The OPOSPM as a Nonlinear Autocorrelation Population Balance Model for Dynamic Simulation of Liquid Extraction Columns

Abstract Dynamic simulation and online control problems in liquid extraction columns are still unresolved issues due to the two-phase flow and the particulate character of the dispersed phase. In this work, the One Primary and One Secondary Particle Model (OPOSPM) with two autocorrelation parameters is used as an alternative to the full population balance model. The model presents the base hierarchy of the SQMOM and consists only of two transport equations for droplet number and volume concentrations. Using the full population balance model or online experimental data, the autocorrelation parameters are identified using a constrained weighted nonlinear least square method. Compared to the experimental data in RDC and Kuhni columns, the autocorrelated OPOSPM predicts accurately the dynamic and steady state mean population properties with a simulation time amounts to only 3% of that required by the detailed model.