A Memory-Efficient Formulation of the Unconditionally Stable FDTD Method for Solving Maxwell's Equations

An unconditionally stable finite-difference time-domain (FDTD) method based on the weighted Laguerre polynomials (WLP) for solving Maxwell's equations had been proposed. In this paper, a memory efficient modification to the proposed methodology is described. In this novel modification, the dive...

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Veröffentlicht in:IEEE transactions on antennas and propagation 2007-12, Vol.55 (12), p.3729-3733
Hauptverfasser: Yi, Yun, Chen, Bin, Sheng, Wei-Xing, Pei, Yu-Ling
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Chen, Bin
Sheng, Wei-Xing
Pei, Yu-Ling
description An unconditionally stable finite-difference time-domain (FDTD) method based on the weighted Laguerre polynomials (WLP) for solving Maxwell's equations had been proposed. In this paper, a memory efficient modification to the proposed methodology is described. In this novel modification, the divergence theorem is introduced in the WLP-FDTD method, in which Maxwell's divergence equation replaces one of the curl equations. This leads to a more memory-efficient matrix equation and a more rapid computational speed. A numerical example considering a two dimensional (2-D) TE case is present to validate the efficiency of the proposed algorithm.
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subjects Algorithms
Antennas
Applied classical electromagnetism
Differential equations
Divergence
Electromagnetic wave propagation, radiowave propagation
Electromagnetism
electron and ion optics
Exact sciences and technology
Finite difference method
Finite difference methods
Finite difference time domain method
Fundamental areas of phenomenology (including applications)
Mathematical analysis
Mathematical model
Mathematical models
Maxwell equations
Maxwell's equations
Memory-efficient
Physics
Polynomials
Scattering
Sparse matrices
Tellurium
Time domain analysis
Two dimensional displays
unconditionally stable finite-difference time-domain
weighted Laguerre polynomials
title A Memory-Efficient Formulation of the Unconditionally Stable FDTD Method for Solving Maxwell's Equations
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