Отправить статью по E-mail Rheological Characteristics of Uni/Bi-Variant Particulate Iron Ore Slurry: Artificial Neural Network Approach
- Авторы: Kumar S.1, Singh M.1, Singh J.1, Singh J.P.2, Kumar S.3
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Учреждения:
- Mechanical Engineering Department
- School of Mechanical Engineering
- Department of Mechanical Engineering
- Выпуск: Том 55, № 2 (2019)
- Страницы: 201-212
- Раздел: Geomechanics
- URL: https://ogarev-online.ru/1062-7391/article/view/184659
- DOI: https://doi.org/10.1134/S1062739119025468
- ID: 184659
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Аннотация
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
Автор, ответственный за переписку.
Email: skumar_me16@thapar.edu
Индия, Patiala, 147004
M. Singh
Mechanical Engineering Department
Email: skumar_me16@thapar.edu
Индия, Patiala, 147004
J. Singh
Mechanical Engineering Department
Email: skumar_me16@thapar.edu
Индия, Patiala, 147004
J. Singh
School of Mechanical Engineering
Email: skumar_me16@thapar.edu
Индия, Jalandhar, 144411
S. Kumar
Department of Mechanical Engineering
Email: skumar_me16@thapar.edu
Индия, Jamshedpur, 831014
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