Purpose
The purpose of this paper is to predict the life of a corroding metallic structure in seawater so that uncertain and unpredictable failures of a structure, leading to accidents, can be prevented.
Design/methodology/approach
Pitting has been known to show a large scatter in the measurable parameters such as corrosion rate, maximum pit depth, time to perforation and so on. Scatter results from the influence on pit development on metal surface heterogeneity and from variations in the corrosive environment over time. All these facts suggest that randomness is an inherent and unavoidable characteristic of pitting corrosion over time, so that stochastic models have been developed to formulate pit depth as a function of parameters influencing the process. Since chloride penetrates the passive film of the metal surface, Cl ion distribution into the metal has been mapped by finite element method (FEM).
Findings
The maximum pit depth which decides the onset of perforation or leakage has been modeled by the following equation: d=36.31(ΔE)0.68×(Δt)0.35. Cl ion distribution within a pit and outside has been modeled for better understanding of pit initiation which till today is not fully understood.
Practical implications
Perforation and leakage of a tank, container, or pipeline occur when the depth of pitting reaches the section thickness of the material of which the metallic structures are made. The pitting corrosion is localized and occurs at any spot or site where electrochemical conditions (ΔE Equation (9)) are prone to pitting. This leads to unpredictable failures of the structures which may look polished and undamaged under naked eyes. In most metallic structures, pitting may be present at some spots, but failures occur only when the depth predicted by the model Equation (9) reaches the section thickness of the material. Thus, determining pipe to soil potential gives a guide to go for maintenance before pit depth reaches the material thickness, and thereby unpredictable failure can be prevented. Second, the map generated by FEM showing Cl distribution throws much information and light on movement of Cl ions from passive layer into the pit, which leads to its growth. This helps scientists and researchers to understand the mechanism and gives much insights on finding new methods for protection of structures.
Social implications
The work will guide the engineers and researchers to prevent unpredictable failures of structures leading to accidents and human and property loss and prevent environment pollution from spilling of oil from tank and pipeline.
Originality/value
This is an original work based on several laboratory-generated simulated experimental data.
Pitting Corrosion Resistance and Repassivation Behavior of C-Bearing Duplex Stainless Steel