Modeling Based on Markov Chains for the Evolution of Pitting Corrosion in Buried Pipelines Carrying Gas

Abstract

An stochastic model based on Markov chains is presented in order to predict the time evolution of pitting depth distributions, as sign of corrosion suffered by pipelines carrying gas. The main obtained results allow estimating the lifetime of pipelines in service, achieving in this manner to optimize the maintenance times and costs.

Predicting the risk of pitting corrosion initiation of stainless steels using a Markov chain model

“…Almost a century ago, Mears and Evans introduced the concept of “probability of corrosion” and emphasized the practical importance of a statistical assessment of corrosion. From the late 1970s, the better understanding of localized corrosion phenomena led to a more detailed study of the stochastic aspects of pitting corrosion, with the application of probabilistic models to the analysis of both pit initiation and propagation . Shibata provided an important contribution, with a review of successful applications of statistical approaches to localized corrosion data.…”

“…Shibata provided an important contribution, with a review of successful applications of statistical approaches to localized corrosion data. Mathematical models were applied . An example is the use of extreme value statistics to pit depth measurements in order to estimate the service life of corroding structures .…”

“…In this work, a probabilistic model based on Markov chain for the assessment of pitting and crevice corrosion of stainless steels is presented. It is well known that the Markov chain‐based model had found some applications in the description of pit propagation and evolution in time . Nevertheless, it can be used to predict corrosion initiation, considered by the authors of major importance in engineering applications where, in most of the cases, it is practically the design life of the component.…”