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


Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

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.

About the authors

S. Kumar

Mechanical Engineering Department

Author for correspondence.
Email: skumar_me16@thapar.edu
India, Patiala, 147004

M. Singh

Mechanical Engineering Department

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

J. Singh

Mechanical Engineering Department

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

J. P. Singh

School of Mechanical Engineering

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

S. Kumar

Department of Mechanical Engineering

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

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2019 Pleiades Publishing, Inc.