Prediction of hardness and electrical properties in ZrB2 particle reinforced metal matrix composites using artificial neural network

Abstract

In the present study, the hardness and electrical properties of copper based composite prepared by hot pressing of mechanically alloyed powders were predicted using Artificial Neural Network (ANN) approach. Milling time (t, h), particles size of mechanically alloyed powders (d, nm), dislocation density (ρ, m -2 ) and compressive yield stress (σ 0.2 , MPa) were used as inputs. The ANN model was developed using general regression neural network (GRNN) architecture. Cu-based composites reinforced with micro and nano ZrB 2 particles were consolidated via powder metallurgy processing by combining mechanical alloying and hot pressing. Analysis of the obtained results concerning hardness and electrical properties of the Cu-7 vol.% ZrB 2 alloy showed that the distribution of micro and nano ZrB 2 particles and the presence of agglomerates in the Cu matrix directly depend on the milling time. Also, the results show a strong influence of the milling time on hardness and electrical properties of Cu-7 vol.% ZrB 2 alloy. Addition of ZrB 2 particles decreases electrical conductivity of copper, but despite this fact Cu-7 vol.% ZrB 2 alloy can be marked as highly conductive alloy (samples made of mechanically alloyed powders milled longer than 20 h). Experimental results of the samples have shown a consistency with the predicted results of ANN.

Experimental and modeling studies on dry sliding wear behavior of Alumina reinforced AMC

“…(number of neurons in both input and output layers, architecture of network, hidden layer neurons, algorithm and transfer function) must be fixed [29,30].…”

Electrical and mechanical properties of Cu-CNT nanocomposites sintered by microwave technique

“…Liquid state processing is an effective technique to fabricate MMCs; however, the main disadvantages are the difficult distribution of reinforcement and high reactivity of the matrix with reinforcement, which occurs at high temperatures [28]. Powder metallurgy has been considered as a prevalent method to produce MMCs with less wasting materials and machining operations [29][30][31].…”