Investigation and optimization of polyolefin elastomers polymerization processes using multi-objective genetic algorithm

Abstract

The aim of this research is to develop continuous reactor network models to determine the reactor configuration and corresponding optimal operating conditions of a polyolefin elastomers polymerization process. To achieve this objective, a modified vapor-liquid equilibrium model is integrated with both the continuous stirred tank reactor (CSTR) model and the plug flow reactor (PFR) model to accurately predict the vaporization rates of liquid. The multi-objective problem is formulated to maximize the monomer conversion and minimize the total annualized cost simultaneously. To solve the multi-objective problem, the genetic algorithm is utilized to identify the optimal operating conditions. Furthermore, the impact of the reactor combination mode is analyzed by varying the number and sequence of CSTR or PFR. The research findings reveal that a multi-phase CSTR without circulating stream followed by a PFR is the optimal reactor configuration. The proposed configuration can enhance reactor productivity and reduce the total annualized cost simultaneously while meeting the desired polymer properties.