Please use this identifier to cite or link to this item:
https://hdl.handle.net/11499/5869
Title: | Estimation of fatigue life for aluminium welded joints with the application of artificial neural networks | Authors: | Karakaş, Özler | Keywords: | Aluminium alloys artificial neural networks SN-lines welded joints Aluminium welded joints Artificial Neural Network Constant amplitude loading Fatigue behaviour Fatigue data Scatter band Tested data Aluminum Aluminum alloys Fatigue of materials Tin alloys Welding Welds Neural networks |
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. | URI: | https://hdl.handle.net/11499/5869 https://doi.org/10.1002/mawe.201100848 |
ISSN: | 0933-5137 |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Show full item record
CORE Recommender
SCOPUSTM
Citations
15
checked on Dec 14, 2024
WEB OF SCIENCETM
Citations
14
checked on Dec 18, 2024
Page view(s)
80
checked on Aug 24, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.