Predicting Molecular Weight Distribution, Melt Flow Index, and Bulk Density in a Polypropylene Reactor via a Validated Mathematical Model

Abstract

One of the main goals of polymer science has been to relate the process variable to their vital macroscopic properties in order to obtain tailor-made products. In particular, this goal is significant when we have to use a catalyst that has a unique and unknown behavior with its own complex kinetics such as a Ziegler–Natta catalyst for polypropylene production. Today, computer simulation with acceptable accuracy has come to the aid of polymer science. The final product properties are highly dependent on the crucial factors comprising the average molecular weight, its dispersity, and bulk density of a polymer, and these factors also depend on process variables with the complexity of a kinetic reaction. A mathematical model can be a worthy replacement to the conventional manner, experiment by trial and error, for designing a favorite product. In this study, a mathematical model is proposed to fulfill this aim. By the model with its offered algorithm, kinetic constants can be easily adjusted with fairly good prediction of the desired product. The modeling approach is a polymer moment balance technique (population balance) in a slurry semibatch reactor and coded in MATLAB/SIMULINK software. The model has been validated via experimental data from a laboratory scale reactor with an acceptable margin of error.