Artificial Neural Networks in Prediction of Mechanical Behavior of High Performance Plastic Composites

Wei He; G. H. Bao; T. J. Ge; A.S. Luyt; X. G. Jian

doi:10.4028/www.scientific.net/KEM.501.27

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HomeKey Engineering MaterialsKey Engineering Materials Vol. 501Artificial Neural Networks in Prediction of...

Artificial Neural Networks in Prediction of Mechanical Behavior of High Performance Plastic Composites

Abstract:

Using a feed-forward artificial neural network (ANN), the tensile strength of a series of poly(phthalazinone ether sulfone ketone)(PPESK) blended with different contents of polyetheretherketone(PEEK), polysulfone(PSF), polyphenylene sulide (PPS) and reinforced with various amounts of whisker(TK) composites has been predicted based on a measured database. Compared with the experimental results, the maximum error obtained is not more than 0.8%. It is concluded that the predicted data are well acceptable. A well-trained ANN is expected to be very helpful mathematical tool in the structure-property analysis of polymer composites. Finally, using ANN modeling data and experimental data, the tensile strength properties related to whisker weight percent were established.

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Periodical:

Key Engineering Materials (Volume 501)

Pages:

27-31

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.501.27

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Online since:

January 2012

Authors:

Wei He, G. H. Bao, T. J. Ge, A.S. Luyt, X. G. Jian

Keywords:

Artificial Neural Network (ANN), Composite

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