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An accurate, robust, and efficient finite element framework with applications to anisotropic, nearly and fully incompressible elasticity.
Karabelas, Elias; Gsell, Matthias A F; Haase, Gundolf; Plank, Gernot; Augustin, Christoph M.
Afiliação
  • Karabelas E; Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Graz, Austria.
  • Gsell MAF; BioTechMed-Graz, Graz, Austria.
  • Haase G; Gottfried Schatz Research Center: Division of Biophysics, Medical University of Graz, Graz, Austria.
  • Plank G; Institute for Mathematics and Scientific Computing, Karl-Franzens-University Graz, Graz, Austria.
  • Augustin CM; BioTechMed-Graz, Graz, Austria.
Comput Methods Appl Mech Eng ; 394: 114887, 2022 May 01.
Article em En | MEDLINE | ID: mdl-35432634
ABSTRACT
Fiber-reinforced soft biological tissues are typically modeled as hyperelastic, anisotropic, and nearly incompressible materials. To enforce incompressibility a multiplicative split of the deformation gradient into a volumetric and an isochoric part is a very common approach. However, the finite element analysis of such problems often suffers from severe volumetric locking effects and numerical instabilities. In this paper, we present novel methods to overcome volumetric locking phenomena for using stabilized P1-P1 elements. We introduce different stabilization techniques and demonstrate the high robustness and computational efficiency of the chosen methods. In two benchmark problems from the literature as well as an advanced application to cardiac electromechanics, we compare the approach to standard linear elements and show the accuracy and versatility of the methods to simulate anisotropic, nearly and fully incompressible materials. We demonstrate the potential of this numerical framework to accelerate accurate simulations of biological tissues to the extent of enabling patient-specific parameterization studies, where numerous forward simulations are required.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article