On the plane receding contact between two functionally graded layers using computational, finite element and artificial neural network methods

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dc.authoridYaylaci, Murat/0000-0003-0407-1685
dc.authoridONER, Erdal/0000-0001-7492-3754
dc.authoriduzun yaylaci, ecren/0000-0002-2558-2487
dc.authoridADIYAMAN, GOKHAN/0000-0002-3076-4090
dc.authoridBirinci, Ahmet/0000-0002-5913-7699
dc.contributor.authorOner, Erdal
dc.contributor.authorSengul Sabano, Bahar
dc.contributor.authorUzun Yaylaci, Ecren
dc.contributor.authorAdiyaman, Gokhan
dc.contributor.authorYaylaci, Murat
dc.contributor.authorBirinci, Ahmet
dc.date.accessioned2024-10-04T18:52:32Z
dc.date.available2024-10-04T18:52:32Z
dc.date.issued2022
dc.departmentBayburt Üniversitesien_US
dc.description.abstractThe frictionless double receding contact problem for two functionally graded (FG) layers pressed by a uniformly distributed load is addressed in this paper. The gradation in the layers is assumed to follow an exponential variation through the height with constant Poisson's ratios. The lower layer rests on a homogeneous half-plane (HP). There is no adhesion between the FG layers or between the lower layer and the HP. The body forces of the FG layers and HP are ignored. First, the governing equations are reduced to a system of two singular integral equations with contact pressures and contact lengths as unknowns using Fourier transform techniques and boundary conditions. The integral equations are solved numerically using the Gauss-Chebyshev integration formula. Then, a parametric finite element analysis is performed using the augmented contact method. Finally, the problem was extended based on the multilayer perceptron (MLP), an artificial neural network used for different problem parameters. The effects of stiffness parameters, the normalized load length, the ratio of shear moduli, the ratio of FG layer heights to the normalized contact lengths, and normalized maximum contact pressures are explored. The results of finite element analysis and the MLP approach are used to validate the normalized maximum contact pressures and contact lengths obtained from an analytical method based on elasticity theory, and finally, good agreement between these three methods results is obtained. The obtained results could help in designing multibody indentation systems with FGMs.en_US
dc.identifier.doi10.1002/zamm.202100287
dc.identifier.issn0044-2267
dc.identifier.issn1521-4001
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85122862882en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1002/zamm.202100287
dc.identifier.urihttp://hdl.handle.net/20.500.12403/3531
dc.identifier.volume102en_US
dc.identifier.wosWOS:000744440200001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWiley-V C H Verlag Gmbhen_US
dc.relation.ispartofZamm-Zeitschrift Fur Angewandte Mathematik Und Mechaniken_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectcontact pressureen_US
dc.subjectfinite element methoden_US
dc.subjectmultilayer perceptronen_US
dc.subjectreceding contacten_US
dc.titleOn the plane receding contact between two functionally graded layers using computational, finite element and artificial neural network methodsen_US
dc.typeArticleen_US

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