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Pitting Corrosion Behavior of 304 SS and 316 SS Alloys in Aqueous Chloride and Bromide Solutions
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The importance of the present work falls on the pitting corrosion behavior investigation of 304 SS and 316 SS alloys in 3.5 wt%  of aqueous solution bearing with chloride and bromide anion  at different solutions temperature range starting from (20-50)oC due to the pitting corrosion tremendous effect on the economic, safety and materials loss due to leakage. The impact of solution temperatures on the pitting corrosion resistance at 3.5wt% (NaCl and  NaBr) solutions for the 304 SS and 316 SS has been investigated utilizing the cyclic polarization techniques at the potential range -400 to1000 mV vs. SCE at 40 mV/sec scan rate followed by the surface characterization employing Scanning Electron  Microscope. The results show that a significant decline in the pitting corrosion potential Ep values of both stainless steel alloys in chloride and bromide solution during temperature increase attributed to the pitting corrosion potential decreased arises from the modification of the passive film properties. The surface examination using optical microscope and scanning electron microscope prove the occurring of higher pitting density over 304 SS in chloride solution than that observed in bromide solution with a non-circular lacy cover pitfall out at the center and falls inside the pits hall in comparison to the isolated circular lacy cover pit formed on 316 SS in 3.5wt% NaBr solution at 50 oC.

 

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
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        In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through  Monte Carlo simulation technique were made depend on mean squared error (MSE)  criteria

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