A Azarafza - Faculty of Chemical Engineering, Malek Ashtar University of Technology, Lavizan, Tehran,Iran
M Aghaziarati
N Khandan - Department of chemical industries, Iranian Research Organization for Science & Technology (IROST

The presented work is part of a study is carried out in order to gain insight of key process parameters for production of iron pyrite nanoparticles in a laboratory unbaffled stirred tank. Reynolds-averaged Navier-Stokes (RANS) equations were solved in a finite volume scheme coupled with the multiple reference frame (MRF) approach to predict mixing time in an unbaffled reactor equipped with a 45° pitched 4-blade turbine impeller. RSM turbulence model was applied to capture high swirling flow inside the reactor. User defined scalar (UDS) was also used to mimic and simulate transient behavior of the injected tracer. The resulted equations were discretized by using power law discretization scheme. The predicted results were compared to the experimental observations as well as to the empirical correlations available in the literatures. All the qualitative aspects of the predicted mixing time were found to be similar to those obtained experimentally. Satisfactory results indicate good agreement between experimental measurements and simulated results which demonstrates the ability of computational fluid dynamic (CFD) as a powerful tool in mixing process.

Iron pyrite, Computational Fluid Dynamic (CFD), Stirred reactor, Mixing Time, Pitched Blade Turbine impeller (PBT