Bourke, Samuel, Dawson, John orcid.org/0000-0003-4537-9977, Robinson, Martin orcid.org/0000-0003-1767-5541 et al. (1 more author) (2018) A Conformal Thin Boundary Model for FDTD. In: 2018 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO) (NEMO2018).
Abstract
Thin layer models are widely used in the finitedifference time-domain (FDTD) technique to efficiently model boundaries in multi-scale simulations as they significantly reduce simulation run-times and memory requirements. These models often utilise surface impedance boundary conditions (SIBCs) to represent the material of the boundary. Conformal meshes are a popular method of representing curved and non-aligned surfaces in FDTD. These meshes deform cells in the FDTD grid around the boundary between bulk materials so as to more accurately represent the shape of the material. Here we present an algorithm that combines the efficiency of a thin layer model with the accuracy of a conformal mesh. The algorithm is applied to three resonant cavity models and the accuracy verified using comparisons to non-conformal meshes and analytic solutions. Improvements are shown in the accuracy of the resonant frequencies and magnitude of the shielding effectiveness (SE) of the cavities. It is also shown to reduce the prevalence of extraneous features in the frequency response of the SE that are apparent when using a stair-cased mesh.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ©2018 IEEE |
Keywords: | Conformal Techniques,Finite-Difference Time-Domain,Surface-Impedance Boundary Condition,Thin Layer |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 01 Jun 2018 11:00 |
Last Modified: | 09 Jan 2025 00:14 |
Published Version: | https://doi.org/10.1109/NEMO.2018.8503410 |
Status: | Published |
Identification Number: | 10.1109/NEMO.2018.8503410 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131594 |