A Polar Scaling Technique for the Regularization of Strongly Singular and Strongly Near-Singular Helmholtz Surface Integrals Evaluated Over 2-D Domains

被引:0
|
作者
Vaughn, Brian J. [1 ]
机构
[1] Fermilab Natl Accelerator Lab, Batavia, IL 60510 USA
关键词
Method of moments; Integral equations; Electromagnetics; Vectors; Shape; Convergence; Accuracy; Numerical stability; Microwave theory and techniques; Mathematical models; method of moments (MoM); numerical Simulation; PRINCIPAL VALUE INTEGRALS; NUMERICAL EVALUATION; QUADRATURE; FORMULAS;
D O I
10.1109/TMTT.2024.3473744
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The numerical integration of expressions containing strong singularities or strong near-singularities has long been a challenging problem in the electromagnetics community. Much attention has been paid to this problem, as strong 1/R-2 singularities routinely appear when implementing electromagnetic simulation techniques like the method of moments (MoM). To date, several techniques, from singularity extraction to singularity cancellation (SC), have been employed to deal with problems that require the evaluation of 2-D strongly singular integrals. However, no single technique has been proposed that can deal with both strong singularities and strong near-singularities in a fully numerical manner for arbitrary 2-D domains. Moreover, it has been claimed that the Helmholtz-type strongly singular integral found in the MoM is convergent in a principal value sense, but this convergence value has yet to be proven mathematically. In this work, we will conduct the convergence proof and introduce a "polar scaling" change of variables method that may be used to evaluate Helmholtz integrals with both strong and weak singularities/near-singularities. The technique is fully numerical and can in principle be applied to any planar or curved polygon and any nonsingular basis function. We will also provide numerical results showing useful convergence behavior for integrals involving both exact and near-singularities.
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页数:16
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