A reduced order method for Allen-Cahn equations

A reduced order method for Allen-Cahn equations
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Allen-Cahn 方程的降阶方法

DOI:
10.1016/j.cam.2015.07.009
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发表时间:
2016-01
影响因子:
2.4
通讯作者:
Qiuqi Li
Qiuqi Li
中科院分区:
数学2区
文献类型:
--
作者:
Huailing Song;Lijian Jiang;Qiuqi Li

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本文给出了Allen-Cahn方程的一种降阶建模和计算方法。在Allen-Cahn方程组的离散化过程中采用了全局基方法,并利用本征正交分解(POD)方法来减少全局基。针对Allen-Cahn方程非线性项的处理困难,我们采用离散经验插值方法(DEIM)对离散系统中的非线性项进行插值。将POD与DEIM相结合,提出了一种降阶方法。众所周知,Allen-Cahn方程具有非线性稳定性,即,自由能泛函随时间减小。用POD-DEIM降阶方法建模的Allen-Cahn离散系统可以继承连续模型的非线性稳定性。通过采用降阶方法,计算效率得到了显著提高。数值结果表明了降阶方法对确定性Allen-Cahn方程和随机Allen-Cahn方程的有效性。
In this article, we present a reduced order method for modeling and computing Allen–Cahn equations. A global basis method is used in the discretized system of the Allen–Cahn equations and Proper Orthogonal Decomposition (POD) method is utilized to reduce the global basis. To treat the difficulty of nonlinearity for Allen–Cahn equations, we apply Discrete Empirical Interpolation method (DEIM) to the nonlinear term from the discretization system. A reduced order method is developed by integrating POD and DEIM. It is well-known that the Allen–Cahn equations have a nonlinear stability property, i.e., the free-energy functional decreases with respect to time. The discretized Allen–Cahn system modeled by the POD–DEIM reduced order method can inherit the nonlinear stability of the continuous model. The computation efficiency is significantly enhanced by using the reduced order method. A few numerical results are presented to illustrate the performance of the reduced order method for deterministic Allen–Cahn equations and stochastic Allen–Cahn equations.
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发表时间: 2010-06
影响因子: 1.1
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