Prediction of gas holdup in an aerated coaxial mixer containing yield stress fluids for mixing process system development

The development of effective gas-liquid mixing systems in mechanically agitated vessels is typically evaluated in terms of the degree of bubbles dispersion. For instance, adequate gas distribution reduces the formation of oxygen-deficient regions and ensures suitable metabolic pathways in bioreactors. In this regard, the gas holdup is a direct measurement of the process performance because the bubbles’ arrangement determines the gas volume fraction inside the vessel. The accurate estimation of this parameter using empirical correlations provides a rapid prediction of the mixing characteristics, which is crucial for designing stirred tanks. However, a challenge in obtaining empirical correlations is related to the experimental ranges of geometrical and process system conditions. In fact, the existing gas holdup correlations have not considered gas dispersion in yield pseudoplastic fluids using a coaxial mixer that comprises concentric shafts rotating independently. As an opportunity in mixing process system design, this study aims to develop empirical gas holdup correlations for an aerated anchor-PBT coaxial mixing system containing a xanthan gum solution, which behaves as a yield stress fluid. The electrical resistance tomography technique was employed to measure the gas holdup based on the conductivity variation throughout the vessel. A central composite design of experiments was conducted to account for the effect of central impeller speed, anchor speed, and gas flow rate on the mixing performance. The tridimensional surface graphs demonstrated a non-monotonic effect of the central impeller speed on the gas holdup, which indicates a variation in the flow regime. Furthermore, the results showed that an increase in the anchor speed either increases or decreases the gas holdup depending on the aeration rate applied to the system. The developed correlations were statistically assessed and a good agreement with the experimental data was verified, which enabled us to accurately predict optimum process conditions that enhance the mixing effectiveness.