Artificial Neural Network Modelling of the Mechanical Properties of Nanocomposite Polypropylene-Nanoclay

Özcanlı, Yeşim; Beken, M.; Cavus, F.; Hadıyeva, A.; Sadıgova, A.; Alekperov, V.

doi:10.1166/jno.2017.2017

Artificial Neural Network Modelling of the Mechanical Properties of Nanocomposite Polypropylene-Nanoclay

Atıf İçin Kopyala

Özcanlı Y., Beken M., Cavus F. K., Hadıyeva A. A., Sadıgova A. R., Alekperov V. A.

JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS, cilt.12, ss.316-320, 2017 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 12
Basım Tarihi: 2017
Doi Numarası: 10.1166/jno.2017.2017
Dergi Adı: JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
Sayfa Sayıları: ss.316-320
Yıldız Teknik Üniversitesi Adresli: Evet

Özet

This study presents the application of artificial neural network for mechanical properties of polypropylene and their composites with nanoclay. The effect of electric field on mechanical properties of polypropylene and nanocomposites is investigated. Then artificial neural network modelling has been used for predicting the mechanical lifetime of samples of pure polypropylene and their composites with nanoclay. Mechanical tensions ratio of nanoclay are used as input parameters and mechanical lifetime is used as output parameter. For artificial neural network modelling multi-layer perceptron architecture and back-propagation algorithm are used. The simulation results show that artificial neural network can predict the mechanical properties of polypropylene and their composites with nanoclay.