Abstract

A pseudo-homogeneous model was developed for fixed bed catalytic styrene monomer reactor based on the reaction mechanisms and mass and energy balance equations. With the proposed mathematical model, the profiles of ethyl benzene conversion, styrene yield and selectivity were achieved through the length of catalytic bed reactor. Good agreement was found between model results and industrial data. The effects of some input parameters such as the molar ratio of the steam to ethyl benzene in the feed (S/E) and inlet temprature were investigated on final conversion of ethyl benzene and styrene selectivity using proposed mathematical model. USING THE RESULTS OF mathematical model, a three-layer perceptron neural network was developed for simulation of the effects of feed composition and operation condition on conversion and selectivity. The optimum structure of neural network was determined by a trial-and-error method and different structures were tried.