Inverse Modeling of Thermal Decomposition of Flame-Retardant PET Fiber with Model-Free Coupled with Particle Swarm Optimization Algorithm

Abstract

The thermal decomposition model of flame-retardant polyethylene terephthalate (FRPET) fiber is essential for predicting its fire behavior and do relevant fire simulation. In this work, the thermal decomposition character of FRPET is investigated via thermogravimetric analysis at four heating rates. Two kinetic schemes are proposed based on the analysis of experimental data and model-free methods. The model-free methods (Friedman and advanced Vyazovkin methods) are employed to determine possible search range for particle swarm optimization algorithm with constriction factor (CFPSO). Thus, this coupled method could evaluate the kinetic parameters for two proposed schemes without initial guess. Both models could reasonably predict the experimental data with obtained parameters, and the second two-step consecutive model shows better performance. The performance of CFPSO on the second model is further compared with improved generalized simulated annealing algorithm, and CFPSO was found to be more effective. Furthermore, global sensitivity analysis was conducted via the Sobol method to investigate the influence of kinetic parameters for the second model on predicted results. The most influential parameters are ln A and Eα of the second reaction and reaction order n of the third reaction.