Loading…

Prediction model for atmospheric corrosion of 7005-T4 aluminum alloy in industrial and marine environments

Accelerated corrosion tests of the 7005-T4 aluminum alloy were conducted to determine a suitable service life prediction method by using alternating wet–dry cycles in three kinds of solutions. The morphology and composition analysis of the corrosion product revealed that slight corrosion occurred on...

Full description

Saved in:
Bibliographic Details
Published in:International journal of minerals, metallurgy and materials metallurgy and materials, 2018-11, Vol.25 (11), p.1313-1319
Main Authors: Sun, Xiao-guang, Lin, Peng, Man, Cheng, Cui, Jian, Wang, Hai-bo, Dong, Chao-fang, Li, Xiao-gang
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Accelerated corrosion tests of the 7005-T4 aluminum alloy were conducted to determine a suitable service life prediction method by using alternating wet–dry cycles in three kinds of solutions. The morphology and composition analysis of the corrosion product revealed that slight corrosion occurred on the surfaces of the samples immersed in a 0.25wt% Na 2 S 2 O 8 solution. However, pitting corrosion occurred on the surfaces of the samples immersed in a 3.5wt% NaCl solution, whereas exfoliation corrosion occurred on the surfaces of the samples immersed in a mixture of 0.25wt% Na 2 S 2 O 8 and 3.5wt% NaCl solutions. A power exponent relationship was observed between the mass loss and exposure time of the 7005-T4 aluminum alloy immersed in the three kinds of solutions. In the mixture of 0.25wt% Na 2 S 2 O 8 and 3.5wt% NaCl solutions, the mass loss of the aluminum alloy yielded the maximum value. Based on the calculation of the correlation coefficients, the alternating wet–dry procedure in a 3.5wt% NaCl solution could be used to predict the corrosion behavior of 7005-T4 aluminum alloy exposed in the atmosphere of Qingdao, China. The prediction model is as follows: T = 104.28· t 0.91 , where T is the equivalent time and t is the exposure time.
ISSN:1674-4799
1869-103X
DOI:10.1007/s12613-018-1684-6