Optimization of convective drying performance of multiple porous moist objects in a 3D channel

dc.contributor.authorSelimefendigil, Fatih
dc.contributor.authorCoban, Seda Ozcan
dc.contributor.authorÖztop, Hakan Fehmi
dc.date.accessioned2026-08-12T18:07:08Z
dc.date.issued2022
dc.departmentFırat Üniversitesi
dc.description.abstractIn this study, a procedure for optimizing the convective drying performance of multi porous moist objects in a three dimensional channel is proposed. The numerical simulation is performed by using the finite element method and COBYLA optimization algorithm is used to find the optimum spacing between the objects without mass transfer in the first stage. Then, heat and mass transfer equations for the porous moist objects are coupled with the channel flow equations at the optimum spacing which delivers the best convective drying performance. It is observed that the flow recirculation and flow reversal in the inter-spacing with various distances between the objects resulted in thermal gradient variations along the multi object surfaces. The average Nusselt number rises for second block while it shows non-monotonic behavior for the first block when the distance between the first and second group objects are varied. Distance between the second and third objects also affected the average Nu variation for all of the objects. The lateral distance between first and second group objects resulted in up to 50% variation in the average Nu for the second block. The optimum spacing between the objects for the maximum Nusselt number of the objects are obtained as d(1)=5.93h(c), d(2)=7h(c). and d(3)=0.584h(c). The moisture reduction amounts for each of the object at the optimums spacing are found higher as compared to parametric variation of unsteady simulation results. The computational cost for the parametric unsteady coupled heat and mass transport equations in the channel and in the porous moist objects is 75 h 12 min while the optimization assisted simulation results reduced the computational cost to 2 h 33 minutes. Also, artificial neural networks are utilized to obtain the dynamic feature of convective drying at the optimum spacing considering various values of hot dry air temperature which delivers fast and accurate prediction results when compared to high fidelity computational fluid dynamics simulation results.
dc.description.sponsorshipTUBITAK (The Scientific and Technological Research Council of Turkey) [119M050]
dc.description.sponsorshipThis study is supported from the TUBITAK (The Scientific and Technological Research Council of Turkey) under the grant no: 119M050 which is gratefully acknowledged.
dc.identifier.doi10.1016/j.ijthermalsci.2021.107286
dc.identifier.issn1290-0729
dc.identifier.issn1778-4166
dc.identifier.orcid0000-0002-5453-2091
dc.identifier.orcid0000-0003-2422-2241
dc.identifier.scopus2-s2.0-85116565251
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.ijthermalsci.2021.107286
dc.identifier.urihttps://hdl.handle.net/11508/62581
dc.identifier.volume172
dc.identifier.wosWOS:000710365900004
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier France-Editions Scientifiques Medicales Elsevier
dc.relation.ispartofInternational Journal of Thermal Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectConvective drying
dc.subjectThree dimensional
dc.subjectPorous moist
dc.subjectOptimization
dc.subjectUnsteady CFD
dc.subjectNeural networks
dc.titleOptimization of convective drying performance of multiple porous moist objects in a 3D channel
dc.typeArticle

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