The purpose of this study was to evaluate the grey relational analysis method as a way of determining quickly the important factors affecting the atmospheric corrosion of Q235 carbon steel in one year.
Atmospheric corrosion exposure tests on Q235 steel were carried out at seven typical test sites in China. The test period lasted one year. The corrosion rate of the Q235 test panels was determined using the weight-loss method and environmental factors were monitored and recorded by standard methods. The importance of the various environmental factors was evaluated using the grey relational analysis method.
The results obtained by the grey relational analysis method showed that the ranking order of factors affecting the corrosion of Q235 carbon steel from “slightly” to “severely” was as follows: relative humidity > dew days > SO3 > pH value of rain > rain precipitation > temperature > rainy days > Cl− > H2S > NO2. Furthermore, the initial atmospheric corrosion of Q235 carbon steel was recognized as being the corrosion of the smooth surface by water medium, or acidic aqueous solution.
Materials corrosion can be defined as a grey system because corrosion has a clear outcome and complex but uncertain characteristics. The grey relational analysis method, a part of grey system theory, is an effective and quick data processing method that can be used to sort out the degree of correlation of environmental factors affecting atmospheric corrosion in terms of it being a grey system with a lot uncertain information.
The authors would like to thank the financial support by Natural Science Foundation Project of CQ CSTC (project No. cstc2011jjA50011). This research is also funded by Research Foundation of Chongqing University of Science & Technology (project No. CK2010Z08).
Cao, X., Deng, H. and Lan, W. (2015), "Use of the grey relational analysis method to determine the important environmental factors that affect the atmospheric corrosion of Q235 carbon steel", Anti-Corrosion Methods and Materials, Vol. 62 No. 1, pp. 7-12. https://doi.org/10.1108/ACMM-10-2013-1308
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