Objective
This article introduces the capabilities of the OLI Studio: Corrosion Analyzer for predicting localized corrosion. We will review how the software calculates key electrochemical potentials, explore the different features, and demonstrate how to interpret the results for assessing corrosion risks.
Introduction
Localized corrosion is the intense attack at specific sites of an otherwise passive metal surface. Metal oxidation occurs at localized anodic sites surrounded by cathodic zones where reduction reactions take place. The small size of anodic sites can lead to extremely high corrosion rates, potentially causing catastrophic failure of equipment or pipelines.
The OLI Corrosion Analyzer models two common forms of localized corrosion: pitting and crevice corrosion. Pitting is characterized by small, isolated cavities forming on the metal surface, while crevice corrosion takes place in confined areas where environmental access is limited.
What does the localized corrosion model predict?
The localized corrosion model in the OLI Corrosion Analyzer predicts the conditions under which localized corrosion, such as pitting or crevice corrosion, may occur. It does so by comparing two key electrochemical parameters: corrosion potential1, 2 and repassivation potential3-5. These values are essential in determining the likelihood of corrosion initiation and propagation on a metal surface.
- Corrosion Potential (Ecorr): The potential at which a metal surface corrodes freely. It is determined by a mixed potential model, which considers anodic reactions, such as metal dissolution, and cathodic reactions, such as the reduction of species like oxygen, water, hydronium ions, etc. Ecorr is the potential where the rates of these anodic and cathodic reactions are balanced.
- Repassivation Potential (Erp): The potential below which a growing pit or crevice will repassivate and a protective oxide layer reforms on the metal surface. Erp is influenced by environmental factors such as the concentration of different species (e.g., chlorides) and temperature.
The model predicts that localized corrosion may occur when:
Ecorr > Erp.
It does not have to occur in a given place and at a given time because localized corrosion is a stochastic process. However, localized corrosion cannot occur if the above condition is not satisfied. This concept is depicted in the figure below, which illustrates various stages of localized corrosion:
- Figure 1a: A corrosion-resistant alloy has a passive film, protecting the metal surface.
- Figure 1b: A local breakdown of the passive film occurs, such as from mechanical damage or chemical attack.
- Figure 1c: Metastable pitting begins at an anodic site, where metal dissolution starts. The cathodic reduction reaction occurs outside the pit.
- Figure 1d: The metastable pits either continue to grow, forming stable pits,
- or —depending on the electrochemical conditions—
- Figure 1e: An incipient passive layer forms, preventing further localized corrosion.
Whether the pit continues to grow or repassivates depends on the relationship between the corrosion potential and the repassivation potential. If Ecorr remains above Erp, the pit may grow deeper or another pit may appear, increasing the risk of equipment failure. However, if Ecorr falls below Erp, the pit repassivates, halting further corrosion.
The OLI Corrosion Analyzer calculates these critical potentials and helps users understand when localized corrosion is likely to occur, enabling preventive actions.
Predicting localized corrosion using OLI Studio: Corrosion Analyzer
The OLI Corrosion Analyzer evaluates localized corrosion risks by calculating both Ecorr and Erp for a given alloy in a specific environment. For example, it can be used to evaluate the NaCl concentration at which alloy 2205 is at risk for localized corrosion in a system with water, NaCl, and O₂ at 95°C. A survey of NaCl concentrations can be set up in Corrosion Analyzer to evaluate the localized corrosion risk.
Dual survey calculation parameters, where NaCl is the varied Component for Variable 1.
The Localized Corrosion tab in the OLI Corrosion Analyzer provides a detailed comparison of Ecorr and Erp. Users can easily view how these two potentials change as environmental conditions, such as NaCl concentration, are adjusted. When Ecorr exceeds Erp, the model predicts that localized corrosion will occur. Additionally, the plot also shows the maximum pit current density, which represents the highest possible corrosion current within a pit. This value, which is proportional to the maximum pit corrosion rate, estimates the maximum pit depth under worst case conditions and helps assess the severity of localized corrosion.
The ‘Polarization Curve’ tab offers a graphical representation of the relationship between potential and current density. This plot demonstrates how Ecorr is determined as the point where the anodic and cathodic reactions are in balance. The anodic curve, which represents metal dissolution (‘Alloy 2205 = {Fe, Ni, Cr, Mo}{x+} + xe’ curve) and the possible cathodic reactions, such as oxygen reduction, water reduction and hydronium ion reduction, are plotted. In the presence of oxygen, Ecorr is raised significantly, increasing the risk of localized corrosion. Without oxygen, Ecorr would fall below Erp, preventing localized corrosion from occurring.
The net current density is the predicted current during a polarization scan in the absence of pitting. The peak current density corresponds to the predicted reverse portion of the polarization scan and is dependent on Erp. As outlined by Anderko et al.6, the equation for calculating the peak current density is directly related to Erp. The maximum pit current density is the peak current density when the potential is equal to Ecorr. The maximum pit current density, which depends on both Ecorr and Erp, reflects the highest possible corrosion rate within a pit under the given electrochemical conditions.
Conclusions
The OLI Corrosion Analyzer is a powerful tool for predicting and evaluating the risk of localized corrosion in corrosion-resistant alloys. By comparing the corrosion potential with the repassivation potential, the software provides essential insights into the likelihood of pitting and crevice corrosion under various environmental conditions. These capabilities allow users to take proactive measures to prevent material failure, optimize operational efficiency and extend the lifespan of critical equipment.
References
1. A. Anderko, Modeling of Aqueous Corrosion, in 'Shreir's Corrosion', (ed. T. J. A. Richardson), Amsterdam, Elsevier; 2010), p. 1585-1629.
2. A. Anderko, L. Cao, F. Gui, N. Sridhar, and G. R. Engelhardt, "Modeling Localized Corrosion of Corrosion-Resistant Alloys in Oil and Gas Production Environments: Part II. Corrosion Potential", Corrosion 73, 6 (2017), p. 634-647.
3. A. Anderko, F. Gui, L. Cao, N. Sridhar, and G. R. Engelhardt, "Modeling Localized Corrosion of Corrosion-Resistant Alloys in Oil and Gas Production Environments: I. Repassivation Potential", Corrosion 71 (2015), p. 1197-1212.
4. A. Anderko, N. Sridhar, M. A. Jakab, and G. Tormoen, "A General Model for the Repassivation Potential as a Function of Multiple Aqueous Species. 2. Effect of Oxyanions on Localized Corrosion of Fe-Ni-Cr-Mo-W-N Alloys", Corrosion Science 50, 12 (2008), p. 3629-3647.
5. A. Anderko, N. Sridhar, and D. S. Dunn, "A General Model for the Repassivation Potential as a Function of Multiple Aqueous Solution Species", Corrosion Science 46, 7 (2004), p. 1583-1612.
6. A. Anderko, N. Sridhar, L. Yang, S. Grise, B. Saldanha, and M. Dorsey, "Validation of localised corrosion model using real time corrosion monitoring in a chemical plant", Corrosion engineering, science and technology 40, 1 (2005), p. 33-42.