Abstract
Pitting, crevice and stress corrosion cracking are the most damaging corrosion forms of stainless steels in industrial applications. Generally, pitting and crevice susceptibility depends on a variety of factors related to the metal (chemical composition, differences in the metallurgical structure, inclusions), the environment (chloride content, pH, temperature, differential aeration) and the geometry of the system. Due to their unpredictable occurrence, localized corrosion events cannot be explained without using a proper statistical method. In this work a probabilistic approach based on Markov chains for the assessment of pitting and crevice corrosion initiation is proposed. A Markov chain is a stochastic process that undergoes transitions from one state to another through a finite number of possible states, until a so-called "absorbing state” from which the system has no tendency to evolve is attained. Formally, a Markov chain is characterized by a set of states and a transition probability matrix. The model calculates the probability to have pitting (and vice versa to maintain a stable passive condition) involving a large number of operating parameters related to both metal and environment. Experimental tests were carried out to validate the model which requires more accurate investigations.
