DEVELOPING OPTIMAL ARTIFICIAL NEURAL NETWORK (ANN) TO PREDICT THE SPECIFIC HEAT OF WATER-BASED YTTRIUM OXIDE (Y2O3) NANOFLUID ACCORDING TO THE EXPERIMENTAL DATA AND PROPOSING NEW CORRELATION

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.contributor.authorColak, Andac Batur
dc.date.accessioned2024-11-07T13:24:34Z
dc.date.available2024-11-07T13:24:34Z
dc.date.issued2020
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, the specific heat values of yttrium oxide-water nanofluid prepared in five different volumetric concentrations using Y2O3 nanoparticles were measured experimentally using the DTA method. Using the experimental results obtained, multilayer perceptron, feed-forward back-propagation artificial neural network with 15 neurons in its hidden layer was developed. Forty-two of the total 60 experimental data were used in the training phase, 12 in the validation phase, and 6 in the test phase. In addition, a new mathematical correlation has been proposed to calculate the specific heat values of yttrium oxide-water nanofluid. The artificial neural network has predicted the specific heat values of yttrium oxide-water nanofluid with an average error of -0.0007%. The error rate of the proposed new correlation was calculated as -0.011% on average.
dc.identifier.doi10.1615/HeatTransRes.2020034724
dc.identifier.endpage1586
dc.identifier.issn1064-2285
dc.identifier.issn2162-6561
dc.identifier.issue17
dc.identifier.scopus2-s2.0-85101935485
dc.identifier.scopusqualityQ3
dc.identifier.startpage1565
dc.identifier.urihttps://doi.org/10.1615/HeatTransRes.2020034724
dc.identifier.urihttps://hdl.handle.net/11480/14164
dc.identifier.volume51
dc.identifier.wosWOS:000618562300004
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherBegell House Inc
dc.relation.ispartofHeat Transfer Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectyttrium oxide
dc.subjectnanofluid
dc.subjectspecific heat
dc.subjectartificial neural network
dc.subjectheat transfer
dc.titleDEVELOPING OPTIMAL ARTIFICIAL NEURAL NETWORK (ANN) TO PREDICT THE SPECIFIC HEAT OF WATER-BASED YTTRIUM OXIDE (Y2O3) NANOFLUID ACCORDING TO THE EXPERIMENTAL DATA AND PROPOSING NEW CORRELATION
dc.typeArticle

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