Efficient crystal size distribution estimation approach for growth dominated crystallisation processes

The paper presents a novel methodology for the estimation of the shape of crystal size distribution (CSD) during crystallization processes. The approach is based on the combination of quadrature method of moment (QMOM) and method of characteristics (MOCH). The computationally efficient solution of the population balance equation allows the fast prediction of the dynamic evolution of the CSD for the entire batch. Furthermore, under the assumption that for supersaturation controlled crystallization the main phenomenon is growth, an analytical CSD estimator is derived for generic size dependent growth kinetics. The approaches are evaluated for the crystallization of potassium alum in water. The model parameters are identified based on industrial experimental data, obtained using an efficient implementation of supersaturation control. The proposed approach is able to predict and reconstruct the dynamic evolution of the CSD during the batch. The technique can serve as a soft sensor for predicting CSD or as a computationally efficient algorithm for off-line design or on-line adaptation of operating policies based on full CSD data