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Crashworthiness design and optimization of bamboo-inspired tube with gradient multi-cells
https://orcid.org/0000-0001-6879-0537
https://orcid.org/0000-0002-6393-1190
Abstract This study seeks to understand how bamboo maintains its stability while being lightweight and flexible in strong winds, with the aim of applying the findings to develop an engineering tube that mimics bamboo’s unique structural properties. Initially, image processing revealed convex distribution along the radial direction of the fiber sheath area between bamboo nodes, which was further analyzed to examine its impact on the bending properties of bamboo. Subsequently, a new bionic tube with gradient multi-cells (BTGCs) was introduced, and its crashworthiness was investigated using the Simplified Super Folding Element (SSFE) theory to establish a theoretical model. Additionally, the influence of the structural parameters of BTGCs on its crashworthiness under different loading angles was investigated in silico. The optimal basic design parameters were selected by using the complex proportional evaluation (COPRAS) method, and a Pareto front set of bionic design parameters and impact angles was obtained using artificial neural network (ANN) and non-dominated sorting genetic algorithm (NSGA-II). The results indicated that the optimized BTGCs demonstrated superior crashworthiness compared to conventional circular and bi-layer tubes with an equal mass. This study can serve as a reference for designing highly-efficient bionic tubes.
Graphical abstract Display Omitted
Highlights The convex distribution of determines its bending properties. A novel bamboo-inspired thin-walled tube with gradient multi-cells was proposed. The basic design parameters of bionic tube were investigated and optimized. The bionic design parameters of bionic tube were investigated and optimized. The optimized novel bionic tube has better crashworthiness than conventional tubes with the same mass.
Crashworthiness design and optimization of bamboo-inspired tube with gradient multi-cells
https://orcid.org/0000-0001-6879-0537
https://orcid.org/0000-0002-6393-1190
Abstract This study seeks to understand how bamboo maintains its stability while being lightweight and flexible in strong winds, with the aim of applying the findings to develop an engineering tube that mimics bamboo’s unique structural properties. Initially, image processing revealed convex distribution along the radial direction of the fiber sheath area between bamboo nodes, which was further analyzed to examine its impact on the bending properties of bamboo. Subsequently, a new bionic tube with gradient multi-cells (BTGCs) was introduced, and its crashworthiness was investigated using the Simplified Super Folding Element (SSFE) theory to establish a theoretical model. Additionally, the influence of the structural parameters of BTGCs on its crashworthiness under different loading angles was investigated in silico. The optimal basic design parameters were selected by using the complex proportional evaluation (COPRAS) method, and a Pareto front set of bionic design parameters and impact angles was obtained using artificial neural network (ANN) and non-dominated sorting genetic algorithm (NSGA-II). The results indicated that the optimized BTGCs demonstrated superior crashworthiness compared to conventional circular and bi-layer tubes with an equal mass. This study can serve as a reference for designing highly-efficient bionic tubes.
Graphical abstract Display Omitted
Highlights The convex distribution of determines its bending properties. A novel bamboo-inspired thin-walled tube with gradient multi-cells was proposed. The basic design parameters of bionic tube were investigated and optimized. The bionic design parameters of bionic tube were investigated and optimized. The optimized novel bionic tube has better crashworthiness than conventional tubes with the same mass.
Crashworthiness design and optimization of bamboo-inspired tube with gradient multi-cells
https://orcid.org/0000-0001-6879-0537
https://orcid.org/0000-0002-6393-1190
Abstract This study seeks to understand how bamboo maintains its stability while being lightweight and flexible in strong winds, with the aim of applying the findings to develop an engineering tube that mimics bamboo’s unique structural properties. Initially, image processing revealed convex distribution along the radial direction of the fiber sheath area between bamboo nodes, which was further analyzed to examine its impact on the bending properties of bamboo. Subsequently, a new bionic tube with gradient multi-cells (BTGCs) was introduced, and its crashworthiness was investigated using the Simplified Super Folding Element (SSFE) theory to establish a theoretical model. Additionally, the influence of the structural parameters of BTGCs on its crashworthiness under different loading angles was investigated in silico. The optimal basic design parameters were selected by using the complex proportional evaluation (COPRAS) method, and a Pareto front set of bionic design parameters and impact angles was obtained using artificial neural network (ANN) and non-dominated sorting genetic algorithm (NSGA-II). The results indicated that the optimized BTGCs demonstrated superior crashworthiness compared to conventional circular and bi-layer tubes with an equal mass. This study can serve as a reference for designing highly-efficient bionic tubes.
Graphical abstract Display Omitted
Highlights The convex distribution of determines its bending properties. A novel bamboo-inspired thin-walled tube with gradient multi-cells was proposed. The basic design parameters of bionic tube were investigated and optimized. The bionic design parameters of bionic tube were investigated and optimized. The optimized novel bionic tube has better crashworthiness than conventional tubes with the same mass.
Crashworthiness design and optimization of bamboo-inspired tube with gradient multi-cells
Xing, Jin (author) / Zhao, Jieliang (author) / Niu, Qun (author) / Zhang, Tianyu (author) / Zhang, Chenyang (author) / Zhang, Yuling (author) / Wang, Wenzhong (author) / Yan, Shaoze (author) / Liu, Xiaonan (author)
Thin-Walled Structures ; 191
2023-07-16
Article (Journal)
Electronic Resource
English
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