Artificial neural network-based prediction technique for wear loss quantities in Mo coatings

dc.contributor.author Hakan Çetinel
dc.contributor.author Hasan Öztürk
dc.contributor.author Erdal Çelik
dc.contributor.author Bekir Karlik
dc.contributor.author Çelik, Erdal
dc.contributor.author Karlik, Bekir
dc.contributor.author Öztürk, Hasan
dc.contributor.author Çetinel, Hakan
dc.date.accessioned 2025-10-06T17:53:20Z
dc.date.issued 2006
dc.description.abstract Mo coated materials are used in automotive aerospace pulp and paper industries in order to protect machine parts against wear and corrosion. In this study the wear amounts of Mo coatings deposited on ductile iron substrates using an atmospheric plasma-spray system were investigated for different loads and environment conditions. The Mo coatings were subjected to sliding wear against AISI 303 counter bodies under dry and acid environments. In a theoretical study cross-sectional microhardness from the surface of the coatings loads environment and friction test durations were chosen as variable parameters in order to determine the amount of wear loss. The numerical results obtained via a neural network model were compared with the experimental results. Agreement between the experimental and numerical results is reasonably good. © 2006 Elsevier B.V. All rights reserved. © 2008 Elsevier B.V. All rights reserved.
dc.identifier.doi 10.1016/j.wear.2006.01.040
dc.identifier.issn 00431648
dc.identifier.issn 0043-1648
dc.identifier.issn 1873-2577
dc.identifier.scopus 2-s2.0-33751062861
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-33751062861&doi=10.1016%2Fj.wear.2006.01.040&partnerID=40&md5=40f2cfe55ea7bbff33fae96fba591257
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/10383
dc.identifier.uri https://doi.org/10.1016/j.wear.2006.01.040
dc.language.iso English
dc.publisher Elsevier Science SA
dc.relation.ispartof Wear
dc.rights info:eu-repo/semantics/closedAccess
dc.source Wear
dc.subject Artificial Neural Networks, Mo Coatings, Plasma Spray, Wear, Friction, Mathematical Models, Molybdenum, Neural Networks, Plasma Spraying, Wear Of Materials, Mo Coatings, Neural Network Model, Sprayed Coatings
dc.subject Friction, Mathematical models, Molybdenum, Neural networks, Plasma spraying, Wear of materials, Mo coatings, Neural network model, Sprayed coatings
dc.subject Wear
dc.subject Artificial Neural Networks
dc.subject Plasma Spray
dc.subject Mo Coatings
dc.title Artificial neural network-based prediction technique for wear loss quantities in Mo coatings
dc.type Article
dspace.entity.type Publication
gdc.author.id Ozturk, Hasan/0000-0002-8308-8428
gdc.author.id KARLIK, Bekir/0000-0002-9112-2964
gdc.author.id Cetinel, Hakan/0000-0001-5938-1213
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gdc.author.scopusid 25927938700
gdc.author.wosid Celik, Erdal/JEF-4673-2023
gdc.author.wosid Cetinel, Hakan/AAA-2345-2020
gdc.author.wosid Ozturk, Hasan/P-2870-2019
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gdc.description.department
gdc.description.departmenttemp Celal Bayar Univ, Dept Mech Engn, TR-45140 Manisa, Turkey; Dokuz Eylul Univ, Dept Mech Engn, TR-35100 Izmir, Turkey; Dokuz Eylul Univ, Dept Met & Mat Engn, TR-35100 Izmir, Turkey; Yasar Univ, Dept Comp Engn, Izmir, Turkey
gdc.description.endpage 1068
gdc.description.issue 10
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
gdc.description.startpage 1064
gdc.description.volume 261
gdc.description.woscitationindex Science Citation Index Expanded
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gdc.opencitations.count 68
gdc.plumx.crossrefcites 34
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person.identifier.scopus-author-id Çetinel- Hakan (6602946248), Öztürk- Hasan (57129064700), Çelik- Erdal (7006256209), Karlik- Bekir (25927938700)
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