1992
DOI: 10.1016/0022-3115(92)90367-t
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Modeling pitting corrosion damage of high-level radioactive-waste containers using a stochastic approach

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Cited by 24 publications
(26 citation statements)
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“…In previous models, these permanent pits were assumed to grow an increment in depth during each simulated time step only if a random number, 0 5 R < 1, is less than the growth probability where 0 I y I 1. This approach led to the time evolution of a distribution of pit depths [3]. However, these distributions did not exhibit the positive skew frequently observed experimentally [4-71, in which the majority of pits have small depths and a long "tail" to the distribution exists at large depths.…”
Section: Modeling Approachmentioning
confidence: 91%
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“…In previous models, these permanent pits were assumed to grow an increment in depth during each simulated time step only if a random number, 0 5 R < 1, is less than the growth probability where 0 I y I 1. This approach led to the time evolution of a distribution of pit depths [3]. However, these distributions did not exhibit the positive skew frequently observed experimentally [4-71, in which the majority of pits have small depths and a long "tail" to the distribution exists at large depths.…”
Section: Modeling Approachmentioning
confidence: 91%
“…Following earlier work [3], Monte Carlo computer codes have been used to simulate the apparently random initiation of permanent pits on a unit surface area of metal in contact with an aggressive environment. In previous models, these permanent pits were assumed to grow an increment in depth during each simulated time step only if a random number, 0 5 R < 1, is less than the growth probability where 0 I y I 1.…”
Section: Modeling Approachmentioning
confidence: 99%
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