(38c) Dns-Derived Models For The Prediction Of Yield And Selectivity In Reactive Bubbly Flows

There has been considerable interest on the outcome of fast chemical reactions happening in the vicinity of rising bubbles. For example, in the pharmaceutical industry the prediction and control of selectivity for parallel or consecutive reaction networks is crucial in order to avoid significant byproduct formation and degradation of product quality, which may increase downstream costs. Our research group has addressed this challenge using direct numerical simulations (DNS) in the past. We are now able to fully resolve the boundary layer in the vicinity of the bubble. This allows us to predict many parameters, such as mass transfer coefficients, which are in very good agreement with experimental techniques even for complex fluids including shear-thinning and viscoelastic media.

In the current work we concentrate on the modeling of chemical reactions in the vicinity of rising bubbles and bubble swarms. We propose a simple model for the bubble as a micro-reactor including the boundary layer, the wake region and the bulk of the fluid. The parameters describing the model quantitatively are derived from DNS. With these models, we are able to (i) interpret our simulation results in more detail and (ii) provide information on selectivity for the large scale simulation of multiphase reactors.

Furthermore, we present some semi-analytical results for reactions with a special focus on the pharmaceutical industry. Finally, we compare the results of our theoretical and numerical work and give an outlook on the implementation of our results in macro-scale simulations.

[1] A. Koynov, G. Tryggvason, J.G. Khinast, 2005, Mass Transfer and Chemical Reactions in Bubble Swarms with Dynamic Interfaces, AIChE J. 51. [2] S. Radl, G. Tryggvason, J.G. Khinast, 2007, Flow and Mass Transfer of Fully Resolved Bubbles in non-Newtonian Fluids, AIChE J. (accepted for publication).