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Nwoye, C. I. (2008). C-NIKBRAN Data Analytical Memory (Software).

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Implicit Analysis of Al-Mn Alloy Corrosion Rate Dependence on Its Pre-Installed Weight and Exposure Time in Atmosphere Environment

1Department of Metallurgical and Materials Engineering, Nnamdi Azikiwe University, Awka, Nigeria

2Department of Metallurgical and Materials Engineering, University of Lagos, Akoka, Nigeria

3Department of Industrial Physics, Ebonyi State University, Abakiliki, Nigeria


International Journal of Materials Lifetime. 2015, Vol. 2 No. 1, 22-29
DOI: 10.12691/ijml-2-1-4
Copyright © 2015 Science and Education Publishing

Cite this paper:
C. Nwoye, E. O. Obidiegwu, N. E. Idenyi. Implicit Analysis of Al-Mn Alloy Corrosion Rate Dependence on Its Pre-Installed Weight and Exposure Time in Atmosphere Environment. International Journal of Materials Lifetime. 2015; 2(1):22-29. doi: 10.12691/ijml-2-1-4.

Correspondence to: C.  Nwoye, Department of Metallurgical and Materials Engineering, Nnamdi Azikiwe University, Awka, Nigeria. Email: nwoyennike@gmail.com

Abstract

An implicit analysis of the Al-Mn corrosion rate dependence on the pre-installed alloy weight and exposure time in atmosphere environment was carried out. Surface structural analysis of corroded and uncorroded Al-Mn alloys were carried out to evaluate the grain boundary morphology. The response coefficient of the alloy corrosion rate to the combined influence of pre-installed alloy weight ϑ and exposure time ɤ was evaluated to ascertain the viability and reliability of the highlighted dependence. Surface structural analysis of the corroded alloy revealed in all cases widely distributed oxide film of the alloy in whitish form. A two-factorial empirical model was derived, validated and used for the analysis and evaluation. The validity of the model; ζ = Log -1(2.4908 (ϑ/ɤ) - 4.3059 (ϑ/ɤ)2 - 2.5941) was rooted on the core model expression Log ζ + 2.5941 = 2.4908 (ϑ/ɤ) - 4.3059 (ϑ/ɤ)2 where both sides of the expression are correspondingly approximately equal. Results generated using regression model showed trend of data point distribution similar to those from experiment and derived model. Evaluations from generated results indicated that the corrosion penetration depth as obtained from experiment, derived model & regression model were 1.394 x 10-5, 1.886 x 10-5 & 1.394 x 10-5 mm respectively. Standard errors incurred in predicting the corrosion rate for each value of the pre-installed alloy weight and exposure time considered as obtained from experiment, derived model & regression model were 8.21 x 10-5, 9.91 x 10-5 & 2.02 x 10-5 % and 5.46 x 10-5, 1.4 x 10-4 & 5.18 x 10-5 % respectively. Deviational analysis indicates that the maximum deviation of model-predicted corrosion rate from the experimental results is less than 19%. This translated into over 80% operational confidence and response level for the derived model as well as over 0.8 response coefficient of corrosion rate to the collective operational contributions of pre-installed alloy weight and exposure time in the atmosphere environment.

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