Abstract Corrosion is a major cause of durability deterioration for reinforced concrete (RC) structures. This paper investigated the random evolution process of corrosion in steel bars under a constant corrosion current density. A probabilistic prediction model was developed combining a continuous-time Markov chain model with the Faraday law. The model parameter, state interval, which represents the difference between the actual adjacent corrosion depths, was calibrated by test data and statistically studied. Markov model predicted results showed that the corrosion depth followed the Poisson distribution while the longitudinal nonuniformity factor of corroded steel bars R, which was defined as the ratio of the average cross-sectional area to the minimum one, followed the Gumbel distribution. The probability distribution parameters of the factor R were determined by Monte-Carlo simulation. The corrosion depth and the factor R predicted by the Markov model agreed well with the experimental data.

中文翻译：

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基于马尔可夫链模型的钢筋混凝土结构钢筋腐蚀演化

摘要 腐蚀是钢筋混凝土（RC）结构耐久性下降的主要原因。研究了恒定腐蚀电流密度下钢筋锈蚀的随机演化过程。结合连续时间马尔可夫链模型和法拉第定律开发了概率预测模型。模型参数状态区间代表实际相邻腐蚀深度之间的差异，通过测试数据进行校准和统计研究。马尔可夫模型预测结果表明，腐蚀深度服从泊松分布，而被腐蚀钢筋纵向不均匀系数R（定义为平均截面积与最小截面积的比值）服从Gumbel分布。因子R的概率分布参数由蒙特卡罗模拟确定。马尔可夫模型预测的腐蚀深度和因子R与实验数据吻合较好。