(601c) Modeling Emulsification Using Cfd | AIChE

(601c) Modeling Emulsification Using Cfd

Authors 

Mohan, L. S. - Presenter, ANSYS Fluent India Pvt. Ltd.
Pal, D. - Presenter, Fluent India Pvt. Ltd.


Emulsions are liquid in liquid dispersions that form an important class of materials produced by the food and the pharmaceutical industry. The quality of emulsions is determined to a large extent by the process by which they are formed ? they are referred to as products by process. The most important characteristic of an emulsion is its Droplet Size Distribution (DSD). The DSD determines its physical properties such as the viscosity and rheology, and qualities such as the mouth-feel for food products, and the rate of drug delivery of pharmaceutical products. An important property that affects that usage of emulsions is their stability, or the lack of it. Being thermodynamically meta-stable, even very small exposure to unfavorable conditions can lead to splitting, as has been sometimes during the filling process, or even a catastrophic phase-inversion.

The physical processes that determine the above mentioned aspects of emulsions are the breakup and coalescence of droplets. While the dynamic balance between the breakage and coalescence events determines the DSD produced during the manufacturing stages, the response of the droplet population to the flow field during the subsequent operations determines how the DSD is modified. In all these cases the change in the DSD brings with it a subsequent change in the rheology, which could further alter the DSD.

In this talk, we show how the framework of the population balance model can be used to model the coupling between the structure and the rheology of the emulsion to predict the DSD for the emulsion. Using a commercial CFD code, FLUENT, of Fluent Inc., we solve two problems related to the production of emulsions in the turbulent and laminar regime, and compare the predictions with experimental observations. Preliminary results available with us suggest that good agreement between the experiments and predictions is obtained.