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Investigation on classification efficiency for coal-fired power plant classifiers using a numerical approach

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dc.contributor.authorIsmail F.B.en_US
dc.contributor.authorAl-Muhsen N.F.O.en_US
dc.contributor.authorLingam R.en_US
dc.contributor.authorid58027086700en_US
dc.contributor.authorid57197748656en_US
dc.contributor.authorid57218280461en_US
dc.date.accessioned2023-05-29T08:09:35Z
dc.date.available2023-05-29T08:09:35Z
dc.date.issued2020
dc.description.abstractIncomplete combustion in boilers often leads to a significant presence of unburnt carbon found in the ash and pollutant emissions. A key factor to overcome this problem is to increase the quality of classification via achieving a greater particle separation quality where at least 70% of the coal particles exiting the classifier are smaller than 75 ?m. Three dimensional (3-D) computational fluid dynamics modelling was used to investigate the effect of the steepness of the classifier blade angle on the classification efficiency in Coal-Fired power plants. The gas flow inside the coal mill was solved by the realizable k-? turbulence model (RKE) with a detailed 3-D classifier geometry meanwhile the discrete phase model was used to solve the coal particles flow. The steepest classifier blade angle of 40� achieved the highest quality of classification where 61.70% of the coal particles are less than 75 ?m. Meanwhile, the classification efficiency dipped to 93.0%. An increase in quality of classification leads to a decrease in classification efficiency. � School of Engineering, Taylor's University.en_US
dc.description.natureFinalen_US
dc.identifier.epage1561
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85088564878
dc.identifier.spage1542
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85088564878&partnerID=40&md5=e030f72db6c7cb25d030a11b995c9736
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25453
dc.identifier.volume15
dc.publisherTaylor's Universityen_US
dc.sourceScopus
dc.sourcetitleJournal of Engineering Science and Technology
dc.titleInvestigation on classification efficiency for coal-fired power plant classifiers using a numerical approachen_US
dc.typeArticleen_US
dspace.entity.typePublication
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