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Efficient and Accurate Simulations of Metamaterials Based on Domain Decomposition and Unit Feature Database
Recently, there has been tremendous interest in studying electromagnetic (EM) metamaterials. However, the full-wave simulations of large and complex metamaterials are challenging. This work proposes a novel technique for efficient and accurate simulations of metamaterials composed of finite types of...
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Published in: | IEEE transactions on antennas and propagation 2024-11, Vol.72 (11), p.8635-8646 |
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Main Authors: | , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Recently, there has been tremendous interest in studying electromagnetic (EM) metamaterials. However, the full-wave simulations of large and complex metamaterials are challenging. This work proposes a novel technique for efficient and accurate simulations of metamaterials composed of finite types of units. The technique follows the framework of finite element method and boundary element method (FEM-BEM) and treats the metamaterial units by domain decomposition method (DDM). Since there are finite types of units, the various couplings among them, including the self and mutual ones, can be fully captured by analyzing characteristic subarrays. The technique first performs such analyses with low memory and CPU costs and stores the results in a database. The stored data are then used in assembling the system matrix of the overall metamaterial. Thanks to this, it is applicable to large-scale arrays without recourse to overall modeling and meshing. Furthermore, the technique significantly reduces the computational burden since only the inverse matrices of finite types of units are calculated during the iteration process of DDM. The effectiveness and accuracy of the technique are validated by realistic numerical examples. The technique facilitates accurate and efficient analyses of metamaterials and will find practical value in engineering applications, especially the design, optimization, and planning of reconfigurable intelligent surfaces (RISs). |
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ISSN: | 0018-926X 1558-2221 |
DOI: | 10.1109/TAP.2024.3436679 |