Heat transfer prediction during curing of thick part of unsaturated polyester resin containing nanoparticles of graphene oxide and modified graphene oxide

In this study, the challenges of using nanoparticles such as graphene oxide (GO) and modified graphene oxide (MGO) in the production of thick parts were investigated. In addition, using various kinetic models, the trend of temperature increases in pure unsaturated polyester resin (UPR), and UPR containing GO and MGO were investigated. The heat transfer equations were solved using programming code in MATLAB software. In the following, the role of the variation in density, convection heat transfer coefficient, and thermal conductivity coefficient on the prediction of temperature at different points of the parts is evaluated. The findings indicated that the choice of the kinetic model can play an effective role in predicting the temperature in the parts. An increased temperature causes a decrease in the structural regularity of the resin network and intensifies phonon scattering to decrease, and will eventually cause a decrease in the thermal conductivity coefficient. Highlights The mathematical modeling was developed on the curing of unsaturated polyester nanocomposite. The cure kinetic models and thermal properties had important roles in the model accuracy. The best prediction of temperature changes was provided by Vyazovkin's model. The results of developed model satisfactorily matched the experimental data. Temperature profile in thick part of unsaturated polyester resin insight from experiment and model.