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Stochastic hyperelastic constitutive laws and identification procedure for soft biological tissues with intrinsic variability

Abstract : In this work, we address the constitutive modeling, in a probabilistic framework, of the hyperelastic response of soft biological tissues. The aim is on the one hand to mimic the mean behavior and variability that are typically encountered in the experimental characterization of such materials, and on the other hand to derive mathematical models that are almost surely consistent with the theory of nonlinear elasticity. Towards this goal, we invoke information theory and discuss a stochastic model relying on a low-dimensional parametrization. We subsequently propose a two-step methodology allowing for the calibration of the model using standard data, such as mean and standard deviation values along a given loading path. The framework is finally applied and benchmarked on three experimental databases proposed elsewhere in the literature. It is shown that the stochastic model allows experiments to be accurately reproduced, regardless of the tissue under consideration.
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https://hal.archives-ouvertes.fr/hal-01367381
Contributor : J. Guilleminot <>
Submitted on : Friday, September 16, 2016 - 9:04:36 AM
Last modification on : Thursday, March 19, 2020 - 11:52:04 AM
Long-term archiving on: : Saturday, December 17, 2016 - 1:46:28 PM

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B Staber, J Guilleminot. Stochastic hyperelastic constitutive laws and identification procedure for soft biological tissues with intrinsic variability. Journal of the mechanical behavior of biomedical materials, Elsevier, 2017, 65, pp.743-752. ⟨10.1016/j.jmbbm.2016.09.022⟩. ⟨hal-01367381⟩

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