FATIGUE LIFE PREDICTIONS OF METAL MATRIX COMPOSITES USING ARTIFICIAL NEURAL NETWORKS
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Dosyalar
Tarih
2014
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Polska Akad Nauk, Polish Acad Sciences, Inst Metall & Mater Sci Pas
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this study, fatigue life predictions for the various metal matrix composites, R ratios, notch geometries, and different temperatures have been performed by using artificial neural networks (ANN) approach. Input parameters of the model comprise various materials (M), such as particle size and volume fraction of reinforcement, stress concentration factor (Kt), R ratio (R), peak stress (S), temperatures (T), whereas, output of the ANN model consist of number of failure cycles. ANN controller was trained with Levenberg-Marquardt (LM) learning algorithm. The tested actual data and predicted data were simulated by a computer program developed on MATLAB platform. It is shown that the model provides intimate fatigue life estimations compared with actual tested data.
Açıklama
Kara, Resul/0000-0001-8902-6837
WOS: 000333983900016
WOS: 000333983900016
Anahtar Kelimeler
MMCs, Fatigue life prediction, Artificial neural networks
Kaynak
Archives Of Metallurgy And Materials
WoS Q Değeri
Q2
Scopus Q Değeri
Q4
Cilt
59
Sayı
1
