Development of a Mathematical Model for the Dynamic Optimization of Batch Reactors,and MINLP Synthesis of Plug-flow Reactors in Complex Networks

Marcel Ropotar,^a,b* Zdravko Kravanja^b
a Tanin Sevnica kemi~na industrija d.d., Hermanova cesta 1, 8290 Sevnica, Slovenia
^b Faculty of Chemistry and Chemical Engineering, University of Maribor, P.O. Box 219, Maribor, Slovenia
E-mail: marcel.ropotar@uni-mb.si

Abstract
This paper describes the development of a robust and efficient reactor model suitable for representing batch and plugflow reactors (PFRs) in different applications. These would range from the nonlinear (NLP) dynamic optimization of a stand-alone batch reactor up to the mixed-integer nonlinear (MINLP) synthesis of a complex reactor network in overall process schemes. Different schemes for the Orthogonal Collocation on Finite Element (OCFE) and various model formulations, in the case of MINLP model, were studied in order to increase the robustness and efficiency of the model. A deterministic model for known kinetics was obtained for batch and PFR reactors and extended for uncertainties in process parameters and reaction kinetics when the kinetics is unknown. Different variations of the developed model were applied to certain problems, as examples. The first motivating example was the dynamic optimization of batch reactor and the second the MINLP synthesis of a process scheme for the production of allyl chloride. The NLP version of the model with moving finite elements was found to be the most efficient for representing a batch reactor in the dynamic optimization example, and PFR trains in the process synthesis example.

Keywords: Batch reactor, PFR reactor, orthogonal collocation, NLP, MINLP, process synthesis