4.4 Article

Three-dimensional progressive damage models for cohesively bonded composite π joint

期刊

JOURNAL OF COMPOSITE MATERIALS
卷 48, 期 6, 页码 707-721

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/0021998313477169

关键词

strength; mechanical properties; finite element analysis; Adhesive joints; carbon fibres

资金

  1. National Science Foundation of China [10902004]
  2. Innovation Foundation of BUAA for PhD Graduates

向作者/读者索取更多资源

Integrated composite structures can significantly reduce the assembling cost and improve the performance of the aircraft. All-composite pi joint, which is a connector of integrated composite structures, has good ability to reduce the weight and assembly cost while retaining good load-carrying capability. To disclose the mechanics behavior of the out-of-plane, complex all-composite joint, the progressive damage methods are investigated for its good ability to trace the damage onset, damage propagation, up to collapse of composite structures. A progressive damage model is established using a new modified maximum stress failure criterion and a material degradation model developed from Chang's model. The material degradation model takes account of the matrix crack direction, which is predicted by the modified maximum stress-failure criterion. Meanwhile, five other progressive damage models are established and applied to static tensile analysis to study the mechanics behavior of the joint. To evaluate the prediction of the six progressive damage models in joint initial failure, damage propagation, joint strength and stiffness, the numerical results of the six progressive damage models are compared with the experiment results. The effects of failure criteria and material degradation model on the prediction results are discussed in detail. By the comparison, it can be concluded that the progressive damage model consisting of the modified maximum failure criteria and its corresponding material degradation model is considered as the best one for the analysis of the all-composite pi joints, because its initial failure prediction, failure process and ultimate failure prediction agree well with the experiment result.

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