Open Access Research Article

Igor Roman, Sorin Ciortan, Iulian Gabriel Birsan Neural Network Based Analysis of Tribological Behaviour for an Epoxy-Aramid System

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Published 30 Sep 2015

Abstract

The aim of this paper is based on neural network model for tribological analyses of an Epoxy composite system. The created epoxy based composites with aramidic powders, were tribologically tested with diverse parameters in order to obtain the following properties: wear rate and friction coefficient. With all the studied tribological properties was created a Neural Network (NN) model. The created NN model can perform optimisations for concentration of aramidic powder in final used composites for different domains of applications. Keywords: epoxy composites, bloc on ring, friction coefficient, neural network analysis, optimisations

How to Cite this Article

(2015). Igor Roman, Sorin Ciortan, Iulian Gabriel Birsan Neural Network Based Analysis of Tribological Behaviour for an Epoxy-Aramid System. Materiale Plastice, 52(3).
. Igor Roman, Sorin Ciortan, Iulian Gabriel Birsan Neural Network Based Analysis of Tribological Behaviour for an Epoxy-Aramid System. Materiale Plastice. 2015;52(3).
, "Igor Roman, Sorin Ciortan, Iulian Gabriel Birsan Neural Network Based Analysis of Tribological Behaviour for an Epoxy-Aramid System,” Materiale Plastice, vol. 52, no. 3, 2015.
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