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dc.contributor.authorGhiasi, Mohammad M.
dc.contributor.authorBahadori, Mohammad
dc.contributor.authorLee, Moonyong
dc.contributor.authorKashiwao, Tomoaki
dc.contributor.authorBahadori, Alireza
dc.date.accessioned2018-09-21T03:37:58Z
dc.date.available2018-09-21T03:37:58Z
dc.date.issued2016
dc.identifier.issn0009-2460en_US
dc.identifier.urihttp://hdl.handle.net/10072/100552
dc.description.abstractTwo methods are presented and compared for quickly calculating this important, yet neglected parameter Over the last few decades, a considerable effort has been directed to toward the evaluation of thermophysical and transport properties of air for a wide range of temperatures. However, relatively limited attention has been given to investigation of the compressed air Prandtl number at elevated pressures. In this article, two new approaches for the accurate prediction of Prandtl number (Pr) of compressed air are presented. The first approach is based on developing a simple-to-use polynomial correlation for predicting Pr of compressed air as a function of temperature and pressure. The second approach is based on the feed-forward back-propagation (FF-BP) artificial neural network (ANN) methodology, wherein the results demonstrate the ability of the presented ANN method to predict accurate Pr values of air at elevated pressures. A comparison of the two approaches indicates that the developed ANN-based model provides slightly more accurate results than the new empirical correlation.en_US
dc.description.peerreviewedYesen_US
dc.languageEnglishen_US
dc.publisherAccess Intelligenceen_US
dc.publisher.urihttps://www.chemengonline.com/rapid-prediction-prandtl-number-compressed-air/en_US
dc.relation.ispartofpagefrom1en_US
dc.relation.ispartofpageto7en_US
dc.relation.ispartofissue6en_US
dc.relation.ispartofjournalChemical Engineeringen_US
dc.relation.ispartofvolume123en_US
dc.subject.fieldofresearchChemical Engineering not elsewhere classifieden_US
dc.subject.fieldofresearchcode090499en_US
dc.titleRapid prediction of Prandtl number of compressed airen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.hasfulltextNo Full Text


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