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Nonlinear Micromechanical Modelling of Transverse Tensile Damage Behavior in Fiber-Reinforced Polymer Composites

Nian Li*

College of Mechanical and Power Engineering, Nanjing Tech University, Nanjing, 211816, China

* Corresponding Author: Nian Li. Email: email

Structural Durability & Health Monitoring 2019, 13(4), 331-346. https://doi.org/10.32604/sdhm.2019.07521

Abstract

The investigation focusing on the mechanical behaviors at the microstructural level in composite materials can provide valuable insight into the failure mechanisms at larger scales. A micromechanics damage model which comprises the coupling of the matrix constitutive model and the cohesive zone (CZM) model at fiber-matrix interfaces is presented to evaluate the transverse tensile damage behaviors of unidirectional (UD) fiber-reinforced polymer (FRP) composites. For the polymeric matrix that exhibits highly non-linear mechanical responses, special focus is paid on the formulation of the constitutive model, which characterizes a mixture of elasticity, plasticity as well as damage. The proposed constitutive model includes the numerical implementation of a fracture plane based ellipse-parabola criterion that is an extension of the classic Mohr-Coulomb criterion, corresponding post-yield flow rule and post-failure degradation rule in the fully implicit integration scheme. The numerical results are in good agreement with experimental measurements. It is found that directly using the matrix properties measured at the ply level to characterize the mechanical responses at the constituent level may bring large discrepancies in homogenized stress-strain responses and dominant failure mechanisms. The distribution of fracture plane angles in matrix is predicted, where it is shown to provide novel insight into the microscopic damage initiation and accumulation under transverse tension.

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Cite This Article

Li, N. (2019). Nonlinear Micromechanical Modelling of Transverse Tensile Damage Behavior in Fiber-Reinforced Polymer Composites. Structural Durability & Health Monitoring, 13(4), 331–346.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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