Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/6250
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bağcı, Mehmet | - |
dc.contributor.author | Bhaumik, Shubrajit | - |
dc.date.accessioned | 2024-09-22T13:32:58Z | - |
dc.date.available | 2024-09-22T13:32:58Z | - |
dc.date.issued | 2024 | - |
dc.identifier.issn | 1751-5831 | - |
dc.identifier.issn | 1751-584X | - |
dc.identifier.uri | https://doi.org/10.1177/17515831241274434 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.13091/6250 | - |
dc.description.abstract | In 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.iso | en | en_US |
dc.publisher | Sage Publications Inc | en_US |
dc.relation.ispartof | Tribology-Materials Surfaces & Interfaces | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | artificial intelligence | en_US |
dc.subject | solid particle erosion | en_US |
dc.subject | epoxy composite | en_US |
dc.subject | erosion resistance | en_US |
dc.subject | neural models | en_US |
dc.subject | Neural-Network | en_US |
dc.subject | Wear | en_US |
dc.subject | Optimization | en_US |
dc.subject | Velocity | en_US |
dc.subject | Performance | en_US |
dc.subject | Prediction | en_US |
dc.subject | Friction | en_US |
dc.subject | Silica | en_US |
dc.title | Investigating the solid particle erosion behavior of H3BO3 / B2O3 / SiO2 / Al2O3 reinforced glass fibre/epoxy composites and parametric evaluation using artificial intelligence | en_US |
dc.type | Article | en_US |
dc.type | Article; Early Access | en_US |
dc.identifier.doi | 10.1177/17515831241274434 | - |
dc.department | KTÜN | en_US |
dc.authorwosid | BHAUMIK, SHUBRAJIT/J-3487-2019 | - |
dc.authorwosid | Bagci, Mehmet/ABI-4797-2020 | - |
dc.identifier.wos | WOS:001290258300001 | en_US |
dc.institutionauthor | … | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
item.grantfulltext | none | - |
item.openairetype | Article | - |
item.openairetype | Article; Early Access | - |
item.cerifentitytype | Publications | - |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.author.dept | 02.10. Department of Mechanical Engineering | - |
Appears in Collections: | WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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