Control of Polymerization Reactors

Control of Polymerization Reactors

Author: Joseph Schork

Publisher: Routledge

Published: 2017-09-20

Total Pages: 378

ISBN-13: 1351457934

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This reference and text provides an in-depth description of developments in control techniques and their application to polymerization reactors and offers important introductory background information on polymerization reaction engineering.;Discussing modelling, identification, linear, nonlinear and multivariable schemes, Control of Polymerization Reactors: presents all available techniques that can be used to control reactors properly for optimal performance; shows how to manipulate pivotal variables that affect reactor control; examines methods for deriving dynamic process models to improve reactor efficiency; reviews reactor control problems and points out end-use properties; supplies methods for measuring process variables, and ways to estimate variables that can't be measured; and explains how single-input, single-output (SISO) strategies can be effectively used for control.;Filled with illustrative examples to clarify concepts, including more than 730 figures, tables and equations, Control of Polymerization Reactors is intended for use as a reference for chemical, process development, process design, research and development, control systems, and polymer engineers; and polymer chemists and physicists; as well as a text for upper-level undergraduate and graduate students in polymerization reactor control courses.


23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering

Author: R. Paulen

Publisher: Elsevier Inc. Chapters

Published: 2013-06-10

Total Pages: 16

ISBN-13: 012808619X

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We study dynamic optimization of a lab-scale semi-batch emulsion copolymerization reactor for styrene and butyl acrylate in the presence of n-dodecyl mercaptan as chain transfer agent (CTA). The previously developed mathematical model of the polymerization reactions is used to predict the glass transition temperature of produced polymer, the global monomer conversion, the number and weight average molecular weights, the particle size distribution, and the amount of residual monomers. This model is implemented within gPROMS environment for modeling and optimization. It is desired to compute optimal profiles of feed rate of pre-emulsioned monomers and CTA which optimize properties (quantitative as well as qualitative) of polymers produced during the reaction subject to operational conditions and constraints.


Modeling, Simulation, Dynamic Optimization and Control of a Semibatch Emulsion Polymerization Process

Modeling, Simulation, Dynamic Optimization and Control of a Semibatch Emulsion Polymerization Process

Author: Iván-Dario Gil

Publisher:

Published: 2014

Total Pages: 0

ISBN-13:

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In this work, modeling, simulation, dynamic optimization and nonlinear control of an industrial emulsion polymerization process to produce poly-vinyl acetate (PVAc) are proposed. The reaction is modeled as a two-phase system composed of an aqueous phase and a particle phase. A detailed model is used to calculate the weight average molecular weight, the number average molecular weight and the dispersity. The moments of the growing and dead chains are used to represent the state of the polymer and to calculate the molecular weight distribution (MWD). The case study corresponds to an industrial reactor operated at a chemical company in Bogotá. An industrial scale reactor (11 m3 of capacity) is simulated where a semi-batch emulsion polymerization reaction of vinyl acetate is performed. Dynamic optimization problem is solved directly using a Nonlinear Programming solver. Integration of differential equations is made using Runge-Kutta method. Three different optimization problems are solved from the more simplistic (only one control variable: reactor temperature) to the more complex (three control variables : reactor temperature, initiator flow rate and monomer flow rate) in order to minimize the reaction time. A reduction of 25% of the batch time is achieved with respect to the normal operating conditions applied at the company. The results show that is possible to minimize the reaction time while some polymer desired qualities (conversion, molecular weight and solids content) satisfy the defined constraints. A nonlinear geometric control technique by using input/output linearization is adapted to the reactor temperature control. An extended Kalman filter (EKF) is implemented to estimate unmeasured states and it is tested in different cases including a robustness study where model errors are introduced to verify its good performance. After verification of controller performance, some process changes were proposed in order to improve process productivity and polymer quality. Finally, the optimal temperature profile and optimal feed policies of the monomer and initiator, obtained in a dynamic optimization step, are used to provide the optimal set points for the nonlinear control. The results show that the nonlinear controller designed here is appropriate to follow the optimal temperature trajectories calculated previously.


Dynamic Modelling and Optimization of Polymerization Processes in Batch and Semi-batch Reactors

Dynamic Modelling and Optimization of Polymerization Processes in Batch and Semi-batch Reactors

Author: W. H. B. W. Ibrahim

Publisher:

Published: 2012

Total Pages:

ISBN-13:

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Dynamic modelling and optimization of three different processes namely (a) bulk polymerization of styrene, (b) solution polymerization of methyl methacrylate (MMA) and (c) emulsion copolymerization of Styrene and MMA in batch and semi-batch reactors are the focus of this work. In this work, models are presented as sets of differential-algebraic equations describing the process. Different optimization problems such as (a) maximum conversion (Xn), (b) maximum number average molecular weight (Mn) and (c) minimum time to achieve the desired polymer molecular properties (defined as pre-specified values of monomer conversion and number average molecular weight) are formulated. Reactor temperature, jacket temperature, initial initiator concentration, monomer feed rate, initiator feed rate and surfactant feed rate are used as optimization variables in the optimization formulations. The dynamic optimization problems were converted into nonlinear programming problem using the CVP techniques which were solved using efficient SQP (Successive Quadratic Programming) method available within the gPROMS (general PROcess Modelling System) software. The process model used for bulk polystyrene polymerization in batch reactors, using 2, 2 azobisisobutyronitrile catalyst (AIBN) as initiator was improved by including the gel and glass effects. The results obtained from this work when compared with the previous study by other researcher which disregarded the gel and glass effect in their study which show that the batch time operation are significantly reduced while the amount of the initial initiator concentration required increases. Also, the termination rate constant decreases as the concentration of the mixture increases, resulting rapid monomer conversion. The process model used for solution polymerization of methyl methacrylate (MMA) in batch reactors, using AIBN as the initiator and Toluene as the solvent was improved by including the free volume theory to calculate the initiator efficiency, f. The effects of different f was examined and compared with previous work which used a constant value of f 0.53. The results of these studies show that initiator efficiency, f is not constant but decreases with the increase of monomer conversion along the process. The determination of optimal control trajectories for emulsion copolymerization of Styrene and MMA with the objective of maximizing the number average molecular weight (Mn) and overall conversion (Xn) were carried out in batch and semi-batch reactors. The initiator used in this work is Persulfate K2S2O8 and the surfactant is Sodium Dodecyl Sulfate (SDS). Reduction of the pre-batch time increases the Mn but decreases the conversion (Xn). The sooner the addition of monomer into the reactor, the earlier the growth of the polymer chain leading to higher Mn. Besides that, Mn also can be increased by decreasing the initial initiator concentration (Ci0). Less oligomeric radicals will be produced with low Ci0, leading to reduced polymerization loci thus lowering the overall conversion. On the other hand, increases of reaction temperature (Tr) will decrease the Mn since transfer coefficient is increased at higher Tr leading to increase of the monomeric radicals resulting in an increase in termination reaction.