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Processes
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Polymer Modeling, Control and Monitoring
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Polymer Modeling, Control and Monitoring

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Materials Processes".

Deadline for manuscript submissions: closed (15 February 2016) | Viewed by 73828

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Prof. Dr. Masoud Soroush

E-Mail Website
Guest Editor
1. Department of Chemical and Biological Engineering, Drexel University, Philadelphia, PA 19104, USA
2. Department of Materials Science and Engineering, Drexel University, Philadelphia, PA 19104, USA
Interests: process systems engineering; polymer reaction engineering; electronic-level modeling of reactions; polymer membranes; renewable power generation and storage systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,
 
This Special Issue includes papers that investigate different approaches to improving polymers, polymer processes, and processes that use polymers. These approaches include state and parameter estimation in polymerization reactors, polymerization reactor modeling for process monitoring, polymerization reactor monitoring, design of optimal polymerization experiments, use of polymeric membranes in integrated gasification combined cycle units, model-based design of polymerization reactors, and polymerization reactor modeling.

Prof. Dr. Masoud Soroush
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • polymers
  • mathematical modeling
  • control
  • monitoring
  • optimization
  • simulation
  • safety analysis

Published Papers (11 papers)

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Editorial

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127 KiB  
Editorial
Special Issue “Polymer Modeling, Control and Monitoring” of Processes
by Masoud Soroush
Processes 2016, 4(3), 24; https://doi.org/10.3390/pr4030024 - 29 Jul 2016
Cited by 1 | Viewed by 3513
Abstract
Polymers range from synthetic plastics, such as polyacrylates, to natural biopolymers, such as proteins and DNA.[...] Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)

Research

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1593 KiB  
Article
Study of n-Butyl Acrylate Self-Initiation Reaction Experimentally and via Macroscopic Mechanistic Modeling
by Ahmad Arabi Shamsabadi, Nazanin Moghadam, Sriraj Srinivasan, Patrick Corcoran, Michael C. Grady, Andrew M. Rappe and Masoud Soroush
Processes 2016, 4(2), 15; https://doi.org/10.3390/pr4020015 - 23 Apr 2016
Cited by 14 | Viewed by 5894 | Correction
Abstract
This paper presents an experimental study of the self-initiation reaction of n-butyl acrylate (n-BA) in free-radical polymerization. For the first time, the frequency factor and activation energy of the monomer self-initiation reaction are estimated from measurements of n-BA conversion [...] Read more.
This paper presents an experimental study of the self-initiation reaction of n-butyl acrylate (n-BA) in free-radical polymerization. For the first time, the frequency factor and activation energy of the monomer self-initiation reaction are estimated from measurements of n-BA conversion in free-radical homo-polymerization initiated only by the monomer. The estimation was carried out using a macroscopic mechanistic mathematical model of the reactor. In addition to already-known reactions that contribute to the polymerization, the model considers a n-BA self-initiation reaction mechanism that is based on our previous electronic-level first-principles theoretical study of the self-initiation reaction. Reaction rate equations are derived using the method of moments. The reaction-rate parameter estimates obtained from conversion measurements agree well with estimates obtained via our purely-theoretical quantum chemical calculations. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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5356 KiB  
Article
Modeling and Optimization of High-Performance Polymer Membrane Reactor Systems for Water–Gas Shift Reaction Applications
by Andrew J. Radcliffe, Rajinder P. Singh, Kathryn A. Berchtold and Fernando V. Lima
Processes 2016, 4(2), 8; https://doi.org/10.3390/pr4020008 - 01 Apr 2016
Cited by 9 | Viewed by 12236
Abstract
In production of electricity from coal, integrated gasification combined cycle plants typically operate with conventional packed bed reactors for the water-gas shift reaction, and a Selexol process for carbon dioxide removal. Implementation of membrane reactors in place of these two process units provides [...] Read more.
In production of electricity from coal, integrated gasification combined cycle plants typically operate with conventional packed bed reactors for the water-gas shift reaction, and a Selexol process for carbon dioxide removal. Implementation of membrane reactors in place of these two process units provides advantages such as increased carbon monoxide conversion, facilitated CO2 removal/sequestration and process intensification. Proposed H2-selective membranes for these reactors are typically of palladium alloy or ceramic due to their outstanding gas separation properties; however, on an industrial scale, the cost of such materials may become exorbitant. High-performance polymeric membranes, such as polybenzimidazoles (PBIs), present themselves as low-cost alternatives with gas separation properties suitable for use in such membrane reactors, given their significant thermal and chemical stability. In this work, the performance of a class of high-performance polymeric membranes is assessed for use in integrated gasification combined cycle (IGCC) units operated with carbon capture, subject to constraints on equipment and process streams. Several systems are considered for use with the polymeric membranes, including membrane reactors and permeative stage reactors. Based upon models developed for each configuration, constrained optimization problems are formulated which seek to more efficiently employ membrane surface area. From the optimization results, the limiting membrane parameter for achieving all carbon capture and H2 production specifications for water–gas shift reactor applications is determined to be the selectivity, α H 2 / C O 2, and thus a minimum value of this parameter which satisfies all the constraints is identified for each analyzed configuration. For a CO2 capture value of 90%, this value is found to be α = 61 for the membrane reactor and the 3-stage permeative stage reactor and α = 62 for the 2-stage permeative stage reactor. The proposed systems approach has the potential to be employed to identify performance limitations associated with membrane materials to guide the development of future polymeric and other advanced materials with desired membrane characteristics for energy and environmental applications. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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2542 KiB  
Article
Gaussian Mixture Model-Based Ensemble Kalman Filtering for State and Parameter Estimation for a PMMA Process
by Ruoxia Li, Vinay Prasad and Biao Huang
Processes 2016, 4(2), 9; https://doi.org/10.3390/pr4020009 - 30 Mar 2016
Cited by 13 | Viewed by 8102
Abstract
Polymer processes often contain state variables whose distributions are multimodal; in addition, the models for these processes are often complex and nonlinear with uncertain parameters. This presents a challenge for Kalman-based state estimators such as the ensemble Kalman filter. We develop an estimator [...] Read more.
Polymer processes often contain state variables whose distributions are multimodal; in addition, the models for these processes are often complex and nonlinear with uncertain parameters. This presents a challenge for Kalman-based state estimators such as the ensemble Kalman filter. We develop an estimator based on a Gaussian mixture model (GMM) coupled with the ensemble Kalman filter (EnKF) specifically for estimation with multimodal state distributions. The expectation maximization algorithm is used for clustering in the Gaussian mixture model. The performance of the GMM-based EnKF is compared to that of the EnKF and the particle filter (PF) through simulations of a polymethyl methacrylate process, and it is seen that it clearly outperforms the other estimators both in state and parameter estimation. While the PF is also able to handle nonlinearity and multimodality, its lack of robustness to model-plant mismatch affects its performance significantly. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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3249 KiB  
Article
Surrogate Models for Online Monitoring and Process Troubleshooting of NBR Emulsion Copolymerization
by Chandra Mouli R. Madhuranthakam and Alexander Penlidis
Processes 2016, 4(1), 6; https://doi.org/10.3390/pr4010006 - 14 Mar 2016
Cited by 2 | Viewed by 5241
Abstract
Chemical processes with complex reaction mechanisms generally lead to dynamic models which, while beneficial for predicting and capturing the detailed process behavior, are not readily amenable for direct use in online applications related to process operation, optimisation, control, and troubleshooting. Surrogate models can [...] Read more.
Chemical processes with complex reaction mechanisms generally lead to dynamic models which, while beneficial for predicting and capturing the detailed process behavior, are not readily amenable for direct use in online applications related to process operation, optimisation, control, and troubleshooting. Surrogate models can help overcome this problem. In this research article, the first part focuses on obtaining surrogate models for emulsion copolymerization of nitrile butadiene rubber (NBR), which is usually produced in a train of continuous stirred tank reactors. The predictions and/or profiles for several performance characteristics such as conversion, number of polymer particles, copolymer composition, and weight-average molecular weight, obtained using surrogate models are compared with those obtained using the detailed mechanistic model. In the second part of this article, optimal flow profiles based on dynamic optimisation using the surrogate models are obtained for the production of NBR emulsions with the objective of minimising the off-specification product generated during grade transitions. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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4678 KiB  
Article
Combining On-Line Characterization Tools with Modern Software Environments for Optimal Operation of Polymerization Processes
by Navid Ghadipasha, Aryan Geraili, Jose A. Romagnoli, Carlos A. Castor, Jr., Michael F. Drenski and Wayne F. Reed
Processes 2016, 4(1), 5; https://doi.org/10.3390/pr4010005 - 15 Feb 2016
Cited by 11 | Viewed by 6472
Abstract
This paper discusses the initial steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization processes. For the first time it combines the powerful capabilities of the automatic continuous [...] Read more.
This paper discusses the initial steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization processes. For the first time it combines the powerful capabilities of the automatic continuous on-line monitoring of polymerization system (ACOMP), with a modern simulation, estimation and optimization software environment towards an integrated scheme for the optimal operation of polymeric processes. An initial validation of the framework was performed for modelling and optimization using literature data, illustrating the flexibility of the method to apply under different systems and conditions. Subsequently, off-line capabilities of the system were fully tested experimentally for model validations, parameter estimation and process optimization using ACOMP data. Experimental results are provided for free radical solution polymerization of methyl methacrylate. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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6350 KiB  
Article
State Observer Design for Monitoring the Degree of Polymerization in a Series of Melt Polycondensation Reactors
by Chen Ling and Costas Kravaris
Processes 2016, 4(1), 4; https://doi.org/10.3390/pr4010004 - 25 Jan 2016
Cited by 7 | Viewed by 6812
Abstract
A nonlinear reduced-order state observer is applied to estimate the degree of polymerization in a series of polycondensation reactors. The finishing stage of polyethylene terephthalate synthesis is considered in this work. This process has a special structure of lower block triangular form, which [...] Read more.
A nonlinear reduced-order state observer is applied to estimate the degree of polymerization in a series of polycondensation reactors. The finishing stage of polyethylene terephthalate synthesis is considered in this work. This process has a special structure of lower block triangular form, which is properly utilized to facilitate the calculation of the state-dependent gain in the observer design. There are two possible on-line measurements in each reactor. One is continuous, and the other is slow-sampled with dead time. For the slow-sampled titration measurement, inter-sample behavior is estimated from an inter-sample output predictor, which is essential in providing continuous corrections on the observer. Dead time compensation is carried out in the same spirit as the Smith predictor to reduce the effect of delay in the measurement outputs. By integrating the continuous-time reduced-order observer, the inter-sample predictor and the dead time compensator together, the degree of polymerization is accurately estimated in all reactors. The observer performance is demonstrated by numerical simulations. In addition, a pre-filtering technique is used in the presence of sensor noise. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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Graphical abstract

2177 KiB  
Article
Modeling of the Copolymerization Kinetics of n-Butyl Acrylate and d-Limonene Using PREDICI ®
by Shanshan Ren, Eduardo Vivaldo-Lima and Marc A. Dubé
Processes 2016, 4(1), 1; https://doi.org/10.3390/pr4010001 - 24 Dec 2015
Cited by 7 | Viewed by 6426
Abstract
Kinetic modeling of the bulk copolymerization of d-limonene (Lim) and n-butyl acrylate (BA) at 80 °C was performed using PREDICI®. Model predictions of conversion, copolymer composition and average molecular weights are compared to experimental data at five different feed [...] Read more.
Kinetic modeling of the bulk copolymerization of d-limonene (Lim) and n-butyl acrylate (BA) at 80 °C was performed using PREDICI®. Model predictions of conversion, copolymer composition and average molecular weights are compared to experimental data at five different feed compositions (BA mol fraction = 0.5 to 0.9). The model illustrates the significant effects of degradative chain transfer due to the allylic structure of Lim as well as the intramolecular chain transfer mechanism due to BA. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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Graphical abstract

271 KiB  
Article
Optimal Design for Reactivity Ratio Estimation: A Comparison of Techniques for AMPS/Acrylamide and AMPS/Acrylic Acid Copolymerizations
by Alison J. Scott, Marzieh Riahinezhad and Alexander Penlidis
Processes 2015, 3(4), 749-768; https://doi.org/10.3390/pr3040749 - 10 Nov 2015
Cited by 21 | Viewed by 7117
Abstract
Water-soluble polymers of acrylamide (AAm) and acrylic acid (AAc) have significant potential in enhanced oil recovery, as well as in other specialty applications. To improve the shear strength of the polymer, a third comonomer, 2-acrylamido-2-methylpropane sulfonic acid (AMPS), can be added to the [...] Read more.
Water-soluble polymers of acrylamide (AAm) and acrylic acid (AAc) have significant potential in enhanced oil recovery, as well as in other specialty applications. To improve the shear strength of the polymer, a third comonomer, 2-acrylamido-2-methylpropane sulfonic acid (AMPS), can be added to the pre-polymerization mixture. Copolymerization kinetics of AAm/AAc are well studied, but little is known about the other comonomer pairs (AMPS/AAm and AMPS/AAc). Hence, reactivity ratios for AMPS/AAm and AMPS/AAc copolymerization must be established first. A key aspect in the estimation of reliable reactivity ratios is design of experiments, which minimizes the number of experiments and provides increased information content (resulting in more precise parameter estimates). However, design of experiments is hardly ever used during copolymerization parameter estimation schemes. In the current work, copolymerization experiments for both AMPS/AAm and AMPS/AAc are designed using two optimal techniques (Tidwell-Mortimer and the error-in-variables-model (EVM)). From these optimally designed experiments, accurate reactivity ratio estimates are determined for AMPS/AAm (rAMPS = 0.18, rAAm = 0.85) and AMPS/AAc (rAMPS = 0.19, rAAc = 0.86). Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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Graphical abstract

1976 KiB  
Article
Model-Based Reactor Design in Free-Radical Polymerization with Simultaneous Long-Chain Branching and Scission
by Hidetaka Tobita
Processes 2015, 3(4), 731-748; https://doi.org/10.3390/pr3040731 - 03 Nov 2015
Cited by 8 | Viewed by 7858
Abstract
Polymers are the products of processes and their microstructure can be changed significantly by the reactor systems employed, especially for nonlinear polymers. The Monte Carlo simulation technique, based on the random sampling technique, is used to explore the effect of reactor types on [...] Read more.
Polymers are the products of processes and their microstructure can be changed significantly by the reactor systems employed, especially for nonlinear polymers. The Monte Carlo simulation technique, based on the random sampling technique, is used to explore the effect of reactor types on the branched polymer structure, formed through free-radical polymerization with simultaneous long-chain branching and scission, as in the case of low-density polyethylene synthesis. As a simplified model for a tower-type multi-zone reactor, a series of continuous stirred-tank reactors, consisting of one big tank and the same N-1 small tanks is considered theoretically. By simply changing the tank arrangement, various types of branched polymers, from star-like globular structure to a more randomly branched structure, can be obtained, while keeping the following properties of the final products, the monomer conversion to polymer, the average branching and scission densities, and the relationship between the mean-square radius of gyration and molecular weight. Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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Graphical abstract

Other

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150 KiB  
Correction
Correction: Study of n-Butyl Acrylate Self-Initiation Reaction Experimentally and via Macroscopic Mechanistic Modeling Processes 2016, 4, 15
by Ahmad Arabi Shamsabadi, Nazanin Moghadam, Sriraj Srinivasan, Patrick Corcoran, Michael C. Grady, Andrew M. Rappe and Masoud Soroush
Processes 2016, 4(3), 26; https://doi.org/10.3390/pr4030026 - 16 Aug 2016
Cited by 2 | Viewed by 3360
Abstract
We wish to correct Table 5 of the published paper in Processes [1].[...] Full article
(This article belongs to the Special Issue Polymer Modeling, Control and Monitoring)
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