چکیده مقاله
Genetic algorithm in prediction of the defect volume fraction in Friction Stir Processing FSP of AZ31 magnesium alloy has been studied in the present work Genetic algorithm is a method of prediction that reduces testing time and cost This study employed experimental data from FSP that is a branch of Friction Stir Welding FSW The input parameters are defined by the rotational speed three parameters , traverse speed three parameters and number of passes four parameters The quality of prediction has been evaluated by comparison of the real results obtained during testing and predicted ones On comparing the experimental data, it was found out that the genetic algorithm model is capable of predicting defect volume fraction in friction stir processing technique
کلیدواژهها
نویسندگان
M Mokhtari
School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Tehran, Iran
S. F. Kashani-Bozorg
School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Tehran, Iran
M Sharififar
School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Tehran, Iran
شیوه ارجاع
Mokhtari, M and Kashani-Bozorg, S. F. and Sharififar, M,1390,Predicting the Defect Volume Fraction in Friction Stir Processing of AZ31 Using Genetic Algorithm,12th Iranian Conference on Manufacturing Engineering (ICME 2010),Tehran
ارائهشده در
مجموعه مقالات دوازدهمین کنفرانس ملی مهندسی ساخت و تولید ایران6 دی 1390 · تهران