A 1D Combined Multifluid-Population Balance Model for the Simulation of Batch Bubble Columns

Bubble columns are widely used as multiphase reactors for gas-liquid reactions in industrial applications. It is important for the design engineer to be able to determine the general influence of the geometry (e.g. diameter and height) and the process conditions (e.g. power input, feed rates) on the behavior of the reactor at an early stage of process development. In this case, it means that models are required that can describe the interaction between the internal fluid dynamics (phase velocities), the thermodynamic properties of the mixtures and the behavior of the dispersed gas phase (e.g. break-up and coalescence of bubbles). To enable the use of these models for sensitivity and design studies, the computation must be fast and at the same time the results must be able to reliably predict the general trends of the reactor behavior. A suitable candidate for that purpose is the kinetic theory approach with size resolution (KTAWSR). This approach combines a multifluid model, which describe the internal fluid dynamics, with a population balance equation model, which describe the behavior of the dispersed gas phase.

A steady-state and one-dimensional version of the KTAWSR model was used and extended to batch bubble columns. For this purpose, a new approach for the determination of the integral gas holdup was developed which does not require additional empirical correlations. Different breakage and coalescence model combinations were calibrated by moments of bubble size distributions that were measured in a laboratory column for the system air-water. To validate the model, the integral gas holdup and the bubble size distribution were measured at four axial positions at three different gas volume fluxes reaching the transition regime. The simulation results show that the novel integral gas holdup calculation approach can predicate the experimental data reliably. Thus, the presented method is well-suited to study the general behavior of bubble columns and gives insights into the process that are important for a reliable design and scale-up.