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Pitting corrosion as a mixed system: coupled deterministic-probabilistic simulation of pit growth

机译:点腐蚀作为混合系统:耦合确定性 - 概率模拟坑生长

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Stochastic behavior of pitting corrosion poses a unique challenge in its computational analysis. However, it also stems from electrochemical activity causing general corrosion. In this paper, a framework for corrosion pit growth simulation based on the coupling of the Cellular Automaton (CA) and Boundary Element Methods (BEM) is presented. The framework assumes that pitting corrosion is controlled by electrochemical activity inside the pit cavity. The BEM provides the prediction of electrochemical activity given the geometrical data and polarization curves, while the CA is used to simulate the evolution of pit shapes based on electrochemical activity provided by BEM. To demonstrate the methodology, a sample case of local corrosion cells formed in pitting corrosion with varied dimensions and polarization functions is considered. Results show certain shapes tend to grow in certain types of environments. Some pit shapes appear to pose a higher risk by being potentially significant stress raisers or potentially increasing the rate of corrosion under the surface. Furthermore, these pits are comparable to commonly observed pit shapes in general corrosion environments.
机译:点腐蚀的随机行为在其计算分析中提出了独特的挑战。然而,它还源于导致一般腐蚀的电化学活性。本文提出了一种基于蜂窝自动机(CA)和边界元方法(BEM)的耦合的腐蚀坑生长模拟框架。该框架假设蚀腐蚀由凹坑腔内的电化学活性控制。 BEM提供给定几何数据和偏振曲线的电化学活动预测,而CA用于模拟基于BEM提供的电化学活动的凹坑形状的演变。为了证明该方法,考虑了在具有变化尺寸和偏振函数的点腐蚀中形成的局部腐蚀细胞的样本情况。结果显示某些形状倾向于在某些类型的环境中生长。一些凹坑形状似乎通过潜在的显着的应力提升器构成更高的风险或可能增加表面下的腐蚀速率。此外,这些凹​​坑与一般腐蚀环境中的常见观察到的凹坑形状相当。

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