Computational Fluid Dynamics Simulation of the Solid Suspension in a Stirred Slurry Reactor

Abstract

A comprehensive computational fluid dynamics CFD model was developed in the present study to gain insight into the solid suspension in a stirred slurry reactor. The preliminary simulations highlighted the need for the correct modeling of the interphase drag force. A two-dimensional model problem was then developed using CFD to understand the influence of free stream turbulence on the particle drag coefficient. The proposed correlation was then incorporated in a two-fluid model (Euler-Euler) along with the standard k-turbulence model with mixture properties to simulate the turbulent solid-liquid flow in a stirred reactor. A multiple reference frame approach was used to simulate the impeller rotation in a fully baffled reactor. A computational model was mapped on to a commercial CFD solver FLUENT6.2 (of Fluent Inc., USA). The model predictions were compared with the published experimental data of Yamazaki et al. [Powder Technol. 1986, 48, 205] and Godfrey and Zhu [AIChE Symp. Ser. 1994, 299, 181]. The predicted results show reasonably good agreement with the experimental data. The computational model and results discussed in this work would be useful for extending the applications of CFD models for simulating large stirred slurry reactors.

Models and Applications for Simulating Turbulent Solid–Liquid Suspensions in Stirred Tanks

“…Wadnerkar et al (2012) compared the effect of four drag models and found that the results from the modified Brucato drag model (Khopkar et al, 2006) were in reasonable agreement with the experimental data. Sardeshpande et al (2011) found that the coefficient in the Brucato drag model was dependent on the particle diameter, solids loading, particle Reynolds number, and prevailing turbulence.…”

“…Several drag force correlations (Clift et al, 1978;Magelli et al, 1990;Brucato et al, 1998;Pinelli et al, 2001;Khopkar et al, 2006) have been summarized (Ochieng and Onyango, 2010;Sardeshpande and Ranade, 2012). Wadnerkar et al (2012) compared the effect of four drag models and found that the results from the modified Brucato drag model (Khopkar et al, 2006) were in reasonable agreement with the experimental data.…”

“…Montante and Magelli (2005) compared these models and found that no apparent difference existed between the results of the "for each phase" and "mixture" models. Thus, the "mixture" model has been widely utilized (Khopkar et al, 2006;Kasat et al, 2008;Tamburini et al, 2009). The "dispersed" model solves the k and ε equations only for the continuous phase, and the effect of the discrete phase on the continuous phase and predictions of the turbulence quantities for the discrete phase are included with source terms (Wang et al, 2004a;Murthy et al, 2007;Feng et al, 2012).…”

“…In particular, the influence of free-stream turbulence on the particle drag must be specified to achieve agreement between simulated and experimental data. Khopkar et al (2006) also proposed that assuming the discrete phase to be a continuum requires somewhat more sophisticated modeling of the interphase momentum exchange terms. Thus, the results of these simulations cannot be interpreted in an unambiguous way (Srinivasa and Jayanti, 2007).…”

Investigation of Mixing in Shear Thinning Fluids Using Computational Fluid Dynamics

“…In the outer region, the relatively small time derivative terms can be neglected. Upon comparing numerical predictions obtained from applying different impeller modeling methodologies, several investigators observed that steady state methods such as MRF can i. provide reasonable predictions to flow field features and power consumption (Jaworski et al, 2001;Bujalski et al, 2002;Kelly & Gigas, 2003;Khopkar et al, 2004;Aubin et al, 2004;Sommerfeld & Decker, 2004;Khopkar et al, 2006), and ii. save about one-seventh of the CPU-time (Brucato et al, 1998).…”