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arXiv 1905.09129math.NAcs.NA
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松弛龙格-库塔法:解可压缩Euler和Navier-斯托克斯方程的全离散显式熵稳定格式

Relaxation Runge-Kutta Methods: Fully-Discrete Explicit Entropy-Stable Schemes for the Compressible Euler and Navier-Stokes Equations

Hendrik Ranocha, Mohammed Sayyari, Lisandro Dalcin, Matteo Parsani, David I. Ketcheson

摘要:

介绍了保内积范数松弛龙格-库塔法(David I. Ketcheson,\emph{Relaxation Runge-Kutta Methods: Conservation and Stability for Inner-Product Norms},SIAM Journal on数值分析,2019)扩展到一般凸量。通过增加{ \em松弛因子}来加强关于任何凸泛函的守恒、耗散或其他解性质,该松弛参数在每一步乘以龙格库塔更新。此外,保持了其它所需的稳定性(如强稳定性保存)和效率(如低储存要求)性质。该技术可以应用于显式和隐式龙格-库塔法,只需要一个小的修改,现有的实现。在每一步的计算成本是一个额外的标量代数方程的解决方案,一个很好的初始猜测是可用的。该方法的有效性被证明分析和证明在几个数值例子中,包括应用到高阶熵守恒和熵稳定的半离散的非结构网格上的可压缩欧拉和Navier-斯托克斯方程。

英文摘要:

The framework of inner product norm preserving relaxation Runge-Kutta methods (David I. Ketcheson, \emph{Relaxation Runge-Kutta Methods: Conservation and Stability for Inner-Product Norms}, SIAM Journal on Numerical Analysis, 2019) is extended to general convex quantities. Conservation, dissipation, or other solution properties with respect to any convex functional are enforced by the addition of a {\em relaxation parameter} that multiplies the Runge-Kutta update at each step. Moreover, other desirable stability (such as strong stability preservation) and efficiency (such as low storage requirements) properties are preserved. The technique can be applied to both explicit and implicit Runge-Kutta methods and requires only a small modification to existing implementations. The computational cost at each step is the solution of one additional scalar algebraic equation for which a good initial guess is available. The effectiveness of this approach is proved analytically and demonstrated in several numerical examples, including applications to high-order entropy-conservative and entropy-stable semi-discretizations on unstructured grids for the compressible Euler and Navier-Stokes equations.

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