Numerical simulation of a tubular polymerization reactor

Lynch, David T.; Kiparissides, Costas

doi:10.1002/app.1981.070260420

Cited by 15 publications

(6 citation statements)

References 7 publications

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“…A nonlinear model, with simple kinetics, to simulate the styrene emulsion polymerization was developed by Lynch and Kiparissides (1981), and is used in this work. This model, originally developed for tubular reactors with full recycle, has been adapted for use in batch and semibatch processes.…”

Section: Off-line Analysis and On-line Monitoring Studiesmentioning

confidence: 99%

Multivariate monitoring of batch processes using batch‐to‐batch information

Flores‐Cerrillo

MacGregor

2004

AIChE Journal

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Multiway principal component analysis (MPCA) and multiway partial-least squares (MPLS) are well-established methods for the analysis of historical data from batch processes, and for monitoring the progress of new batches. Direct measurements made on prior batches can also be incorporated into the analysis by monitoring with multiblock methods. An extension of the multiblock MPCA/MPLS approach is introduced to explicitly incorporate batch-to-batch trajectory information summarized by the scores of previous batches, while keeping all the advantages and monitoring statistics of the traditional IntroductionBatch and semibatch processes are the main production devices in pharmaceuticals, paint-coating, adhesive, and in most of the specialty-chemical industries. However, such processes suffer from variations in initial charge, operating conditions, and impurity concentrations in raw materials. To allow for more consistent operation and final product quality, control and monitoring schemes have been implemented around such processes. The use of multivariate statistical process control methods based on multiway principal component analysis (MPCA), and multiway partial-least squares (MPLS), and their associated monitoring statistics have been shown to be successful with industrial data for both the analysis of completed batches, and for the on-line monitoring of new batches (MacGregor and Nomikos, 1992; MacGregor, 1994, 1995a,b;MacGregor and Kourti, 1995;. The success of such methods is largely because of the fact that the type of normal operating data necessary for building the required model is always readily available, and that the statistical control charts used for analysis and monitoring are easily developed from these data. One of the main characteristics of such methods is that the evolving within-batch measurement trajectories are projected into low dimensional latent variable spaces that summarize all the relevant information, and allow monitoring charts to be built in the reduced spaces where visually inspection and interpretation are easier.Multiway PCA and PLS for the analysis, monitoring, and prediction of final product quality in batch processes were first introduced by Nomikos and MacGregor (1992, 1995a. They illustrated the detection of abnormal batches with several criteria, such as the Q statistic (also known as square prediction error (SPE) or distance to the model in the X space (DMODX)), the instantaneous SPE (for on-line monitoring) and the PCA or PLS score plots or equivalently Hotelling's T 2 statistic. modes of operation, and prior processing conditions into the analysis and monitoring of batch processes. These multiblock methods allow one to incorporate any measured variable from prior batches into the analysis and monitoring schemes. In this article, we propose a variation of these multiblock methods to incorporate the PCA or PLS scores from prior batches.Recently, Dorsey and Lee (2001) proposed a monitoring framework based on state-space models that purported to consider batch-to-batch vari...

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Section: Off-line Analysis and On-line Monitoring Studiesmentioning

confidence: 99%

Multivariate monitoring of batch processes using batch‐to‐batch information

Flores‐Cerrillo

MacGregor

2004

AIChE Journal

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“…A non-linear model to simulate styrene emulsion polymerisation was developed by Lynch and Kiparissides (1981), and used in this case study for data generation and model performance evaluation. This model has been lightly modified for use in both batch and semi-batch policies.…”

Section: Case Study I Control Of Np and Xmentioning

confidence: 99%

Inferential-Learning Control of Quality Properties in Semi-Batch Reactors

MacGregor

2002

IFAC Proceedings Volumes

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A strategy for controlling product quality properties, subject to batch-to-batch and within batch disturbances is presented. The methodology is based on readily available measurements, information extracted from existing databases and a few simple identification experiments. This approach extends the mid-course correction control strategies to overcome model error when the process is affected by constant, correlated and uncorrelated disturbances. Adaptive PLS (Partial Least Squares) methods are used to extract the information and to update the models used for prediction and control. The methodology is illustrated with a few emulsion polymerisation examples.

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“…Because turbulent flow produced smaller monomer drops which absorbed more surfactant, this leads to fewer micelles and hence fewer polymer particles. Lynch and Kiparissides (1981) simulated the turbulent flow regime experiments of Rollin et al (1977). Their monodisperse model included axial dispersion of initiator (which they found to contribute negligibly to the initiator concentration profile), micellar nucleation, and particle loss by coalescence.…”

Section: Loop Reactorsmentioning

confidence: 99%

Tubular reactors for emulsion polymerization: I. Experimental investigation

Paquet

Ray

1994

AIChE Journal

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Experimental results using a pulsed tubular reactor are presented. The use of a pulsation source eliminates the reactor fouling and plugging issue that has occurred in previous investigations. Startup data and steady-state profiles are presented. Comparisons in monomer conversion and particle-size distribution for batch, CSTR and tubular reactor are made. The influence of pulsation on the particle-size distribution is discussed. It is shown that high-conversion latex with a narrow particlesize distribution can be produced continuously in the pulsed tubular reactor.

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Numerical simulation of a tubular polymerization reactor

Cited by 15 publications

References 7 publications

Multivariate monitoring of batch processes using batch‐to‐batch information

Multivariate monitoring of batch processes using batch‐to‐batch information

Inferential-Learning Control of Quality Properties in Semi-Batch Reactors

Tubular reactors for emulsion polymerization: I. Experimental investigation

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