A one-dimensional combined multifluid-population balance model for the simulation of batch bubble columns

Application and parameterization of a one‐dimensional multifluid population balance model to bubble columns

“…Therefore, due to the strong simplifications and the assumptions made, our model was not able to predict the properties of the dispersed phase correctly when all model parameters were adopted directly from literature. 22 However, good agreement between model predictions and experiments was obtained when only a few parameters (four) of the models describing coalescence and breakage of bubbles were fitted to the measurement of local BSD in the bubble column. Obviously, the fitted parameters lump all the specific information of the process (e.g., turbulence) and the chemical system.…”

“…Recently, we applied successfully an 1D multifluid population balance (MPB) approach to describe the axial profiles of gas volume fraction, the bubble size distribution (BSD) and gas phase velocity in a semi-batch bubble column operated with water and air. 22 Our 1D MPB approach reduces the physical space ðx, y, zÞ T to 1D ðzÞ along the main flow direction. To describe the complex behavior of the dispersed phases namely breakage, coalescence, nucleation and growth as well as the dependency of the velocity of the bubbles on their size we applied the kinetic gas theory with size resolution (KTAWSR).…”

“…As mentioned above, we applied the MPB based on the KATSWR approach successfully to describe the velocity and size distribution in a bubble column. 22 However, since the equations are cross-sectional averaged resulting in a 1D physical space along the vertical axis, local information about turbulence, back-mixing or radial gradients of the gas volume fraction cannot be calculated by the model. This assumption is both the greatest strength and weakness of the developed approach.…”

“…So far, the model approach has only been used to describe the bubble column process for a few variations of process conditions (superficial gas velocity). 22 Therefore, no reliable statements can be made about the ability of the model to predict the process reliably over a wide range of parameters. In particular, it is important to know whether the model can predict process conditions outside the parameter range for which the model was trained.…”

“…It provides new insights into the complex behavior of multiphase processes. 22 but without the air saturator. The primary function of the saturator was to ensure complete saturation of the air with water, thereby minimizing the interfacial mass transfer of water from the liquid phase into the gas bubbles.…”