Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • apa.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Grindability and abrasive behavior of coal blends: analysis and prediction
Universiti Teknologi PETRONA, MYS.
Universiti Teknologi PETRONA, MYS.
Universiti Teknologi PETRONA, MYS.
Show others and affiliations
2022 (English)In: International Journal of Coal Preparation and Utilization, ISSN 1939-2699, Vol. 42, no 4, p. 1143-1169Article in journal (Refereed) Published
Abstract [en]

Low-grade coals are blended with high-quality coals to meet economic, environmental, and quality specifications. Hence, the grindability and abrasiveness of coal blends are crucial economic and operational parameters. This work evaluates, analyzes, and predicts the grindability and abrasive behavior of coal blends. Three binary coal blends with common low-grade coal were first prepared at various ratios. Blends 1 and 2 were composed of identical and similar ranks, whereas Blend 3 was composed of different ranks. The blends were analyzed using proximate, ultimate analyzers, and a Bomb calorimeter. The grindability and abrasive behavior of the blends were measured using Hardgrove grindability index (HGI) and Yancey, Geer, and Price methods, respectively. Further, the coarser (+75 mu m) and finer (-75 mu m) fractions of HGI experiment were characterized using proximate, ultimate and heating value analyses. The additivity of HGI values was observed for Blend 1 and Blend 2, whereas, the non-additive behavior was observed in Blend 3. Further, the blends' mineral matter contents and abrasiveness index were found to be additive. Several existing models were found to be inaccurate for HGI predictions. Therefore, a new cross-validated model using multi-linear regression was proposed. The model exhibited better HGI predictions of coal blends with a coefficient of determination R-2 = 0.9416.

Place, publisher, year, edition, pages
Taylor & Francis, 2022. Vol. 42, no 4, p. 1143-1169
National Category
Chemical Engineering
Research subject
Chemical Engineering
Identifiers
URN: urn:nbn:se:kau:diva-81006DOI: 10.1080/19392699.2019.1694009ISI: 000497293300001Scopus ID: 2-s2.0-85075333637OAI: oai:DiVA.org:kau-81006DiVA, id: diva2:1478456
Available from: 2020-10-22 Created: 2020-10-22 Last updated: 2024-07-23Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopushttps://doi.org/10.1080/19392699.2019.1694009

Authority records

Idris, Alamin

Search in DiVA

By author/editor
Idris, Alamin
Chemical Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 28 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • apa.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf