Experimental analysis of the effect of nanofluid use on power and efficiency enhancement in heat pipe solar collectors and modeling using artificial neural networks

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dc.contributor.authorÜnvar, Sinan
dc.contributor.authorÇolak, Andaç Batur
dc.contributor.authorMenlik, Tayfun
dc.date.accessioned2024-03-26T09:26:51Z
dc.date.available2024-03-26T09:26:51Z
dc.date.issued2023en_US
dc.departmentRektörlük, Bilişim Teknolojileri Uygulama ve Araştırma Merkezien_US
dc.description.abstractSolar energy systems have significant advantages over traditional energy production methods, but improvements are needed to improve performance and efficiency. In this study, the effect of the use of nanofluids on power and efficiency values in a heat pipe solar collector was analyzed using experimental and artificial intelligence approaches. A heat pipe solar collector was fabricated and the effects of prepared water-based Al2O3 and TiO2 nanofluids on power and efficiency values were experimentally investigated. Using the obtained experimental data, an artificial neural network model has been developed to predict power and efficiency values. The values obtained from the network model were compared with the experimental data and the prediction performance of the network model was extensively examined using various performance parameters. The coefficient of performance value for the neural network model was calculated as 0.99332 and the mean squared error value was calculated as 2.77E-03. The study findings revealed that the use of nanofluids in the heat pipe solar collector improves the power and efficiency values. It has also been seen as a result of the study that the developed artificial neural network model can predict power and efficiency values with deviation rates lower than 0.48%.en_US
dc.identifier.doi10.1615/HeatTransRes.2023047576en_US
dc.identifier.endpage18en_US
dc.identifier.issue13en_US
dc.identifier.startpage1en_US
dc.identifier.urihttps://hdl.handle.net/11467/7193
dc.identifier.urihttps://doi.org/10.1615/HeatTransRes.2023047576
dc.identifier.volume54en_US
dc.identifier.wosWOS:001041554700001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherBegell House Inc.en_US
dc.relation.ispartofHeat Transfer Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Başka Kurum Yazarıen_US
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_US
dc.subjectartificial neural network, efficiency, heat pipe solar collector, nanofluids, poweren_US
dc.titleExperimental analysis of the effect of nanofluid use on power and efficiency enhancement in heat pipe solar collectors and modeling using artificial neural networksen_US
dc.typeArticleen_US

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