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Single and bi-compartment poro-elastic model of perfused biological soft tissues: FEniCSx implementation and tutorial

Article dans une revue avec comité de lecture
Author
LAVIGNE, Thomas
366875 Université du Luxembourg = University of Luxembourg = Universität Luxemburg [uni.lu]
1001017 Institut de Biomécanique Humaine Georges Charpak [IBHGC]
1002421 Institut de Mécanique et d'Ingénierie [I2M]
ccURCUN, Stéphane
ccROHAN, Pierre-Yves
1001017 Institut de Biomécanique Humaine Georges Charpak [IBHGC]
ccSCIUME, Giuseppe
1002421 Institut de Mécanique et d'Ingénierie [I2M]
ccBAROLI, Davide
BORDAS, Stéphane Pierre Alain
300863 University of Utah

URI
http://hdl.handle.net/10985/25443
DOI
10.1016/j.jmbbm.2023.105902
Date
2023-05
Journal
Journal of the mechanical behavior of biomedical materials

Abstract

Soft biological tissues demonstrate strong time-dependent and strain-rate mechanical behavior, arising from their intrinsic visco-elasticity and fluid–solid interactions. The time-dependent mechanical properties of soft tissues influence their physiological functions and are related to several pathological processes. Poro-elastic modeling represents a promising approach because it allows the integration of multiscale/multiphysics data to probe biologically relevant phenomena at a smaller scale and embeds the relevant mechanisms at the larger scale. The implementation of multiphase flow poro-elastic models however is a complex undertaking, requiring extensive knowledge. The open-source software FEniCSx Project provides a novel tool for the automated solution of partial differential equations by the finite element method. This paper aims to provide the required tools to model the mixed formulation of poro-elasticity, from the theory to the implementation, within FEniCSx. Several benchmark cases are studied. A column under confined compression conditions is compared to the Terzaghi analytical solution, using the L2-norm. An implementation of poro-hyper-elasticity is proposed. A bi-compartment column is compared to previously published results (Cast3m implementation). For all cases, accurate results are obtained in terms of a normalized Root Mean Square Error (RMSE). Furthermore, the FEniCSx computation is found three times faster than the legacy FEniCS one. The benefits of parallel computation are also highlighted.

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