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Buckling load estimation of cracked columns using artificial neural network modeling technique     
Yazarlar (4)
Prof. Dr. Mahmut BİLGEHAN Prof. Dr. Mahmut BİLGEHAN
İstanbul Arel Üniversitesi, Türkiye
Muhammet Arif Gürel
Harran Üniversitesi, Türkiye
Recep Kadir Pekgökgöz
Harran Üniversitesi, Türkiye
Murat Kısa
Harran Üniversitesi, Türkiye
Devamını Göster
Özet
In this paper, buckling analysis of slender prismatic columns with a single non-propagating open edge crack subjected to axial loads has been presented utilizing the transfer matrix method and the artificial neural networks. A multi-layer feedforward neural network learning by backpropagation algorithm has been employed in the study. The main focus of this work is the investigation of feasibility of using an artificial neural network to assess the critical buckling load of axially loaded compression rods. This is explored by comparing the performance of neural network models with the results of the matrix method for all considered support conditions. It can be seen from the results that the critical buckling load values obtained from the neural networks closely follow the values obtained from the matrix method for the whole data sets. The final results show that the proposed methodology may constitute an efficient tool for …
Anahtar Kelimeler
buckling,stability,crack,slender prismatic columns,artificial neural networks
Makale Türü Özgün Makale
Makale Alt Türü SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale
Dergi Adı Journal of Civil Engineering and Management
Dergi ISSN 1392-3730 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce
Basım Tarihi 08-2012
Cilt No 18
Sayı 4
Sayfalar 568 / 579
Doi Numarası 10.3846/13923730.2012.702988
Makale Linki http://www.tandfonline.com/doi/abs/10.3846/13923730.2012.702988