Volume 2, Issue 2 (Journal OF Welding Science and Technology of Iran 2016)
JWSTI 2016, 2(2): 56-70 |
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Gharaei H, Salehi M, Nahvi M, Sadeghian B. Optimization of gas tungsten arc welding (GTAW) to develop the NiAl coating using neural networks and genetic algorithm. JWSTI 2016; 2 (2) :56-70
URL: http://jwsti.iut.ac.ir/article-1-98-en.html
URL: http://jwsti.iut.ac.ir/article-1-98-en.html
1- , h.gharaei@ma.iut.ac.ir
Abstract: (9187 Views)
In this research, artificial neural network (ANN) and genetic algorithm (GA) were used in order to produce and develop the NiAl intermetallic coating with the best wear behavior and the most value of hardness. The effect of variations of current, voltage and gas flow on the hardness and wear resistance were optimized by ANN and GA. In the following, the optimum values of current, voltage and gas flow were obtained 90(A), 10(v) and 9 (Lit/min), respectively. Then, the wear behavior in the environment temperature and high temperature for optimized NiAl compound was compared with two other experimental samples.
Keywords: Intermetallic NiAl compound, Cladding, Artificial neural networks, Genetic algorithm, High temperature wear
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