Continuous production of polystyrene in a tubular reactor: Part II

Wallis, J. P. A.; Ritter, Robert; Andre, Hanalde

doi:10.1002/aic.690210408

Cited by 21 publications

(2 citation statements)

References 10 publications

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“…This method has the advantage of yielding high polymerisation rates because of the high concentration of monomer. The model adopted in this work is a very simplified model taken from Wallis et al (1975) and Young and Lovell (1991) loosely based on the basic mechanisms of free radical polymerisation as presented in Table 1. The purpose of using the simple kinetic model is to avoid the complexity associated with higher order models and keep the focus on the performance of the controllers for this simplified set of equations.…”

Section: Free Radical Polymerisation and System Modellingmentioning

confidence: 99%

Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor

Ekpo¹,

Mujtaba²

2007

Chemical Product and Process Modeling

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The performance analysis of three advanced non linear controllers is the main focus of this paper. All three controllers are applied for the control of a batch polymerisation reactor which is defined by a very simple kinetic model for the polymerisation of styrene. This simple set of equations describing the polymerisation process is first solved using the sequential strategy i.e. Control Vector Parameterisation (CVP) technique within gPROMS to find optimal initial initiator concentrations and the reactor temperature trajectory necessary to yield desired polymer molecular properties (defined here as fixed values of monomer conversion and number average chain length) in minimum time. The sequential solution strategy has had limited application in solving optimisation problems for polymerisation in batch reactors, most researchers instead employing the Pontryagin's Maximum Principle (PMP) to solve optimal control problems involving these systems.The temperature trajectory obtained from the dynamic optimisation is used as the setpoint to be tracked by the three controllers: Dual Mode control with PID, which is representative of industrial practice, Generic Model Control (GMC) with Neural Networks as online heat release estimator, and Direct Inverse Control (DIC). Published work on the last two controllers as applied to the control of a batch polymerisation reactor is absent from the literature.When the performances of the different controllers are evaluated, it is seen that the GMC-NN controller performs better than the other two for the system under consideration.

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Section: Free Radical Polymerisation and System Modellingmentioning

confidence: 99%

Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor

Ekpo¹,

Mujtaba²

2007

Chemical Product and Process Modeling

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“…The density of the styrene-polystyrene reaction mixture in the ith reactor is estimated with the density correlation taken from Wallis et al ( 1975). …”

Section: Monomer Conversionmentioning

confidence: 99%

Simulation of a Continuous Bulk Styrene Polymerization Process with Catalytic Initiation for Crystal-Clear Polystyrene and Rubber-Modified Polystyrene

Chen

1998

Polymer Reaction Engineering

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A mathematical model has been developed to predict the steady state performance of a continuous bulk styrene polymerization process with catalytic initiation for crystal-clear polystyrene and impact-modified polystyrene. The present process contains one prepolymerizer and four post-polymerizers. Both acyclic and cyclic peroxyketal free radical initiators were considered. The polymer moment equations were solved simultaneously with the reactor modeling equations. The non-linear algebraic equations were solved by a Newton-Raphson iteration technique to give the steady-state value of styrene monomer weight fraction in the reactor. The coupled, non-linear ordinary differential equations were integrated by means of a single-step, fourth-order Runge-Kutta technique, followed by a multi-step Adams-Moulton technique . The resulting computer simulation model is capable of analyzing what effect feed composition, reaction temperature, initiator type, and initiator concentration have on styrene monomer conversion, polystyrene molecular weights, grafting of styrene to rubber, formation of oligomers, density, viscosity, melt flow rate, thermal properties, and tensile strength. Several case studies were given for commercially important crystal-clear grades and high-impact products. As compared with pure thermal initiation , higher reactor productivity and better grafting of styrene to rubber can be obtained with catalytic initiation. The higher molecular weights as obtained with the thermal process can be maintained with bifunctional initiation . The presence of catalytic polymerization in the post-reactors is necessary to decrease further the molecular weights of the polymer formed. The polydispersity of the final polystyrene product is highly dependent upon mean residence time and tube wall temperature in a shell-and-tube devolatilization preheater. Low molecular weight oligomers are relatively stable but occur in low concentrations. The concentration of styrene dimer and trimer can be substantially reduced with catalytic initiation.

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Bulk and Solution Processes

Villalobos¹,

Debling²

2013

Handbook of Polymer Synthesis, Characterization, and Processing

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Continuous production of polystyrene in a tubular reactor: Part II

Cited by 21 publications

References 10 publications

Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor

Performance Analysis of Three Controllers for the Polymerisation of Styrene in a Batch Reactor

Simulation of a Continuous Bulk Styrene Polymerization Process with Catalytic Initiation for Crystal-Clear Polystyrene and Rubber-Modified Polystyrene

Bulk and Solution Processes

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