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https://hdl.handle.net/11499/5869
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Karakaş, Özler | - |
dc.date.accessioned | 2019-08-16T12:03:02Z | |
dc.date.available | 2019-08-16T12:03:02Z | |
dc.date.issued | 2011 | - |
dc.identifier.issn | 0933-5137 | - |
dc.identifier.uri | https://hdl.handle.net/11499/5869 | - |
dc.identifier.uri | https://doi.org/10.1002/mawe.201100848 | - |
dc.description.abstract | The aim of this investigation was determining the fatigue behaviour of welded aluminium joints and so the appertaining SN-lines by application of Artificial Neural Network (ANN) architectures. For this, fatigue data obtained with aluminium welded joints subjected to constant amplitude loading were used. The main benefit of ANN is the good description of the effects of different factors on fatigue life. The results determined by the ANN method for four aluminium alloys are displayed in scatter bands of SN-lines. It is observed that the trained results are in good agreement with the tested data and enable the estimation of SN-lines. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Materialwissenschaft und Werkstofftechnik | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Aluminium alloys | en_US |
dc.subject | artificial neural networks | en_US |
dc.subject | SN-lines | en_US |
dc.subject | welded joints | en_US |
dc.subject | Aluminium welded joints | en_US |
dc.subject | Artificial Neural Network | en_US |
dc.subject | Constant amplitude loading | en_US |
dc.subject | Fatigue behaviour | en_US |
dc.subject | Fatigue data | en_US |
dc.subject | Scatter band | en_US |
dc.subject | Tested data | en_US |
dc.subject | Aluminum | en_US |
dc.subject | Aluminum alloys | en_US |
dc.subject | Fatigue of materials | en_US |
dc.subject | Tin alloys | en_US |
dc.subject | Welding | en_US |
dc.subject | Welds | en_US |
dc.subject | Neural networks | en_US |
dc.title | Estimation of fatigue life for aluminium welded joints with the application of artificial neural networks | en_US |
dc.type | Article | en_US |
dc.identifier.volume | 42 | en_US |
dc.identifier.issue | 10 | en_US |
dc.identifier.startpage | 888 | |
dc.identifier.startpage | 888 | en_US |
dc.identifier.endpage | 893 | en_US |
dc.authorid | 0000-0002-6648-7865 | - |
dc.identifier.doi | 10.1002/mawe.201100848 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopus | 2-s2.0-80054990792 | en_US |
dc.identifier.wos | WOS:000296906100007 | en_US |
dc.identifier.scopusquality | Q2 | - |
dc.owner | Pamukkale University | - |
item.languageiso639-1 | en | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.openairetype | Article | - |
item.grantfulltext | none | - |
crisitem.author.dept | 10.07. Mechanical Engineering | - |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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