Prediction of the wear rates of epoxy-based nanocomposites using artificial neural network approach

Abstract EN

The present investigation aims to use the artificial neural networks (ANN) approach to develop models that could be used to predict the wear rates of epoxy-based nanocomposites.

the epoxy matrix was reinforced with different volume fractions (vol-%) of boron carbide (BC) nanoparticles having average sizes of 50 nm.

the BC nanoparticles were dispersed into the epoxy matrix using mechanical stirring technique.

the wear tests were conducting under dry sliding conditions and several sliding speeds and applied loads.

the developed ANN model was successfully used to predict the influence of the sliding speed, load, and BC nanoparticles volume fraction on wear rates of the EPOXY / BC nanocomposites.

the mean relative absolute error (MARE) of the developed ANN model was 4.27%.