A new hybridization of MS-GEC and PO methods for study of electromagnetic scattering in waveguides
M. Hajji,
M. Aidi and
T. Aguili
Journal of Electromagnetic Waves and Applications, 2017, vol. 31, issue 15, 1596-1608
Abstract:
This paper proposes a new hybrid method called MS-GEC/PO. This method is based on the coupling between the multi-scale combined to generalized equivalent circuit method (MS-GEC) and the hybrid approach MoM-GEC/PO (MoM-GEC method coupled to Physical Optic method). The MS-GEC method, in its new formulation based on local modal operators, can reduce considerably the requirements (CPU time and memory resources) especially when the number of scales increases. However, the MoM-GEC/PO can reduce these requirements because it is based on a single test function permitting an important reduction of the manipulated matrices size. Consequently, applying the new hybridization MS-GEC/PO, we can take the advantageous of both of these methods assuring a multiple gain in requirements. In this paper, we present the new considered hybridization and we validate it on an example of application. The obtained results are in agreement with the MoM-GEC method.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/09205071.2017.1356752 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tewaxx:v:31:y:2017:i:15:p:1596-1608
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tewa20
DOI: 10.1080/09205071.2017.1356752
Access Statistics for this article
Journal of Electromagnetic Waves and Applications is currently edited by Mohamad Abou El-Nasr and Pankaj Kumar Choudhury
More articles in Journal of Electromagnetic Waves and Applications from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().