Polymer Composites, 2025 (SCI-Expanded)
This work investigates the enhancement of creep resistance in glass-fiber-reinforced polymer (GFRP) composites through the incorporation of bio-derived cellulose nanocrystals (CNCs). Using a combination of experimental testing and numerical modeling, epoxy and GFRP samples were reinforced with CNCs at varying concentrations (0, 0.5, 1, and 1.5 wt%) and subjected to tensile and creep tests under stress levels corresponding to 20%–30% of their ultimate tensile strength. Results demonstrated significant improvements in creep resistance for epoxy at 1 wt% CNC, with the creep coefficient (A) reduced by up to 14% and the time exponent (m) decreased by 5%, highlighting enhanced time-dependent performance. At this optimal CNC concentration, creep strain reductions of 11%, 13%, and 19% were observed for GFRPs in the 0°, 45°, and 90° directions, respectively. However, at higher CNC contents, agglomeration diminished these enhancements, underscoring the critical need for optimal dispersion. A finite element (FE) model incorporating a Representative Volume Element (RVE) approach was developed to simulate the creep behavior of GFRP composites. This RVE-based modeling strategy uniquely enables a more precise representation of the microscale stress distribution and time-dependent deformation mechanisms. The FE analysis of the GFRPs using the Norton-Bailey creep models for the neat and CNC-reinforced epoxies further validated the experimental observations and provided deeper insights into the mechanisms governing creep behavior. This study highlights the potential of CNCs as sustainable reinforcements for advanced composites, paving the way for their application in high-performance and environmentally friendly materials. Highlights: An RVE-based FE model for creep prediction in GFRPs. Enhanced GFRP properties using bio-derived CNCs as sustainable reinforcement. Identified 1 wt% CNC as optimal for creep resistance and tensile modulus. Validated findings via experimental and numerical simulations.