Turbulence Modeling in Side-Entry Stirred Tank Mixing Time Determination

Abstract

Mixing is one of the critical processes in the industry. The stirred tank is one of the operating units commonly used in the mixing process. Several factors greatly influence the efficiency of the stirred tank, including the stirred-tank design, operating conditions, and working fluid properties. The side-entry stirred tank is widely applied in industry, among others; the processing of crude oil in the refinery industry, water-molasses mixing in the bioethanol industry, pulp stock chest in the pulp and paper industry, and anaerobic digester for biogas reactors. Mixing time is one of the critical parameters used in the design of the stirred tank. This research will model mixing time in a flat bottomed-cylindrical side-entry stirred tank with dimensions D = 40 cm and T = 40 cm using CFD ANSYS 18.2 by applying the Standard κ − ε (SKE) and Realizable κ − ε (RKE) turbulence models. The stirrer used is a three-blade marine propeller d = 4 cm which is an axial type impeller. The phenomenon of mixing in the side-entry stirred tank, qualitatively described through computational prediction results in the form of flow profiles and tracer density change contours locally. Moreover, quantitatively indicated by mixing time validated using experimental data carried out by the conductometry method. The computational prediction shows that the mixing time modeled using the SKE turbulence model shows a similarity level of 68.16%, while the RKE turbulence model shows 31.94%.

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation

“…There have been valuable contributions made in the literature for the application of CFD to model volumetric mass transfer coefficient (k L a) [ 40 , 41 , 42 ], power density (P/V) [ 43 , 44 , 45 ], mixing time [ 46 , 47 , 48 ], Kolmogorov length ( λ k ) [ 49 , 50 ], shear stress (τ) [ 51 , 52 , 53 ] and sedimentation [ 54 , 55 ] in bioreactors. Cell culture dynamics, metabolism and product glycosylation have been modelled in the past using mechanistic models [ 56 , 57 , 58 ], statistical models [ 59 , 60 , 61 ], and hybrid models [ 61 , 62 ].…”