Experimental study for predicting the specific heat of water based Cu-Al2O3 hybrid nanofluid using artificial neural network and proposing new correlation

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.authoridBAYRAK, Prof. Dr. Mustafa/0000-0002-2443-0502
dc.contributor.authorColak, A. Batur
dc.contributor.authorYildiz, Oguzhan
dc.contributor.authorBayrak, Mustafa
dc.contributor.authorTezekici, Bekir S.
dc.date.accessioned2024-11-07T13:24:48Z
dc.date.available2024-11-07T13:24:48Z
dc.date.issued2020
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, an artificial neural network model has been created in order to estimate the specific heat of Cu-Al2O3/water hybrid nanofluid based on temperature (T) and volume concentration (phi). Specific heat values of the Cu-Al2O3/water hybrid nanofluid prepared in five-volume concentration were measured experimentally in the 20 degrees C to 65 degrees C temperature range. The dataset was reserved into three primary parts, with the inclusion of 901 (70%) for the training, 257 (20%) for the test and 129 (10%) for the validation. As a result of comparison with experimental values, it is concluded that this model predicts specific heat with R-value of 0.99994 and an average relative error of approximately 5.84e-9. In addition, a mathematical correlation has been developed to estimate the specific heat of the Cu-Al2O3/water hybrid nanofluid. The data acquired from the mathematical correlation, developed, were in great correlation with all the experimental values with an average deviation of -0.005%. This result has revealed that the developed mathematical correlation is an ideal design for estimating the specific heat of the Cu-Al2O3/water hybrid nanofluid.
dc.description.sponsorshipNigde Universitesi [FEB2018/17-BAGEP]
dc.description.sponsorshipNigde Universitesi, Grant/Award Number: FEB2018/17-BAGEP
dc.identifier.doi10.1002/er.5417
dc.identifier.endpage7215
dc.identifier.issn0363-907X
dc.identifier.issn1099-114X
dc.identifier.issue9
dc.identifier.scopus2-s2.0-85084232441
dc.identifier.scopusqualityQ1
dc.identifier.startpage7198
dc.identifier.urihttps://doi.org/10.1002/er.5417
dc.identifier.urihttps://hdl.handle.net/11480/14332
dc.identifier.volume44
dc.identifier.wosWOS:000529738700001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWiley-Hindawi
dc.relation.ispartofInternational Journal of Energy Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241106
dc.subjectartificial neural networks
dc.subjectdifferential thermal analysis
dc.subjecthybrid nanofluid
dc.subjectspecific heat
dc.titleExperimental study for predicting the specific heat of water based Cu-Al2O3 hybrid nanofluid using artificial neural network and proposing new correlation
dc.typeArticle

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