Noniterative localized exponential time differencing methods for hyperbolic conservation laws

IF 2.1 3区 数学 Q2 MATHEMATICS, APPLIED
Cao-Kha Doan, Phuoc-Toan Huynh, Thi-Thao-Phuong Hoang
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引用次数: 0

Abstract

The paper is concerned with efficient time discretization methods based on exponential integrators for scalar hyperbolic conservation laws. The model problem is first discretized in space by the discontinuous Galerkin method, resulting in a system of nonlinear ordinary differential equations. To solve such a system, exponential time differencing of order 2 (ETDRK2) is employed with Jacobian linearization at each time step. The scheme is fully explicit and relies on the computation of matrix exponential vector products. To accelerate such computation, we further construct a noniterative, nonoverlapping domain decomposition algorithm, namely localized ETDRK2, which loosely decouples the system at each time step via suitable interface conditions. Temporal error analysis of the proposed global and localized ETDRK2 schemes is rigorously proved; moreover, the schemes are shown to be conservative under periodic boundary conditions. Numerical results for the Burgers’ equation in one and two dimensions (with moving shocks) are presented to verify the theoretical results and illustrate the performance of the global and localized ETDRK2 methods where large time step sizes can be used without affecting numerical stability.

双曲型守恒律的非迭代局域指数差分方法
本文研究了基于指数积分器的标量双曲守恒律的有效时间离散方法。首先用不连续伽辽金方法在空间上离散模型问题,得到一个非线性常微分方程组。为了求解这样的系统,在每个时间步长采用2阶指数时间差(ETDRK2)和雅可比线性化。该方案是完全显式的,依赖于矩阵指数向量积的计算。为了加速这种计算,我们进一步构建了一种非迭代、非重叠的域分解算法,即局部化ETDRK2,该算法通过适当的接口条件在每个时间步对系统进行松散解耦。严格证明了ETDRK2方案的时域误差分析;此外,在周期边界条件下,该格式是保守的。给出了一维和二维(含运动冲击)的Burgers方程的数值结果来验证理论结果,并说明了全局和局部ETDRK2方法的性能,其中大时间步长可以在不影响数值稳定性的情况下使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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