蜂巢
材料科学
蜂窝结构
复合数
辅助
复合材料
刚度
变形(气象学)
吸收(声学)
超材料
压缩(物理)
棒
高原(数学)
纵横比(航空)
有限元法
夹层结构复合材料
内能
结构工程
相(物质)
平面的
屈曲
变形机理
能量(信号处理)
比能量
优化设计
弹性能
抗压强度
芯(光纤)
作者
Fangyi Li,Weian Huang,Qiang Zhang,Zijie Wang
出处
期刊:Structures
[Elsevier BV]
日期:2026-01-28
卷期号:85: 111202-111202
标识
DOI:10.1016/j.istruc.2026.111202
摘要
As a classical auxetic metamaterial, the internal concave structure has become a hot spot in metamaterials research. However, most of the improved reinforced ribbed inner concave structures, although improving the problem of weakened stiffness existing in the traditional inner concave structures to a certain extent, also reduce the negative Poisson's ratio effect of the structure as a result, which has an impact on the comparison of energy absorption. To address this limitation, this paper proposes a novel composite honeycomb structure combining concave and rhombic configurations. This design enhances both compressive stability and energy absorption capacity per unit volume. For comparison, a hexagonal structure connected to straight rods is introduced. The energy absorption capabilities of these three configurations are investigated through quasi-static compression tests and finite element analysis. Results indicate that the novel composite honeycomb structure, composed of rhombic and concave cells, significantly enhances energy absorption. Its specific energy absorption efficiency surpasses the other two structures by 10 % and 65 %, respectively. It exhibits the lowest Poisson's ratio (-1) and a more stable compression deformation pattern than other configurations, with minimal stress fluctuations during the plateau phase and a standard deviation of 6.754 for the average plateau stress. Furthermore, multi-objective optimization of the novel composite honeycomb structure yielded parameters with low initial peak force and high specific energy absorption capacity. These findings offer new insights for metamaterial design by integrating composite honeycomb structures with reinforced ribs and internal concave surfaces to achieve optimization.
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