The probability distributions of external-corrosion pit depth and pit growth rate were investigated in underground pipelines using Monte Carlo simulations. The investigation is based on a field study recently reported by the authors, from which a non-linear, multivariate predictive model for maximum pit depth in underground pipelines was proposed (Corrosion 65(2009)pp. 332-342). The study combines a predictive pit growth model developed by the authors with the observed distributions of the model variables in a range of soils. Depending on the pipeline age, any of the three maximal extreme value distributions, i.e. Weibull, Frechet or Gumbel, can arise as the best fit to the pitting depth and rate data. The Frechet distribution best fits the corrosion data for long exposure periods. This can be explained by considering the long-term stabilization of the diffusion-controlled pit growth. The findings of the study provide reliability analysts with accurate information regarding the stochastic characteristics of the pitting damage in underground pipelines.
Probability distribution of pitting corrosion depth and rate in underground pipelines: A Monte Carlo study
Wahrscheinlichkeitsverteilung von Lochkorrosionstiefe und Lochkorrosionsgeschwindigkeit an erdverlegten Rohrleitungen: Eine Monte-Carlo-Methode
Corrosion Science ; 51 , 9 ; 1925-1934
2009
10 Seiten, 9 Bilder, 7 Tabellen, 31 Quellen
Aufsatz (Zeitschrift)
Englisch
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