99e Prediction of Velocity Field and Particle Deformation In An In-Line Rotor-Stator Mixer

B. N. Murthy1, Karl R. Kevala1, Kenneth T. Kiger2, and Richard V. Calabrese1. (1) Chemical & Biomolecular Engineering, University of Maryland, Building 090, Room 2113, College Park, MD 20742-2111, (2) Mechanical Engineering, University of Maryland, College Park, MD 20742-3035

In-line rotor-stator mixers are employed to produce and control particle size in liquid-liquid and solid-liquid dispersions. With respect to ultimate particle size, these devices often operate far from equilibrium and fluids passing through them experience a limited residence time in the highest shear regions of the flow field. Models that quantify breakage phenomena in the kinetic regime are quite limited and a fundarnenta1 basis for scale-up of in-line rotor-stator, multiphase processes is lacking.

The ultimate goal of this study is to quantify dispersion and emulsification processes in in-line rotor-stator mixers operating in the turbulent regime. Previously, we reported results using a fast particle tracking algorithm in conjunction with RANS sliding mesh CFD simulations, for a Silverson L4RT in-line device. We demonstrated that we could obtain physically realistic results for the paths of particles of various density and size ('real particles'). We have now further developed our simulation techniques to track 'real particles' to acquire their shear rate history and to statistically analyze particle trajectories to provide practical suggestions for scale-up. Furthermore, we have preformed parametric studies varying operating conditions (rotor speed and throughput) and particle properties.

We will report systematic results for the flow field and particle path/shear rate history for several operating conditions. In addition to qualitative comparisons, statistical data will be provided to quantify the effect of operating conditions and particle properties on shear history and particle residence time. Our ultimate goal is to further develop the particle tracking code into a population balance algorithm to allow prediction of particle size in liquid-liquid and solid-liquid systems. We will discuss our future plans in the context of what can realistically be accomplished in the short term.