Enhancing material efficiency of energy absorbers through graded thickness structures
Enhancing material efficiency of energy absorbers through graded thickness structures
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DOI：
10.1016/j.tws.2015.09.020
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发表时间：
2015-12
影响因子：
6.4
通讯作者：
Fengxiang Xu
中科院分区：
文献类型：
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作者：
Fengxiang Xu
目前，在车辆工业中一直存在对先进薄壁结构的期望，以更有效地使用材料，从而实现更轻的重量和甚至更高的能量吸收。本文提出了一种变壁厚的功能梯度管，以提高其吸能效率。除了直径和长度等几何参数外，控制厚度分布变化的梯度指数也对床层能量的增加有显著影响。通过对FGT管的碰撞实验，验证了数值模型的正确性。参数分析表明，FGT柱上级等厚度柱。以比能量吸收（SEA）和撞击力效率（CFE）为目标，以直径、初始长度和壁厚变化梯度指数为设计变量，对FGT管进行了轴向撞击多目标优化。采用多目标粒子群优化算法（MOPSO）求解Pareto最优解.此外，不同的代理模型，如响应面法（RSM），克里格法（KRM），径向基函数（RBF）的比较研究，也进行了深入了解他们的相对性能和特点的计算建模和设计优化。结果表明，通过优化几何参数和梯度指数，可以显著提高FGT管的性能。
At present, there has been constant aspiration of advanced thin-walled structures in vehicular industries for more efficient usage of materials to achieve much lighter weight and even higher energy absorption. In this paper, functionally graded thickness (FGT) tubes with a varying wall thickness are introduced and their energy-absorbing efficiency is enhanced. Apart from the geometrical parameters such as diameter and length, the gradient exponent that controls the variation of thickness distributions has also a significant effect on the increase in absorbed-energy. Numerical model is validated by performed crashing experiments of FGT tube. Parametric analysis demonstrates that the FGT column is superior to the uniform thickness (UT) column. Further, the multiobjective optimization (MOO) of FGT tubes is conducted for axial impacting by considering specific energy absorption (SEA) and crashing force efficiency (CFE) as objectives, and the diameter, initial length and gradient exponent of thickness variation as the design variables. The multiobjective particle swarm optimization algorithm (MOPSO) is applied to obtain the Pareto optimal solutions. In addition, a comparative study on different surrogate models, such as response surface method (RSM), Kriging method (KRM), and radial basis function (RBF), is also carried out to gain insights into their relative performance and features in computational modeling and design optimization. It is indicated that the performance of FGT tubes can be significantly improved by optimizing the geometrical parameters and gradient exponent.