Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

Valor, A.; Caleyo, F.; Alfonso, L.; Rivas, D.; Hallen, J.M.

doi:10.1016/j.corsci.2006.05.049

Cited by 223 publications

(95 citation statements)

References 30 publications

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“…Although the work produced better results than those obtained from available literature (see ref [21]), however, the assumption that the entire pits tested nucleates instantaneously may not always be the case practically.…”

Section: Introductioncontrasting

confidence: 51%

“…Rivas et al [3] used block maxima and peak over threshold approach for extreme value analysis of laboratory simulated field data of buried carbon steel pipeline and concluded that the peak over threshold approach was more robust in estimating the maximum pit depth of the samples. In their own work, Valor et al [21] described pit initiation and propagation as a stochastic process of non-homogenous Poisson process and non-homogenous continuous time Markov process respectively.…”

Section: Introductionmentioning

confidence: 99%

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Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines

Ossai

Boswell

Davies

2016

Engineering Failure Analysis

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A continuous time non-homogenous linear growth pure birth Markov model was used to predict the future pit depth distribution of internally corroded oil and gas pipelines. A negative binomial distribution was used for calculating the transition probability functions of the pit depths whilst pit depths growth was estimated for low, moderate, high and severe pitting corrosion rates using field measured data of pit depths, temperatures, CO2 partial pressures, pH and flow rates. The Markov predicted results agreed well with field measured pit depth data from X52 grade pipeline and L-80 and N-80 grades offshore well tubing.

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Section: Introductioncontrasting

confidence: 51%

Section: Introductionmentioning

confidence: 99%

Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines

Ossai

Boswell

Davies

2016

Engineering Failure Analysis

View full text Add to dashboard Cite

show abstract

“…It is worth noting that methodologies based on extreme value theory suppose that pit process has the property of homogeneity in law and that it requires occurring with the same frequency in time and space. However, it is acknowledged that pitting corrosion is a stochastic process mainly related to its initiation stage [17]. Furthermore, preliminary hypotheses related to homogeneity are difficult to verify before applying the extreme value methodologies.…”

Section: Introductionmentioning

confidence: 99%

“…In literature, the most common method for safety or reliability was found in the application of the statistical extreme value analysis using the Gumbel methodology to predict the maximum pit depth that will be found in a large scale installation by using a small number of samples with a small area [1][2][3][4][5][6][11][12][13][14]17,18]. This methodology is based on the estimation of the two parameters of the Gumbel distribution.…”

Section: Introductionmentioning

confidence: 99%

A generic statistical methodology to predict the maximum pit depth of a localized corrosion process

et al. 2011

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This paper outlines a new methodology to predict accurately the maximum pit depth related to a localized corrosion process. It combines two statistical methods: the Generalized Lambda Distribution (GLD), to determine a model of distribution fitting with the experimental frequency distribution of depths, and the Computer Based Bootstrap Method (CBBM), to generate simulated distributions equivalent to the experimental one. In comparison with conventionally established statistical methods that are restricted to the use of inferred distributions constrained by specific mathematical assumptions, the major advantage of the methodology presented in this paper is that both the GLD and the CBBM enable a statistical treatment of the experimental data without making any preconceived choice neither on the unknown theoretical parent underlying distribution of pit depth which characterizes the global corrosion phenomenon nor on the unknown associated theoretical extreme value distribution which characterizes the deepest pits.Considering an experimental distribution of depths of pits produced on an aluminium sample, estimations of maximum pit depth using a GLD model are compared to similar estimations based on usual Gumbel and Generalized Extreme Value (GEV) methods proposed in the corrosion engineering literature. The GLD approach is shown having smaller bias and dispersion in the estimation of the maximum pit depth than the Gumbel approach both for its realization and mean. This leads to comparing the GLD approach to the GEV one. The former is shown to be relevant and its advantages are discussed compared to previous methods.

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“…Turnbull et al (2006a;2006b) proposed a mathematical model to simulate the evolution of corrosion pits and the transition from corrosion pits to stress corrosion cracks. Valor et al (2007) established a stochastic model of pitting corrosion to depict corrosion pit initiation and growth.…”

Section: Introductionmentioning

confidence: 99%

3D analysis for pit evolution and pit-to-crack transition during corrosion fatigue

Huang

2013

J. Zhejiang Univ. Sci. A

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This paper presents a deterministic model to predict the pit evolving morphology and crack initiation life of corrosion fatigue. Based on the semi-ellipsoidal pit assumption, the thermodynamic potential including elastic energy, surface energy and electrochemical energy of the cyclically stressed solid with an evolving pit is established, from which specific parameters that control the pit evolution are introduced and their influence on the pit evolution are evaluated. The critical pit size for crack nucleation is obtained from stress intensity factor criterion and the crack nucleation life is evaluated by Faraday's law. Meanwhile, this paper presents a numerical example to verify the proposed model and investigate the influence of cyclic load on the corrosion fatigue crack nucleation life. The corrosion pit appears approximately as a hemisphere in its early formation, and it gradually transits from semicircle to ellipsoid. The strain energy accelerates the morphology evolution of the pit, while the surface energy decelerates it. The higher the stress amplitude is, the smaller the critical pit size is and the shorter the crack initiation life is.

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Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

Cited by 223 publications

References 30 publications

Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines

Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines

A generic statistical methodology to predict the maximum pit depth of a localized corrosion process

3D analysis for pit evolution and pit-to-crack transition during corrosion fatigue

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