A comparison of the Newton-Krylov method with high order Newton-like methods to solve nonlinear systems

We compare the CPU time and error estimates of some variants of Newton method of the third and fourth-order convergence with those of the Newton-Krylov method used to solve systems of nonlinear equations. By expanding some numerical experiments we show that the use of Newton-Krylov method is better in the cost and accuracy points of view than the use of other high order Newton-like methods when the system is sparse and its size is large.     

A matrix‐free preconditioned Newton/GMRES method for unsteady Navier–Stokes solutions

The unsteady compressible Reynolds‐averaged Navier–Stokes equations are discretized using the Osher approximate Riemann solver with fully implicit time stepping. The resulting non‐linear system at each time step is solved iteratively using a Newton/GMRES method. In the solution process, the Jacobian matrix–vector products are replaced by directional derivatives so that the evaluation and storage of the Jacobian matrix is removed from the procedure. An effective matrix‐free preconditioner is proposed to fully avoid matrix storage. Convergence rates, computational costs and computer memory requirements of the present method are compared with those of a matrix Newton/GMRES method, a four stage Runge–Kutta explicit method, and an approximate factorization sub‐iteration method. Effects of convergence tolerances for the GMRES linear solver on the convergence and the efficiency of the Newton iteration for the non‐linear system at each time step are analysed for both matrix‐free and matrix methods. Differences in the performance of the matrix‐free method for laminar and turbulent flows are highlighted and analysed. Unsteady turbulent Navier–Stokes solutions of pitching and combined translation–pitching aerofoil oscillations are presented for unsteady shock‐induced separation problems associated with the rotor blade flows of forward flying helicopters. Copyright © 2000 John Wiley & Sons, Ltd.     

An Investigation of Restarted GMRES Method by Using Flexible Starting Vectors

<正>We discuss a variant of restarted GMRES method that allows changes of the restarting vector at each cycle of iterations.The merit of the variant is that previously generated information can be utilized to select a new starting vector,such that the occurrence of stagnation be mitigated or the convergence be accelerated.The more appealing utilization of the new method is in conjunction with a harmonic Ritz vector as the starting vector,which is discussed in detail.Numerical experiments are carried out to demonstrate that the proposed procedure can effectively mitigate the occurrence of stagnation due to the presence of small eigenvalues in modulus.     

有界多连通区域数值保角变换的GMRES(m)法北大核心CSCD

求解复杂多连通区域的保角变换函数是困难的.针对这一问题,该文将求解保角变换函数转化为利用模拟电荷法求解一对定义在问题区域上的共轭调和函数,再根据边界条件建立约束方程,并利用GMRES(m)(the generalized minimal residual method)算法求解约束方程,获得了模拟电荷,进而构造了高精度的近似保角变换函数,将有界多连通区域映射为三种无界正则狭缝域.数值实验验证了该文算法的有效性.     

EFFECTS OF IMPLICIT PRECONDITIONERS ON SOLUTION ACCELERATION SCHEMES IN CFD

Several solution acceleration techniques, used to obtain steady state CFD solutions as quickly as possible, are applied to an implicit, upwind Euler solver to evaluate their effectiveness. The implicit system is solved using either ADI or ILU and the solution acceleration techniques evaluated are quasi-Newton iteration, Jacobian freezing, multigrid and GMRES. ILU is a better preconditioner than ADI because it can use larger time steps. Adding GMRES does not always improve the convergence. However, GMRES preconditioned with ILU and multigrid can take advantage of Jacobian freezing to produce an efficient scheme that is relatively independent of grid size and grid quality.     

三次相位板波前编码系统彩色图像恢复的迭代算法

采用三次相位板进行景深延拓的波前编码系统得到非对称的点扩展函数.为了获得最终清晰的彩色图像.研究了一种基于广义极小残差法(GMREs)的迭代算法,结合Tikhonov规整化方法,并利用多通道处理过程对中间图像进行左卷积恢复.为了消除恢复图像边界的振铃效应,推导了新的光学成像过程数学模型,该模型采用反镜像边界条件并利用直积近似对卷积核进行处理.模拟数据的分析表明,采用多通道处理过程对彩色图片进行恢复时,新的算法在给出精确的反巷积结果的同时能有效地抑制噪声的放大;实验结果显示,较之经典的维纳滤波恢复结果,新算法能够更好的消除边界的振铃和图像边缘的振动波纹.     

Simultaneous solution of large-scale linear systems and eigenvalue problems with a parallel GMRES method

A method for simultaneous solution of large and sparse linearized equation sets and the corresponding eigenvalue problems is presented. Such problems arise from the discretization and the solution of nonlinear problems with the finite element method and Newton iteration. The method is based on a parallel version of the preconditioned GMRES(m$m$) by deflation. The parallel code exploits the architecture of the computational clusters using the MPI (Message Passing Interface). The convergence rate, the parallel speedup and the memory requirements of the proposed method are reported and evaluated.