Multiscale identification of stochastic apparent elasticity field of heterogeneous microstructures : application to a biological tissue

In the framework of linear elasticity 3D for complex microstructures that cannot be simply described in terms of components such as biological tissues, we propose, in this research work, a methodology for multiscale experimental identification of the apparent elasticity random field of the microstructure at mesoscopic scale using displacement field measurements at macroscopic scale and mesoscopic scale. We can then use this methodology in the case of changing scale to obtain the mechanical properties at macroscale. In this context, the major issue is the experimental identification by solving a statistical inverse problem of the stochastic modeling introduced for the apparent elasticity random field at mesoscale. This experimental identification allows to validate the modeling and makes it useful for existing materials with complex microstructures. This research work is proposed in this context in which experimentation and experimental validation based on simultaneous measurements of field imaging at macroscale and mesoscale are made on the cortical bonemakes it useful for existing materials with complex microstructures. This research work is proposed in this context in which experimentation and experimental validation based on simultaneous measurements of field imaging at macroscale and mesoscale are made on the cortical bone.

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Source https://theses.hal.science/tel-00977384
Author Nguyen, Manh Tu
Maintainer CCSD
Last Updated May 5, 2026, 15:15 (UTC)
Created May 5, 2026, 15:15 (UTC)
Identifier NNT: 2013PEST1135
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire de Modélisation et Simulation Multi Echelle (MSME) ; Université Paris-Est Marne-la-Vallée (UPEM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)
creator Nguyen, Manh Tu
date 2013-10-08T00:00:00
harvest_object_id 3307dd49-2d80-41e9-b442-53553ec06da8
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE