Bridging hydrodynamics and granulation kinetics: An efficient 2D CFD-coupled compartmental PBM approach for fluidised bed granulation

Spray fluidised bed granulation (SFBG) is a widely used technology in the pharmaceutical, agricultural, and chemical industries to produce granules with controlled particle-size distributions (PSD) and enhanced functional properties. The present study develops an efficient coupled computational fluid dynamics (CFD)-population balance model (PBM) to optimise the SFBG process. A compartmental modelling strategy is employed to capture the evolution of PSD resulting from aggregation and breakage mechanisms in the wetting and drying compartments, respectively. The CFD model adopts an Eulerian–Eulerian formulation in a two-dimensional (2D) computational domain to estimate particle exchange rates between compartments. The two-compartment PBM is solved using a two-moment-preserving finite-volume scheme. The predictions of the present study are compared against available experimental results and previously reported computational studies. The 2D CFD model reproduces the expected pressure-drop behaviour and shows bed-expansion behaviour comparable to the reported 3D CFD results, while reducing computational cost. Within the PBM framework, several aggregation kernels are evaluated to optimise the PSD. Sensitivity analysis indicates that the size-dependent generalised shear aggregation kernel provides superior predictive performance compared with the Kapur, Brownian and other kernels. Overall, the proposed 2D coupled CFD–PBM modelling offers an accurate and computationally efficient approach for modelling and optimisation of the SFBG process compared with the existing model.