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首页> 外文期刊>Applied numerical mathematics >Parallel finite element variational multiscale algorithms for incompressible flow at high Reynolds numbers
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Parallel finite element variational multiscale algorithms for incompressible flow at high Reynolds numbers

机译:高雷诺数不可压缩流的并行有限元变分多尺度算法

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Based on two-grid discretizations, some parallel finite element variational multiscale algorithms for the steady incompressible Navier-Stokes equations at high Reynolds numbers are presented and compared. In these algorithms, a stabilized Navier-Stokes system is first solved on a coarse grid, and then corrections are calculated independently on overlapped fine grid subdomains by solving a local stabilized linear problem. The stabilization terms for the coarse and fine grid problems are based on two local Gauss integrations. Error bounds for the approximate solution are estimated. Algorithmic parameter scalings are also derived. The theoretical results show that, with suitable scalings of the algorithmic parameters, these algorithms can yield an optimal rate of convergence. Numerical results are given to verily the theoretical predictions and demonstrate the effectiveness of the proposed algorithms.
机译:基于两网格离散化,提出并比较了高雷诺数下稳态不可压缩Navier-Stokes方程的一些并行有限元变分多尺度算法。在这些算法中,首先在粗糙网格上求解稳定的Navier-Stokes系统,然后通过解决局部稳定线性问题,在重叠的精细网格子域上独立计算校正。粗网格和细网格问题的稳定项基于两个局部高斯积分。估计近似解的误差范围。还推导了算法参数缩放。理论结果表明,通过对算法参数进行适当的缩放,这些算法可以产生最优的收敛速度。数值结果证明了理论上的正确性,并证明了所提算法的有效性。

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