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Record W4412441854 · doi:10.1016/j.aeue.2025.155929

Compact wideband twofold orthomode transducer

2025· article· en· W4412441854 on OpenAlexaff
Mahmoud Gadelrab, Shoukry I. Shams, Mahmoud Elsaadany, Abdel-Razik Sebak

Bibliographic record

VenueAEU - International Journal of Electronics and Communications · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsMacEwan UniversityConcordia University
Fundersnot available
KeywordsWidebandTransducerAcousticsElectrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Satellite networks now play an important role in various applications due to their unique features of global coverage and mobility assistance. Low Earth Orbit (LEO) satellites are currently gaining popularity in the wireless communications community, as they will be heavily used in future wireless communication networks. To enable polarization diversity, satellite systems commonly use dual-polarized antennas. Orthomode transducers (OMTs) are deployed in such systems to feed the antennas with the two orthogonal polarizations. The objective OMT is featured with deep matching levels, high isolation levels between its ports as well as a compact cross-sectional footprint. In this article, we propose a twofold OMT that is suitable for LEO satellite ground station applications. The proposed design covers a bandwidth ratio of about 54.6% with a deep matching level and high isolation. The electrical cross-sectional size of the proposed design is 4 λ o by 2.2 λ o , where λ o is calculated at the central frequency of operation. This promotes the proposed design for MIMO satellite applications. Moreover, the prototype for the design is fabricated and compared, where the measured responses are in good agreement with the simulated ones. Finally, the proposed structure is studied for compatibility with the LEO satellite feeding structures regarding thermal, power, and passive intermodulation analysis. This analysis is a typical mandatory analysis for space qualified units in the space industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.260
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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