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Confidence Bounds for the Estimation of the Volume Phase Fraction from a Single Image in a Nickel Base Superalloy

Blanc, Rémi ; Baylou, Pierre ; Germain, Christian ; Da Costa, Jean-Pierre

In: Microscopy and Microanalysis, 2010, vol. 16, no. 3, p. 273-281

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    Titre
    • Confidence Bounds for the Estimation of the Volume Phase Fraction from a Single Image in a Nickel Base Superalloy
    Auteur
    • Blanc, Rémi. Rémi Blanc, Computer Vision Laboratory, ETHZ, Sternwartstrasse 7, ETH-Zentrum, CH-8092 Zürich, Switzerland
    • Baylou, Pierre. IMS, LAPS Department, CNRS UMR 5218, University of Bordeaux, Université Bordeaux 1, 351 Cours de la Libération, 33405 Talence, France
    • Germain, Christian. IMS, LAPS Department, CNRS UMR 5218, University of Bordeaux, Université Bordeaux 1, 351 Cours de la Libération, 33405 Talence, France
    • Da Costa, Jean-Pierre. IMS, LAPS Department, CNRS UMR 5218, University of Bordeaux, Université Bordeaux 1, 351 Cours de la Libération, 33405 Talence, France
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • Microscopy and Microanalysis, 2010, vol. 16, no. 3, p. 273-281. Cambridge University Press
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:300769
    Summary
    We propose an image-based framework to evaluate the uncertainty in the estimation of the volume fraction of specific microstructures based on the observation of a single section. These microstructures consist of cubes organized on a cubic mesh, such as monocrystalline nickel base superalloys. The framework is twofold: a model-based stereological analysis allows relating two-dimensional image observations to three-dimensional microstructure features, and a spatial statistical analysis allows computing approximate confidence bounds while assessing the representativeness of the image. The reliability of the method is assessed on synthetic models. Volume fraction estimation variances and approximate confidence intervals are computed on real superalloy images in the context of material characterization