Citation

Lv J, Bai Z, Du X, Zhu F, Chou CC, Jiang B, Xu S. Int. J. Crashworthiness 2023; 28(3): 435-448.

Copyright

(Copyright © 2023, Informa - Taylor and Francis Group)

DOI

10.1080/13588265.2022.2101306

PMID

unavailable

Abstract

Lattice structures and thin-walled tubes are two types of energy-absorbers widely studied and applied in engineering practice. In this study, a new type of lattice-structure filled thin-walled tube (LFT) was proposed by combining these two energy absorbers and designed via a new explainable data mining method. In this new type of LFT, a BCC-Z (Body- centred cubic unit cell with vertical struts) lattice structure was filled into a square thin-walled tube. Then, the new LFT was parameterized by five design variables, that is, the number of layers in the longitudinal direction (n), number of cells in the transverse direction (m), rod diameter (d), tube thickness (t) and height difference between tube and lattice structures (h). Using Latin hypercubic sampling algorithm, 150 design cases were generated. Numerical models were then developed to simulate their crush behavior, and the simulation dataset was used for data mining. The results showed that (1) Filling the BBC-Z lattice structure into a thin-walled tube can significantly improve the energy absorption (EA) capacity of the structure. (2) SEA (Specific Energy Absorption) of LFT significantly increased by increasing the rod diameter d, number of cells in the transverse direction m and number of layers in longitudinal direction n. (3) The decision trees generated in the data mining process indicated that the rod diameter d of the lattice structure is the key design variable that has most significant impact on EA, followed by m and n. (4) The design rules to build LFTs with high EA efficiency (SEA ≥ 16 kJ/kg and CFE (Crush Force Efficiency)≥45%), high total EA (SEA ≥ 16 kJ/kg and EA ≥ 6 kJ) and lightweight (SEA ≥ 16 kJ/kg and Mass ≤ 0.45 kg) were obtained from decision trees. The ideal configurations of LFT corresponding to these three objectives are: d > 2 mm, n > 2 and m > 3 for high EA efficiency; d > 2 mm, n > 2 and m > 3 for high total EA; and d > 2 mm, n > 2, m ≤ 4 and t ≤ 1.7 mm for lightweight.

Language: en

Keywords

3-D parametric design; data mining; decision tree; filled thin-wall tube; Lattice structure