• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Laboratoire Mechanics, Surfaces and Materials Processing (MSMP)
  • View Item
  • Home
  • Laboratoire Mechanics, Surfaces and Materials Processing (MSMP)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Corrosion pit depth extreme value prediction from limited inspection data

Communication avec acte
Author
NAJJAR, Denis
11230 Laboratoire de Métallurgie Physique et Génie des Matériaux [LMPGM]
BIGERELLE, Maxence
11230 Laboratoire de Métallurgie Physique et Génie des Matériaux [LMPGM]
BOURDEAUX, Laurent
GUILLOU, Delphine
IOST, Alain
11230 Laboratoire de Métallurgie Physique et Génie des Matériaux [LMPGM]

URI
http://hdl.handle.net/10985/10821
Date
2004

Abstract

Passive alloys like stainless steels are prone to localized corrosion in chlorides containing environments. The greater the depth of the localized corrosion phenomenon, the more dramatic the related damage that can lead to a structure weakening by fast perforation. In practical situations, because measurements are time consuming and expensive, the challenge is usually to predict the maximum pit depth that could be found in a large scale installation from the processing of a limited inspection data. As far as the parent distribution of pit depths is assumed to be of exponential type, the most successful method was found in the application of the statistical extreme-value analysis developed by Gumbel. This study aims to present a new and alternative methodology to the Gumbel approach with a view towards accurately estimating the maximum pit depth observed on a ferritic stainless steel AISI 409 subjected to an accelerated corrosion test (ECC1) used in automotive industry. This methodology consists in characterising and modelling both the morphology of pits and the statistical distribution of their depths from a limited inspection dataset. The heart of the data processing is based on the combination of two recent statistical methods that avoid making any choice about the type of the theoretical underlying parent distribution of pit depths: the Generalized Lambda Distribution (GLD) is used to model the distribution of pit depths and the Bootstrap technique to determine a confidence interval on the maximum pit depth.

Files in this item

Name:
LMPGM_LTPMC_2004_IOST.pdf
Size:
654.4Kb
Format:
PDF
View/Open

Collections

  • Laboratoire Mechanics, Surfaces and Materials Processing (MSMP)

Related items

Showing items related by title, author, creator and subject.

  • A multi-scale approach of roughness measurements: Evaluation of the relevant scale 
    Article dans une revue avec comité de lecture
    VAN GORP, Adrien; BIGERELLE, Maxence; GRELLIER, Alain; IOST, Alain; NAJJAR, Denis (Elsevier, 2007)
    This paper proposes a new multi-scale measurement approach performed to compare the surface roughness and the visual aspect of polished surfaces. In this investigation, five specimens of glass moulds presenting different ...
  • An expert system to characterise the surfaces morphological properties according to their tribological functionalities: The relevance of a pair of roughness parameters 
    Article dans une revue avec comité de lecture
    BIGERELLE, Maxence; NAJJAR, Denis; MATHIA, Thomas; IOST, Alain; COOREVITS, Thierry; ANSELME, Karine (Elsevier, 2013)
    Knowing that a surface or profile can be characterized by numerous roughness parameters, the objective of this investigation was to present a methodology which aims to determine quantitatively and without preconceived ...
  • Assessment of the constitutive law by inverse methodology: Small punch test and hardness 
    Article dans une revue avec comité de lecture
    ISSELIN, Jérôme; IOST, Alain; GOLEK, Jocelyn; NAJJAR, Denis; BIGERELLE, Maxence (Elsevier, 2006)
    The relevance of small-punch tests and indentation (hardness) tests are compared with regard to the determination of a constitutive law in the case of non active ferrite–bainite steel taken from a French power plant. ...
  • Influence of the morphological texture on the low wear damage of paint coated sheets 
    Article dans une revue avec comité de lecture
    HENNEBELLE, François; NAJJAR, Denis; BIGERELLE, Maxence; IOST, Alain (Elsevier, 2006)
    The influence of the morphological texture (flat and structured) of a polyester based paint coating on the low wear damage is characterised by means of roughness and gloss measurements. Using statistical methods, the aim ...
  • Mesure de la Pertinence de la Physique Multi-échelle Génie Logiciel et Mesures Statistiques Projet CETIM 
    Communication avec acte
    IOST, Alain; COOREVITS, Thierry; ZAHOUANI, Hassan; ANSELME, Karine; EL MANSORI, Mohamed; NAJJAR, Denis; GUILLEMOT, Gildas; HAGEGE, Benjamin; JOURANI, Abdeljalil; REVEL, Phllippe; MAZERAN, Pierre-Emmanuel; BIGERELLE, Maxence (Université de Poitiers, 2007)
    L'objet principal des études en morphologie des surfaces consiste à résumer l'information de manière optimale. Dans nos études, nous étudions plus particulièrement la signification physique, les méthodes numériques et les ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales