Neural network based simulation of the sieve plate absorption column in nitric acid industry

Abstract

Modeling of an absorption column performance using feed-forward type of neural network has been presented. The input and output data for training of the neural network are obtained from a rigorous model of the absorption column. The results obtained from the neural network models are then compared with the results obtained mainly from the simulation calculations. The results show that relatively simple neural network models can be used to model the steady state behavior of the column.