2011
DOI: 10.1016/j.electacta.2010.10.025
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Multiscale modelling of the corrosion of metals under atmospheric corrosion

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Cited by 71 publications
(34 citation statements)
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“…Díaz and López 6 developed a deterministic model for the damage function of carbon steel expressed in terms of corrosion penetration as a function of environmental variables using an Artificial Neural Network (ANN) to fit the data. Cole et al 7 describe a multiscale (from global to micron) model for the prediction of atmospheric corrosion of zinc. The model is able to predict corrosion rates of metal components to enable appropriate material selection and to determine how microstructure and oxide development influence corrosion rates.…”
mentioning
confidence: 99%
“…Díaz and López 6 developed a deterministic model for the damage function of carbon steel expressed in terms of corrosion penetration as a function of environmental variables using an Artificial Neural Network (ANN) to fit the data. Cole et al 7 describe a multiscale (from global to micron) model for the prediction of atmospheric corrosion of zinc. The model is able to predict corrosion rates of metal components to enable appropriate material selection and to determine how microstructure and oxide development influence corrosion rates.…”
mentioning
confidence: 99%
“…For larger droplets, a second spreading effect occurred around the salt droplets, 24 indicating a relatively strong cathodic activity caused by the Evans effect. 61 The central area served as anode (equation 4) while the secondary spreading area served as cathode (equation 3). 24,35,62 Zn → Zn 2+ + 2e…”
Section: Resultsmentioning
confidence: 99%
“…Dealing with corrosion, several holistic multiscale models have been developed linking the behaviour of a given structure to the one of the surfaces involved in the corrosion processes (Cole et al 2011;Cole and Hughes 2014). Inspired from these approaches, models dealing with different kinds of alteration processes could try to describe and predict the behaviour of materials encountered in Cultural Heritage.…”
Section: Analyses At Nanometer Scalementioning
confidence: 99%