Abstract

The augmented electric field integral equation (A-EFIE) with charge neutrality enforcement provides a stable formulation to conquer low-frequency breakdown characteristic of conventional EFIE. It is augmented with additional charge unknowns through current continuity equation. The A-EFIE combined with the multilevel adaptive cross-approximation (MLACA) algorithm is developed to further reduce the memory requirement and computation time for analyzing electromagnetic problems. Numerical examples are given to demonstrate the accuracy and efficiency of the proposed method.

Highlights

  • Electromagnetic integral equations are often discretized with the method of moments (MoM) [1, 2], one of the most widespread and generally accepted techniques for electromagnetic problems

  • It is convenient to model objects with arbitrary shape using triangular patches; RWG functions are widely used for representing unknown current distributions

  • The augmented electric field integral equation (A-electric field integral equation (EFIE)) with charge neutrality enforcement (CNE) accelerated by the multilevel adaptive cross-approximation (MLACA) algorithm is presented for solving electromagnetic scattering and microstrip circuit problems

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Summary

Introduction

Electromagnetic integral equations are often discretized with the method of moments (MoM) [1, 2], one of the most widespread and generally accepted techniques for electromagnetic problems. The augmented electric field equation (A-EFIE) [16, 29,30,31,32,33] method has been proposed to solve the low-frequency problem without the loop-tree decomposition. Qian and Chew proposed a perturbation method for solving the possible low-frequency inaccuracy problem of A-EFIE [31]. Compared to the MLFMA, the multilevel adaptive crossapproximation (MLACA) algorithm [34,35,36] is another popular technique for analyzing scattering/radiation problems. It makes use of the well-known fact that the approximate rank of the submatrices is low when the subscatterers are sufficiently separated.

A-EFIE with MLACA Algorithm
Numerical Experiments
Method
Conclusions
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