Optimal convergence analysis of two RPC-SAV schemes for the unsteady incompressible magnetohydrodynamics equations

IF 2.3 2区 数学 Q1 MATHEMATICS, APPLIED IMA Journal of Numerical Analysis Pub Date : 2024-05-15 DOI:10.1093/imanum/drae016
Xiaojing Dong, Huayi Huang, Yunqing Huang, Xiaojuan Shen, Qili Tang
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Abstract

In this paper, we present and analyze two linear and fully decoupled schemes for solving the unsteady incompressible magnetohydrodynamics equations. The rotational pressure-correction (RPC) approach is adopted to decouple the system, and the recently developed scalar auxiliary variable (SAV) method is used to treat the nonlinear terms explicitly and keep energy stability. One is the first-order RPC-SAV-Euler and the other one is generalized Crank–Nicolson-type scheme: GRPC-SAV-CN. For the RPC-SAV-Euler scheme, both unconditionally energy stability and optimal convergence are derived. The new GRPC-SAV-CN is constructed and can be regarded as a parameterized scheme, which includes PC-SAV-CN when the parameter $\beta =0$ and RPC-SAV-CN when $\beta \in (0,\frac {1}{2}]$; see Algorithm 3.2. However, Jiang and Yang (Jiang, N. & Yang, H. (2021) SIAM J. Sci. Comput., 43, A2869–A2896) point out that the SAV method has low accuracy by several commonly tested benchmark flow problem when solving Navier–Stokes equations. To improve the accuracy, we added two stabilization $-\alpha _{1}\varDelta t\nu \varDelta (\widetilde {\textbf {u}}^{n+1}-{\textbf {u}}^{n})$ and $\alpha _{2}\varDelta t\sigma ^{-1}\mbox {curl}\mbox {curl} (\textbf {H}^{n+1}-\textbf {H}^{n})$ in the GRPC-SAV-CN scheme, which play decisive roles in giving optimal error estimates. The unconditionally energy stability of the proposed scheme is given. We prove that the PC-SAV-CN scheme has second-order convergence speed, and the RPC-SAV-CN one has 1.5-order convergence rate. Finally, some numerical examples are presented to verify the validity and convergence of the numerical schemes.
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针对非稳态不可压缩磁流体动力学方程的两种 RPC-SAV 方案的最佳收敛性分析
本文提出并分析了两种线性完全解耦方案,用于求解非稳态不可压缩磁流体动力学方程。采用旋转压力校正(RPC)方法来解耦系统,并使用最近开发的标量辅助变量(SAV)方法来显式处理非线性项并保持能量稳定性。其中一个是一阶 RPC-SAV-Euler 方案,另一个是广义 Crank-Nicolson-type 方案:GRPC-SAV-CN。对于 RPC-SAV-Euler 方案,推导出了无条件能量稳定性和最优收敛性。新的 GRPC-SAV-CN 被构建并可视为参数化方案,其中包括当参数 $\beta =0$ 时的 PC-SAV-CN 和当 $\beta\in (0,\frac {1}{2}]$ 时的 RPC-SAV-CN;见算法 3.2。然而,Jiang 和 Yang(Jiang, N. & Yang, H. (2021) SIAM J. Sci. Comput.为了提高精度、我们添加了两个稳定 $-\alpha _{1}\varDelta t\nu \varDelta (\widetilde {\textbf {u}}^{n+1}- {\textbf {u}}^{n+1}){和 $\alpha _{2}\varDelta t\sigma ^{-1}\mbox {curl}\mbox {curl} (\textbf {H}^{n+1}-\textbf {H}^{n})$ 在 GRPC-SAV-CN 方案中、在给出最佳误差估计值方面起着决定性作用。我们给出了所提方案的无条件能量稳定性。我们证明 PC-SAV-CN 方案具有二阶收敛速度,而 RPC-SAV-CN 方案具有 1.5 阶收敛速度。最后,我们给出了一些数值示例来验证数值方案的有效性和收敛性。
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来源期刊
IMA Journal of Numerical Analysis
IMA Journal of Numerical Analysis 数学-应用数学
CiteScore
5.30
自引率
4.80%
发文量
79
审稿时长
6-12 weeks
期刊介绍: The IMA Journal of Numerical Analysis (IMAJNA) publishes original contributions to all fields of numerical analysis; articles will be accepted which treat the theory, development or use of practical algorithms and interactions between these aspects. Occasional survey articles are also published.
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