We introduce and analyze a discontinuous Galerkin method for the numerical modelling of the equations of Multiple-Network Poroelastic Theory (MPET) in the dynamic formulation. The MPET model can comprehensively describe functional changes in the brain considering multiple scales of fluids. Concerning the spatial discretization, we employ a high-order discontinuous Galerkin method on polygonal and polyhedral grids and we derive stability and a priori error estimates. The temporal discretization is based on a coupling between a Newmark $\beta$-method for the momentum equation and a $\theta$-method for the pressure equations. After the presentation of some verification numerical tests, we perform a convergence analysis using an agglomerated mesh of a geometry of a brain slice. Finally we present a simulation in a three dimensional patient-specific brain reconstructed from magnetic resonance images. The model presented in this paper can be regarded as a preliminary attempt to model the perfusion in the brain.
翻译:我们引入并分析一种不连续的Galerkin 方法, 用于动态配方中多Network Poroelistic Theory(MPET) 等式的数值建模。 MPET 模型可以全面描述考虑到多种流体比例的大脑功能变化。 关于空间离散, 我们在多边形和多面网格上采用高分不连续的Galerkin 方法, 我们得出稳定性和先验误差估计。 时间离散基于动力方程式的Newmark $\beta$- 方法与压力方程的$\theta$meta- 方法的混合。 在演示一些校验数字测试后, 我们使用大脑切片几何学的聚合模型进行趋同分析。 最后, 我们用磁共振图像重建的三维特定病人大脑进行模拟。 本文中的模型可以被视为模拟大脑中渗透的初步尝试 。