Study on interlaminar fracture toughness of self-healing composites based on multi-scale analysis

doi:10.19936/j.cnki.2096-8000.20230928.004

Abstract

Abstract: In order to study the dual toughening effect of the thermoplastic EMAA fiber suture on the interlayer fracture toughness of carbon fiber composite laminates and the toughness after heat repair, experimental and numerical multi-scale modeling methods were used, the type Ⅰ interlaminar fracture toughness of carbon fiber composite laminates with EMAA suture network before and after thermal repair was analyzed. The equivalent mechanical parameters of carbon fiber bundles were predicted by the microscopic model of carbon fiber bundles, by measuring the meso-structure of the monolayer at the suture line, a meso-scale unit cell model was established to predict the equivalent mechanical parameters of the unit cell. The macro model of DCB specimen was constructed, and a viscous layer was added to the macro model to simulate EMAA repair agent to conduct type Ⅰ interlaminar fracture toughness analysis. Three-dimensional Hashin failure criterion and progressive degradation model were used to conduct damage analysis on fiber bundle and matrix, and bilinear constitutive model was used to determine the failure of viscous layer. The effectiveness of the multi-scale model is verified by comparing the experimental results with the simulation results. The simulation and experimental results show that the EMAA suture network can effectively improve the fracture toughness between layers and slow down crack propagation. Moreover, the three-dimensional suture network can send self-healing EMAA into the injury area, and then achieve high recovery of fracture toughness between layered cracks (repair rate of 175%).

Key words: carbon fiber composites, multiscale analysis, homogenization methods, interlayer fracture toughness, EMAA

CLC Number:

TB332

YANG Weiya, GAO Dongchen, TIE Ying, ZHANG Zhenzhen, GE Chaokun. Study on interlaminar fracture toughness of self-healing composites based on multi-scale analysis[J]. COMPOSITES SCIENCE AND ENGINEERING, 2023, 0(9): 29-35.

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