mohammad Tabeahmadi - Material science and Engineering department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
Reza Dehmolaei - Material science and engineering department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
Sayed Reza Alavi Zaree - Material science and engineering department, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

In this study, optimization of advanced square wave alternative current GTAW(ASW-AC-GTAW) parameters were conducted to improve localized corrosion resistance of AA۶۰۸۲-T۶۵۱ aluminum alloy welds. To this objective, positive half cycle current(PHC), negative half cycle current(NHC), frequency(F) and positive half cycle current percentage(PHC%) were selected as main welding parameters and altered at three levels according to Taguchi method and L_۹ (۳^۴) orthogonal array. To study the localized corrosion resistance of weld metals; potentiodynamic polarization test was performed on all samples and corresponding "Δ" "E" _"pit" (E_pit-E_corr )(mV) were measured and considered as evaluation criterion. Implementation of variance analysis(ANOVA) on measured data and "S" ⁄"N" (Signal-to-Noise) ratios indicated that the optimum levels of PHC, NHC, F, and PHC% were ۳۰۰A, ۱۹۰A, ۲Hz, ۴۰%, respectively. According to ANOVA of "S" ⁄"N" ratios, contribution of PHC, NHC, F, and PHC% to the results were ۳۵.۰۵%, ۲۵.۹۸%, ۲۳.۵۷%, and ۱۵.۲۷%, consecutively. Interval domain for average "Δ" "E" _"pit" calculated with ۹۵% confidence level to be (۳۷۹.۴ , ۳۸۶.۵۴) (mV). confirmation sample was welded under optimum condition. The values of "Δ" "E" _"pit" of optimum sample were ۳۸۱.۱۳ and ۳۸۵.۴۷ mV. Both of this measurement fallen in the Interval domain. Therefore, the experimental results were in excellent agreement with analytical predictions. The regression model for predicting ΔE_pit values was obtained using multivariate nonlinear regression.

AA۶۰۸۲-T۶۵۱ alloy, localized corrosion, Taguchi Method, Analysis of variance(ANOVA), regression method