The Butler-Volmer equation for surface electrochemistry potential and Laplace equation for electrolyte solutions have been available in CFD code for a while, but the challenge remains to find a numerically affordable way to model the mass-transfer-limited corrosion rates. Mass-transfer coefficient using the Sherwood number (Nesic et al., Corr Sci., 1996) approach seems promising, but it is limited by the use of average pipe velocity values, which is unable to differentiate local flow changes in geometries like pipe bend and welding locations. Conventional methods use the wall shear stress as the surface mass transfer parameter, but it was found that the shear stress is a strong function of flow velocity and the resulted corrosion rates are too sensitive to velocity changes. A consistent rate-limiting expression cannot be found even for flows in a straight pipe. A better method is proposed to use the mass-transfer coefficients as the limiting mechanism for corrosion. However, the mass-transfer coefficient can be expressed in various forms and their values can be sensitive to boundary layer thickness. It was found that by using the scalable wall function model it is possible to have a consistent rate-limiting formulation for corrosion rates. The comparison to experimental results [Zhang et al. Corr. Sci., 2013] showed that the hybrid model can predict the corrosion rate with reasonable accuracy. This method effectively addresses the drawbacks of the Sherwood number approach, and avoids the costly computation needed to accurately predict the wall shear stress. Further validations with the experimental data by Nesic et al. [1996] were also satisfactory demonstrating the validity of the mass-transfer limited approach. However, it should be noted that wall shear stress and mass transfer may have different impacts on the types of corrosion chemistry involved depending on how the mechanism of surface chemistry alters the metal morphology.
Reference
Nesic et al., Corrosion Science 52, pp. 280-, (1996).
Zhang et al., Corrosion Science 77, pp. 334-, (2013).
