Unconditionally stable numerical scheme for the 2D transport equation

IF 2.5 2区 数学 Q1 MATHEMATICS, APPLIED Computers & Mathematics with Applications Pub Date : 2025-02-14 DOI:10.1016/j.camwa.2025.02.003
Bérénice Grec , Davor Kumozec , Yohan Penel
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Abstract

The main goal of this paper is to extend the numerical scheme for the transport equation described in previous works [Penel, 2012; Bernard et al., 2014] from one to two dimensional problems. It is based on the method of characteristics, which consists in solving two ordinary differential equations rather than a partial differential equation. Our scheme uses an adaptive 6-point stencil in order to reach second-order accuracy whenever it is possible, and preserves some essential physical properties of the equation, such as the maximum principle. The resulting scheme is proved to be unconditionally stable and to reach second-order accuracy. We show numerical examples with comparisons to the well known Essentially Non-Oscillatory (ENO) scheme [Shu, 1998], in order to illustrate the good properties of our scheme (order of convergence, unconditional stability, accuracy). Using a Gaussian initial condition, several test cases are considered, using a constant or a rotating velocity field, taking into account or not variable source terms. Also, a test is given that shows the possibility of applying the scheme in more realistic fluid mechanics case.
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二维输运方程的无条件稳定数值方案
本文的主要目标是扩展先前工作中描述的输运方程的数值格式[Penel, 2012;Bernard et al., 2014]从一维问题到二维问题。它是基于特征方法,包括解决两个常微分方程,而不是一个偏微分方程。我们的方案使用自适应的6点模板,以便在可能的情况下达到二阶精度,并保留方程的一些基本物理性质,如最大值原理。证明了所得到的方案是无条件稳定的,并达到了二阶精度。我们给出了数值例子,与众所周知的基本非振荡(ENO)方案[Shu, 1998]进行比较,以说明我们的方案的良好性质(收敛顺序,无条件稳定性,准确性)。使用高斯初始条件,考虑几个测试用例,使用恒定或旋转速度场,考虑或不考虑可变源项。最后给出了一个实验,证明了该格式在更实际的流体力学情况下应用的可能性。
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来源期刊
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
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