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Automotive Engineering ›› 2024, Vol. 46 ›› Issue (7): 1323-1334.doi: 10.19562/j.chinasae.qcgc.2024.07.019

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Crushing Analysis and Interval Optimization Design for Multi Cell Aluminum Alloy Thin-Walled Tubes

Lijun Qian1,Luxin Yu1,2,Xianguang Gu1(),Wenyu Liang1   

  1. 1.School of Automobile and Traffic Engineering,Hefei University of Technology,Hefei  230009
    2.School of Mechanical Engineering,Anhui Technical College of Mechanical and Electrical Engineering,Wuhu  241002
  • Received:2024-01-23 Revised:2024-02-17 Online:2024-07-25 Published:2024-07-22
  • Contact: Xianguang Gu E-mail:gxghfut@163.com

Abstract:

Aluminum alloy multi-cell thin-walled tubes have better mechanical properties in energy absorption than ordinary square tubes in axial compression conditions, with a wide range of application prospects in automotive, aviation, military equipment, and other industries. To study the anisotropic characteristics of extruded 6061-T6 aluminum alloy material, uniaxial tensile mechanical properties tests are conducted on the sheet along the extrusion direction of 0°, 45°, and 90°. The corresponding stress-strain curves and anisotropic characteristic parameters are obtained, and the material constitutive model is established based on the yield criterion of anisotropic hardening behavior. Tubes with different cross-sectional configurations shaped as the Chinese characters of mouth, day and eye are designed and quasi-static crushing tests are conducted. By analyzing the deformation crushing force curve, it is shown that the thin-walled structure of the triple-cell alloy has superior crash resistance performance. In order to further obtain the optimal design parameters of the triple-shaped tube, considering the uncertain effect of material parameter fluctuations such as Poisson's ratio and elastic modulus on the structural impact resistance, the multi-cell aluminum alloy thin-walled tube impact resistance interval uncertainty optimization model is established. The interval possibility degree method is used to transform it into a deterministic problem. By combining the Artificial Neural Networks (ANNs) model with the Intergeneration Projection Genetic Algorithm (IP-GA) method, a double-layer nested optimization is performed on this problem to analyze the impact of different likelihood levels on uncertainty optimization results, providing guidance for the selection of different reliability optimization design.

Key words: aluminum alloy thin-walled tubes, material constitutive, multi cell structure, crash resistance, interval optimization