Multiscale modeling of skeletal muscle tissues based on analytical and numerical homogenization - École polytechnique
Article Dans Une Revue Journal of the mechanical behavior of biomedical materials Année : 2019

Multiscale modeling of skeletal muscle tissues based on analytical and numerical homogenization

Résumé

A novel multiscale modeling framework for skeletal muscles based on analytical and numerical homogeniza-tion methods is presented to study the mechanical muscle response at finite strains under three-dimensional loading conditions. First an analytical microstructure-based constitutive model is developed and numerically implemented in a general purpose finite element program. The analytical model takes into account explicitly the volume fractions, the material properties, and the spatial distribution of muscle's constituents by using homogenization techniques to bridge the different length scales of the muscle structure. Next, a numerical homogenization model is developed using periodic eroded Voronoi tessellation to virtually represent skeletal muscle microstructures. The eroded Voronoi unit cells are then resolved by finite element simulations and are used to assess the analytical homogenization model. The material parameters of the analytical model are identified successfully by use of available experimental data. The analytical model is found to be in very good agreement with the numerical model for the full range of loadings, and a wide range of different volume fractions and heterogeneity contrasts between muscle's constituents. A qualitative application of the model on fusiform and pennate muscle structures shows its efficiency to examine the effect of muscle fiber concentration variations in an organ-scale model simulation.
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Dates et versions

hal-01965947 , version 1 (27-12-2018)

Identifiants

Citer

L.A. A Spyrou, K. Danas, Sébastien Brisard. Multiscale modeling of skeletal muscle tissues based on analytical and numerical homogenization. Journal of the mechanical behavior of biomedical materials, 2019, ⟨10.1016/j.jmbbm.2018.12.030⟩. ⟨hal-01965947⟩
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