An artificial neural network for prediction of the friction coefficient of multi-layer polymeric composites in three different orientations

Nasir, T. and Yousif, B. F. and McWilliam, S. and Salih, N. D. and Hui, L. T. (2010) An artificial neural network for prediction of the friction coefficient of multi-layer polymeric composites in three different orientations. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 224 (2). pp. 419-429. ISSN 0954-4062

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Abstract

In the present work, an artificial neural network (ANN) model was developed to predict frictional performance of a polymeric composite. The experimental dataset at different applied loads (30–100 N), sliding speeds (300–700 r/min), and up to 10 min of sliding duration was used to train the model. The ANN model was trained with a large volume of experimental data (7389 sets). In addition to that, fibre mat orientation was considered in ANN development. Various configurations with different functions of training were used to find the optimal model. As a result of this work, single-layered models with large number of neurons showed high accuracy, up to 90 per cent in prediction, when trained with the Levenberg–Marqurdt function.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: License to Publish Agreement signed. © Nasir, T. and Yousif, B. F. and McWilliam, S. and Salih, Nbhan D. and Hui, L. T. (2010) The definitive, peer reviewed and edited version of this article is published in Proceedings of the Institution of Mechanical Engineers Part C: Journal of Mechanical Engineering Science, 224 (2). pp. 419-429. doi:10.1243/09544062JMES1677
Depositing User: Dr Belal Yousif
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Mechanical and Mechatronic Engineering
Date Deposited: 29 Aug 2010 10:40
Last Modified: 02 Jul 2013 23:57
Uncontrolled Keywords: artificial neural network; friction coefficient; multi-layer composites
Fields of Research (FOR2008): 09 Engineering > 0913 Mechanical Engineering > 091309 Tribology
09 Engineering > 0912 Materials Engineering > 091202 Composite and Hybrid Materials
09 Engineering > 0912 Materials Engineering > 091209 Polymers and Plastics
09 Engineering > 0913 Mechanical Engineering > 091307 Numerical Modelling and Mechanical Characterisation
09 Engineering > 0913 Mechanical Engineering > 091308 Solid Mechanics
Socio-Economic Objective (SEO2008): B Economic Development > 86 Manufacturing > 8699 Other Manufacturing > 869999 Manufacturing not elsewhere classified
Identification Number or DOI: doi: 10.1243/09544062JMES1677
URI: http://eprints.usq.edu.au/id/eprint/8317

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