Process Intensification of Polymerization Processes with Embedded Molecular Weight Distributions Models: An Advanced Optimization Approach

被引:16
作者
Chen, Xi [1 ,4 ]
Shao, Zhijiang [1 ,4 ]
Gu, Xueping [2 ,4 ]
Feng, Lianfang [2 ,4 ]
Biegler, Lorenz T. [3 ]
机构
[1] Zhejiang Univ, Coll Control Sci & Engn, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Zhejiang Univ, Coll Chem & Biol Engn, State Key Lab Chem Engn, Hangzhou 310027, Zhejiang, Peoples R China
[3] Carnegie Mellon Univ, Dept Chem Engn, Pittsburgh, PA 15213 USA
[4] Zhejiang Univ, Natl Ctr Int Res Qual Targeted Proc Optimizat & C, Hangzhou 310027, Zhejiang, Peoples R China
基金
美国安德鲁·梅隆基金会;
关键词
CHAIN-LENGTH DISTRIBUTIONS; OPTIMAL GRADE TRANSITION; MONTE-CARLO-SIMULATION; PARAMETER-ESTIMATION; ETHYLENE POLYMERIZATION; DYNAMIC OPTIMIZATION; NUMERICAL INVERSION; REACTOR NETWORKS; SLURRY PROCESS; STEADY-STATE;
D O I
10.1021/acs.iecr.8b04424
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The manufacturing industry is challenged by increasing costs of scarce resources, rapid change, and tight competition in global markets, and the need for efficient and sustainable process design and operating strategies. Addressing these challenges has been the focus of process intensification (PI). Polymerization processes face the additional challenge of meeting tight product specifications, which are dictated by the demands of high quality and advanced materials. Meeting these specifications requires the incorporation of complex molecular weight distribution (MWD) models based on population balances of all the polymer chains. Addressing these challenges through process intensification requires the development and application of efficient, robust, and powerful optimization strategies and modeling frameworks, leading to an essential strategy for process intensification of polymerization systems. This survey presents the development and application of novel optimization strategies for model development, process synthesis and design, and the operation of polymer processes. The effectiveness of these optimization-based approaches will be demonstrated on a slurry process for high density polyethylene (HDPE), where significant advances in process intensification have been realized. Future directions are given, with the aim of benefiting both research and application in this field.
引用
收藏
页码:6133 / 6145
页数:13
相关论文
共 71 条
[1]   ALGORITHMIC SYNTHESIS OF CHEMICAL REACTOR NETWORKS USING MATHEMATICAL-PROGRAMMING [J].
ACHENIE, LEK ;
BIEGLER, LT .
INDUSTRIAL & ENGINEERING CHEMISTRY FUNDAMENTALS, 1986, 25 (04) :621-627
[2]   A SUPERSTRUCTURE BASED APPROACH TO CHEMICAL REACTOR NETWORK SYNTHESIS [J].
ACHENIE, LKE ;
BIEGLER, LT .
COMPUTERS & CHEMICAL ENGINEERING, 1990, 14 (01) :23-40
[3]   Dynamic Monte Carlo simulation of ATRP with bifunctional initiators [J].
Al-Harthi, Mamdouh ;
Soares, Joao B. P. ;
Simon, Leonardo C. .
MACROMOLECULAR REACTION ENGINEERING, 2007, 1 (01) :95-105
[4]   Dynamic Monte Carlo simulation of atom-transfer radical polymerization [J].
Al-Harthi, Mamdouh ;
Soares, Joao B. R. ;
Simon, Leonardo C. .
MACROMOLECULAR MATERIALS AND ENGINEERING, 2006, 291 (08) :993-1003
[5]   Control of molecular weight distribution of polyethylene in gas-phase fluidized bed reactors [J].
Ali, Mohammad Al-haj ;
Ajbar, Emadadeen Ali AbdelHamid ;
Alhumaizi, Khalid .
KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2010, 27 (01) :364-372
[6]  
[Anonymous], 2012, POLYOLEFIN REACTION
[7]   Effect of multiple feedings in the operation of a high-pressure polymerization reactor for ethylene polymerization [J].
Asteasuain, M ;
Ugrin, PE ;
Lacunza, MH ;
Brandolin, A .
POLYMER REACTION ENGINEERING, 2001, 9 (03) :163-182
[8]   Modeling and optimization of a high-pressure ethylene polymerization reactor using gPROMS [J].
Asteasuain, Mariano ;
Brandolin, Adriana .
COMPUTERS & CHEMICAL ENGINEERING, 2008, 32 (03) :396-408
[9]  
BASEDOW AM, 1978, MACROMOLECULES, V11, P744
[10]   Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization [J].
Biegler, L. T. ;
Zavala, V. M. .
COMPUTERS & CHEMICAL ENGINEERING, 2009, 33 (03) :575-582