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


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A rigorous literature review has been carried out on rheological behavior 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.

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S. Kumar

Mechanical Engineering Department

编辑信件的主要联系方式.
Email: skumar_me16@thapar.edu
印度, Patiala, 147004

M. Singh

Mechanical Engineering Department

Email: skumar_me16@thapar.edu
印度, Patiala, 147004

J. Singh

Mechanical Engineering Department

Email: skumar_me16@thapar.edu
印度, Patiala, 147004

J. Singh

School of Mechanical Engineering

Email: skumar_me16@thapar.edu
印度, Jalandhar, 144411

S. Kumar

Department of Mechanical Engineering

Email: skumar_me16@thapar.edu
印度, Jamshedpur, 831014

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