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 hal.structure.identifier
JARRAH, Adil
211915 Mechanics surfaces and materials processing [MSMP]
dc.contributor.authorBIGERELLE, Maxence
dc.contributor.author
 hal.structure.identifier
GUILLEMOT, Gildas
1252 Laboratoire de Mécanique de Lille - FRE 3723 [LML]
dc.contributor.author
 hal.structure.identifier
NAJJAR, Denis
1252 Laboratoire de Mécanique de Lille - FRE 3723 [LML]
dc.contributor.author
 hal.structure.identifier
IOST, Alain
1252 Laboratoire de Mécanique de Lille - FRE 3723 [LML]
dc.contributor.authorNIANGA, Jean-Marie
dc.date.accessioned2015
dc.date.available2016
dc.date.issued2011
dc.date.submitted2015
dc.identifier.issn0010-938X
dc.identifier.urihttp://hdl.handle.net/10985/9626
dc.descriptionThe authors would like to thank V. Hague for her help in English.
dc.description.abstractThis paper outlines a new methodology to predict accurately the maximum pit depth related to a localized corrosion process. It combines two statistical methods: the Generalized Lambda Distribution (GLD), to determine a model of distribution fitting with the experimental frequency distribution of depths, and the Computer Based Bootstrap Method (CBBM), to generate simulated distributions equivalent to the experimental one. In comparison with conventionally established statistical methods that are restricted to the use of inferred distributions constrained by specific mathematical assumptions, the major advantage of the methodology presented in this paper is that both the GLD and the CBBM enable a statistical treatment of the experimental data without making any preconceived choice neither on the unknown theoretical parent underlying distribution of pit depth which characterizes the global corrosion phenomenon nor on the unknown associated theoretical extreme value distribution which characterizes the deepest pits. Considering an experimental distribution of depths of pits produced on an aluminium sample, estimations of maximum pit depth using a GLD model are compared to similar estimations based on usual Gumbel and Generalized Extreme Value (GEV) methods proposed in the corrosion engineering literature. The GLD approach is shown having smaller bias and dispersion in the estimation of the maximum pit depth than the Gumbel approach both for its realization and mean. This leads to comparing the GLD approach to the GEV one. The former is shown to be relevant and its advantages are discussed compared to previous methods.
dc.language.isoen
dc.publisherElsevier
dc.rightsPost-print
dc.subjectAluminium; Modelling studies; Pitting corrosion
dc.titleA generic statistical methodology to predict the maximum pit depth of a localized corrosion process
ensam.embargo.terms1 Year
dc.identifier.doi10.1016/j.corsci.2011.03.026
dc.typdocArticle dans une revue avec comité de lecture
dc.localisationCentre de Lille
dc.subject.halChimie: Matériaux
dc.subject.halSciences de l'ingénieur: Matériaux
dc.subject.halSciences de l'ingénieur: Mécanique: Mécanique des matériaux
ensam.audienceInternationale
ensam.page2453-2467
ensam.journalCorrosion Science
ensam.volume53
ensam.issue8
hal.identifierhal-01167104
hal.version1
hal.statusaccept


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