Artificial Neural Network Modelling of the Mechanical Properties of Nanocomposite Polypropylene-Nanoclay
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.
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Document Type: Research Article
Publication date: April 1, 2017
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- 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.
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