Bionic design and multi-objective optimization of thin-walled structures inspired by conchs

Xiaoyan Song; Lianfeng Lai; Shungen Xiao; Yaohong Tang; Mengmeng Song; Jie Zhang; Yong Zhang; Xiaoyan Song; Lianfeng Lai; Shungen Xiao; Yaohong Tang; Mengmeng Song; Jie Zhang; Yong Zhang

doi:10.3934/era.2023028

Electronic Research Archive

2023, Volume 31, Issue 2: 575-598. doi: 10.3934/era.2023028

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Bionic design and multi-objective optimization of thin-walled structures inspired by conchs

1.
College of Information, Mechanical and Electrical Engineering, Ningde Normal University, Ningde 352000, China
2.
New Energy Automobile Motor Industry Technology Development Base, Ningde Normal University, Ningde 352000, China
3.
College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China

Received: 14 September 2022 Revised: 20 October 2022 Accepted: 02 November 2022 Published: 14 November 2022

Thin-walled structures have been widely used in various parts of vehicle subsystems because of their high-efficiency impact energy absorption and lightweight characteristics. However, the impact deformation mode of conventional thin-walled structures is unstable and the energy absorption efficiency is low. Therefore, a series of novel bionic conch structures (BCS) are proposed to find a more excellent crashworthiness design in this study. First, the finite element simulation model of BCS verified by experiments is established. Then, the energy absorption characteristics of bionic conch structures, and conventional single-cell and multi-cell tubes under axial loading are compared by employing finite element simulation. The results show that the thin-walled structures inspired by conchs have a higher energy absorption efficiency than the other two structures with the same mass. In addition, the influence of main design parameters (wall thickness, inner and outer ring diameter, and the number of inner and outer panels) on the crashworthiness of BCS is studied through parameter design and factor significance analysis. Finally, the optimal geometric configuration is found by combining the approximation model and multi-objective particle swarm optimization, and the crashworthiness of BCS is further optimized. The bionic crashworthiness design and optimization framework proposed in this study can also provide a reference for other engineering protective structures.
- thin-walled structures,
- multi-objective optimization,
- energy absorption,
- bionic design,
- crashworthiness
Citation: Xiaoyan Song, Lianfeng Lai, Shungen Xiao, Yaohong Tang, Mengmeng Song, Jie Zhang, Yong Zhang. Bionic design and multi-objective optimization of thin-walled structures inspired by conchs[J]. Electronic Research Archive, 2023, 31(2): 575-598. doi: 10.3934/era.2023028

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Abstract

Thin-walled structures have been widely used in various parts of vehicle subsystems because of their high-efficiency impact energy absorption and lightweight characteristics. However, the impact deformation mode of conventional thin-walled structures is unstable and the energy absorption efficiency is low. Therefore, a series of novel bionic conch structures (BCS) are proposed to find a more excellent crashworthiness design in this study. First, the finite element simulation model of BCS verified by experiments is established. Then, the energy absorption characteristics of bionic conch structures, and conventional single-cell and multi-cell tubes under axial loading are compared by employing finite element simulation. The results show that the thin-walled structures inspired by conchs have a higher energy absorption efficiency than the other two structures with the same mass. In addition, the influence of main design parameters (wall thickness, inner and outer ring diameter, and the number of inner and outer panels) on the crashworthiness of BCS is studied through parameter design and factor significance analysis. Finally, the optimal geometric configuration is found by combining the approximation model and multi-objective particle swarm optimization, and the crashworthiness of BCS is further optimized. The bionic crashworthiness design and optimization framework proposed in this study can also provide a reference for other engineering protective structures.

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