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Modelling Turbulent Inter-Phase Drag in Mechanically Stirred Solid-Liquid Suspensions

DOI: 10.1615/ICHMT.2012.ProcSevIntSympTurbHeatTransfPal.1100
pages 1063-1074

A. Tamburini
Department of Chemical, Production, Computing and Mechanical Engineering, University of Palermo, Viale delle Scienze bdg. 6, 90128 Palermo, Italy

Andrea Cipollina
Department of Chemical, Production, Computing and Mechanical Engineering, University of Palermo, Viale delle Scienze bdg. 6, 90128 Palermo, Italy

G. Micale
Dipartimento di Ingegneria Chimica dei Processi e dei Materiali, Università degli Studi di Palermo, Palermo, Italy

A. Brucato
Dipartimento di Ingegneria Chimica, Gestionale, Informatica, Meccanica, University of Palermo, Viale delle Scienze bdg. 6, 90128 Palermo, Italy

Michele Ciofalo
Dipartimento di Ingegneria Nucleare, Università degli Studi di Palermo, Palermo, Italy

Resumo

In the present work Computational Fluid Dynamics (CFD) is used to investigate solid-liquid suspensions in two similar baffled tanks stirred by a Rushton turbine. Both transient (via Sliding Grid) and steady state (via Multiple Reference Frame) simulation were carried out to predict experimental suspension curves (i.e. amount of suspended solids as a function of the impeller speed) as well as local axial profiles of solids concentration. In solid-liquid stirred tanks, the drag force is the most important among the inter-phase momentum transfer terms: it may significantly affect both solids suspension and distribution. The main purpose of the present work was to find the drag force modelling providing the most accurate overall predictions of the whole set of experimental data ranging from partial to complete suspension conditions. In particular, two aspects were addressed: the influence of background turbulence and the effects of particle-particle interactions at high solids loading. Results show that: (i) accounting for particle-particle interactions by models largely accepted in the literature may lead to substantial discrepancies from the experimental data, (ii) taking into account the effect of background turbulence on the particle drag coefficient is necessary to obtain accurate predictions.

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