2013
DOI: 10.1155/2013/108386
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Markov Chain Models for the Stochastic Modeling of Pitting Corrosion

Abstract: The stochastic nature of pitting corrosion of metallic structures has been widely recognized. It is assumed that this kind of deterioration retains no memory of the past, so only the current state of the damage influences its future development. This characteristic allows pitting corrosion to be categorized as a Markov process. In this paper, two different models of pitting corrosion, developed using Markov chains, are presented. Firstly, a continuous-time, nonhomogeneous linear growth (pure birth) Markov proc… Show more

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Cited by 62 publications
(46 citation statements)
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References 26 publications
(102 reference statements)
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“…where N represents the number of states the pipeline wall is divided, Pi(t) is the probability that the pit depth is at i th state at time t and can be determined by measuring the pit depth distribution at such a time or by expert knowledge [1,8 ].…”
Section: Finite Markov Chain Modelling Of Internal Pitting Corrosion mentioning
confidence: 99%
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“…where N represents the number of states the pipeline wall is divided, Pi(t) is the probability that the pit depth is at i th state at time t and can be determined by measuring the pit depth distribution at such a time or by expert knowledge [1,8 ].…”
Section: Finite Markov Chain Modelling Of Internal Pitting Corrosion mentioning
confidence: 99%
“…Manipulating Equation (14) will give the Kolmogorov forward and backward equations, however, for a continuous time non-homogenous linear growth Markov process which the pit depth is assumed to follow in this research, the probability that a process at state i will be in state j for j≥i at a later time follows Kolmogorov forward equation shown in Equation (15) [1,8,13].…”
Section: Figure 2: Graphical Representation Of Chapman-kolmogorov Equmentioning
confidence: 99%
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