Cohesive Zone Modeling of the Elastoplastic and Failure Behavior of Polymer Nanoclay Composites

• Main Authors: Uraching Chowdhury, Xiang-Fa Wu
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Journal of Composites Science
• Subjects: cohesive zone model (CZM); polymer nanoclay composites (PNCs); finite element analysis (FEA); effective strength and stiffness; elastoplastic deformations; scaling analysis
• Online Access: https://www.mdpi.com/2504-477X/5/5/131

Cohesive zone model (CZM) is commonly used to deal with the nonlinear zone ahead of crack tips in materials with elastoplastic deformation behavior. This model is capable of predicting the behavior of crack initiation and growth. In this paper, CZM-based finite element analysis (FEA) is performed to examine the effects of processing parameters (i.e., the clay nanoparticle volume fraction and aspect ratio) in the mechanical behaviors of a polymeric matrix reinforced with aligned clay nanoparticles. The polymeric matrix is treated as an ideal elastoplastic solid with isotropic hardening behavior, whereas the clay nanoparticles are simplified as stiff, linearly elastic platelets. Representative volume elements (RVEs) of the resulting polymer nanoclay composites (PNCs) are adopted for FEA with the clay nanoparticle distributions to follow both stack and stagger configurations, respectively. In the study, four volume fractions (Vf = 2.5%, 5%, 7.5% and 10%) and four aspect ratios (ρ = 5, 7.5, 10, and 20) of the clay nanoparticles in the PNCs are considered. Detailed computational results show that either increasing volume fraction or aspect ratio of the clay nanoparticles enhances the effective tensile strength and stiffness of the PNCs. The progressive debonding process of the clay nanoparticles in the polymeric resin was predicted, and the debonding was initiated in the linearly elastic loading range. The numerical results also show that PNCs with stagger nanoparticle configuration demonstrate slightly higher values of the engineering stress than those based on the stack nanoparticle configuration at both varying volume fractions and aspect ratios of the clay nanoparticles. In addition, CZM-based FEA predicts a slightly lower stress field around the clay particles in PNCs than that without integration of CZM. The present computational studies are applicable for processing PNCs with controllable mechanical properties, especially the control of the key processing parameters of PNCs, i.e., the volume fraction and aspect ratio of the clay nanoparticles.