Crashworthiness design and multi-objective optimization of bionic gradient circular multi-cell structure

被引:0
作者
Gong, Chao [1 ,2 ]
Yan, Hang [1 ]
Chong, Qi [1 ]
Liu, Yu [3 ]
机构
[1] Hefei Univ Technol, Sch Automot & Transportat Engn, Hefei, Peoples R China
[2] Luzhou Rongda Intelligent Transmiss Ltd Co, Luzhou, Peoples R China
[3] China Automot Engn Res Inst Ltd Co, Chongqing, Peoples R China
关键词
Bionic design; energy-absorbing structures; crashworthiness; gradient circular multi-cell; multi-objective optimization; prediction model; THIN-WALLED STRUCTURES; ENERGY-ABSORPTION CHARACTERISTICS; THEORETICAL PREDICTION; CRUSHING ANALYSIS; GRADED THICKNESS; TUBES;
D O I
10.1080/15376494.2025.2484430
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
As bionic design principles have been widely used in the design of energy-absorbing structures in recent years, this paper proposes a new bionic gradient circular multi-cell structure (BGCM) combining gradient and micro-circular features inspired by nature, such as bamboo and beetles, to enhance crashworthiness in energy-absorbing structures. A finite element model of the BGCM is developed and validated against experimental data, showing a maximum error of 7%. Comparative analysis between the bionic gradient multi-cell round tube (BGM) and BGCM demonstrates that the combination of gradient and micro-circular structures improves energy absorption capacity and load stability, yielding a 50% average increase in specific absorbed energy (SEA). The optimal cross-sectional structure of the bionic thin-walled tube was also selected using the E-TOPSIS method, and the BGCM structure exhibited excellent crashworthiness when the number of cell elements was 8. Additionally, the BGCM-8 has been optimized using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) for SEA and Initial Peak Force (IPF) with emphasis on wall thickness t and radius r. The comparison between the prediction model and the finite element model shows a maximum error of 0.4%, confirming the model's high accuracy in predicting BGCM mechanical behavior.
引用
收藏
页数:15
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