Bionic design of thin-walled bilinear tubes with excellent crashworthiness inspired by glass sponge structures

• Published in: Bioinspiration & biomimetics Vol. 19; no. 4; pp. 46018 - 46036
• Main Authors: Liu, Yansong, Zou, Meng, Qi, Yingchun, Chen, Lining, Wang, Zhaoyang, Song, Jiafeng, He, Lianbin
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.07.2024
• Subjects: bionic; energy absorption; glass sponge; lightweight and high strength; thin-walled structure
• ISSN: 1748-3182; 1748-3190; 1748-3190
• DOI: 10.1088/1748-3190/ad580a

Abstract In order to enhance energy absorption, this study draws inspiration from the diagonal bilinear robust square lattice structure found in deep-sea glass sponges, proposing a design for thin-walled structures with superior folding capabilities and high strength-to-weight ratio. Firstly, the crashworthiness of bionic glass sponge tube (BGSTO) is compared with that of equal-wall-thickness equal-mass four-X tube through both experiments and simulations, and it is obtained that the specific energy absorption of BGSTO is increased by 78.64%. And the crashworthiness of BGSTO is also most significant compared to that of multicellular tubes with the similar number of crystalline cells. Additionally, we found that the double-line spacing of the glass sponge can be freely adjusted without changing the material amount. Therefore, based on BGSTO, we designed two other double-line structures, BGSTA and BGSTB. Then with equal wall thickness and mass as a prerequisite, this study proceeds to design and compare the energy absorption properties of three bilinear thin-walled tubes in both axial and lateral cases. The deformation modes and crashworthiness of the three types of tubes with variable bilinear spacing ( β O/A/B ) are comparatively analysed. The improved complex proportional assessment (COPRAS) synthesis decision is used to obtain that BGSTO exhibits superior crashworthiness over the remaining two kinds of tubes. Finally, a surrogate model is established to perform multi-objective optimization on the optimal bilinear configuration BGSTO selected by the COPRAS method.