Akademik Veri Yönetim Sistemi
POLYMER COMPOSITES, 2025 (SCI-Expanded, Scopus)
The present study investigates the optimization of process parameters for the fabrication of thick-section glass fiber-reinforced epoxy composites, with a particular focus on glass fiber-reinforced leaf springs designed for heavy-duty vehicles. Manufacturing such components presents significant challenges due to low thermal conductivity and the exothermic nature of the curing reaction, which often results in temperature overshoots and potential resin degradation. To address these issues, a combined experimental and computational approach was adopted. Cure kinetics were characterized via Differential Scanning Calorimetry (DSC) and thermal properties by the Hot Disk method. These properties were subsequently integrated into a Finite Element (FE) model to predict curing behavior. A Genetic Algorithm (GA) was employed in two stages: initially for model parameter calibration and subsequently for process parameter optimization. This approach enabled a reduction in overall curing time by up to 50%, while effectively mitigating excessive temperature rise. Furthermore, some practical strategies-such as mold temperature adjustments, enhancement of resin thermal conductivity, and implementation of B-staging-were proposed to improve process efficiency and product quality. The results demonstrate a process optimization framework for the high-volume production of thick-section composite components in automotive applications, achieving an optimal balance between thermal management and manufacturing efficiency.