论文标题

具有修改的patankar时间整合的界限不连续的Galerkin方法,用于化学反应流

Bound-preserving discontinuous Galerkin methods with modified Patankar time integrations for chemical reacting flows

论文作者

Zhu, Fangyao, Huang, Juntao, Yang, Yang

论文摘要

在本文中,我们开发了具有化学反应性流动的不连续的盖金(DG)方法。构建合适的数值方案有几个困难。首先,密度和内部能量是正的,每个物种的质量分数在0到1之间。其次,由于反应速率的快速反应速率,该系统可能包含硬源,并且强大的明确runge-kutta方法可能会导致时间步长尺寸有限。为了获得与物理相关的数值近似值,我们将界限技术应用于DG方法。对于时间离散化,我们应用了修改的runge-kutta/Multi-step patankar方法,这些方法是明确的,同时隐含了源。这种方法可以使用相对较大的时间步长处理硬源,保留目标变量的阳性,并使质量分数的总和保持在1。最后,结合边界提供的DG方法和patankar时间集成并不直接。 DG方法的阳性阳性技术需要在细胞接口处进行正数近似值,而Patankar方法可以保持目标变量预选的点值的阳性。为了匹配自由度,我们在矩形网格上使用$ q^k $多项式在两个空间维度中的问题。为了随着时间的流逝而发展,我们首先在高斯点读了多项式。然后,可以应用合适的坡度限制器来在这些点上强制实施溶液的阳性,这可以通过patankar方法保存,从而导致阳性更新的数值单元格平均值。此外,我们使用另一个坡度限制器来获取用于磁通限制技术的正面解决方案。

In this paper, we develop bound-preserving discontinuous Galerkin (DG) methods for chemical reactive flows. There are several difficulties in constructing suitable numerical schemes. First of all, the density and internal energy are positive, and the mass fraction of each species is between 0 and 1. Secondly, due to the rapid reaction rate, the system may contain stiff sources, and the strong-stability-preserving explicit Runge-Kutta method may result in limited time step sizes. To obtain physically relevant numerical approximations, we apply the bound-preserving technique to the DG methods. For time discretization, we apply the modified Runge-Kutta/multi-step Patankar methods, which are explicit for the flux while implicit for the source. Such methods can handle stiff sources with relatively large time steps, preserve the positivity of the target variables, and keep the summation of the mass fractions to be 1. Finally, it is not straightforward to combine the bound-preserving DG methods and the Patankar time integrations. The positivity-preserving technique for DG method requires positive numerical approximations at the cell interfaces, while Patankar methods can keep the positivity of the pre-selected point-values of the target variables. To match the degree of freedom, we use $Q^k$ polynomials on rectangular meshes for problems in two space dimensions. To evolve in time, we first read the polynomials at the Gaussian points. Then suitable slope limiters can be applied to enforce the positivity of the solutions at those points, which can be preserved by the Patankar methods, leading to positive updated numerical cell averages. In addition, we use another slope limiter to get positive solutions used for the bound-preserving technique for the flux.

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