Abstract
Due to their good corrosion resistance, copper and copper alloys such as 90:10 Cu-Ni are used extensively in high-quality marine and industrial piping systems and also in marine, urban, and industrial environments. Their corrosion loss and pitting behaviour tends to follow a bi-modal trend rather than the classic power law. Field data for 90:10 copper nickel immersed in natural seawater are used to explore the effect of water pollution and in particular the availability of critical nutrients for microbiologically induced corrosion. It is shown, qualitatively, that increased dissolved inorganic nitrogen increases corrosion predominantly in the second, long-term, mode of the model. Other, less pronounced, influences are salinity and dissolved oxygen concentration.
Highlights
Copper and copper alloys have good corrosion resistance and are widely used for high quality applications in the marine industry
For pure copper exposed to pure water the bi-modal function degenerates into a simpler mono-modal function that can be approximated by the power law [2]
BackgrouFonrdsteels, the trend in corrosion mass loss most consistent with data for exposures extending over many years is a bi-modal functional relationship [4]
Summary
Copper and copper alloys have good corrosion resistance and are widely used for high quality applications in the marine industry. Using data available in the literature, it was shown that the corrosion loss trends of various copper alloys consistently show a bi-modal corrosion characteristic (Figure 1), provided exposures over several years are considered [2]. The bi-modal functional form is considerably different from the traditional power law function commonly described in the corrosion literature (e.g., [2]). It was inherited as a simplification of the original theoretical work by Tammann [3], who was interested in the atmospheric corrosion of copper roofs. No attention was given to the relative magnitudes of the first and the second mode, or to the values of the parameters shown in Figure 1 and how these might be related to environmental and possibly material factors. The parameters (r0, ta, ca, cs and rs) used to describe the model are shown
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