Skip to main content
padlock icon - secure page this page is secure

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

Buy Article:

$106.51 + tax (Refund Policy)

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.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: ANN; MECHANICAL PROPERTIES; NANOCLAY; POLYPROPYLENE

Document Type: Research Article

Publication date: April 1, 2017

More about this publication?
  • Journal of Nanoelectronics and Optoelectronics (JNO) is an international and cross-disciplinary peer reviewed journal to consolidate emerging experimental and theoretical research activities in the areas of nanoscale electronic and optoelectronic materials and devices into a single and unique reference source. JNO aims to facilitate the dissemination of interdisciplinary research results in the inter-related and converging fields of nanoelectronics and optoelectronics.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more