Mechanistical and non-linear modelling approaches to in-duct desulfurization

The prediction of the SO2 removal efficiency achieved in the in-duct desulfurization process at low temperatures was performed from data obtained in an entrained flow reactor at pilot scale. It was used a synthetic flue gas stream with the typical composition of the coal–power plants, and the solid sorbent was commercial Ca(OH)2. The variables included in the experimental study were calcium to sulfur molar ratio, SO2 inlet concentration, temperature, relative humidity, CO2 content in the gas stream, and residence time in the flow reactor. The experimental facility provided the evaluation of SO2 concentration along the reactor up to 4 s of residence time. Two different approaches to model were used for the evaluation of the process behaviour: a mechanistical approach from the basis of the shrinking core and the grain models, and a statistical non-linear approach using neural network analysis.