Microscopic‐to‐macroscopic finite element analysis for predicting polymer‐graphene nanocomposite laminate mechanical strength

Abstract Graphene fillers significantly enhance the mechanical properties of polymer composites. While experimental analysis remains crucial, computational approaches such as finite element analysis ( FEA ) provide an efficient alternative for characterizing these enhancements. In this work, we developed a multiscale framework where composite properties were obtained by microscale modeling using representative volume elements ( RVE ) in FEA validated by experimental results, which were then used as the input for macroscopic multi‐layered laminate structures under pure and open‐hole tensile tests. The effects of filler orientation and filler loading on composite laminate mechanical strength were investigated. Our results reveal that orthotropic laminates exhibit superior mechanical performance compared to quasi‐isotropic laminates and those with randomly oriented fillers. The in‐plane filler alignment in orthotropic laminates provides more effective reinforcement, leading to on average 28.40% lower maximum failure index (FI) values than quasi‐isotropic laminates. Additionally, laminates with uniform filler loading outperform those with variable filler distributions, as stress is more evenly distributed, reducing the maximum FI on average by 44.71% and 19.62% in orthotropic and quasi‐isotropic laminates, respectively. Furthermore, the choice of polymer matrix affects composite performance as well. Polycarbonate, with its higher modulus, enhances graphene reinforcement more effectively than high‐density polyethylene. These findings highlight the importance of filler alignment, filler loading distribution, and matrix selection in optimizing the mechanical properties of polymer‐graphene composite laminates and provide design insights for experimental explorations. Highlights Developed a microscopic FEA model validated by experimental results. Utilized a multiscale FEA approach linking the microscale RVE to the macroscale model. Achieved design guide for polymer‐graphene nanocomposite laminate structures.

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Publication Details

Journal
Polymer Composites
Published
2025-03-25
DOI
https://doi.org/10.1002/pc.29764
Primary Topic
Mechanical Behavior of Composites
Type
article
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article

Microscopic‐to‐macroscopic finite element analysis for predicting polymer‐graphene nanocomposite laminate mechanical strength

Bennie Grové, Derek L. Patton, Boran Ma
Polymer Composites
Mechanical Behavior of Composites
article

Microscopic‐to‐macroscopic finite element analysis for predicting polymer‐graphene nanocomposite laminate mechanical strength

Bennie Grové, Derek L. Patton, Boran Ma
article en

Abstract

Abstract Graphene fillers significantly enhance the mechanical properties of polymer composites. While experimental analysis remains crucial, computational approaches such as finite element analysis ( FEA ) provide an efficient alternative for characterizing these enhancements. In this work, we developed a multiscale framework where composite properties were obtained by microscale modeling using representative volume elements ( RVE ) in FEA validated by experimental results, which were then used as the input for macroscopic multi‐layered laminate structures under pure and open‐hole tensile tests. The effects of filler orientation and filler loading on composite laminate mechanical strength were investigated. Our results reveal that orthotropic laminates exhibit superior mechanical performance compared to quasi‐isotropic laminates and those with randomly oriented fillers. The in‐plane filler alignment in orthotropic laminates provides more effective reinforcement, leading to on average 28.40% lower maximum failure index (FI) values than quasi‐isotropic laminates. Additionally, laminates with uniform filler loading outperform those with variable filler distributions, as stress is more evenly distributed, reducing the maximum FI on average by 44.71% and 19.62% in orthotropic and quasi‐isotropic laminates, respectively. Furthermore, the choice of polymer matrix affects composite performance as well. Polycarbonate, with its higher modulus, enhances graphene reinforcement more effectively than high‐density polyethylene. These findings highlight the importance of filler alignment, filler loading distribution, and matrix selection in optimizing the mechanical properties of polymer‐graphene composite laminates and provide design insights for experimental explorations. Highlights Developed a microscopic FEA model validated by experimental results. Utilized a multiscale FEA approach linking the microscale RVE to the macroscale model. Achieved design guide for polymer‐graphene nanocomposite laminate structures.

Polymer CompositesVol. 46(S1)
University of Southern Mississippi (US)
Openalex Percentile: Top 93%
Mechanical Behavior of Composites
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