Modeling of the wear behavior in A356–B4C composites

In this study, attempts were made to coat the boron carbide (B4C) powders with TiB2 via a sol–gel process. Different volume fraction of coated B4C particles were incorporated into the aluminum alloy by a mechanical stirrer and wear properties of unreinforced A356 alloy and composites with different vol% of coated B4C particles were experimentally investigated. Further study was carried out on the performance of artificial neural network (ANN) in prediction of the composites wear behavior. The finite element technique was implemented to obtain two of the inputs, cooling rate and temperature gradient. It is observed that predictions of ANN are consistent with experimental measurements for A356 composite and considerable savings in terms of cost and time could be obtained by using neural network model.