Process Model for Styrene and n‑Butyl Acrylate Emulsion Copolymerization in Smart-Scale Tubular Reactor

Real-time optimization-based control methodologies in emulsion (co)­polymerization allow achievement of a significant intensification of the process and increase of the product quality. This paper describes the development of the fast and computationally simple process model of continuous styrene an...

Full description

Saved in:
Bibliographic Details
Published inIndustrial & engineering chemistry research Vol. 55; no. 2; pp. 472 - 484
Main Authors Pokorný, Richard, Zubov, Alexandr, Matuška, Petr, Lueth, Fabian, Pauer, Werner, Moritz, Hans-Ulrich, Kosek, Juraj
Format Journal Article
LanguageEnglish
Published American Chemical Society 20.01.2016
Online AccessGet full text

Cover

Loading…
More Information
Summary:Real-time optimization-based control methodologies in emulsion (co)­polymerization allow achievement of a significant intensification of the process and increase of the product quality. This paper describes the development of the fast and computationally simple process model of continuous styrene and n-butyl acrylate emulsion copolymerization for use in nonlinear model predictive control (NMPC) of a smart-scale tubular reactor. The model predictions agree well with experimental data for monomer conversion, copolymer composition, temperature profile, average particle size, and number-average molecular weight. To account for the slower reaction rate at the beginning of the reaction, the model incorporates a thermodynamic description of comonomer partitioning between particle, water, and droplet phases based on Morton equations. For the purpose of the process model, a simple empirical function representing the solution of Morton partitioning was implemented. The number concentration of particles was estimated from measured monomer conversion profiles, as the predictions by first-principle nucleation models generally provide values substantially different from experiments. After the model incorporation into a framework for online state estimation and control, it will be used for open- and closed-loop control of the smart-scale tubular reactor.
ISSN:0888-5885
1520-5045
DOI:10.1021/acs.iecr.5b02909