On the Prediction of Atmospheric Corrosion of Metals and Alloys in Chile Using Artificial Neural Networks

被引：0

作者：

Vera, Rosa ^{[1
]}

Ossandon, Sebastian ^{[2
]}

机构：

[1] Pontificia Univ Catolica Valparaiso, Fac Ciencias, Inst Quim, Valparaiso, Chile

[2] Pontificia Univ Catolica Valparaiso, Fac Ciencias, Inst Matemat, Valparaiso, Chile

来源：

INTERNATIONAL JOURNAL OF ELECTROCHEMICAL SCIENCE | 2014年 / 9卷 / 12期

关键词：

Atmospheric corrosion; weight loss; artificial neural networks; carbon steel; galvanised steel; copper; aluminium; POWER ELECTRICAL CONDUCTORS; MARINE; STEEL; POLLUTANTS;

D O I：

暂无

中图分类号：

O646 [电化学、电解、磁化学];

学科分类号：

081704 ;

摘要：

Most metals and alloys exposed to the environment suffer deterioration due to the effects of atmospheric corrosion. This study presents results obtained for the corrosion of carbon steel, galvanised steel, copper and aluminium exposed to the environment for a period of 3 years, at 9 different sites around Chile. Mathematical models based on artificial neural networks are used to evaluate the corrosion of the metals and alloys as a function of meteorological variables (relative humidity, temperature and amount of rainfall), pollutants (chloride and sulphur dioxide) and time. The advantages of these models in predicting corrosion is also shown in comparison to traditional statistical regression models when considering the dependence of corrosion as a function of time alone.

引用

页码：7131 / 7151

页数：21

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