51314-4091-Probabilistic Model Based on Markov Chain for the Assessment of Localized Corrosion of Stainless Steels

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Product Number: 51314-4091-SG

ISBN: 4091 2014 CP

Author: Andrea Brenna

Publication Date: 2014

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Localized corrosion of stainless steels is the main concern in industrial applications. Pitting crevice and stress corrosion cracking in chloride-containing solutions are common corrosion forms which must be accurately avoided. Localized corrosion generally takes place in corrosion cells with clearly separated anode and cathode surfaces so that it results in worse damage than uniform corrosion because it can lead to perforation in a very short period of time (high corrosion rate). Generally pitting and crevice susceptibility depends on a variety of factors associated with the metal (chemical composition differences in the metallurgical structure presence of heterogeneities) the environment (chlorides content differential aeration pH temperature) and the geometry on the system (presence of crevices discontinuities). It follows that localized corrosion events due to their unpredictable occurrence cannot be explained without using a proper statistical method.The aim of this research is to carry out laboratory tests to validate a probabilistic model based on a Markov chain approach for the assessment of localized corrosion of stainless steels. A Markov chain is a mathematical system used to describe a stochastic process that undergoes transitions from one state to another through a finite number of possible states. It is a random process usually characterized as “memory-less”: the next state depends only on the current state and not on the sequence of events that preceded it. Formally a Markov chain is characterized by a set of states and parameters and a transition probability function. The model lets to take into account steel composition (expressed by PREN index) and various operating parameters such as pH of the environment temperature chlorides content and the oxidizing power in order to assess localized corrosion occurrence.