Open AccessARTIFICIAL NEURAL NETWORK IN THE MODELLING OF THE EFFECT OF CHROMIUM DOPANTS ON THE MECHANICAL PROPERTIES OF AL-4%CU ALLOY
Author(s) -
Eyere Emagbetere,
OGHENEKOWHO PETER ARUOTURE,
FESTUS IFEANYI ASHIEDU
Publication year - 2019
Publication title -
journal of engineering studies and research
Language(s) - English
Resource type - Journals
eISSN - 2344-4932
pISSN - 2068-7559
DOI - 10.29081/jesr.v25i1.37
Subject(s) - chromium , dopant , ultimate tensile strength , materials science , elongation , alloy , artificial neural network , yield (engineering) , metallurgy , doping , composite material , computer science , machine learning , optoelectronics
Artificial Neural Network (ANN) was used to model the effect of Chromium dopants on the mechanical properties duralumin (Al-4 %Cu). The results showed that the hardness, yield strength, and ultimate tensile strength increased, while the energy absorbed and percentage elongation decreased, with increasing %wt of Chromium dopants. Simulation results of ANN show strong agreement with experimental values, having satisfactory R-values of Mean Square Error. ANN can suitably be used to predict the mechanical properties of Al-4%Cu doped with Chromium.
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