Thermal analysis of flowing stream in partially heated double forward-facing step by using artificial neural network

Basit Öğe Kaydı
dc.authoridRehman, Khalil Ur/0000-0002-4218-6582
dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.contributor.authorRehman, Khalil Ur
dc.contributor.authorShatanawi, Wasfi
dc.contributor.authorColak, Andac Batur
dc.date.accessioned2024-11-07T13:35:05Z
dc.date.available2024-11-07T13:35:05Z
dc.date.issued2022
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractThe regulators for thermal energy transfer, performances of heat exchangers, turbine blades subject to cooling structure, and energy storage procedures claim the use of a heated fluid with partially heated circular obstructions rooted in confined domains. Owing to such importance we consider a partially heated double forward-facing step (DFFS). To be more specific, from the inlet of DFFS, the viscous stream flows in parabolic form and the Neumann condition is implemented at the outlet. At each wall, no slip is incorporated. The mathematical formulation is constructed to narrate the flow field. The translation of the centers of mounted heated obstructions is considered in three separate situations. For every event, the strength of the Nusselt number is debated numerically. For all cases, the drag coefficient for partially heated obstruction is found a decreasing function of the Reynolds number. Besides this, for better estimation of Drag Coefficient (DC) and Lift Coefficient (LC), an artificial neural network (ANN) model with multilayer per-ceptron (MLP) is developed. MoD values shows that the error rates of the ANN model are very low. The findings show that the constructed ANN model can accurately predict DC and LC values with very low error rates.
dc.description.sponsorshipPrince Sultan University through the TAS research lab
dc.description.sponsorshipThe authors would like to thank Prince Sultan University for their support through the TAS research lab.
dc.identifier.doi10.1016/j.csite.2022.102221
dc.identifier.issn2214-157X
dc.identifier.scopus2-s2.0-85133974871
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.csite.2022.102221
dc.identifier.urihttps://hdl.handle.net/11480/16330
dc.identifier.volume37
dc.identifier.wosWOS:000834770600001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofCase Studies in Thermal Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectHeat transfer
dc.subjectHeated obstruction
dc.subjectDFFS
dc.subjectANN model
dc.subjectHybrid meshing
dc.subjectFinite element analysis
dc.titleThermal analysis of flowing stream in partially heated double forward-facing step by using artificial neural network
dc.typeArticle

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu