The, adaptive cross approximation algorithm for accelerated method of moments computations of EMC problems
The, adaptive cross approximation algorithm for accelerated method of moments computations of EMC problems
复制标题
DOI：
10.1109/temc.2005.857898
复制
发表时间：
2005-11-01
影响因子：
2.1
通讯作者：
Lee, JF
中科院分区：
文献类型：
--
作者：
Zhao, KZ;Vouvakis, MN;Lee, JF
提出了一种自适应交叉逼近算法，以减少矩量法求解曲面积分方程时的内存和CPU时间开销。本算法是纯代数的，因此，它的制定和实施是积分方程核（绿色的功能）独立的。该算法从计算域的多级划分开始。良好分离的分区集群的相互作用占通过秩揭示LU分解。蚁群算法的加速和内存节省来自于秩亏交互作用子矩阵的部分组装。它已被证明，ACA算法的结果在O（NlogN）的复杂性（其中N是未知数的数量）时，适用于静态和电气小电磁问题。在本文中，ACA算法扩展到电磁兼容相关的问题，中等电气尺寸。具体而言，ACA算法用于研究紧凑范围的接地平面和电磁干扰和屏蔽车辆。通过数值实验，得出结论，对于中等的电气尺寸的问题的ACA算法的内存和CPU时间的需求规模为N-4/3 logN。
This paper presents the adaptive cross approximation (ACA) algorithm to reduce memory and CPU time overhead in the method of moments (MoM) solution of surface integral equations. The present algorithm is purely algebraic; hence, its formulation and implementation are integral equation kernel (Green's function) independent. The algorithm starts with a multi-level partitioning of the computational domain. The interactions of well-separated partitioning clusters are accounted through a rank-revealing LU decomposition. The acceleration and memory savings of ACA come from the partial assembly of the rank-deficient interaction submatrices. It has been demonstrated that the ACA algorithm results in O (NlogN) complexity (where N is the number of unknowns) when applied to static and electrically small electromagnetic problems. In this paper the ACA algorithm is extended to electromagnetic compatibility-related problems of moderate electrical size. Specifically, the ACA algorithm is used to study compact-range ground planes and electromagnetic interference and shielding in vehicles. Through numerical experiments, it is concluded that for moderate electrical size problems the memory and CPU time requirements for the ACA algorithm scale as N-4/3 logN.