Estimation of Olefin Polymerization Kinetic Parameters Based on Particle Swarm Optimization Algorithm
TIAN Zhou 1,2, HONG Huaping 3, SHI Jie 1, WANG Zhenlei 1
1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;
2. Shanghai Inst Intelligent Science & Technology, Tongji University, Shanghai 200092, China;
3. Sinopec Zhenhai Refining & Chemical Company, Ningbo 315207, China
Abstract Estimation of polymerization kinetics parameters is an important step in the modeling and optimization of olefin polymerization process. According to the problem of multi-active center characteristics of Ziegler-Natta catalyst, complex reactions and numerous kinetic parameters, a method of estimating kinetics parameters of olefin polymerization based on particle swarm optimization (PSO) was proposed. In the method, an optimization problem was constructed, in which the polyolefin molecular weight distribution (MWD), short branching chain distribution (SCB) and copolymer composition distribution (CCD) were taken as the optimization objective and kinetics parameters as the optimization variables, and it was solved directly by using immune algorithm (IA) and PSO algorithm respectively. The results showed that the kinetics parameters of homopolymerization with MWD as the goal could be estimated by both algorithms. However, the PSO algorithm was more accurate to estimate the kinetics parameters of multi-active olefin polymerization, and the solving speed was faster than that by IA. This method provides a new tool for chain microstructure oriented modeling of olefin polymerization process.
TIAN Zhou,HONG Huaping,SHI Jie et al. Estimation of Olefin Polymerization Kinetic Parameters Based on Particle Swarm Optimization Algorithm[J]. Chemical Reaction Engineering and Technology, 2022, 38(1): 12-22.
TIAN Zhou,HONG Huaping,SHI Jie et al. Estimation of Olefin Polymerization Kinetic Parameters Based on Particle Swarm Optimization Algorithm[J]. Chemical Reaction Engineering and Technology, 2022, 38(1): 12-22.
