Parallel Wideband MLFMA for Analysis of Electrically Large, Nonuniform, Multiscale Structures

• Published in: IEEE transactions on antennas and propagation Vol. 67; no. 2; pp. 1094 - 1107
• Main Authors: Hughey, Stephen, Aktulga, H. M., Vikram, Melapudi, Lu, Mingyu, Shanker, Balasubramaniam, Michielssen, Eric
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accuracy; Adaptive algorithms; Algorithms; Broadband; Computational electromagnetics; Electromagnetic scattering; Integral equations; Method of moments; method of moments (MoM); MLFMA; multilevel fast multipole algorithm (MLFMA); Multiscale analysis; Parallel algorithms; Partitioning algorithms; Trees; Vegetation; Wideband
• ISSN: 0018-926X; 1558-2221
• DOI: 10.1109/TAP.2018.2882621

Electromagnetic scattering from electrically large objects with multiscale features is an increasingly important problem in computational electromagnetics. A conventional approach is to use an integral equation-based solver that is then augmented with an accelerator, a popular choice being a parallel multilevel fast multipole algorithm (MLFMA). One consequence of multiscale features is locally dense discretization, which leads to low-frequency breakdown and requires nonuniform trees. To the authors' knowledge, the literature on parallel MLFMA for such multiscale distributions capable of arbitrary accuracy is sparse; this paper aims to fill this niche. We prescribe an algorithm that overcomes this bottleneck. We demonstrate the accuracy (with respect to analytical data) and performance of the algorithm for both PEC scatterers and point clouds as large as <inline-formula> <tex-math notation="LaTeX">755{\lambda } </tex-math></inline-formula> with several hundred million unknowns and nonuniform trees as deep as 16 levels.