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    Finite Element Analysis for Modelling Microbial and Atmospheric Thin Film Corrosion
    Mohsen Saeedikhani1; Daniel John Blackwood2;
    1, Melbourne, Australia; 2NATIONAL UNIVERSITY OF SINGAPORE, Singapore, Singapore;
    PAPER: 186/Corrosion/Regular (Oral)
    SCHEDULED: 12:45/Mon. 28 Nov. 2022/Andaman 2



    ABSTRACT:
    Thin-film corrosion is a severe issue in almost every sector. Thus, corrosion simulation under thin electrolyte films has always been of high interest as experimental studies are often challenging. For microbial corrosion, the existence of a biofilm on the metal surface impacts corrosive species' production and transportation, which is yet understood poorly. Therefore, the present corrosion models are risk-based and meant for ranking potential threats to the industrial assets, rather than trying to quantify those threats. Thus far, especially for atmospheric corrosion, progress has been made to model the effect of several essential factors on thin-film corrosion rates. Some of these parameters are electrolyte thickness, electrolyte composition, chemical reactions in the electrolyte, electrode size and change in electrode size, environmental parameters, and corrosion product deposition. However, these parameters are mainly drawn from different studies and have not been modelled concurrently in a single simulation study, making the thin film corrosion model far from being complete yet. Our research aims to resolve the problems mentioned above by employing finite element analysis using the corrosion module of COMSOL Multiphysics software. We have developed a multi-species multi-reaction moving boundary (MSMRMB) model, which not only provides flexibility for modelling altering corrosive environments but can quantify the corrosion rate. Quantification of corrosion rate will enable the industries to apply fitness for service (FFS) to the corroded pressure vessels based on the maximum pit size, operating pressure, lifetime, etc. We are aware that there is a long way to achieve a complete model, but our developed MSMRMB model is promising for this journey.

    References:
    [1] M. Saeedikhani and DJ. Blackwood, Corros. Mater. Degrad. 2020, 1(2), 273-281
    [2] M. Saeedikhani et al. J. Electrochem. Soc. 2020, 167, 041503
    [3] M. Saeedikhani et al. Corros. Sci. 2020, 163, 108296