A Study on Stochastic Models for Localized Corrosion

对于不锈钢等耐腐蚀材料，已知一半以上的腐蚀失效是由局部腐蚀引起的。众所周知，局部腐蚀数据在空间或时间上表现出广泛的分散性，即统计和概率变化。为了更可靠地评估各种结构材料的失效寿命，需要对局部腐蚀的统计和概率特性进行更深入的研究，本文对已有的点蚀生灭随机模型进行了改进，并在此基础上采用Monte Carlo模拟方法对实际点蚀形成过程进行了模拟。模拟的点蚀电位和点蚀产生的诱导时间的分布与实验观察到的分布进行了比较，以建立该模型的置信度。出生和死亡随机模型的基本假设如下： 关于我们 如下所示：1）凹坑的产生服从泊松随机过程，凹坑产生时间服从指数概率分布，对应于凹坑产生率的跃迁概率由势函数给出。2)孔核的大小随时间的增加而增加，其比例常数与电位成指数关系。3)在某一临界尺寸以下，由于再钝化，纹孔核的生长将停止。纹孔核的死亡过程也服从Poisson过程，因此到死亡为止的寿命分布规律也服从指数概率规律。4)基于上述模型和假设，MonteCarlo模拟结果表明：1）点蚀电位的分布服从一级近似正态概率分布; 2)点蚀电位中值与电位扫描速度的平方根成正比。3)蚀坑产生的诱导时间的概率分布服从畸变分布。发现上述结果以高置信度模拟了实验中观察到的结果。在此基础上，分析了非晶合金热处理再结晶引起的异质性增加。少

For corrosion resistant materials such as stainless steels, more than half cases of corrosion failure had been known to be caused by localized corrosion. It is well known that data of localized corrosion show wide scatter in space or in time, namely statistical and probabilistic variations. For this reason, statistical and probabilistic nature of localized corrosion shckild be studied in more detail in order to evaluate failure life of materials for various structures with more confidence.This study aims to refine the birth and death stochastic model of pitting corrosion which had been proposed previously and to simulate the actual pit foreation process by using Monte Carlo similation based on the proposed model. Simulated distributions of pitting potential and induction time for pit generation were compared with the observed distributions by the experiments in order to establish the confidence of the proposed model. The basic assumptions for the birth and death stochastic model are as … More follows: 1) Pit generation obeys a Posson stochastic process, so that the distribution of pit senation time follows exponential probability distribution.Transition probability corresponding to the pit generation rate is given by a function of potential. 2) The size of pit nucleus increases with time and the proportional constant of the rate law is expressed as an exponential function of potential. 3) Below a critical size, the growth of pit nucleus will stop due to repassivation. Death process of pit nucleus obeys also Poisson process, so that the distribution law for life time until death follows also exponential probability law. 4) Large pit which grows over a critical size will not die and continue to grow.Based on the above model and assumptions, Monte Carlo simulation provided the following results: 1) The distribution of pitting potential obeys normal probability distribution as a first approximation. 2) Median of pitting potential is proportional to the square root of potential sweep velocity. 3) The probability distribution of induction time for pit generation obeys distorted distribution. The above results were found to simulate the results observed in the experiments with a high confidence. Increase in heterogenuity due to recrystalization of amorphous alloys by heat treatment was analyzed based on the model. Less