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Characterization and rheological studies of Indian high ash coal water slurries: effect of particle size distribution with artificial neural network (ANN) analysis.

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Title: Characterization and rheological studies of Indian high ash coal water slurries: effect of particle size distribution with artificial neural network (ANN) analysis.
Authors: Shastri, Anurag Kumar1 (AUTHOR), Yatirajula, Suresh Kumar1 (AUTHOR) suresh@iitism.ac.in
Source: International Journal of Coal Preparation & Utilization. 2026, Vol. 46 Issue 6, p1654-1678. 25p.
Subject Terms: *Particle size distribution, *Artificial neural networks, *Temperature effect, *Herschel-Bulkley model, *Rheology, *Slurry, *Yield stress, *Shear rate dependent viscosity
Geographic Terms: India, Jharkhand (India)
Abstract: In present work, rheological behavior of coal-water slurries (CWSs), prepared using high-ash coal taken from Sijua (SJ) coal field area in Jharkhand (India), was analyzed. Consistency in particle size distribution is challenging for rheological studies. Different particle size distributions were made to evaluate their impact on slurry flow properties. Slurries prepared from these particle size distributions were tested at concentrations of 44–56%, and their rheological behaviors were analyzed across temperatures ranging from 25°C to 55°C using an Anton Paar MCR 102 rheometer over a shear rate range of 1–1000 s−1. The findings exhibit that all slurry formulations show pseudoplastic behavior; concentration of 52% shows superior fluidity at 30°C, which is evidenced by the lowest yield stress (0.8471 Pa) and moderate apparent viscosity (~75 mPa.s) at a shear rate of 100 s−1. Temperature influences flow behavior, reducing pseudoplasticity at higher temperatures. Herschel – Bulkley model accurately describes the flow behavior of the slurries, offering precise predictions of yield stress, consistency, and flow indices. This was further corroborated by artificial neural network (ANN) analysis, highlighting robustness of the model. Results underscore the importance of optimizing particle size distribution and concentration for improved CWS performance, offering insights into efficient slurry design for industrial applications. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 194221857
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  Label: Title
  Group: Ti
  Data: Characterization and rheological studies of Indian high ash coal water slurries: effect of particle size distribution with artificial neural network (ANN) analysis.
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  Data: <searchLink fieldCode="AR" term="%22Shastri%2C+Anurag+Kumar%22">Shastri, Anurag Kumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yatirajula%2C+Suresh+Kumar%22">Yatirajula, Suresh Kumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> suresh@iitism.ac.in</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Coal+Preparation+%26+Utilization%22">International Journal of Coal Preparation & Utilization</searchLink>. 2026, Vol. 46 Issue 6, p1654-1678. 25p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Particle+size+distribution%22">Particle size distribution</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br />*<searchLink fieldCode="DE" term="%22Temperature+effect%22">Temperature effect</searchLink><br />*<searchLink fieldCode="DE" term="%22Herschel-Bulkley+model%22">Herschel-Bulkley model</searchLink><br />*<searchLink fieldCode="DE" term="%22Rheology%22">Rheology</searchLink><br />*<searchLink fieldCode="DE" term="%22Slurry%22">Slurry</searchLink><br />*<searchLink fieldCode="DE" term="%22Yield+stress%22">Yield stress</searchLink><br />*<searchLink fieldCode="DE" term="%22Shear+rate+dependent+viscosity%22">Shear rate dependent viscosity</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
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  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink><br /><searchLink fieldCode="DE" term="%22Jharkhand+%28India%29%22">Jharkhand (India)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In present work, rheological behavior of coal-water slurries (CWSs), prepared using high-ash coal taken from Sijua (SJ) coal field area in Jharkhand (India), was analyzed. Consistency in particle size distribution is challenging for rheological studies. Different particle size distributions were made to evaluate their impact on slurry flow properties. Slurries prepared from these particle size distributions were tested at concentrations of 44–56%, and their rheological behaviors were analyzed across temperatures ranging from 25°C to 55°C using an Anton Paar MCR 102 rheometer over a shear rate range of 1–1000 s−1. The findings exhibit that all slurry formulations show pseudoplastic behavior; concentration of 52% shows superior fluidity at 30°C, which is evidenced by the lowest yield stress (0.8471 Pa) and moderate apparent viscosity (~75 mPa.s) at a shear rate of 100 s−1. Temperature influences flow behavior, reducing pseudoplasticity at higher temperatures. Herschel – Bulkley model accurately describes the flow behavior of the slurries, offering precise predictions of yield stress, consistency, and flow indices. This was further corroborated by artificial neural network (ANN) analysis, highlighting robustness of the model. Results underscore the importance of optimizing particle size distribution and concentration for improved CWS performance, offering insights into efficient slurry design for industrial applications. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194221857
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/19392699.2025.2505455
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 25
        StartPage: 1654
    Subjects:
      – SubjectFull: Particle size distribution
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Temperature effect
        Type: general
      – SubjectFull: Herschel-Bulkley model
        Type: general
      – SubjectFull: Rheology
        Type: general
      – SubjectFull: Slurry
        Type: general
      – SubjectFull: Yield stress
        Type: general
      – SubjectFull: Shear rate dependent viscosity
        Type: general
      – SubjectFull: India
        Type: general
      – SubjectFull: Jharkhand (India)
        Type: general
    Titles:
      – TitleFull: Characterization and rheological studies of Indian high ash coal water slurries: effect of particle size distribution with artificial neural network (ANN) analysis.
        Type: main
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          Name:
            NameFull: Shastri, Anurag Kumar
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            NameFull: Yatirajula, Suresh Kumar
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            – D: 01
              M: 06
              Text: 2026
              Type: published
              Y: 2026
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              Value: 46
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            – TitleFull: International Journal of Coal Preparation & Utilization
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