Tribological Behavior Prediction for an Epoxy Aramid System Based on Mechanical and Thermal Properties Analyses
Year: 2015
Type: conference-paper
Abstract: Taking into account that the tribological processes are a combination of many other processes the aim of this paper is building a neural network model based on mechanical and thermal properties for prediction of the tribological behaviour of an Epoxy- Aramidic composite system. The created epoxy based composites with aramidic powders, were tribological tested with diverse parameters in order to obtain follow properties: wear rate and friction coefficient. Bending and compression tests were performed for obtain main mechanical properties. Thermal tests were performed in order to obtain follow properties: specific heat, thermal conductivity and thermal expansions. With all the studied properties was created an Artificial Neural Network (ANN) model. The created ANN model can perform prediction for tribological behaviour of studied composites.
Source: BALTTRIB
Authors: I.G. Birsan, I. Roman, S. Ciortan
Institution: "Dunarea de Jos" University of Galati
Language: English
Topic: Tribology and Wear Analysis
Subfield: Mechanics of Materials
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2467196692