TY - JOUR T1 - Optimization of gas tungsten arc welding (GTAW) to develop the NiAl coating using neural networks and genetic algorithm TT - بهینه سازی پارامتر های جوشکاری قوسی تنگستن-گاز جهت توسعه پوشش ترکیب NiAl توسط شبکه عصبی و الگوریتم ژنتیک JF - JWSTI JO - JWSTI VL - 2 IS - 2 UR - http://jwsti.iut.ac.ir/article-1-98-en.html Y1 - 2016 SP - 56 EP - 70 KW - Intermetallic NiAl compound KW - Cladding KW - Artificial neural networks KW - Genetic algorithm KW - High temperature wear N2 - 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. M3 ER -