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

被引：8

作者：

Ozcanli, Y. ^{[1
]}

Beken, M. ^{[2
]}

Cavus, F. Kosovali ^{[3
]}

Hadiyeva, A. A. ^{[4
]}

Sadigova, A. R. ^{[4
]}

Alekperov, V. A. ^{[4
]}

机构：

[1] Yildiz Tech Univ, Dept Phys, TR-34220 Istanbul, Turkey

[2] Hal Univ, Beykent Univ, Dept Elect Elect Engn, TR-34398 Istanbul, Turkey

[3] Halic Univ, Dept Elect Technol, TR-34445 Istanbul, Turkey

[4] Azerbaijan Acad Sci, Inst Phys, AZ-1000 Baku, Azerbaijan

来源：

JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS | 2017年 / 12卷 / 04期

关键词：

ANN; Polypropylene; Nanoclay; Mechanical Properties; POLYMER COMPOSITES; TEMPERATURE; BASE; TIME;

D O I：

10.1166/jno.2017.2017

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：316 / 320

页数：5

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