Numerical simulation of microstrip circuits using unconditional stable CN-FDTD method combined with preconditioned GMRES

Y. Yang, R. Chen
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引用次数: 1

Abstract

The increase of the time step size significantly deteriorates the property of the coefficient matrix generated from the Crank-Nicolson finite-difference time-domain (CN-FDTD) method. As a result, the convergence of classical iterative methods, such as generalized minimal residual method (GMRES) would be substantially slowed down. To address this issue, this paper mainly concerns efficient computation of this large sparse linear equations using preconditioned generalized minimal residual (PGMRES) method Some typical preconditioning techniques, such as the Jacobi preconditioner, the sparse approximate inverse (SAI) preconditioner and the symmetric successive over-relaxation (SSOR) preconditioner, are introduced to accelerate the convergence of the GMRES iterative method. Numerical simulation shows that the SSOR preconditioned GMRES method can reach convergence three times faster than GMRES for this structure.
利用无条件稳定CN-FDTD方法结合预处理GMRES对微带电路进行数值模拟
随着时间步长的增大,由Crank-Nicolson时域有限差分(CN-FDTD)方法得到的系数矩阵的性质明显变差。这将大大降低经典迭代方法的收敛速度,如广义最小残差法(GMRES)。为了解决这一问题,本文主要研究了用预条件广义最小残差(PGMRES)方法高效地计算这类大型稀疏线性方程,并引入了Jacobi预条件、稀疏近似逆(SAI)预条件和对称连续过松弛(SSOR)预条件等典型的预条件技术来加速GMRES迭代方法的收敛性。数值仿真结果表明,对于该结构,SSOR预处理GMRES方法的收敛速度比GMRES方法快3倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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