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Multiscale modeling of mechanically recycled glass fiber reinforced polyamide 6 composites accounting for viscoelasticity, viscoplasticity, and anisotropic damage

Article dans une revue avec comité de lecture
Author
SEKKAL, Saïf Eddine
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]
ccMERAGHNI, Fodil
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]
ccCHATZIGEORGIOU, George
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]
PRAUD, Francis
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]
DURAND, N.
302796 Centre technique des industries mécaniques [Cetim, France] [Cetim]

URI
http://hdl.handle.net/10985/26182
DOI
10.1016/j.compstruct.2025.119016
Date
2025-03
Journal
Composite Structures

Abstract

Fiber-reinforced thermoplastic composites are valued for their strength-to-weight ratio, cost-effectiveness, and recyclability, highlighting the need for efficient recycling technologies amid environmental concerns. This study addresses these challenges by examining the mechanical response of recycled glass fiber reinforced polyamide 6 composites and modeling their nonlinear, time-dependent behavior under complex loading conditions. Advanced nonlinear constitutive and multiscale models, initially developed for conventional fiber composites, are adapted to capture the stochastic response of recycled materials. These models integrate viscoelasticity, viscoplasticity and damage in the polymer matrix and account for anisotropic damage in the strands, addressing the heterogeneity introduced by the recycling process. A modified random sequential adsorption technique replicates the microstructures for nonlinear response modeling. Hypotheses based on microstructural investigations consider processing effects that disrupt the initial chip woven structure and create matrix-rich areas. The model captures anisotropy and variability observed in experimental data, providing a reliable framework for predicting the performance of recycled thermoplastic com- posites and improving the understanding of the relationship between microstructure and mechanical properties, with a focus on inelastic nonlinear behavior.

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