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International Journal of Automotive Technology > Volume 24(4); 2023 > Article
International Journal of Automotive Technology 2023;24(4): 1075-1088.
doi: https://doi.org/10.1007/s12239-023-0088-4
CRASHWORTHINESS OPTIMIZATION OF TAPERED UD-CFRP TUBE ACCOUNTING FOR MULTIPLE LOADING PANGLES
Yisong Chen , Guohua Zhu , Zhen Wang
School of Automobile, Chang’an University
PDF Links Corresponding Author.  Zhen Wang  , Email. zhenwang_chd@chd.edu.cn
ABSTRACT
Tapered composite energy-absorbing components have superior advantages in weight reduction and crashworthiness improvement subjected to oblique compressions compared to straight structures. This study investigated the crashworthiness characteristics of uni-directional carbon fiber reinforced plastic (UD-CFRP) tubes under various loading angles, and further provided the guidance on multi-objectives optimization for UD-CFRP tubes accounting for multiple loading cases. The crashworthiness characteristics of straight UD-CFRP tubes subjected to three compressive angles (0°, 10° and 20°) were firstly explored experimentally, and results indicated that energy-absorbing capacity of samples decreased with the loading angles increasing due to changes in deformation behaviors. The multi-layer finite element modes (FEMs) were developed and validated, and simulations found that internal energy (IE) of intra-CFRP layer and inter-cohesive layer, friction energy decreased with the increase in loading angles. Parametric studies indicated crashworthy performances of UD-CFRP samples under multiple loading angles can be further improved by adjusting the tapered angle or wall thickness. Consequently, the synthetic special energy absorption (SEAβ), synthetic peak crushing force (PCFβ) and mass of tapered tube were optimized accounting for three different loading groups. Compared to baseline sample, the SEAβ was improved by 14 %, while the PCFβ and mass were reduced by 30.2 % and 19 %, respectively.
Key Words: Tapered composite structures, Energy absorption mechanism, Multiple loading angles, Multi-objectives optimization
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