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International Journal for Multiscale Computational Engineering
Impact-faktor: 1.016 5-jähriger Impact-Faktor: 1.194 SJR: 0.554 SNIP: 0.68 CiteScore™: 1.18

ISSN Druckformat: 1543-1649
ISSN Online: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.2015011435
pages 281-295

MULTISCALE IDENTIFICATION OF THE RANDOM ELASTICITY FIELD AT MESOSCALE OF A HETEROGENEOUS MICROSTRUCTURE USING MULTISCALE EXPERIMENTAL OBSERVATIONS

M. T. Nguyen
Universite Paris-Est, Laboratoire Modelisation et Simulation Multi-Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-La-Vallee, Cedex 2, France
Christophe Desceliers
Universite Paris-Est, Laboratoire Modelisation et Simulation Multi-Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, 77454 Marne-La-Vallee, Cedex 2, France
Christian Soize
Université Paris-Est Marne-La-Vallée Cité Descartes 5, bd Descartes, Champs sur Marne, 77454 Marne La Vallee Cedex 2, France
J. M. Allain
Ecole Polytechnique, Laboratoire de Mecanique des Solides, 91128, Palaiseau cedex, France
H. Gharbi
Ecole Polytechnique, Laboratoire de Mecanique des Solides, 91128, Palaiseau cedex, France

ABSTRAKT

This paper deals with a multiscale statistical inverse method for performing the experimental identification of the elastic properties of materials at macroscale and at mesoscale within the framework of a heterogeneous microstructure which is modeled by random elastic media. New methods are required for carrying out such multiscale identification using experimental measurements of the displacement fields carried out at macroscale and at mesoscale with only a single specimen submitted to a given external load at macroscale. In this paper, for a heterogeneous microstructure, a new identification method is presented and formulated within the framework of the three-dimensional linear elasticity. It permits the identification of the effective elasticity tensor at macroscale, and the identification of the tensor-valued random field, which models the apparent elasticity field at mesoscale. A validation is presented first with simulated experiments using a numerical model based on the hypothesis of 2D-plane stresses. Then, we present the results given by the proposed identification procedure for experimental measurements obtained by digital image correlation (DIC) on cortical bone.


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