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


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

JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS, vol.12, pp.316-320, 2017 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 12
  • Publication Date: 2017
  • Doi Number: 10.1166/jno.2017.2017
  • Title of Journal : JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS
  • Page Numbers: pp.316-320

Abstract

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.