DYNAMIC MODELING OF SUSPENSION CRYSTALLIZERS, USING EXPERIMENTAL-DATA

A model for the dynamics of a single-stage suspension crystallizer is developed which serves as a basis for process analysis and the design of controllers. A population balance for the dynamics of the crystal s ize distribution (CSD) with mass and heat balances is described as wel l as empirical relations for the separation efficiency of classified p article removal systems, the initial CSD, and the crystallization kine tics. A continuous pilot crystallizer is used that is equipped with a separator and dissolver for fine crystals and a CSD sensor based on fo rward light scattering. The process and sensor are modeled separately. The sensor model is based on Fraunhofer light scattering theory assum ing rectangular-shaped particles. CSD dynamics data are obtained from startup experiments with the pilot plant at different process conditio ns. Experimental process data show a strong effect of fines and the sl urry retention time on the CSD dynamics, A nonlinear parameter estimat ion procedure determines the empirical parameters directly from raw se nsor data, The model fits accurately to the measured data. Evidence is found for the existence of a population of slow growing crystals with a growth rate approximately ten times lower than the fast growing cry stals. A strong correlation is found between the total surface area of crystals with a size larger than 600 mu m and the nucleation rate.