@misc{giegen_enhanced_predictive_2019, author={Gießgen, T., Mittelbach, A., Höche, D., Zheludkevich, M., Kainer, K.}, title={Enhanced predictive corrosion modeling with implicit corrosion products}, year={2019}, howpublished = {journal article}, doi = {https://doi.org/10.1002/maco.201911101}, abstract = {An advanced mathematical approach to describe the influence of corrosion products on the corrosion rate is presented here. The related model can be used as input equation for numerical predictive corrosion simulations or simply as an empirical model, to extrapolate experimental data of corrosion tests to longer times and to interpret the physical parameters behind. This semiempirical model assumes that a constant share of the dissolved metal precipitates on the surface and hinders the diffusion processes. Hence, the effective corrosion rate decreases exponentially with increasing dissolution. The explicit corrosion progress over time is derived by time integration on a newly developed, time dependent corrosion rate equation. The derived expression can be effortlessly implemented in existing for example finite element method, which is demonstrated for the uniform corrosion of a zinc surface. Furthermore, this approach is qualitatively compared with other empirical models for corrosion products and the validity is demonstrated by fitting of experimental data. A very good agreement between experiment and theory can be achieved for various materials and environments considering no change of the driving corrosion mechanism.}, note = {Online available at: \url{https://doi.org/10.1002/maco.201911101} (DOI). Gießgen, T.; Mittelbach, A.; Höche, D.; Zheludkevich, M.; Kainer, K.: Enhanced predictive corrosion modeling with implicit corrosion products. Materials and Corrosion. 2019. vol. 70, no. 12, 2247-2255. DOI: 10.1002/maco.201911101}}