The atmospheric corrosion data of steels after a 16-year exposure at various sites in China were obtained, and power function was used for regression of the corrosion mass loss. Parameters of the power function derived from these exposure data were used as the variants for a multi-argument linear stepwise regression, which was utilized to analyze the effects of various factors on the corrosion. Chemical composition of steels and environment factors were used as the arguments in the step regression. Quantitative relation of the corrosion parameters with both environment factors and chemical compositions of steels was obtained. As a result, corrosion can be predicted for most carbon and low-alloy steels in a variety of environments.
NACE International
2004
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