Numerical simulations of corrosion processes. Properties of the corrosion front and formation of islands
Using a one-parameter model and a cellular automaton description we investigate the formation of a cavity in a material for which a small area has been deprotected and put in contact with an aggressive environment. Corrosion processes take place in a medium where the diffusion is assumed to be v...
Збережено в:
Дата: | 2004 |
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Автори: | , , , |
Формат: | Стаття |
Мова: | English |
Опубліковано: |
Інститут фізики конденсованих систем НАН України
2004
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Назва видання: | Condensed Matter Physics |
Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/119014 |
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Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
Цитувати: | Numerical simulations of corrosion processes. Properties of the corrosion front and formation of islands / C. Vautrin-Ul, A. Chausse, J. Stafiej, J.P. Badiali // Condensed Matter Physics. — 2004. — Т. 7, № 4(40). — С. 813–828. — Бібліогр.: 16 назв. — англ. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of UkraineРезюме: | Using a one-parameter model and a cellular automaton description we investigate
the formation of a cavity in a material for which a small area has
been deprotected and put in contact with an aggressive environment. Corrosion
processes take place in a medium where the diffusion is assumed
to be very rapid. We investigate the mean size of the cavity, the roughness
of the corrosion front, the chemical composition of the front and the formation
of islands resulting from the detachment of pieces of material. For the
simulation times that we have investigated, a stationary regime is observed
in which the relative composition of the front and the roughness become
constant. An increase of the roughness produces the islands which leads
to a smoothing of the front, and thus the roughness exhibits a maximum
value. A mean field approach quite satisfactoryly reproduces the combination
of processes involved in the corrosion model. Although we consider a
one-parameter model, some results such as the value of roughness and its
maximum are difficult to predict in a quantitative way. |
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