The prediction of maximum failure loads of two serial pinned/bolted composite joints with ANN

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dc.contributor.authorKömür, Mehmet Aydın
dc.contributor.authorŞen, Faruk
dc.contributor.authorSayman, Onur
dc.date.accessioned13.07.201910:50:10
dc.date.accessioned2019-07-16T08:23:48Z
dc.date.available13.07.201910:50:10
dc.date.available2019-07-16T08:23:48Z
dc.date.issued2011
dc.departmentMühendislik Fakültesi
dc.description.abstractThe scope of this study is to examine the development of an artificial neural network (ANN) method for the prediction of maximum failure loads of two serial pinned/bolted E-glass reinforced epoxy composite joints. The experimental data provided from the previous study with different geometrical parameters without preload moments and various applied preload moments were used for developing the ANN model. Comparisons of ANN results with desired values pointed out that there is an excellent agreement between input and output variables of the experimental data. Consequently, ANN was showed to be a suitable powerful tool for the prediction of maximum failure loads of two serial pinned/bolted composite joints.
dc.identifier.endpage103en_US
dc.identifier.issn1070-9789
dc.identifier.issue1en_US
dc.identifier.scopusqualityN/A
dc.identifier.startpage90en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12451/2823
dc.identifier.volume43en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.relation.ispartofJournal of Advanced Materials
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleThe prediction of maximum failure loads of two serial pinned/bolted composite joints with ANN
dc.typeArticle

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