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Journal of Mining Sciences

2019 year, number 2

Rheological Characteristics of Uni/Bi-Variant Particulate Iron Ore Slurry: Artificial Neural Network Approach

S. Kumar, S. Kumar, M. Singh, J. P. Singh, J. Singh
Thapar Institute of Engineering and Technology, Patiala, India
Keywords: железная руда, реология, однородный, бимодальный, эффективная вязкость, Iron-ore, rheology, unimodal, bimodal, apparent viscosity

Abstract

A rigorous literature review has been carried out on rheological behaviour of hard and soft particle slurries.The rheological characteristics of unimodal and bimodal suspension are presented. From experimentation, it was observed that mineral viscosity increases with solid concentration, while decreases with temperature. Addition of 30% (by weight) proportion of finer particles in coarse particles resulted in significant decrease in apparent viscosity of iron ore suspension. Artificial neural network approach was used for predicting the apparent viscosity of slurry.