论文标题
Anderson的超线性融合加速了牛顿的求解固定Navier-Stokes方程的方法
Superlinear convergence of Anderson accelerated Newton's method for solving stationary Navier-Stokes equations
论文作者
论文摘要
本文研究了牛顿的迭代，随着安德森加速度应用于解决不可压缩的稳定纳维尔 - stokes方程。我们表明，这种方法以良好的初始猜测进行了超线性的收敛，此外，与小安德森（Anderson）深度相比，大安德森（Anderson）深度降低了收敛速度。我们观察到数值测试证实了这些分析收敛的结果，此外，安德森加速度有时会扩大牛顿方法的收敛域。
This paper studies the performance Newton's iteration applied with Anderson acceleration for solving the incompressible steady Navier-Stokes equations. We manifest that this method converges superlinearly with a good initial guess, and moreover, a large Anderson depth decelerates the convergence speed comparing to a small Anderson depth. We observe that the numerical tests confirm these analytical convergence results, and in addition, Anderson acceleration sometimes enlarges the domain of convergence for Newton's method.
