Multi-objective optimization of an industrial slurry phase ethylene polymerization reactor

被引：9

作者：

Thakur, Amit K. ^{[1
]}

Gupta, Santosh K. ^{[1
]}

Kumar, Rahul ^{[1
]}

Banerjee, Nilanjana ^{[1
]}

Chaudhari, Pranava ^{[1
]}

机构：

[1] Univ Petr & Energy Studies, Dept Chem Engn, Dehra Dun, Uttarakhand, India

来源：

INTERNATIONAL JOURNAL OF CHEMICAL REACTOR ENGINEERING | 2022年 / 20卷 / 06期

关键词：

NSGA II; optimization; polyethylene; slurry reactor; POLYETHYLENE TUBULAR REACTOR; FREE-RADICAL POLYMERIZATIONS; GENETIC ALGORITHM; PROPYLENE POLYMERIZATION; OLEFIN POLYMERIZATION; DYNAMIC OPTIMIZATION; BULK-POLYMERIZATION; METHACRYLATE; SIMULATION;

D O I：

10.1515/ijcre-2021-0196

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Slurry polymerization processes using Zeigler-Natta catalysts are most widely used for the production of polyethylene due to their several advantages over other processes. Optimal operating conditions are required to obtain the maximum productivity of the polymer at minimal cost while ensuring operational safety in the slurry phase ethylene polymerization reactors. The main focus of this multi-objective optimization study is to obtain the optimal operating conditions corresponding to the maximization of productivity and yield at a minimal operating cost. The tuned reactor model has been optimized. The single objective optimization (SOO) and multi-objective optimization (MOO) problems are solved using non-dominating sorting genetic algorithm-II (NSGA-II). A complete range of Pareto optimal solutions are obtained to obtain the maximum productivity and polymer yield at different input costs.

引用

页码：649 / 659

页数：11

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