(133e) Predicting Pressure Filtration Performance By CFD-DEM Coupling Approach
To obtain a fundamental understanding of the various factors affecting pressure filtration performance, we developed a coupled computational fluid dynamics (CFD) and discrete element method (DEM) model for simulating the effect of the solid particle characteristics on fluid flow through the cake. The combined CFD-DEM model captured both particle-particle and particle-fluid interactions through fundamental mathematical descriptions. The model was validated using data collected by filtering spherical glass beads and deionized water mixtures using a dead-end cell over a range of applied pressures and for two mean particle sizes. Numerical experiments were then performed to study the effects of particle properties, liquid properties and operating conditions on filtration performance. The model predicted that the cake resistance and filtrate flow rate could be strongly affected by the mean size and polydispersity of the spherical particles, the presence of small particles (i.e. fines) in the particle distribution, the viscosity of the liquid, and particle deformation leading to cake compression. We extended the filtration model to account for non-spherical, polydisperse particles more representative of actual APIs (active pharmaceutical ingredients). Simulations predicted that particle shape can have a strong impact on filtration performance, especially when the shape distribution is strongly polydisperse.