Mass Loss Prediction of Newly Developed Aluminium-based Alloys Using Artificial Neural Network
نویسندگان
چکیده
The purpose of this study is to predict the mass loss of newly developed aluminium based alloy. Two different alloys are prepared by cladding process and the sliding friction and wear properties of this alloy against high carbon high chromium steel are investigated at different normal loads (50 N, 60 N and 70 N) under different sliding distances. Tests are carried at a constant speed of 1 m/sec under oil lubricated conditions by preheating the circulating engine oil 20w40 at a temperature of 80C. The mass losses are measured and recorded for every interval. An artificial neural network (ANN) model is developed to predict the mass loss of newly developed aluminium-based alloy. It is observed that the predicted values have shown good agreement with experimental values with a correlation coefficient of 0.999973. This model can also be used to predict the mass loss of any material.
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