Broadband solutions of potential integral equations with NSPWMLFMA

In this communication, a mixed-form multilevel fast multipole algorithm (MLFMA) is combined with the recently introduced potential integral equations (PIEs), also called as the A-phi system, to obtain an efficient and accurate broadband solver that can be used for the solution of electromagnetic scattering from perfectly conducting surfaces over a wide frequency range including low frequencies. The mixed-form MLFMA uses the nondirective stable planewave MLFMA (NSPWMLFMA) at low frequencies and the conventional MLFMA at middle/ high frequencies. Various numerical examples are presented to assess the validity, efficiency, and accuracy of the developed solver.Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) (117E113)Publisher's Versio

Solution of Potential Integral Equations with NSPWMLFMA

In this contribution, we present a numerical implementation of recently developed potential integral equations (PIEs) by using nondirective stable plane wave multilevel fast multipole algorithm (NSPWMLFMA). The proposed method is efficient and accurate to solve large scattering problems involving perfectly conducting bodies with geometrical details, which require dense discretizations with respect to the operating wavelength. Numerical results in the form of scattered field from various objects are provided to assess the accuracy and efficiency of PIEs solved using NSPWMLFMA

Broadband Analysis of Multiscale Electromagnetic Problems: Novel Incomplete-Leaf MLFMA for Potential Integral Equations

Recently introduced incomplete tree structures for the magnetic-field integral equation are modified and used in conjunction with the mixed-form multilevel fast multipole algorithm (MLFMA) to employ a novel broadband incomplete-leaf MLFMA (IL-MLFMA) to the solution of potential integral equations (PIEs) for scattering/radiation from multiscale open and closed surfaces. This population-based algorithm deploys a nonuniform clustering that enables to use deep levels safely and, when necessary, without compromising the accuracy resulting in an improved efficiency and a significant reduction for the memory requirements (order of magnitudes), while the error is controllable. The superiority of the algorithm is demonstrated in several canonical and real-life multiscale geometries