TY - JOUR
T1 - Stochastic modeling of pitting corrosion in underground pipelines using Markov chains
AU - Velázquez, J. C.
AU - Caleyo, F.
AU - Valor, A.
AU - Hallen, J. M.
AU - Araujo, J. E.
N1 - Publisher Copyright:
Copyright 2009, Brazilian Petroleum, Gas and Biofuels Institute - IBP.
PY - 2009
Y1 - 2009
N2 - A non-homogenous, linear growth (pure birth) Markov process, with discrete states in continuous time, has been used to model external pitting corrosion in underground pipelines. The transition probability function for the pit depth is obtained from the analytical solution of the forward Kolmogorov equations for this process. The parameters of the transition probability function between depth states can be identified from the observed time evolution of the mean of the pit depth distribution. Monte Carlo simulations were used to predict the time evolution of the mean value of the pit depth distribution in soils with different physicochemical characteristics. The simulated distributions have been used to create an empirical Markov-chain-based stochastic model for predicting the evolution of pitting corrosion from the observed properties of the soil in contact with the pipeline. Real-life case studies, involving simulated and measured pit depth distributions are presented to illustrate the application of the proposed Markov chains model.
AB - A non-homogenous, linear growth (pure birth) Markov process, with discrete states in continuous time, has been used to model external pitting corrosion in underground pipelines. The transition probability function for the pit depth is obtained from the analytical solution of the forward Kolmogorov equations for this process. The parameters of the transition probability function between depth states can be identified from the observed time evolution of the mean of the pit depth distribution. Monte Carlo simulations were used to predict the time evolution of the mean value of the pit depth distribution in soils with different physicochemical characteristics. The simulated distributions have been used to create an empirical Markov-chain-based stochastic model for predicting the evolution of pitting corrosion from the observed properties of the soil in contact with the pipeline. Real-life case studies, involving simulated and measured pit depth distributions are presented to illustrate the application of the proposed Markov chains model.
UR - http://www.scopus.com/inward/record.url?scp=85044635254&partnerID=8YFLogxK
M3 - Artículo de la conferencia
AN - SCOPUS:85044635254
SN - 2447-2069
VL - 2009-September
JO - Rio Pipeline Conference and Exposition, Technical Papers
JF - Rio Pipeline Conference and Exposition, Technical Papers
T2 - 2009 Rio Pipeline Conference and Exposition
Y2 - 22 September 2009 through 24 September 2009
ER -