CFD and PBM of Latex Particle Aggregation in Mixing Tanks | AIChE

CFD and PBM of Latex Particle Aggregation in Mixing Tanks

This project focuses on modeling both the mixing properties and particle aggregation involved in an industrial emulsion manufacturing process. The system consists of a discrete phase of latex particles dispersed in a continuous aqueous phase. During the mixing process, small latex particles aggregate into larger and more uniform particles, thereby creating a particle size distribution (PSD). Particle aggregation and colloidal interactions are governed by the Derjaguin, Landau, Verwey, Overbeek (DLVO) theory. Brownian motion leads to the perikinetic aggregation of latex particles. Computational Fluid Dynamics (CFD) along with Population Balance Modeling (PBM) are used to track the PSD of latex particles, allowing for simulations and computational models of emulsion mixing processes, such as that of Latex, to be developed. The aim of this project is to better understand the complexities associated with colloidal dispersions and emulsion aggregation in different sized mixing tanks especially when trying to scale-up such mixing processes. Through the examination of velocity profiles and the change in PSD over time, two tanks of different sizes can be modeled and compared. CFD-PBM simulations of latex particle aggregation in water were carried out for a Pilot Plant tank and a larger Manufacturing tank using a total of three user-defined functions (UDF’s). A UDF is an additional piece of code inserted in the ANSYS program to enable more complex calculations to be performed in conjunction with the CFD analysis. The first UDF, based off the DLVO theory, is used to calculate particle aggregation rates. The second UDF, a velocity UDF, is used to specify the different velocities experienced by the impeller during different stages of the mixing process. The third UDF, a viscosity UDF, is used to determine the change in viscosity of the mixture over the entire process. Our goal is to be able to formulate a scenario where the pilot tank can be used to better understand the manufacturing system.