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Polymers 2018, 10(6), 644; https://doi.org/10.3390/polym10060644

Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network

1
Faculty of Industrial Technologies in Púchov, Alexander Dubček University of Trenčín, Ivana Krasku 491/30, 020 01 Púchov, Slovakia
2
Faculty of Engineering, Slovak University of Agriculture in Nitra, Trieda Andreja Hlinku 609/2, 949 76 Nitra, Slovakia
3
Department of Mechanical Engineering, Faculty of Technology, Institute of Technology and Business in České Budějovice, Okružní 10, 370 01 České Budějovice, Czech Republic
*
Author to whom correspondence should be addressed.
Received: 25 April 2018 / Revised: 3 June 2018 / Accepted: 6 June 2018 / Published: 9 June 2018
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Abstract

The precise experimental estimation of mechanical properties of rubber blends can be a very costly and time-consuming process. The present work explores the possibilities of increasing its efficiency by using artificial neural networks to study the mechanical behavior of these widely used materials. A multilayer feed-forward back-propagation artificial neural network model, with a strain and the carbon black content as input parameters and stress as an output parameter, has been developed to predict the uniaxial tensile response of vulcanized natural rubber blends with different contents of carbon black in the form of engineering stress-strain curves. A novel procedure has been created for the simulation of the optimized artificial neural network model with input datasets generated by a regression model of an experimental dependence of tensile strain-at-break on the carbon black content in the investigated blends. Errors of the prediction of experimental stress-strain curves, as well as of tensile strain-at-break, tensile stress-at-break and M100 tensile modulus were estimated for all simulated stress-strain curves. The present study demonstrated that the performance of a developed neural network model to predict the stress-strain curves of rubber blends with different contents of carbon black is also exceptionally high in the case of a network that had never learned the input data, which makes it a suitable tool for extensive use in practice. View Full-Text
Keywords: carbon black filled rubber blends; mechanical properties and characteristics; tensile tests of polymers; stress-strain curves; artificial neural network carbon black filled rubber blends; mechanical properties and characteristics; tensile tests of polymers; stress-strain curves; artificial neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Kopal, I.; Labaj, I.; Harničárová, M.; Valíček, J.; Hrubý, D. Prediction of the Tensile Response of Carbon Black Filled Rubber Blends by Artificial Neural Network. Polymers 2018, 10, 644.

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