颗粒局域共振增强仿生复合材料中应力波的衰减行为
Locally resonant particles enhance the stress wave attenuation in bioinspired composites
洪爽 1于瀛洋 2张作启3
作者信息
- 1. 武汉大学 土木工程建筑学院,武汉 430072
- 2. 武汉大学 土木工程建筑学院,武汉 430072;杭州市富阳区发展和改革局,杭州 311400
- 3. 武汉大学 土木工程建筑学院,武汉 430072;建筑物检测与加固教育部工程研究中心,武汉 430072
- 折叠
摘要
快速衰减应力波的冲击防护复合材料在民防、装甲、舰船等许多工业领域有着巨大的需求.受蜻蜓翅膀的启发,本文提出了基于颗粒局域共振原理的仿生微结构防护复合材料设计.研究发现:(1)当入射波频率接近局域共振单元的固有频率时,局域共振机制被最大程度激发,大量的入射应力波能量转化为颗粒的机械能;(2)单元固有频率随重芯直径、密度、软涂层厚度增大而减小,随软涂层弹性模量增大而增大;(3)在复合材料中引入不同固有频率单元的混杂设计,可以实现对宽频域入射应力波的高效衰减.本研究对于利用局域共振原理和仿生微结构开发设计高性能冲击防护复合材料具有指导意义.
Abstract
The demand for protective composites that can rapidly attenuate stress waves is high across various industrial sectors such as civil defense,armor,and ships.Drawing inspiration from dragonfly wings,this paper introduces a novel design of protective composites combining the principle of particle local resonance and bio-inspired microstructures.The key findings include:(1)When the frequency of the incident wave closely matches the intrinsic frequency of the local resonance unit,maximum excitation of the local resonance mechanism occurs,and a significant amount of incident stress wave energy is converted into the mechanical energy of particles;(2)The intrinsic frequency of a local resonant unit decreases with the increase of the core particle size and density,and the soft coating thickness,but increases with the rise in the elastic modulus of the soft coatings;(3)A hybrid design with a mix of units with varying intrinsic frequencies incorporated into the composite material,can achieve effective attenuation of incident stress waves across a broad frequency range.This research provides valuable guidance for developing high-performance impact-resistant composites utilizing the principles of local resonance and bionic microstructures.
关键词
应力波/仿生微结构/防护材料/衰减行为/局域共振Key words
stress wave/biomimetic microstructure/protective material/damping and attenuation/local reson-ance引用本文复制引用
基金项目
国家自然科学基金(11720101002)
国家自然科学基金(12272279)
国家自然科学基金(11772240)
湖北省重点研发计划项目(2021BCA106)
出版年
2024
NETL
NSTL
万方数据