arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2006.12959math.NAcs.NA
收藏

基于GMsFEM的非线性抛物型方程自适应多尺度模型降阶

Adaptive multiscale model reduction for nonlinear parabolic equations using GMsFEM

Yiran Wang, Eric Chung, Shubin Fu

摘要:

本文提出了一种耦合的离散经验插值方法(DEIM)和广义多尺度有限元法(GMsFEM)求解非线性抛物型方程,并将其应用于Allen-Cahn方程。Allen-Cahn方程是描述非线性反应-扩散过程的模型。它通常用于模拟界面运动的时间,例如合金中的相分离。GMsFEM允许通过在粗网格上构造解的降阶表示来以降低的计算成本解决多尺度问题。在arXiv:1301.2866中,GMsFEM提供了一种灵活的工具,通过构建适当的快照,离线和在线空间来解决多尺度问题。在本文中,我们解决了一个不定常的问题,其中使用在线富集。主要贡献是比较不同的在线富集方法。更具体地说,我们比较均匀的在线富集和自适应方法。我们还比较了两种自适应方法。此外,我们使用DEIM,降维方法,以减少复杂性时,我们评估的非线性项。我们的研究结果表明,DEIM可以近似的非线性项,而不会显着增加的误差。最后,我们将我们提出的方法应用于Allen Cahn方程。

英文摘要:

In this paper, we propose a coupled Discrete Empirical Interpolation Method (DEIM) and Generalized Multiscale Finite element method (GMsFEM) to solve nonlinear parabolic equations with application to the Allen-Cahn equation. The Allen-Cahn equation is a model for nonlinear reaction-diffusion process. It is often used to model interface motion in time, e.g. phase separation in alloys. The GMsFEM allows solving multiscale problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. In arXiv:1301.2866, it was shown that the GMsFEM provides a flexible tool to solve multiscale problems by constructing appropriate snapshot, offline and online spaces. In this paper, we solve a time dependent problem, where online enrichment is used. The main contribution is comparing different online enrichment methods. More specifically, we compare uniform online enrichment and adaptive methods. We also compare two kinds of adaptive methods. Furthermore, we use DEIM, a dimension reduction method to reduce the complexity when we evaluate the nonlinear terms. Our results show that DEIM can approximate the nonlinear term without significantly increasing the error. Finally, we apply our proposed method to the Allen Cahn equation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑