仿生层级薄壁方管的耐撞性研究

为了进一步改善车辆结构部件的耐撞性能,基于甲虫翅鞘微观锥形小梁结构提出新颖的仿生层级薄壁方管(BHST)结构,包括SBHST-4,SBHST-9,BHST-4和BHST-9。通过非线性有限元软件和试验验证结果建立BHST有限元模型,并对比其与传统多胞薄壁方管结构的轴向吸能特性。考虑到结构壁厚、截面尺寸和空间位置因素对BHST-9结构耐撞性能的影响,采用参数分析方法,研究小方锥管下截面尺寸b分别和空间位置参数λ、结构壁厚t对BHST-9结构轴向吸能特性的影响。此外,结合径向基函数(RBF)神经网络代理模型技术与非支配排序遗传算法(NSGA-Ⅱ)对BHST-9结构进行多目标优化分析,以获取BHST-9结构的最优配置。研究结果表明:BHST-9结构呈现出较优异的轴向吸能效果,其比吸能较传统9胞薄壁方管在等质量的条件下提高了22.87%,初始峰值力降低了10.22%;适当增加结构壁厚和小方锥管下截面尺寸有利于提升BHST-9结构的吸能能力;随着λ的增加,BHST-9结构的比吸能呈现出先增后减的趋势,当λ为0.5时,不同下截面尺寸小方锥管的BHST-9结构整体上具有较高的比吸能和较稳定的折叠变形模式,且初始峰值力变化幅度较小,但BHST-9结构中的仿生小方锥管下截面尺寸和结构壁厚较空间位置参数对比吸能的提升作用更为显著;当BHST-9结构初始峰值力不高于140kN时,其最优设计参数t,b分别为1.61,24.67mm。

Crashworthiness of Bio-inspired Hierarchical Thin-walled Square Tubes

To further improve the crashworthiness of the structural components of vehicles, bio-inspired hierarchical thin-walled square tubes (BHSTs) inspired by the microstructure of conical trabecula in the beetle elytron were proposed, which included SBHST-4, SBHST-9, BHST-4, and BHST-9. According to the nonlinear finite-element software and experimental validation results, the finite-element models of BHSTs were established. In addition, the axial energy absorption characteristics of BHSTs and conventional multicell thin-walled square tubes were compared. BHST-9 exhibits superior axial energy absorption characteristics compared with conventional nine-cell thin-walled square tube; The specific energy absorption (E_s) of BHST-9 is increased by 22.87%, and the initial peak crushing force (F_p) is reduced by 10.22% under equal mass. By considering the influence of the wall thickness, cross-sectional size, and spatial position on the crashworthiness of BHSTs, the effects of the lower cross-sectional size b, spatial position parameter λ of a small square cone, and structural wall thickness t on the axial energy absorption characteristics of BHST-9 were studied by using the parameter analysis method. In addition, to explore the optimal configuration of BHST-9, the multi-objective optimization of BHST-9 was carried out by combining the radial basis function (RBF) neural network proxy model and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The results show that a reasonable increase in t and b is beneficial for improving the energy absorption capacity of BHST-9. With an increase in λ, the E_s of BHST-9 increases first and then decreases. When λ was 0.5, BHST-9 with different b had higher E_s and more stable folding deformation mode and the range of variation of F_p was small. However, the structural wall thickness and lower cross-sectional size of the bionic small square cone in BHST-9 were more significant in improving E_s than λ. When F_p of BHST-9 was not greater than 140 kN, the optimal design parameters of t and b were 1.61 and 24.67 mm, respectively.