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Lookup NU author(s): Dr Umair AhmedORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2018 Institution of Chemical Engineers Rotor–stator mixers such as the inline Silverson are widely used by the process industry. Existing literature on experimental and computational investigations of these devices focus on characterising the power draw and turbulent mixing of Newtonian fluids and non-Newtonian fluids such as emulsions. The current knowledge on the performance of these mixers in blending and mixing fluids with an underlying complex structure is limited. Modelling and simulation of such structured liquids has traditionally been challenging due to the complexity of the constitutive governing equations which are to be solved for the prediction of rheology. In this paper a novel approach to model evolving rheology is proposed. This approach incorporates important physical phenomenon such as the strain rate history effects in the generalised Newtonian fluid model. The new approach is used to model mixing in a pilot scale inline Silverson mixer via Computational Fluid Dynamics (CFD) simulations. A sliding mesh algorithm coupled to eddy viscosity turbulence closure is used. Experiments have been performed with the inline Silverson mixer placed in a recirculation loop for two different rotor speeds, and rheological measurements have been performed on the samples taken at the outlet of the mixer. Computational results are compared with the viscosity measurements and it is found that the model predictions for the evolution of viscosity are in reasonable agreement with the experimental data.
Author(s): Ahmed U, Michael V, Hou R, Mothersdale T, Prosser R, Kowalski A, Martin P
Publication type: Article
Publication status: Published
Journal: Chemical Engineering Research and Design
Print publication date: 01/05/2018
Online publication date: 21/02/2018
Acceptance date: 13/02/2018
Date deposited: 29/04/2018
ISSN (print): 0263-8762
ISSN (electronic): 1744-3563
Publisher: Elsevier Ltd
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