Stochastic Modeling of the Influence of Environment on Pitting Corrosion Damage of Radioactive-Waste Containers

Abstract

Thisisa preprintof a paper intended forpublication ina jonmalorpmceedinga Since changes may be made before publication, this preprint is made available with the understanding that it will not be cited or reproduced without the permission of the author. ABSTRACTA physically-based, phenomenological stochastic model for pit initiation and growth is presented as a potential tool for predicting the degradation of high-level radioactive-waste containers by aqueous pitting corrosion. Included in the model are simple phenomenological equations describing the dependence of the controlling stochastic parameters on the applied (or corrosion) potential, chloride ion concentration, and absolute temperature. Results from this model are presented that demonstrate its ability to simulate several important environmental effects on pitting.

Review of the Modelling of Corrosion Processes and Lifetime Prediction for HLW/SF Containers—Part 1: Process Models

“…Pitting of passive alloys [109][110][111] Addresses variability and uncertainty inherent to localised corrosion. Lack of mechanistic basis.…”

“…Henshall [109][110][111] described a stochastic-based model for predicting the initiation and growth of pits for the YMP, but the approach is broadly applicable to any container material in any type of repository. The probability of pit initiation and stifling, of pit growth and the resulting distribution in pit depths can all be predicted based on this stochastic treatment, provided there is suitable empirical input data.…”

Engineered materials characterization report, volume 3 - corrosion data and modeling update for viability assessments

“…Several pitting models have been reviewed in detail by Farmer (Farmer, 1991). Those for pit initiation include the halide nuclei theory by Okada (Okada, 1984b(Okada, , 1984a; the point-defect model by Chao, Lin, and McDonald (Chao, Lin, and McDonald, 1980, the electrostriction model by Sato (Sate, 1971), and the stochastic probability model by Shibata (Shibata andTakeyama, 1977, Shibata, 1996) Models for pit propagation include the Pickering-Frankenthal model (Pickering and Frankenthal, 1972), which assumes passive walls and an active base, the Galvele modification of the l'ickeringFranker&al model (Galvele, 1976), which accounts for the effects of metal ion hydrolysis on pH suppression, and the Beck-Alkire model, which deals with a hemispherical pit covered by a thin, resistive halide film (Beck and Alkire, 1979) Henshall was the first to apply 2.8 Corrosion Model Development probabilistic pitting models to the performance assessment of high-level waste containers (Henshall, 1992(Henshall, ,1994…”

“…A probabilistic model has been developed for pitting of the Cl&l in the harsh crevice environment (Farmer, 1997, Farmer and This model divides the container surface into a two-dimensional (2D) array of hypothetical cells, where probabilities for the transition from one pitting state to another can be assigned As described by Shibata W.ibata andTakeyama, 1977, Shibata, 1996), nucleation or death of a pit embryo is determined by comparing random numbers to an environment-dependent birth or death probability, respectively Random numbers are generated by a power residue method After a pit embryo reaches a critical age, it is assumed to become a stable pit This approach has already been explored for modeling pit initiation and growth on high-level waste containers by Henshall (Henshall, 1992(Henshall, ,1994(Henshall, ,1996a. However, the approach employed by Henshall required additional work to enable it to deal with important environmental parameters, such as pH Furthermore, that approach used functions for calculating the birth and death probabilities could have values much greater than unity (>>l), though the code limited the values to one (Cl) It is better to use probability expressions where all calculated values lie between zero and one, as done by Shibata.…”

Yucca Mountain project canister material corrosion studies as applied to the electrometallurgical treatment metallic waste form

“…Yet, much quantitative validation of these models remains, in particular, "the determination of the pit depth distribution as a function of time and potential repository environment." Stochastic models have been presented that simulate the effects of electrochemical potential, chloride ion concentration, and temperature on the aqueous pitting corrosion behavior of container materials [69]. Also, stochastic models have been constructed to simulate waste package degradation.…”