Neural Networks as a Tool for Gray Box Modelling in Reactive Distillation

In this paper we discuss the use of neural networks as a tool for gray box modelling of the reactive distillation column. The basic idea is to replace certain correlations for the calculation of physical properties by neural networks. Different architectures as radial basis function networks and feedforward networks are compared and their approximation abilities are demonstrated.