Prediction of Particle Growth during Melt Spray Granulation Using a Five-fluid Cfd-pbe Approach

The process of fluidized bed spray granulation unites the steps of solid formation and product formulation in one apparatus and is used to produce granules out of a liquid. Thereby, a melt is atomized into small droplets and sprayed into the fluidized bed, which consists of seed particles of the same material. Droplets deposit on the particles near the spray zone and form a film which solidifies in the cold fluidization air. Layer-by-layer, granulate products with defined particle sizes are formed. In a previous investigation, Li et al. (2011) developed a model using computational fluid dynamics (CFD) and population balance equations (PBE) to predict the development of particle size distributions (PSD) in fluidized bed spray systems. Thereby, they focused on low solution spray flow rates (< 5 kg/h per nozzle) and small specific bed masses (< 40 kg/m2). The aim of this work is to extend this model and to apply it to industrial melt granulation processes with high spray flow rates (> 100 kg/h per nozzle) and high specific bed masses (> 200 kg/m2). Using this CFD-PBE model, it is possible to predict the development of PSD in melt granulation processes using PBE. For such predictions, it is necessary to evaluate internal process variables, e.g. size-dependent growth rates of the granules, as a function of the current state of the process. This can be obtained using a two-dimensional rotationally symmetric CFD multiphase batch model with one nozzle at its centre. A five-fluid model is solved for short process times (~ s) considering fluid dynamics, particle growth due to drop deposition and energy equations. Extracting size-dependent and timeand spaceaveraged particle growth rates, the PBE can finally be solved to predict the particle size distribution for long process times (~ min). The numerical results are validated with experimental data of a melt spray granulation process in batch mode.