arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1602.02245math.NAcs.NA
收藏

高阶分层渐近保持节点不连续伽辽金IMEX方案用于BGK方程

High Order Hierarchical Asymptotic Preserving Nodal Discontinuous Galerkin IMEX Schemes For The BGK Equation

Xiamen University(厦门大学);University of Houston(休斯顿大学)

Tao Xiong, Jingmei Qiu

AI总结:

本文提出高阶渐近保持方案,结合节点不连续伽辽金与IMEX方法,有效处理BGK方程的三种不同流体动力学 regime,显著降低计算成本。

摘要:

Xiong等人(2015)[37]开发了一类高阶渐近保持(AP)方案用于BGK方程,基于微-宏观公式。引入节点不连续伽辽金(NDG)方法与全局刚性隐式-显式(IMEX)Runge-Kutta(RK)方案,具有渐近保持性质。当流体动力学描述失效时,仅需求解动能方程。受Filbet和Rey(2015)[23]工作启发,在NDG-IMEX框架下构建分层方案,无需混合。形式分析显示,当ε较小时,NDG-IMEX方案变为局部不连续伽辽金(LDG)方案用于可压缩纳维-斯托克斯方程;当ε=0时,变为不连续伽辽金(DG)方案用于可压缩欧拉方程。本文提出将动能 regime 与流体动力学 regime 结合,包括可压缩欧拉与纳维-斯托克斯方程。数值实验显示新方法性能优异,三种 regime 明确区分,显著降低计算成本。

英文摘要:

A class of high order asymptotic preserving (AP) schemes has been developed for the BGK equation in Xiong et. al. (2015) [37], which is based on the micro-macro formulation of the equation. The nodal discontinuous Galerkin (NDG) method with Lagrangian basis functions for spatial discretization and globally stiffly accurate implicit-explicit (IMEX) Runge-Kutta (RK) scheme as time discretization are introduced with asymptotic preserving properties. However, it is only necessary to solve the kinetic equation when the hydrodynamic description breaks down. Motivated by the recent work in Filbet and Rey (2015) [23], it is more naturally to construct a hierarchy scheme under the NDG-IMEX framework without hybridization, as the formal analysis in [37] shows that when $ε$ is small, the NDG-IMEX scheme becomes a local discontinuous Galerkin (LDG) scheme for the compressible Navier-Stokes equations, and when $ε=0$ it is a discontinuous Galerkin (DG) scheme for the compressible Euler equations. Moveover, we propose to combine the kinetic regime with the hydrodynamic regime including both the compressible Euler and Navier-Stokes equations. Numerical experiments demonstrate very decent performance of the new approach. In our numerics, all three regimes are clearly divided, leading to great savings in terms of the computational cost.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑