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arXiv 2009.01133math.NAcs.NA
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双曲型守恒律高阶显式Runge-Kutta时间离散的保界通量限制

Bound-preserving flux limiting for high-order explicit Runge-Kutta time discretizations of hyperbolic conservation laws

Dmitri Kuzmin, Manuel Quezada de Luna, David I. Ketcheson, Johanna Grüll

摘要:

我们介绍了一个一般的框架,在高阶时空离散的标量双曲型守恒律执行本地或全局极大值的原则。首先给出了空间离散化保界(BP)且满足半离散最大值原理的充分条件。其次,我们提出了一种全局整体凸(GMC)通量限制器,它具有通量校正传输(FCT)算法的结构,但适用于空间半离散,并确保了强稳定性保持(SSP)Runge-Kutta时间离散的全离散格式的BP属性。为了规避SSP时间积分器的顺序障碍,我们约束的中间阶段和/或最后阶段的一般高阶RK方法使用GMC型限制器。在这项工作中,我们的理论和数值研究仅限于显式计划,证明BP足够小的时间步长。新的GMC限制框架提供了放宽不等式约束的界限,以实现更高的精度,在更严格的时间步长限制的成本的可能性。三个代表性的RK方法结合加权基本无振荡(WENO)有限体积空间离散的线性和非线性测试问题在一维的能力,所提出的限制器,以保持整体边界和识别良好解决的光滑解决方案的数值验证。

英文摘要:

We introduce a general framework for enforcing local or global maximum principles in high-order space-time discretizations of a scalar hyperbolic conservation law. We begin with sufficient conditions for a space discretization to be bound preserving (BP) and satisfy a semi-discrete maximum principle. Next, we propose a global monolithic convex (GMC) flux limiter which has the structure of a flux-corrected transport (FCT) algorithm but is applicable to spatial semi-discretizations and ensures the BP property of the fully discrete scheme for strong stability preserving (SSP) Runge-Kutta time discretizations. To circumvent the order barrier for SSP time integrators, we constrain the intermediate stages and/or the final stage of a general high-order RK method using GMC-type limiters. In this work, our theoretical and numerical studies are restricted to explicit schemes which are provably BP for sufficiently small time steps. The new GMC limiting framework offers the possibility of relaxing the bounds of inequality constraints to achieve higher accuracy at the cost of more stringent time step restrictions. The ability of the presented limiters to preserve global bounds and recognize well-resolved smooth solutions is verified numerically for three representative RK methods combined with weighted essentially nonoscillatory (WENO) finite volume space discretizations of linear and nonlinear test problems in 1D.

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