Development of Correlations for Overall Gas Hold-up, Volumetric Mass Transfer Coefficient, and Effective Interfacial Area in Bubble Column Reactors Using Hybrid Genetic Algorithm-Support Vector Regression Technique: Viscous Newtonian and Non-Newtonian Liquids

Abstract

The objective of this study was to develop hybrid genetic algorithm−support vector regression (GA-SVR)-based correlations for overall gas hold-up (ϵG), volumetric mass-transfer coefficient (kLa), and effective interfacial area (a) in bubble column reactors for gas−liquid systems employing viscous Newtonian and non-Newtonian systems as the liquid phase. The hybrid GA-SVR is a novel technique based on the feature generation approach using genetic algorithm (GA). In the present study, GA has been used for nonlinear rescaling of attributes. These, exponentially scaled, are eventually subjected to SVR training. The technique is an extension of conventional SVR technique, showing relatively enhanced results. For this purpose an extensive literature search was done. From the published literature, 1629 data points for viscous Newtonian and 845 data points for viscous non-Newtonian systems for ϵG, 500 data points for viscous Newtonian and 556 data points for viscous non-Newtonian systems for kLa, and 208 data poin...