Suspension flow in crystallizers with and without hydraulic classification

doi:10.1016/j.cherd.2009.08.008

Chemical Engineering Research and Design

Volume 88, Issue 9, September 2010, Pages 1194-1199

https://doi.org/10.1016/j.cherd.2009.08.008 Get rights and content

Abstract

The main goal of this paper is to model a multiphase flow of a monodispersed suspensions in various types of crystallizers: Draft Tube Magma (DTM), Double Draft Tube (DDT) and Fluidized bed (FL). To do this, the CFD (Computational Fluid Dynamics) methods were used. The geometry of model apparatus was similar to those applied in industry. The composition of suspensions and their physical properties were the same as in practical cases.

The computations showed that axial velocity distribution in the investigated types of crystallizers were far from optimal. In each case backward circulation loops have been observed.

Introduction

Concentration distribution of crystals suspension plays an important but diverse role in the crystallizers of DTM, DDT and FL type, e.g. (Synowiec and Tomanek, 1999, Synowiec, 1998, Wójcik and Plewik, 2007, Plewik et al., 2008). Suspension distribution in DTM apparatus indicates good or bad mixing. Intensity of mixing in DDT device determines the degree of suspension flux division between central and outside tubes, whereas in FL apparatus—visualizes hydraulic classification of grains. Development of a reliable method for describing a suspension concentration distribution would permit to optimize the shape of vessel, depending on:

•
minimal power consumption,
•
vortexes and circulation loops elimination,
•
high mixing efficiency (DTM type),
•
hydraulic classification (FL or DDT type),
•
the best localization of the suspension collection point (FL, DTM or DDT type apparatus).

In this paper the results of computer simulations as well as measurements of fluid axial velocity and solid concentration distribution in the discussed crystallizers are presented. For solids suspension flow modeling, the CFD (Computational Fluid Dynamics) package was used.

Section snippets

Computational model

The crystallizers usually applied in industry are DTM for crystallization of grains smaller than 0.5 mm in size, DDT for obtaining crystals of size 0.5–1.2 mm and FL to get crystals larger than 1 mm. The schemes of these types are shown in Fig. 1.

For these three constructional solutions numerical calculations of the fluid axial velocity distribution and local suspension concentration distribution were performed. They were verified by experimental data obtained from literature (Synowiec, 1998,

Results

Axial velocity distribution plays a different role in DTM, DDT and FL crystallizer. In the first type it should ‘protect’ the particles from settling, guarantee an even solid phase distribution and uniform supersaturation within the whole volume. In DDT it affects the degree of crystals division between central and external pipe, whereas in FL crystallizer it should enable the hydraulic classification of solids.

In Fig. 2 fluid axial velocity distribution in discussed types of apparatus are

Experimental validation of applied models

Data obtained by the CFD method (for standard k–ɛ method) were verified.

Velocity distributions were determined using Laser Doppler Anemometer (LDA) method (Ruck, 1987). Local axial velocity distributions were read out in three cross-sections of conical–cylindrical tank at the height h equal to 0.06, 0.14 and 0.23, respectively (Fig. 5). Calculations were conducted for the tank of similar geometry to the experimental one. In both cases a constant pumping capacity equal to $\dot{V} = 3 \times 10^{- 3} m^{3} /s$ was

Summary

Interactions between crystallizer configuration and local solid concentration in suspension are presented. It is concluded that multiphase computation method is a very useful tool for such analysis. In the case of FL and DDT crystallizers the best was Eulerian model, whereas Mixture model with standard k–ɛ method was used to describe suspension dynamics in DTM crystallizer.

Computer simulations of described cases were consistent with experimental data, and that validations CFD in places in which

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Suspension flow in crystallizers with and without hydraulic classification

Abstract

Introduction

Section snippets

Computational model

Results

Experimental validation of applied models

Summary

Aquacult Eng

Chem Eng Sci

Trans IChemE

Chem Eng Process

Continuous crystallizer design

Chem Proc Eng

Exact solution of generalized Percus–Yevick equation for a mixture of hard spheres

Phys Rev

Industrielle Kristallisation—Moderne groβtechnische Anlagen und Fallstudien

Chem Ing Technol

The simulation the two-phase CFD of hydraulic classification of deposit in cisternal apparatus from circulatory pipe

Pol J Chem Technol