Prediction of Dispersion Characteristics and Rheology in Dense Slurries(Journal Review)

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  • Usui Hiromoto
    Department of Chemical Science and Engineering, Kobe University

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  • Prediction of Dispersion Characteristics and Rheology in Dense Slurries.

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The prediction of slurry viscosity for the suspensions with and without particle size distribution has become possible by using the suspension rheology model proposed in this study. The viscosity prediction model is based on Simha’s cell model, which is applicable to completely dispersed systems. It was certified experimentally that the Simha’s model was able to predict the slurry viscosity for the case of the suspensions with particle size distribution. The present suspension rheology model adopted the assumption that the effect of agglomeration appeared only for the cluster formation with the minimum sized particles, and the other larger particles were completely dispersed. Usui previously proposed the same type model, but the model is modified to give more accurate viscosity predictions. The present model makes the assumption that multi-breakup of inter-particle bonding occurs when a cluster breaks into two parts under a simple shear flow. It is demonstrated that the present model combined with the Simha’s cell model can be successfully used to predict the rheological behavior of slurries.<BR>Prediction of the maximum packing volume fraction with non-spherical particles has been one of the important problems in powder technology. The sphericity depending on the particle diameter was measured by means of an image processing instrument. An algorithm to predict the maximum packing volume fraction with non-spherical particles was proposed. The maximum packing volume fraction was used to predict the slurry viscosity with completely dispersed condition. For this purpose, Simha’s cell model was applied for the concentrated slurry with wide particle size distribution. Also, Usui’s model developed for aggregative slurries was applied to predict the non-Newtonian viscosity of dense calcium carbonate-water slurry and fly ash slurry. It was certified that the maximum packing volume fraction for non-spherical particles can be successfully used to predict the slurry viscosity, and this means indirectly the maximum packing volume fraction determined in this study may be reasonable.

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