Dynamic Modeling and Simulation of a Fixed-Bed Reactor for Ethylene Oxide Production in ASPEN PLUS and Optimization Using Artificial Neural Networks (ANN)

Nasiri, Amir Hossein; Bayat, Mehdi

doi:10.22078/pr.2026.5765.3563

Dynamic Modeling and Simulation of a Fixed-Bed Reactor for Ethylene Oxide Production in ASPEN PLUS and Optimization Using Artificial Neural Networks (ANN)

Document Type : Research Paper

Authors

Amir Hossein Nasiri ¹

mehdi bayat ²

¹ Department of Chemical Engineering, Faculty of Petrochemical Engineering, University of Bojnord, Iran

² Department of Chemical Engineering, Faculty of Petrochemical Engineering, University of Bojnord, Bojnord, Iran

10.22078/pr.2026.5765.3563

Abstract

In this study, the industrial production of ethylene oxide (EO) in a fixed-bed reactor was modeled and simulated using Aspen Plus V14. The catalytic oxidation of ethylene over a silver (Ag) bed requires accurate modeling due to its highly exothermic nature and the presence of side reactions. Reactor performance was evaluated under both steady-state and dynamic conditions. Thermodynamic modeling was carried out using the Soave–Redlich–Kwong (SRK) equation of state and nonlinear kinetic relations, while the effects of pressure drop (calculated using the Ergun equation), heat transfer, and catalyst deactivation were incorporated into the model. Dynamic simulation was performed over a 1100-day period, and the obtained results were compared with actual industrial data, showing good agreement. The influence of ethylene dichloride (EDC) on selectivity, with respect to acceptable EO production levels, was also investigated. Finally, optimization using artificial neural networks (ANN) in the MATLAB environment demonstrated the potential of the proposed model for improving industrial processes.

Keywords

Reactor

Modeling

Optimization

Simulation

Kinetics

ASPEN PLUS

Subjects