丝织物编织结构与迎/背爆面组合对抗爆性能的影响OA
Influence of the Weaving Structure of Silk Fabrics and the Combination of the Front and Back Explosion Sides on the Anti-Explosion Performance
针对柔性防爆材料的结构优化需求,系统探究了丝织物编织构型与迎/背爆面组合模式对其抗爆性能的作用机理.基于显式动力学理论,建立了单丝截面0.15 cm×0.02 cm的Kevlar平纹、斜纹编织及双层结构的丝织物细观有限元模型,通过数值仿真对比分析了不同结构在同当量TNT爆炸载荷作用下的动态响应过程.结果表明:斜编织丝织物在受到冲击时变形较小,能够更有效地分散冲击能量,表现出优于正编织丝织物的抗爆性能,其相同时间下的变形量较正编织小19.0%,网后压力降低56.3%;同时,当迎爆面为正编织丝织物,背爆面为斜编织丝织物时,双/多层织物的抗爆性能最优,相比其他组合方式,最大可减小39.4%的冲击压力.
Aiming to the structural optimization requirements of flexible explosion-proof materials,this study systematically explored the mechanism by which the weaving configuration of silk fabrics and the combination mode of the front and back explosion-proof surfaces affected their explosion-proof performance.Based on the explicit dynamics theory,mesoscopic finite element models of Kevlar plain weave,twill weave and double-layer structure silk fabrics with a single filament cross-section of 0.15 cm×0.02 cm were established.The dynamic response processes of different structures under the same equivalent TNT explosion load were compared and analyzed through numerical simulation.The results show that the twill weave silk fabric has less deformation when it is to impacted,and can more effectively disperse the impact energy,and exhibits superior anti-explosion performance compared to the plain weave silk fabric.The deformation amount under the same time is 19.0%smaller than that of the plain weave silk fabric,and the pressure behind the silk mesh is 56.3%lower.Meanwhile,when the front facing the explosion is a plain weave silk fabric and the back facing is a twill weave silk fabric,the anti-explosion performance of double/multi-layer fabrics is the best.Compared with other combination methods,the impact pressure can be reduced by up to 39.4%at most.
陶洋;张会锁;谢天奇;李程;牛欣乐
中北大学 机电工程学院,山西 太原 030051中北大学 机电工程学院,山西 太原 030051中北大学 机电工程学院,山西 太原 030051中北大学 机电工程学院,山西 太原 030051中北大学 机电工程学院,山西 太原 030051
军事科技
编织方向背爆面抗爆性细观建模
positive weavingback exposed faceantiknock propertymesoscopic modeling
《中北大学学报(自然科学版)》 2026 (1)
46-52,70,8
山西省研究生学术创新项目(2025XS427)
评论