Abstract
In this paper, crashworthiness performance of multi-cell conical tubes with new sectional configuration design (i.e. square, hexagonal, octagonal, decagon and circular) has been evaluated under axial and three different oblique loads. The same weight conical tubes were comparatively studied using an experimentally validated finite element model generated in LS-DYNA. Complex proportional assessment (COPRAS) method was then employed to select the most efficient tube using two conflicting criteria, namely peak collapse force (PCF) and energy absorption (EA). From the COPRAS calculations, the multi-cell conical tube with decagonal cross-section (MCDT) showed the best crashworthiness performance. Furthermore, the effects of possible number of inside ribs on the crashworthiness of the decagonal conical tubes were also evaluated, and the results displayed that the tubes performed better as the number of ribs increased. Finally, parameters (the cone angle, θ, and ratio of the internal tube size to the external one, S) of MCDT were optimized by adopting artificial neural networks (ANN) and genetic algorithm (GA) techniques. Based on the multi-objective optimization results, the optimum dimension parameters were found to be θ=7.9°, S=0.46 and θ=8°, S=0.74 from the minimum distance selection (MDS) and COPRAS methods, respectively.
摘要
本文对采用新型截面结构设计(正方形、六边形、八边形、十边形和圆形)的多元锥管在轴向和 三种不同斜向载荷作用下的耐撞性能进行了评价。利用 LS-DYNA 建立的有限元模型对相同重量的不 同结构的锥管进行了对比研究。采用了复比例评估法(COPRAS), 利用峰值临界力(PCF)和能量吸收 (EA)两个相互矛盾的准则来选择最优管结构。从 COPRAS 计算结果可以看出, 具有十边形截面的多元 锥形管(MCDT)具有最优耐撞性能。评价了可能的内肋数对十边形截面锥形管耐撞性的影响, 结果表 明, 随着内肋数的增加, 十边形截面锥形管的耐撞性能得到增强。采用了人工神经网络(ANN)和遗传 算法(GA)对MCDT 的参数(锥角θ 和内外管尺寸比S)进行了优化。基于多目标优化的结果, 利用最小 距离选择法(MDS)和COPRAS 方法得到的最优尺寸分别是θ=7.9°, S=0.46 和θ=8°, S=0.74。
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Pirmohammad, S., Esmaeili-Marzdashti, S. Multi-objective optimization of multi-cell conical structures under dynamic loads. J. Cent. South Univ. 26, 2464–2481 (2019). https://doi.org/10.1007/s11771-019-4187-3
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DOI: https://doi.org/10.1007/s11771-019-4187-3
Keywords
- crashworthiness
- multi-cell conical tube
- axial and oblique loads
- complex proportional assessment (COPRAS)
- multi-objective optimization