Quantitative estimation of MIC corrosion processes by electrochemical techniques and MIC modelling
Proceedings Publication Date
Friso Postma
Herman de Vries, Elsemiek Croese, Jelmer Bekius, Friso Postma, Eugenio Lo Piccolo, Luciana Intiso, Roberta Prencipe, Serena Colella
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Microbiologically influenced corrosion (MIC) is becoming better known and several models are developed to try and estimate MIC. However, current models for the estimation of microbiologically influenced corrosion do not offer generalized or quantitative abilities because they are unable to take into account the quantitative influence of their factors. Additionally, current models often rely heavily on operational history of the system, which means risk in a sense of material loss cannot be as accurately estimated beforehand.

A generalized quantitative estimation of MIC processes from environmental conditions might be useful in order to develop more reliable models.

Indeed, by having the ability to quantify MIC from environmental starting conditions, it is possible to think about prevention options before MIC has occurred or even before an installation is built. Combining quantitative with qualitative assessment of MIC risk will provide insight into how to optimize a system for the lowest MIC risk. By providing fact based insight into the rate at which MIC occurs, the consequences of specific material selection can be more easily evaluated, which support decision making on a management level.

There are different microbial processes that affect the velocity and significance of material degradation. The most common processes are the formation of chemicals that have high corrosivity (e.g. H2S) and a second mechanism is direct utilization of metals’ as electron donor.

For the purpose of this study, different nondestructive electrochemical techniques were used to investigate the microbiologically influenced corrosion (MIC) on CRA alloy by Sulphate Reducing Bacteria (SRB). This includes electrochemical impedance spectroscopy (EIS), Open Circuit Potential (OCP) and linear polarization resistance (LPR). These techniques are sensitive enough to measure very low corrosion rates.

This study shows the quantitative estimation of MIC processes on selected CRA using nondestructive electrochemical techniques and modelling.

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