Experimental investigation and prediction of wear properties of Al/SiC metal matrix composites produced by thixomoulding method using Artificial Neural Networks

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dc.authorid/0000-0003-3300-1336
dc.authoridYILDIRIM, MUSA/0000-0002-2464-1182
dc.contributor.authorOzyurek, Dursun
dc.contributor.authorKalyon, Ali
dc.contributor.authorYildirim, Musa
dc.contributor.authorTuncay, Tansel
dc.contributor.authorCiftci, Ibrahim
dc.date.accessioned2024-09-29T15:57:53Z
dc.date.available2024-09-29T15:57:53Z
dc.date.issued2014
dc.departmentKarabük Üniversitesien_US
dc.description.abstractIn this study, the wear properties of the SiC particle reinforced aluminium (A356) composite materials (MMCs), produced with thixomoulding method, were investigated both by experimental and Artificial Neural Network (ANN) model in order to determine the weight loss after the wear tests. Two different temperatures (590 degrees C and 600 degrees C) were used in production of the MMCs containing 5%, 10%, 15% and 20% SiC (vol%). The samples of MMC were tested at 2 ms (1) constant sliding speed under 30 N and 60 N loads against four different sliding distances (500 m, 1000 m, 1500 m, and 2000 m). The results indicated that by increasing the production temperature increased the grain size of the MMCs was increased, but the hardness was decreased. The MMCs produced at 590 degrees C were found to have lower weight loss as compared with ones produced at 600 degrees C. In the theoretical prediction model of the MMCs, weight loss, SiC per cent, production temperature, applied weight and sliding distance were used as input values. After comparing the experimental results and the ANNs predicted data it was observed that R-2 was 0.9855. This shows that the developed prediction model has a high level of reliability. (C) 2014 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.matdes.2014.06.005
dc.identifier.endpage277en_US
dc.identifier.issn0264-1275
dc.identifier.issn1873-4197
dc.identifier.scopus2-s2.0-84920063962en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage270en_US
dc.identifier.urihttps://doi.org/10.1016/j.matdes.2014.06.005
dc.identifier.urihttps://hdl.handle.net/20.500.14619/5079
dc.identifier.volume63en_US
dc.identifier.wosWOS:000340949300033en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofMaterials & Designen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAbrasive Wearen_US
dc.subjectTribological Propertiesen_US
dc.subjectAluminum Compositesen_US
dc.subjectMechanical-Propertiesen_US
dc.subjectSurface-Roughnessen_US
dc.subjectParticle-Sizeen_US
dc.subjectBehavioren_US
dc.subjectModelen_US
dc.subjectMicrostructureen_US
dc.subjectResistanceen_US
dc.titleExperimental investigation and prediction of wear properties of Al/SiC metal matrix composites produced by thixomoulding method using Artificial Neural Networksen_US
dc.typeArticleen_US

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