(198a) An Eulerian-Lagrangian Computational Model to Predict Pressure Filtration – Modeling and Experimentation | AIChE

(198a) An Eulerian-Lagrangian Computational Model to Predict Pressure Filtration – Modeling and Experimentation

Authors 

Mpagazehe, J. N. - Presenter, Carnegie Mellon University
Higgs, C. F. III - Presenter, Carnegie Mellon University

Fluid-solid separation is a key component in many industries such as energy production, pharmaceuticals and waste treatment. As a result, the development of models to predict the separation process is currently an area of great research activity. In this work an Eulerian-Lagrangian model is developed to predict the filtration of particle suspensions. The model uses computational fluid dynamics (CFD) to model the fluid phase and the discrete element method (DEM) to model the solid phase. A fluid-structure interaction technique is used to model the effect of a piston working to push the filtrate through a porous membrane. The results from this model are compared to a bench-top filtration rig under varying solid (volume) fraction, base fluid viscosity, and applied filtration pressure. The model is shown to be able to predict trends in filtrate flow rate and other relevant filtration parameters.

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