Extended Multi-branch basis functions for non-conformal problems

Discontinuous Galerkin (DG) approaches [1] used to connect two non-conformal surfaces in the Method of Moments typical employ Interior Penalty (IP) methods to mitigate charge accumulation along the half RWG basis functions connection boundary. These IP approaches are introduced via a combined impedance matrix $(Z-\beta$. $I P$). Alternatively in soft non-conforming problems, Multi-branch (MB-RWG) basis functions can be utilized [2]. Generalizations of multibranch basis functions can lead to higher degress of nonconformality as the use of $N^{+}-N^{-}$ branches MB_RWG [3] when $N^{+}$ and $N^{-}$ triangles have common vertices at the endpoints of the shared countour, but not along the contour.

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Published
2024-09-02
DOI
https://doi.org/10.1109/iceaa61917.2024.10701706
Citations
1
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
Field-Weighted Citation Impact
0.37
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article

Extended Multi-branch basis functions for non-conformal problems

J. M. Taboada, Victor F. Martín, L. Landesa, Manuel Parejo
1 citations
Advanced Numerical Methods in Computational Mathematics
0.37
article

Extended Multi-branch basis functions for non-conformal problems

J. M. Taboada, Victor F. Martín, L. Landesa, Manuel Parejo
article en
1 citations

Abstract

Discontinuous Galerkin (DG) approaches [1] used to connect two non-conformal surfaces in the Method of Moments typical employ Interior Penalty (IP) methods to mitigate charge accumulation along the half RWG basis functions connection boundary. These IP approaches are introduced via a combined impedance matrix $(Z-\beta$. $I P$). Alternatively in soft non-conforming problems, Multi-branch (MB-RWG) basis functions can be utilized [2]. Generalizations of multibranch basis functions can lead to higher degress of nonconformality as the use of $N^{+}-N^{-}$ branches MB_RWG [3] when $N^{+}$ and $N^{-}$ triangles have common vertices at the endpoints of the shared countour, but not along the contour.

Universidad de Extremadura (ES)
Openalex Percentile: Top 42%
Advanced Numerical Methods in Computational Mathematics
0.37
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