Emulsion polymerization and copolymerization in continuous reactor systems

Continuous reactors are important for commercial production of latex products and they can be useful tools for fundamental polymerization kinetics studies. Results are presented for four projects: (i) elimination of conversion oscillations in continuous stirred-tank reactors (CSTR) by use of a tubular prereactor; (ii) use of a seed-fed CSTR to measure free radical transport from monomer-swollen latex particles; (iii) development of a continuous process as an alternative to a commercial batch process; and (iv) determination of copolymerization kinetic parameters with a steady-state CSTR system.     

OPERATING REGIME DECOMPOSITION USING NEURAL NETWORKS

This article addresses the problem of identification of a nonlinear process operating over a wide range of conditions. The global space is divided into multiple local regimes, a nonlinear model is developed for each regime, and a quadratic programming-based algorithm is used to ensure smooth transition between the regimes on-line. The use of nonlinear models as opposed to linear models reduces the number of local regimes needed. Neural networks are used to model these regimes because of their strong ability to capture nonlinearity, and their combination with the switching algorithm improves transient performance. The performance of the method is demonstrated on an exothermic CSTR and a pH neutralization process.     

Operating regime decomposition using neural networks

This article addresses the problem of identification of a nonlinear process operating over a wide range of conditions. The global space is divided into multiple local regimes, a nonlinear model is developed for each regime, and a quadratic programming-based algorithm is used to ensure smooth transition between the regimes on-line. The use of nonlinear models as opposed to linear models reduces the number of local regimes needed. Neural networks are used to model these regimes because of their strong ability to capture nonlinearity, and their combination with the switching algorithm improves transient performance. The performance of the method is demonstrated on an exothermic CSTR and a pH neutralization process.     

基于T-S模糊模型的间歇过程的迭代学习容错控制

间歇过程不仅具有强非线性,同时还会受到诸如执行器等故障影响,研究非线性间歇过程在具有故障的情况下依然稳定运行至关重要。针对执行器增益故障及系统所具有的强非线性,提出一种新的基于间歇过程的T-S模糊模型的复合迭代学习容错控制方法。首先根据间歇过程的非线性模型,利用扇区非线性方法建立其T-S模糊故障模型,再利用间歇过程的二维特性与重复特性,在2D系统理论框架内,设计2D复合ILC容错控制器,进而构建此T-S模糊模型的等价二维Rosser模型,接着利用Lyapunov方法给出系统稳定充分条件并求解控制器增益。针对强非线性的连续搅拌釜进行仿真,结果表明所提出方法具有可行性与有效性。     

PVC反应釜釜温自抗扰控制器设计

针对反应釜釜温过程控制中存在时变性、非线性、不确定性和多干扰性的问题,在分析自抗扰技术的基础上,采用PD控制器代替非线性反馈部分对补偿后的串联积分式对象进行控制的方法,设计了反应釜釜温动态模型的自抗扰控制器。仿真结果表明：在缺乏对象精确数学模型的情况下,该系统表现出良好的静、动态品质。同时,通过Monte—Carlo实验方法验证了系统具有较强的鲁棒性。     

The use of momentum ratio to evaluate the performance of CSTRs

In this study, the residence time distribution of a CSTR was measured and analysed for variations in CSTR feed geometry, impeller speed and inlet flow rate. The measured residence time distributions were also used to characterise the degree of plug flow behaviour and short-circuiting. The data showed that the performance of a CSTR could not be evaluated using the ratio of the mean residence time to the batch-mode mixing time (τ/t_M), and that this approach can lead to process over-design and excessive energy requirements. Instead, it was shown that all process parameters could be correlated using the ratio of the inlet jet momentum to the impeller discharge momentum. The prediction of the degree of short-circuiting and plug flow in the CSTR could be used to improve process control. In addition, the results can be used to identify whether the inlet position or diameter of an existing CSTR should be modified to improve process performance.     

基于KSFDA-SVDD的非线性过程故障检测方法

慢特征分析(SFA)是一种无监督的线性学习算法,没有考虑过程数据的类别信息和非线性特征。针对此问题,提出一种基于核慢特征判别分析(KSFDA)和支持向量数据描述(SVDD)的非线性过程故障检测方法KSFDA-SVDD。该方法首先利用核技巧将数据从原始空间映射到高维空间,然后通过最大化正常工况数据和故障模式数据之间伪时间序列的时间变化同时最小化正常工况数据内部伪时间序列的时间变化计算判别矩阵,最后利用SVDD描述采用判别矩阵降维后的正常工况数据的分布域,构建监控统计量检测过程故障。在连续搅拌反应器(CSTR)过程上的仿真结果表明所提出方法的故障检测性能优于传统的KPCA方法。     

Continuous reactive crystallization of pharmaceuticals using impinging jet mixers

For reactive crystallization of pharmaceuticals that show a rapid reaction rate, low solubility of active pharmaceutical ingredient and hence a large supersaturation, it was found in a recent study that a process design which integrates an impinging jet mixer and batch stirred tank produces high quality crystals. The current investigation examines if the short processing time of reactive crystallization permits the impinging jet mixer—stirred tank design to be modified to operate in a continuous mode. The new design combines an impinging jet mixer for feed introduction and reaction with a continuous stirred tank reactor (CSTR) and tubular reactor for crystal growth. A study of reactive crystallization of sodium cefuroxime (an antibiotic), using first a 1L CSTR then scaling to a 50L CSTR, found that the new design produces crystals of higher crystallinity, narrower particle size, and improved product stability, than batch crystallizers. © 2016 American Institute of Chemical Engineers AIChE J, 63: 967–974, 2017     

Operating zone segregation of chemical reaction systems based on stability and non-minimum phase behavior analysis

Many chemical reaction systems exhibit input/output multiplicity characteristics and non-minimum phase behavior. These inherent characteristics are known to cause limitations in process operation, so it is useful to have some knowledge of these at the early design stage of a chemical reaction process. Focusing on inherently safer designs, this paper addresses a strategy for classifying the process operating region into distinct zones at the early stage of process design, based on stability/instability and minimum/non-minimum phase behavior analysis. The strategy is illustrated by two case studies, where the operating spaces of an isothermal CSTR and an exothermic CSTR are classified into zones with different characteristics. The results provide information that is very important for guiding process design and operation about how the inherent properties of a process change with changes in its operating conditions.     

Evolutionary polymorphic neural network in chemical process modeling

Evolutionary polymorphic neural network (EPNN) is a novel approach to modeling dynamic process systems. This approach has its basis in artificial neural networks and evolutionary computing. As demonstrated in the studied dynamic CSTR system, EPNN produces less error than a traditional recurrent neural network with a less number of neurons. Furthermore, EPNN performs networked symbolic regressions for input–output data, while it performs multiple step ahead prediction through adaptable feedback structures formed during evolution. In addition, the extracted symbolic formulae from EPNN can be used for further theoretical analysis and process optimization.     

Measurement of nonlinearity in chemical process control systems: The steady state map

Most chemical processes exhibit some degree of nonlinearity, and when selecting an appropriate controller design approach it is important to understand the extent of this nonlinearity. In this paper a quantitative measure of steady-state process nonlinearity is proposed. Drawing from results for nonlinear regression, the curvature is decomposed into tangential and normal components. It is shown that the tangential curvature can be reduced or eliminated by transforming the control inputs, whereas the normal curvature can be reduced or eliminated only by a combination of state feedback and transformations. The problem of scaling is addressed by identifying a “region of interest”, and scale-independent measures of curvature are proposed. Nonlinearity is measured both as root mean squared curvature and directional curvature. The importance of curvature in the foward and inverse steady-state maps is discussed, and a transformation suggested by the curvature arrays is presented. This transformation reduces the static nonlinearity in the process, and can be used to improve the controller performance. Application of the proposed techniques is illustrated using chemical process examples.     

Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.     

Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.     

基于废料最少的反应器网络综合(Ⅰ)同时进行反应与混合的几何表达

将废料最少问题分别等同于选择性、相对选择性和瞬时选择性等多个目标 ,根据目标函数的定义和在状态空间内反应、混合加工的几何特征 ,导出了全混流反应器 (CSTR)和微分侧流反应器 (DSR)两种极限情况下的浓度变化轨迹方程 ,同时满足这两个方程 ,可作为反应器系统选择性最大的判据     

Input Multiplicity Analysis in a Non‐Isothermal CSTR for Acid‐Catalyzed Hydrolysis of Acetic Anhydride

Multiplicity analysis gives practical guidance for process design to eliminate difficult operating regions associated with input and output multiplicities. Continuous stirred tank reactors (CSTRs) present challenging operational problems due to complex behavior such as input and output multiplicities, ignition/extinction, parametric sensitivity, and nonlinear oscillations. In the absence of a unified mathematical theory for representing various nonlinear system characteristics, the present study was aimed at understanding the dynamic behavior of CSTRs by means of experiments and to link the experimental data to theoretical considerations for further detection and elimination of operating problems. Theoretical modeling and analysis of a non‐isothermal CSTR with acid‐catalyzed hydrolysis of an acetic anhydride system for input multiplicity are discussed. Theoretical modeling of a non‐isothermal CSTR using a root‐finding technique was carried out for predicting steady‐state temperatures. Alternatively, a mathematical model for a non‐isothermal CSTR using unsteady‐state mass and energy balance equations is proposed. Computer‐based simulation was carried out using a program developed in MATLAB for final transient temperature and time‐temperature data of the CSTR system under investigation. The results of a theoretical analysis conducted for confirming the existence of input multiplicity in non‐isothermal CSTRs with acid‐catalyzed hydrolysis of acetic anhydride were compared with experimental investigations for validation.     

SYNTHESIS OF REACTOR NETWORK FOR WASTE MINIMIZATION(Ⅰ) GEOMETRY EXPRESSION OF REACTION AND MIXING PROCESS

将废料最少问题分别等同于选择性、相对选择性和瞬时选择性等多个目标 ,根据目标函数的定义和在状态空间内反应、混合加工的几何特征 ,导出了全混流反应器 (CSTR)和微分侧流反应器 (DSR)两种极限情况下的浓度变化轨迹方程 ,同时满足这两个方程 ,可作为反应器系统选择性最大的判据     

基于废料最少的反应器网络综合(Ⅰ)同时进行反应与混合的几何表达

将废料最少问题分别等同于选择性、相对选择性和瞬时选择性等多个目标,根据目标函数的定义和在状态空间内反应、混合加工的几何特征,导出了全混流反应器(CSTR)和微分侧流反应器(DSR)两种极限情况下的浓度变化轨迹方程,同时满足这两个方程,可作为反应器系统选择性最大的判据.     

MATLAB在反应器优化设计中的应用

反应器设计过程中,如何确定最佳的操作条件,使得设计方案既满足工艺要求,又能降低设备投资及产品成本是一个非常重要的问题.本文分别采用传统方法和MATLAB优化工具箱中的fminsearch命令,对具有循环操作的平推流反应器、全混流反应器与平推流反应器串联两种反应器进行了优化,得到了最佳的操作条件.与传统方法相比,MATLAB方法简便快捷,结果准确可靠.     

Effects of carboxylic additives on the polymerization characteristics of nylon‐6 reactors with diffusional water removal

The effects of carboxylic acid on the polymerization characteristics of nylon‐6 were investigated in reactor models that consist of a continuous‐flow stirred tank reactor (CSTR) and a tubular reactor with a diffusional water‐removal system, which are connected in series. Mathematical models for the CSTR and the tubular reactor were established and solved by numerical methods. In the CSTR, with an increase of the feed acetic acid content, the monomer conversion, and the molecular weights are increased. In the tubular reactor, the acid behaves like a catalyst and a modifier at the same time in the polymerization of nylon 6. The effects of the feed acetic acid content and the diffusional water removal on the zeroth, first, and second moments and the polydispersity index of the polymer were investigated. The polydispersity index is greatly affected by the feed content of carboxylic acid in the CSTR, but it finally approaches to values of ～ 2 in the tubular reactor. The diffusional water removal is found to have little effect on the polydispersity index of the polymer. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 1226–1237, 2001     

Anaerobic/aerobic sequential treatment of a cotton textile mill wastewater

The treatment of a wastewater taken from a cotton textile mill was investigated using an anaerobic/aerobic sequential system during an operational period of 87 days. The process units consisted of an upflow anaerobic sludge blanket (UASB) reactor and a continuous stirred tank reactor (CSTR). Wastewater characterization was performed before feeding the reactor system. Glucose‐COD, and azo dyes were added to the textile wastewater for comparative purposes in the final period of operation. The pH values in the effluent of the UASB reactor were suitable for optimal anaerobic treatment in all runs. The biodegradable part of the COD in wastewater was removed effectively, with the anaerobic stage improving the biodegradability of wastewater entering the aerobic stage. The UASB reactor permitted COD and color removals of 9–51% and 46–55%, respectively, at a hydraulic retention time (HRT) of 30 h. COD removal efficiencies were between 40 and 85% and color removal efficiencies were 39–81% in normal and artificially‐colored wastewaters at a total HRT of 5.75 days in the UASB/CSTR reactor system. Benzidine produced from the cleavage of azo bond in the anaerobic stage was effectively removed in the aerobic stage, and was identified by comparison of its HPLC spectrum with that of an authentic specimen. Copyright © 2004 Society of Chemical Industry