A Computationally Efficient CFD Framework for Oxygen Mass Transfer Prediction in Aerated Stirred-Tank Reactors Using the Interfacial Area Concentration Model

Accurate estimation of the overall mass transfer coefficient (kLa) in aerated stirred tank reactors remains of interest. Conventional models, especially those utilizing population balance models, frequently have sluggish convergence and high processing expenses. This study introduces an innovative computational fluid dynamics methodology that integrates an iterative transport equation for the discrete phase with models for interfacial area concentration, bubble breakup, and coalescence. We facilitate expedited kLa estimation, resulting in a 30–50% decrease in computing time. Furthermore, a temperature-dependent user-defined function (UDF) has been integrated to estimate Henry’s coefficient into the species mass transfer model to enhance the precision of dissolved gas concentration forecasts. The model predictions demonstrate significant concordance with experimental data, with an absolute error of under 8% for kLa and under 1% for oxygen saturation values. Thus, the proposed approach offers a more computationally efficient and experimentally tested approach, rendering it suitable for industrial-scale bioreactor simulations.