果表明：随着波纹数增大，结构比吸能先增大后减小；增大内管壁厚和减小外管壁厚能有效地提高结构的抗爆性能，当结构内管壁厚为2.5 mm、外管壁厚为1.5 mm时，相比于内管壁厚为1.5 mm、外管壁厚为2.5 mm时，外管中点最大挠度降低了67.6%，质量降低了6.0%；随着TNT当量的增加，内管吸收的能量占比逐渐下降，而芯层和外管吸收的能量占比增加。建立了BP（back propagation）神经网络模型、PSO-BP（particle swarm optimization-back propagation）神经网络模型以及响应面分析模型，分别对结构的比吸能与外管中点最大挠度进行预测，优化了所提出的结构。
- 夹芯管 /
- 双向波纹芯层 /
- 内爆炸载荷 /
- 抗爆性能
Abstract: A bi-directional corrugated sandwich tube structure was proposed, inspired by the front jaw of peacock mantis shrimp. The dynamic responses and energy absorption characteristics of bi-directional corrugated sandwich tubes under inner blast loading were investigated numerically and experimentally. It was found that three typical deformation modes including localized plastic deformation, elliptical plastic large deformation and laceration. The numerical results of the mid-point deflection of the outer tube and the final deformation mode of the structure agree well with the experimental results. Subsequently, the effects of the number of corrugation of the bi-directional corrugated core tube, the inner and outer tube wall thicknesses and TNT dose on its dynamic response and energy absorption characteristics were investigated thoroughly. The results show that the energy absorption ratio of the structure increases first, and then decreases with the increase of the number of corrugation. Increasing the inner tube wall thickness and decreasing the outer tube wall thickness can improve the shock resistance performance. Compared with the inner tube wall thickness of 1.5 mm and an outer tube wall thickness of 2.5 mm, the structure with an inner tube wall thickness of 2.5 mm and an outer tube wall thickness of 1.5 mm can reduce the maximum mid-point deflection (MD) of the outer tube by 67.6% and reduce the mass by 6.0%. As the TNT dose increases, the percentage of energy absorbed by the inner tube decreases gradually, while the percentage of energy absorbed by the core and outer tube increases. Finally, the specific energy absorption (SEA) of the structure and MD of the outer tube were predicted using BP (back propagation) neural network model, PSO-BP (particle swarm optimization-back propagation) neural network model, and RSM (response surface methodology) model to optimize the proposed structure.
- sandwich tube /
- bi-directional corrugate core /
- internal blast loading /
- blast resistance performance

HTML全文

图 1 (a) 螳螂虾的CT扫描图像^[18]，(b) 冲击区^[18]，(c) 冲击区的宏观微观结构^[18]，(d) 夹芯管示意图

Figure 1. (a) CT image of mantis shrimp^[18]; (b) impact zone^[18]; (c) macroscopic and microscopic structure of shrimp claws^[18]; (d) schematic diagram of sandwich tube

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图 2 3种波纹芯层示意图

Figure 2. Schematic diagram of three types of corrugated core

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图 3 实验装置示意图

Figure 3. Schematic diagram of experimental setup

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图 4 双向波纹管内外管变形图

Figure 4. Deformation diagram of inner and outer tubes of bidirectional bellows

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图 5 内部爆炸载荷下双向波纹夹芯管的实验结果

Figure 5. Experimental results of bi-directionally corrugated sandwich tubes under inner blast loading

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图 6 应力-应变曲线

Figure 6. Stress-strain curves

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图 7 R4A2试件的数值模拟与实验变形模态对比

Figure 7. Comparison of the deformation modes between the simulation and experimental results of R4A2

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图 8 不同波纹夹芯管的抗爆性能对比

Figure 8. Comparison of the blast resistance for different corrugated sandwich tubes

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图 9 不同波纹数的双向波纹夹芯管的抗爆性能

Figure 9. Blast resistance of bi-directional corrugated sandwich tubes with different corrugation numbers

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图 10 不同内外管厚度下R5A5结构的抗爆性能

Figure 10. Blast resistance of R5A5 structure with different thicknesses of inner and outer tubes

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图 11 不同TNT当量下R5A5的抗爆性能

Figure 11. Blast resistance of R5A5 under different equivalent TNT dosage

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图 12 BP神经网络模型

Figure 12. BP neural network structure diagram

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图 13 粒子群优化神经网络算法流程

Figure 13. Flow chart of particle swarm optimization neural network algorithm

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图 14 预测结果对比：(a) S_EA的BP预测与FE结果比较，(b) M_D的BP预测与FE结果比较，(c) S_EA的PSO-BP预测与FE结果比较，(d) M_D的PSO-BP预测与FE结果比较，(e) S_EA的RSM预测与FE结果比较，(f) M_D的RSM预测与FE结果比较

Figure 14. Comparison of predicted results: (a) comparison of BP prediction with FE results of S_EA; (b) comparison of BP prediction with FE results of M_D; (c) comparison of PSO-BP prediction with FE results of S_EA; (d) comparison of PSO-BP prediction with FE results of M_D; (e) comparison of RSM prediction with FE results of S_EA; (f) comparison of RSM prediction with FE results of M_D

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图 15 RSM生成的样本点与对照组的动态响应

Figure 15. Dynamic responses of the sample nodes by RSM and the control group

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表 1 材料参数

Table 1. Material parameters

Material	Density/(kg∙m⁻³)	Young’s modulus/GPa	Poisson’s ratio	Yield stress/MPa
316L steel	7830	185	0.30	470
304 steel	7830	193	0.25	250

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表 2 双向波纹夹芯管的变形/失效实验测定值

Table 2. Deformation/failure test values of bidirectional bellows sandwich tube

Sample	$ {\varepsilon _h} $/%		$ l $/mm		c_l/mm			c_w/mm
Sample	Inner tube	Outer tube	Inner tube	Outer tube	Inner tube crack	Core crack	Outer tube crack	Inner tube crack	Core crack	Outer tube crack
A2	4.1	2.6	85	48
R4	5.1	2.1	112	30	46			0.3
R4A2	4.6	2.6	127	40	76	57		14	3
R5A2	4.6	3.1	145	64	80	72		11	5

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表 3 内外管中点挠度的数值模拟与实验结果的对比

Table 3. Comparison between numerical simulation and experimental results for mid-point deflection of inner and outer tubes

Sample	R	A	t_i/mm	t_o/mm	M_D for inner tube			M_D for outer tube
Sample	R	A	t_i/mm	t_o/mm	Sim./mm	Exp./mm	Error/%	Sim./mm	Exp./mm	Error/%
A2	0	2	2	2	10.8	11.2	3.7	4.9	4.6	−6.1
R4	4	0	2	2	11.8	12.0	1.7	6.0	5.6	−6.7
R4A2	4	2	2	2	15.2	14.0	−7.9	5.5	5.0	−8.2
R5A2	5	2	2	2	18.8	18.0	−4.2	9.5	8.5	−10.5

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表 4 计算模型数与CPU计算时间

Table 4. Calculated model number and CPU calculation time

Model	Number of CPU^*	Number of meshes	Calculation time/min
Model	Number of CPU^*	Number of meshes	k=50	k=100	k=200	k=500	k=1000
FE	8	55850	475	950	1 900	4750	9500
BP	2		950	951	952	954	958
PSO-BP	2		954	959	968	996	1042
RSM	2		950	950	951	954	957
Note: * Intel (R) Core (TM) i7-13700 2.10 GHz

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表 5 预测模型误差分析

Table 5. Error analysis of prediction models

Model	$ {\theta _{{\text{relative}}}} $/%		$ {\theta _{{\text{average}}}} $/%		$ {R^2} $
Model	S_EA	M_D	S_EA	M_D	S_EA	M_D
BP	2.05	33.2	0.48	6.65	0.999	0.975
PSO-BP	2.15	28.3	0.35	3.52	0.999	0.994
RSM	0.97	22.1	0.25	0.24	0.999	0.996

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表 6 最大$M_{\mathrm{D}}$约束下最大化$S_{\mathrm{EA}} $的优化设计

Table 6. Optimal design of maximized $S_{\mathrm{EA}} $ with maximum $M_{\mathrm{D}} $ constraints

No.	R	A	t_i/mm	t_o/mm	M_D/mm		S_EA/(J∙g⁻¹)
No.	R	A	t_i/mm	t_o/mm	RSM	FE	RSM	FE
1	3	6	2.40	1.50	2.00	2.12	6.27	6.28
2	6	4	2.20	1.50	4.00	4.00	6.96	6.97
3	6	5	2.05	1.50	5.24	5.22	7.57	7.56
4	6	5	1.94	1.50	6.00	5.97	8.00	8.02
5	6	6	1.58	1.50	8.00	8.05	9.40	9.44
6	5	5	1.50	1.50	10.00	8.80	9.89	9.93

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