Effects of using perforated fins on the melting in different type heated trapezoidal cavity equipped with encapsulated PCM during forced convection and modeling with FNN/GNN

dc.contributor.authorSelimefendigil, Fatih
dc.contributor.authorÖztop, Hakan Fehmi
dc.date.accessioned2026-08-12T17:42:06Z
dc.date.issued2025
dc.departmentFırat Üniversitesi
dc.description.abstractIn the present study, melting process in a trapezoidal cavity equipped with encapsulated phase change materials (PCMs) under the combined impacts of using perforated fins and different heating types is numerically explored during forced convection. Effects of Re (between 300 and 1000), fin height (Lf between 0.01H and 0.14H), fin number (N between 0 and 4), number of holes in the perforated case (Nh between 1 and 8), and size of the trapezoidal cavity upper wall (Hp between 0.01H and 0.75H) on the flow features and melting dynamics are explored by using finite element method. It is observed that installation of the fins is very effective on the melting process at the highest size and highest number. As compared to non-perforated case, perforated fins produces almost the same performance in the melting process but volume per fin can be reduced up to 42.85%. At Re = 1000, finned configuration improves melting by 21.6%. As compared to one fin case, melting performance improves by 37.8% with four fins. The improvement in the melt fraction is 18.9% when the fin length is increased from Lf = 0.1H to Lf = 0.14H. The melting performance improvement is 8.2% higher when all sides of the inner part are heated as compared to one side heating case for N = 1. Perforated fins in the trapezoidal cavity with nanofluid improve the melting process by 40.6% when compared to a square cavity without fins and using base fluid. Feed forward networks (FFN) and generalized neural networks (GNN) are used to successfully estimate the dynamics of the melting process.
dc.identifier.doi10.1016/j.est.2025.116928
dc.identifier.issn2352-152X
dc.identifier.issn2352-1538
dc.identifier.scopus2-s2.0-105006481940
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.est.2025.116928
dc.identifier.urihttps://hdl.handle.net/11508/59610
dc.identifier.volume128
dc.identifier.wosWOS:001504073400001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofJournal of Energy Storage
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectHeating type
dc.subjectEncapsulated PCM
dc.subjectPerforated fin
dc.subjectNanofluid
dc.subjectCFD
dc.subjectArtificial neural network
dc.titleEffects of using perforated fins on the melting in different type heated trapezoidal cavity equipped with encapsulated PCM during forced convection and modeling with FNN/GNN
dc.typeArticle

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