计算电磁学中快速模态的介绍

A. Baghai-Wadji
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引用次数: 0

摘要

只提供摘要形式。微波封装的特性和设计,预测新型互连结构的辐射指向性和干涉模式的需求,以及验证更简单模型的必要性,都需要严格的数值方法和允许并行计算的快速算法。为此,积分公式比微分公式似乎更有优势。计算电磁学中积分方程的各种形式涉及体积积分和表面积分,通常必须用数值方法求解。近三十年来,哈林顿矩量法(mom)已经成功地用于离散这些积分,并获得可靠的近似场解。然而,MoM有三个缺点:(1)得到的(频率相关的阻抗)矩阵是密集的。(2)相互作用系数(非对角矩阵元素)为傅里叶型积分,其数值计算相对耗时。(3)自旋系数(对角矩阵元素)是傅里叶型奇异积分,必须在柯西意义(Hadamard有限部分)下仔细计算。作者最近为消除这些缺点所做的努力导致了快速mom。在许多应用中,快速矩阵分析消除了(2)和(3)中的困难,如果与小波分析相结合,则缓解了(1)中的缺点。在本文中,作者首先简要指出了小波理论的有用特征,并强调了迭代技术在求解大型矩阵方程中的作用。然后,他将重点放在(2)和(3)中的问题上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An introduction to the fast-MoM in computational electromagnetics
Summary form only given. The characterisation and design of microwave packaging, and the need for predicting the radiation directivity and interference pattern of novel interconnect structures, and also the necessity for validating simpler models, all require rigorous numerical methods and fast algorithms which allow parallel computing. To this end integral- rather than differential-formulations seem to be advantageous. The various formulations of integral equations in computational electromagnetics involve volume and surface integrals, which, generally, have to be solved numerically. For nearly three decades Harrington's method of moments (MoMs) has been successfully used to discretize these integrals and to obtain reliable approximations to the field solutions. However, MoM has three drawbacks: (1) The resulting (frequency-dependent impedance) matrices are dense. (2) The interaction coefficients (nondiagonal matrix elements) are Fourier-type integrals, and their numerical calculation is comparatively time consuming. (3) The selfaction coefficients (diagonal matrix elements) are Fourier-type singular integrals, and have to be evaluated carefully in Cauchy's sense (Hadamard's finite part). The author's recent efforts to remove these drawbacks have led to the fast-MoM. In many applications fast-MoM eliminates the difficulties in (2) and (3), and if combined with the wavelet analysis relaxes the drawback in (1). In this review the author first briefly points out useful features of the wavelet theory, and emphasizes the role of iterative techniques for solving large matrix equations. He then focuses on the problems in (2) and (3).
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