论文标题

约束能量最大程度地限制多范围理查兹方程的通用多尺度有限元法

Constraint Energy Minimizing Generalized Multiscale Finite Element Method for multi-continuum Richards equations

论文作者

Mai, Tina, Cheung, Siu Wun, Park, Jun Sur Richard

论文摘要

在流体流量模拟中,多核模型是一个有用的策略。当系数的异质性和对比度很高时,系统将变为多尺度,并且需要一些减少阶的方法。将这些技术与非线性相结合,我们将在本文中考虑一个双键盘模型,在复杂的异质性裂缝多孔的多孔多孔培养基中,在非线性理查兹方程组合的耦合系统中被推广为一个非线性理查兹方程的耦合系统;我们将利用一种新颖的多尺度方法来解决它,该方法利用约束能量最大程度地减少广义多尺度有限元方法(CEM-GMSFEM)。特别是,这种非线性系统将随时间离散,然后通过PICARD迭代(理论上证明其全局收敛性)线性化。随后,我们通过CEM-GMSFEM来应对所得的线性化方程,并获得适当的离线多尺度函数以跨越多尺度空间(其中包含压力解决方案)。更具体地说,我们首先引入了两个新的样本来源,并且在每个粗块上使用GMSFEM来通过解决局部光谱问题来构建局部辅助多尺度基础函数,这对于检测高对比度通道至关重要。其次,每个过采样的粗糙区域,局部多尺度基础函数是通过CEM创建的,因为它被约束最小化的能量功能。针对我们的方法进行的各种数值测试表明,误差仅与粗网格大小收敛,并且只需要几个过采样层以及基本功能。

In fluid flow simulation, the multi-continuum model is a useful strategy. When the heterogeneity and contrast of coefficients are high, the system becomes multiscale, and some kinds of reduced-order methods are demanded. Combining these techniques with nonlinearity, we will consider in this paper a dual-continuum model which is generalized as a multi-continuum model for a coupled system of nonlinear Richards equations as unsaturated flows, in complex heterogeneous fractured porous media; and we will solve it by a novel multiscale approach utilizing the constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM). In particular, such a nonlinear system will be discretized in time and then linearized by Picard iteration (whose global convergence is proved theoretically). Subsequently, we tackle the resulting linearized equations by the CEM-GMsFEM and obtain proper offline multiscale basis functions to span the multiscale space (which contains the pressure solution). More specifically, we first introduce two new sources of samples, and the GMsFEM is used over each coarse block to build local auxiliary multiscale basis functions via solving local spectral problems, that are crucial for detecting high-contrast channels. Second, per oversampled coarse region, local multiscale basis functions are created through the CEM as constrainedly minimizing an energy functional. Various numerical tests for our approach reveal that the error converges with the coarse-grid size alone and that only a few oversampling layers, as well as basis functions, are needed.

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