A Hybrid Mathematical Model for a Three-Phase Industrial Hydrogenation Reactor

摘要

This paper presents a hybrid mathematical model for describe a three-phase reactor behavior, which combines a neural network architecture (as a predictor block for the liquid-solid mass transfer coefficient) and phenomenological equations describing the mass conservation principle. The optimization procedure used in the network training was based on the Fletcher-Powell algorithm. Results of the network training and validation showed the predictive capacity of the proposed model and its great potential to be used as a support for process modeling and control.