TY - JOUR
T1 - Stochastic modeling of pitting corrosion
T2 - A new model for initiation and growth of multiple corrosion pits
AU - Valor, A.
AU - Caleyo, F.
AU - Alfonso, L.
AU - Rivas, D.
AU - Hallen, J. M.
PY - 2007/2
Y1 - 2007/2
N2 - In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.
AB - In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.
KW - B. Modelling studies
KW - C. Pitting corrosion
UR - http://www.scopus.com/inward/record.url?scp=33751423132&partnerID=8YFLogxK
U2 - 10.1016/j.corsci.2006.05.049
DO - 10.1016/j.corsci.2006.05.049
M3 - Artículo
SN - 0010-938X
VL - 49
SP - 559
EP - 579
JO - Corrosion Science
JF - Corrosion Science
IS - 2
ER -