Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/6250
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dc.contributor.authorBağcı, Mehmet-
dc.contributor.authorBhaumik, Shubrajit-
dc.date.accessioned2024-09-22T13:32:58Z-
dc.date.available2024-09-22T13:32:58Z-
dc.date.issued2024-
dc.identifier.issn1751-5831-
dc.identifier.issn1751-584X-
dc.identifier.urihttps://doi.org/10.1177/17515831241274434-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/6250-
dc.description.abstractIn this experimental study, the erosion wear behavior of glass fibre-reinforced (GF) composite materials was examined according to ASTM G76-95. Pure/GF reinforced epoxy composite (EP) materials were chosen as the main test sample. Boric Acid (H3BO3), Borax (B2O3), Silicon Dioxide (SiO2), and Aluminium Oxide (Al2O3) were added to the resin as reinforcement at a rate of 15% by weight. The erosion wear rate was investigated with various impingement angles (30 degrees, 60 degrees, and 90 degrees), impact velocities (approximate to 23, 34, and 53 m/s), alumina abrasive particle sizes (approximate to 200 and 400 mu m), and fibre directions (0 degrees and 45 degrees). Neural network models were employed effectively to predict the influence of the reinforcements on erosive wear rate. The erosive wear rate indicated that Al2O3 added GF/EP exhibited the most anti-erosive characteristics followed by silicon dioxide GF/EP and pure GF/EP however, the anti-erosive nature of GF/EP deteriorated with the addition of Borax and Boric Acid.en_US
dc.language.isoenen_US
dc.publisherSage Publications Incen_US
dc.relation.ispartofTribology-Materials Surfaces & Interfacesen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial intelligenceen_US
dc.subjectsolid particle erosionen_US
dc.subjectepoxy compositeen_US
dc.subjecterosion resistanceen_US
dc.subjectneural modelsen_US
dc.subjectNeural-Networken_US
dc.subjectWearen_US
dc.subjectOptimizationen_US
dc.subjectVelocityen_US
dc.subjectPerformanceen_US
dc.subjectPredictionen_US
dc.subjectFrictionen_US
dc.subjectSilicaen_US
dc.titleInvestigating the solid particle erosion behavior of H3BO3 / B2O3 / SiO2 / Al2O3 reinforced glass fibre/epoxy composites and parametric evaluation using artificial intelligenceen_US
dc.typeArticleen_US
dc.typeArticle; Early Accessen_US
dc.identifier.doi10.1177/17515831241274434-
dc.departmentKTÜNen_US
dc.authorwosidBHAUMIK, SHUBRAJIT/J-3487-2019-
dc.authorwosidBagci, Mehmet/ABI-4797-2020-
dc.identifier.wosWOS:001290258300001en_US
dc.institutionauthor-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
item.grantfulltextnone-
item.openairetypeArticle-
item.openairetypeArticle; Early Access-
item.cerifentitytypePublications-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.dept02.10. Department of Mechanical Engineering-
Appears in Collections:WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections
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