论文标题
通过毕业生稳定和安德森的加速，改善了箭头 - 赫维兹迭代的收敛性
Improved convergence of the Arrow-Hurwicz iteration for the Navier-Stokes equation via grad-div stabilization and Anderson acceleration
论文作者
论文摘要
我们考虑了箭头 - 赫维兹（AH）迭代的两种修改，以解决不可压缩的稳定纳维尔 - 螺旋式方程，以加速算法：Grad-Divive稳定和Anderson加速。 AH是通用马鞍点线性系统的古典迭代，后来扩展到了1970年代的Navier-Stokes迭代，该迭代最近再次研究了。我们将最近开发的思想用于毕业划分稳定和无差异有限元方法以及安德森的固定点迭代加速度加速到AH，以改善其收敛性。分析和数值结果表明，这些方法中的每一种都改善了AH的融合，但是它们的组合产生了一种与更常用的求解器竞争的有效方法。
We consider two modifications of the Arrow-Hurwicz (AH) iteration for solving the incompressible steady Navier-Stokes equations for the purpose of accelerating the algorithm: grad-div stabilization, and Anderson acceleration. AH is a classical iteration for general saddle point linear systems and it was later extended to Navier-Stokes iterations in the 1970's which has recently come under study again. We apply recently developed ideas for grad-div stabilization and divergence-free finite element methods along with Anderson acceleration of fixed point iterations to AH in order to improve its convergence. Analytical and numerical results show that each of these methods improves AH convergence, but the combination of them yields an efficient and effective method that is competitive with more commonly used solvers.
