基于粒子群优化算法的烯烃聚合反应动力学参数估计  

Estimation of Olefin Polymerization Kinetic Parameters Based on Particle Swarm Optimization Algorithm

作　　者：田洲[1,2] 洪华平 石杰[1] 王振雷 TIAN Zhou;HONG Huaping;SHI Jie;WANG Zhenlei(Key Laboratory of Smart Manufacturing in Energy Chemical Process,Ministry of Education,East China University of Science and Technology,Shanghai 200237,China;Shanghai Inst Intelligent Science&Technology,Tongji University,Shanghai 200092,China;Sinopec Zhenhai Refining&Chemical Company,Ningbo 315207,China)

机构地区：[1]华东理工大学能源化工过程智能制造教育部重点实验室,上海200237 [2]同济大学上海智能科学与技术研究院,上海200092 [3]中国石油化工股份有限公司镇海炼化分公司,浙江宁波315207

出　　处：《化学反应工程与工艺》2022年第1期12-22,共11页Chemical Reaction Engineering and Technology

基　　金：国家重点研发计划项目(2018YFB1701103)。

摘　　要：聚合反应动力学参数估计是烯烃聚合过程建模与优化的重要环节和难点。针对Ziegler-Natta催化剂多活性中心特性、反应复杂、动力学参数多的问题,提出了基于粒子群优化(PSO)算法的烯烃聚合反应动力学参数估计方法。该方法以聚烯烃分子量分布(MWD)、短支链分布(SCB)、共聚组成分布(CCD)等微观链结构为目标,以动力学参数为优化变量,采用免疫算法(IA)和PSO算法直接进行优化求解。结果表明:两种算法均可以实现以MWD为目标的均聚反应动力学参数的估计,但PSO算法可以实现多活性位烯烃聚合反应动力学参数的准确估计,且求解速度比IA法更快。该方法为面向精细链结构的烯烃聚合过程模型化研究提供了新手段。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.

关 键 词：粒子群优化算法 免疫算法 动力学参数估计 微观链结构 

分 类 号：TQ325.1[化学工程—合成树脂塑料工业]