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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%.

Abstract. Flame assisted spray dryer are widely uses for large-scale production of nanoparticles because of it ability. Numerical approach is needed to predict combustion and particles production in scale up and optimization process due to difficulty in experimental observation and relatively high cost. Computational Fluid Dynamics (CFD) can provide the momentum, energy and mass transfer, so that CFD more efficient than experiment due to time and cost. Here, two turbulence models, k-ε and Large Eddy Simulation were compared and applied in flame assisted spray dryer system. The energy sources for particle drying was obtained from combustion between LPG as fuel and air as oxidizer and carrier gas that modelled by non-premixed combustion in simulation. Silica particles was used to particle modelling from sol silica solution precursor. From the several comparison result, i.e. flame contour, temperature distribution and particle size distribution, Large Eddy Simulation turbulence model can provide the closest data to the experimental result.