Many chemical engineering processes involve the suspension of solid particles in a liquid. In dense systems, agitation leads to the formation of a clear liquid layer above a solid cloud. Cloud height, defined as the location of the clear liquid interface, is a critical measure of process performance. In this study, solid-liquid mixing experiments were conducted and cloud height was measured as a function operating conditions and stirred tank configuration. Computational fluid dynamics simulations were then performed using an Eulerian-Granular multiphase model. The effects of hindered and unhindered drag models and turbulent dispersion force on cloud height were investigated. A comparison of the experimental and computational data showed excellent agreement over the full range of conditions tested. 1. Introduction The suspension of solid particles in a liquid is a key requirement of many industrial processes. Examples relevant to this work include crystallisation, dissolution, and adsorption processes. Each of these can be characterized as complex multiphase processes that are often facilitated by mechanically stirred tanks. Maximizing contact between the solid and liquid phases facilitates mass transfer and reaction, therefore, assessing the ability of the process to suspend particles is a key objective. The quality of suspension can be quantified by three parameters: just suspension velocity, solids distribution, and cloud height. The latter is defined as the location of the interface between solids-rich liquid and clear liquid regions. Cloud height is critical because of limited mixing between the suspended solids and the upper clear liquid layer. The current study aims to develop and validate a computational model of a solids suspension process using experimental measurements of cloud height. The hydrodynamics in stirred vessels are complex, three-dimensional, and turbulent. The interplay between solid and liquid materials, vessel design, impeller type and location, and level of agitation all determine the efficiency of the mixing process. Numerous empirical models have been developed to relate tank performance to operating conditions and geometry [1, 2]. However, these models lack wider application, owing to the complexity of the flow field. This has helped to motivate the need for more detailed analysis. Computational fluid dynamics (CFD) methods are powerful tools for improving our understanding of mixing in stirred tanks. In the last few years, encouraging results have been obtained in the simulation of solid suspension systems [3]. The solids
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