Scale-Compressed Technique in Finite-Difference Time-Domain Method for Multi-Layered Anisotropic Media | IEEE Journals & Magazine | IEEE Xplore

Scale-Compressed Technique in Finite-Difference Time-Domain Method for Multi-Layered Anisotropic Media


The research is divided into two parts, theoretical derivation and algorithm implementation. By applying SCT to the Maxwell equation for a completely new treatment, an up...

Abstract:

In this article, to breakthrough the constraint from conventional finite-difference time-domain (FDTD) method, we firstly propose a scale-compressed technique (SCT) worki...Show More

Abstract:

In this article, to breakthrough the constraint from conventional finite-difference time-domain (FDTD) method, we firstly propose a scale-compressed technique (SCT) working for the FDTD method, been called SCT-FDTD for short, to reduce three-dimensional (3-D) into one-dimensional (1-D) processes and capture the propagation coefficients. Combining with Maxwell's curl equations, the transverse wave vectors (kx, ky) can be defined as the fixed values, which let the curl operator become the curl matrix with only z-directional derivative. The obvious advantage demonstrated by above is that it does not require excessive computational processes to obtain high-dimensional numerical results with reasonable accuracy. By comparing with commercial software COMSOL by the TE/TM illumination in multi-layered biaxial anisotropy, those results from SCT-FDTD method are entirely consistent. More importantly, the SCT-FDTD possesses less CPU time and lower computational resources for COMSOL.
The research is divided into two parts, theoretical derivation and algorithm implementation. By applying SCT to the Maxwell equation for a completely new treatment, an up...
Page(s): 85 - 93
Date of Publication: 31 December 2024

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I. Introduction

With the advancement of modern equipment, such as antennas and microwave circuits, several complex structures are designed and expanded into its application. It is known that electromagnetic propagation can be absorbed effectively with the anisotropic coatings for the military aircraft surface, which avoid the enemy radar monitoring [1]. In other engineering application, such as geological exploration, deep-sea discovery, and integrated optics, we will face more anisotropic materials as their background. However, the current algorithms are all stuck in the technical processing of geometric meshing in three-dimensional (3-D) space [2], and many high-performance methods are considered to solve these anisotropic problems [3]. Therefore, how to improve the current algorithms and save the computer memory is meaningful research.

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References

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