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首页> 外文期刊>SIAM Journal on Scientific Computing >NEWTON-GMRES PRECONDITIONING FOR DISCONTINUOUS GALERKIN DISCRETIZATIONS OF THE NAVIER-STOKES EQUATIONS
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NEWTON-GMRES PRECONDITIONING FOR DISCONTINUOUS GALERKIN DISCRETIZATIONS OF THE NAVIER-STOKES EQUATIONS

机译:Navier-Stokes方程的连续Galerkin离散的Newton-GMRES预处理

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摘要

We study preconditioners for the iterative solution of the linear systems arising in the implicit time integration of the compressible Navier-Stokes equations. The spatial discretization is carried out using a discontinuous Galerkin method with fourth order polynomial interpolations on triangular elements. The time integration is based on backward difference formulas resulting in a nonlinear system of equations which is solved at each timestep. This is accomplished using Newton's method. The resulting linear systems are solved using a preconditioned GMRES iterative algorithm. We consider several existing preconditioners such as block Jacobi and Gauss-Seidel combined with multilevel schemes which have been developed and tested for specific applications. While our results are consistent with the claims reported, we find that these preconditioners lack robustness when used in more challenging situations involving low Mach numbers, stretched grids, or high Reynolds number turbulent flows. We propose a preconditioner based on a coarse scale correction with postsmoothing based on a block incomplete LU factorization with zero fill-in (ILU0) of the Jacobian matrix. The performance of the ILU0 smoother is found to depend critically on the element numbering. We propose a numbering strategy based on minimizing the discarded fill-in in a greedy fashion. The coarse scale correction scheme is found to be important for diffusion dominated problems, whereas the ILU0 preconditioner with the proposed ordering is effective at handling the convection dominated case. While little can be said in the way of theoretical results, the proposed preconditioner is shown to perform remarkably well for a broad range of representative test problems. These include compressible flows ranging from very low Reynolds numbers to fully turbulent flows using the Reynolds averaged Navier-Stokes equations discretized on highly stretched grids. For low Mach number flows, the proposed preconditioner is more than one order of magnitude more efficient than the other preconditioners considered.
机译:我们研究可压缩的Navier-Stokes方程的隐式时间积分中产生的线性系统迭代解的预处理器。使用不连续Galerkin方法对三角形元素进行四阶多项式插值,可以实现空间离散化。时间积分基于后向差分公式,从而导致方程组的非线性系统在每个时间步都得到求解。这是使用牛顿方法完成的。使用预处理的GMRES迭代算法求解所得的线性系统。我们考虑了几种现有的预处理器,例如结合了针对特定应用进行了开发和测试的多层方案的Jacobcoi和Gauss-Seidel模块。尽管我们的结果与所报道的主张相符,但我们发现,当这些预处理器用于更具挑战性的情况时,如马赫数低,网格扩展或雷诺数高的湍流,则缺乏鲁棒性。我们提出了一种预处理器,该预处理器基于具有雅可比矩阵零填充(ILU0)的块不完整LU分解的后平滑平滑粗校正。发现ILU0平滑器的性能主要取决于元素编号。我们提出了一种基于贪婪的方式将丢弃的填充最小化的编号策略。发现粗尺度校正方案对于扩散主导的问题很重要,而具有建议顺序的ILU0预调节器在处理对流主导情况下有效。虽然理论上的说法很少,但是对于多种代表性的测试问题,建议的预处理器表现出了出色的性能。这些包括可压缩流,范围从非常低的雷诺数到完全湍流,使用在高度拉伸的网格上离散的雷诺平均Navier-Stokes方程即可。对于低马赫数流,拟议的预处理器的效率比所考虑的其他预处理器高一个数量级。

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