Estimating of CO2 Conversion in Falling Film Reactor Using Artificial Neural Network

Abstract

This paper presents the development of Artificial Neural Network (ANN) model for absorption process of CO2 gas using monoethanolamine (MEA) as a solvent in a falling film reactor. Although studies on ANN applications in chemical engineering in the literature are more concentrated on utilizing dynamic models, there has been an increasing trend for diverse application of ANN to model steady state systems. The feed-forward artificial neural network was adopted and trained by back-propagation algorithm. In this paper 216 sets of data are used to train and test the network. This study shows that ANN model with one hidden layer and nine neurons in the hidden layer gives a very close estimation of the CO2 conversion and there is high potential for absorption application of ANN model.