摘要
为解决汽车轻量化中混合材料车身的异质材料连接问题,研究了碳纤维增强环氧树脂复合材料(carbon fiber reinforced polymer,CFRP)与铝合金非平衡刚度四钉压铆胶接混合连接接头力学性能及失效机制.基于重导入和预定义场技术,建立了CFRP/Al非平衡刚度混合连接接头的非线性有限元分析模型,据此对混合连接压铆、回弹及拉伸载荷渐进失效机制进行仿真;对混合连接与单一连接力学性能和失效形式进行了对比分析.结果表明,所提出的建模方法能够同时考虑铆接成型过程和混合连接工艺顺序对混合接头连接特性的影响,混合连接最大载荷及能量吸收预测误差分别为2.3%、5.2%,具有较高的性能预测精度;铆接在失效初期对胶接具有加强作用,失效形式为先胶层失效后铝板拉伸失效,仿真与试验结果较为一致.
To solve the problem of multi-material connection in lightweight automotive bodies,the mechanical properties and failure mechanism of carbon fiber reinforced polymer(CFRP)and aluminum alloy unbalanced four-rivets bonded-riveted hybrid joints were studied.Based on re-import and predefined field,a nonlinear finite element analysis model of CFRP/Al unbalanced hybrid joint was established.The process of riveting,springback and progressive failure mechanism under tensile load of the hybrid joint were simulated.And comparative analysis of mechanical properties and failure modes between bonded joint,riveted joint and hybrid joint was carried out.It is shown that the modeling method proposed can take into consideration the impact of the riveting process and the process sequence on the characteristics of the hybrid joint simultaneously.The error value of the peak load and energy absorption predicted by the model is of 2.3%and 5.2%respectively with high prediction accuracy.The riveting can provide a strengthening effect on the bonding at the early stage of failure.The failure takes place usually in the form,the adhesive layer fails firstly and after that the aluminum plate fails.The simulation and test results are consistent relatively,verifying the correctness of the modeling method proposed.
作者
陈潇凯
郭子煜
金嘉威
孙凌玉
CHEN Xiaokai;GUO Ziyu;JIN Jiawei;SUN Lingyu(School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China;Department of New Energy, SAIC Volkswagen, Shanghai 201805, China;School of Transportation Science and Engineering,Beihang University, Beijing 100191, China)
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2021年第3期251-257,共7页
Transactions of Beijing Institute of Technology
基金
国家重点研发计划项目(2016YFB0101606)
国家自然科学基金资助项目(51675044)。