Abstract
The biomechanical characterization of human brain tissue and the development of appropriate mechanical models is crucial to provide realistic computational predictions that can assist personalized treatment of neurological disorders with a strong biomechanical component. Here, we present a novel material model that combines finite viscoelasticity with a nonlinear biphasic poroelastic formulation, developed within the context of the Theory of Porous Media. Embedded in a finite element framework, our model is capable of predicting the brain tissue response under multiple loading conditions. We show that our model can capture both experimentally observed fluid flow and conditioning aspects of brain tissue behavior in addition to its well-established nonlinear and compression–tension asymmetric characteristics. Our results support the notion that porous and viscous effects are highly interrelated and that additional experimental data are required to reliably identify the model parameters. The modular and object-oriented design with automatic differentiation makes our open-source code easily amendable to future extensions. We provide a solid foundation towards the development of a reliable and comprehensive biomechanical model for brain tissue, which will be a versatile and useful tool in elucidating the rheology of brain tissue behavior to help the biomedical and clinical communities in the future study, prevention and treatment of brain injury and disease.
Original language | English |
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Article number | 113128 |
Journal | Computer Methods in Applied Mechanics and Engineering |
Volume | 369 |
DOIs | |
Publication status | Published - 1 Sept 2020 |
Keywords
- Brain mechanics
- Finite element method
- Finite viscoelasticity
- Material modeling
- Mechanical testing
- Theory of porous media
ASJC Scopus subject areas
- Mechanics of Materials
- Mechanical Engineering
- Physics and Astronomy(all)
- Computer Science Applications
- Computational Mechanics