Title of article :
Optimization of Advanced Square Wave AC-GTAW Parameters to Improve Localized Corrosion Resistance of AA6082-T651 Aluminum Welds
Author/Authors :
Tabeahmadi, Mohammad Department of Material Science and Engineering - Shahid Chamran University of Ahvaz - Ahvaz, Iran , Dehmolaei, Reza Department of Material Science and Engineering - Shahid Chamran University of Ahvaz - Ahvaz, Iran , Alavi Zaree, Reza Department of Material Science and Engineering - Shahid Chamran University of Ahvaz - Ahvaz, Iran
Pages :
12
From page :
20
To page :
31
Abstract :
In this study, optimization of advanced square wave alternative current GTAW(ASW-AC-GTAW) parameters were conducted to improve localized corrosion resistance of AA6082-T651 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 L9(34) orthogonal array. To study the localized corrosion resistance of weld metals; potentiodynamic polarization test was performed on all samples and corresponding ΔEpit(𝐸𝑝𝑖𝑡−𝐸𝑐𝑜𝑟𝑟)(𝑚𝑉) were measured and considered as evaluation criterion. Implementation of variance analysis(ANOVA) on measured data and SN⁄ (Signal-to-Noise) ratios indicated that the optimum levels of PHC, NHC, F, and PHC% were 300A, 190A, 2Hz, 40%, respectively. According to ANOVA of SN⁄ ratios, contribution of PHC, NHC, F, and PHC% to the results were 35.05%, 25.98%, 23.57%, and 15.27%, consecutively. Interval domain for average ΔEpit calculated with 95% confidence level to be (379.4 , 386.54) (mV). confirmation sample was welded under optimum condition. The values of ΔEpit of optimum sample were 381.13 and 385.47 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 𝛥𝐸𝑝𝑖𝑡 values was obtained using multivariate nonlinear regression.
Keywords :
AA6082-T651 alloy , Advanced square wave AC-GTAW , Localized corrosion , Taguchi method , Analysis of variance(ANOVA) , Regression method
Journal title :
Journal of Advanced Materials and Processing
Serial Year :
2020
Record number :
2630412
Link To Document :
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