Extracting modal field profiles from 3D unstructured transmission line modelling meshes for use as sources and observers

Sewell, Phillip; Vukovic, Ana; Benson, Trevor M.; Meng, Xuesong

Abstract

Large-scale three-dimensional (3D) electromagnetic simulations are commonly used as design and investigation tools in a wide variety of technological fields. It is not uncommon for both excitations and observation quantities to be expressed in terms of particular field profiles of feed waveguides. These may then be used to evaluate, e.g. scattering parameters. These field profiles must be obtained as a pre-processing task before the main simulation. Use of a theoretical field profile as an excitation to a discretised structure will typically cause a non-physical reflection. It is therefore more desirable in practice to use a field profile that is consistent with both the discretisation of the geometry and the 3D method of simulation. The authors present an approach to extracting these 2D field profiles from large-scale 3D unstructured meshes which are to be simulated with the unstructured transmission line modelling method. Discretised slices from the 3D mesh are extracted and incrementally extruded into a form suitable for consistent pre-processing. The impacts of all the parameters of the approach are investigated. Benchmarking is undertaken on both coaxial cable and microstrip waveguide feed structures showing that good quality results can be obtained straightforwardly.

Citation

Sewell, P., Vukovic, A., Benson, T. M., & Meng, X. (2017). Extracting modal field profiles from 3D unstructured transmission line modelling meshes for use as sources and observers. IET Science, Measurements and Technology, 11(6), 780-785. doi:10.1049/iet-smt.2016.0357

• Journal Article Type: Article
• Acceptance Date: Apr 13, 2017
• Online Publication Date: Sep 7, 2017
• Publication Date: Sep 1, 2017
• Deposit Date: Jul 24, 2018
• Publicly Available Date: Jan 7, 2019
• Electronic ISSN: 1751-8830
• Publisher: Institution of Engineering and Technology
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 6
• Pages: 780-785
• DOI: https://doi.org/10.1049/iet-smt.2016.0357
• Public URL: https://nottingham-repository.worktribe.com/output/1126135
• Publisher URL: https://ieeexplore.ieee.org/document/8025450?arnumber=8025450&tag=1
• PMID: 00041015