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Research and Development of WRD600: Innovations in High-Power Double-Ridge Waveguide Combiners for Ultra-Wideband Applications

2024· article· en· W4401114531 on OpenAlexaff
Mohamed Mamdouh M. Ali, Mostafa O. Shady, Mahmoud Elsaadany, Shoukry I. Shams, Ghyslain Gagnon, Ke Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsPolytechnique MontréalConcordia UniversityÉcole de Technologie SupérieureApollo Microwaves (Canada)
FundersSave the Manatee Club
KeywordsWidebandRidgePower (physics)OptoelectronicsElectrical engineeringElectronic engineeringTelecommunicationsMaterials scienceEngineering physicsComputer scienceEngineeringPhysicsGeology

Abstract

fetched live from OpenAlex

This paper proposes for the first time a novel double-ridge waveguide standard, the WRD600, tailored for high-power applications across a wide frequency range. Overcoming the operational constraints of existing standards, the WRD600 offers a 3:1 bandwidth (6–18 GHz) with a cutoff frequency at 4.45 GHz. Optimized dimensions ensure non-dispersive transmission behavior, which is essential for achieving a promising performance. In addition, a complete ultra-wideband 4-way power combining assembly is presented as an application for the proposed double-ridge standard. This includes building the test setup and experimentally validating the combining network from 6 to 18 GHz, where an agreement has been shown between the simulated and measured responses. The assembly achieves and demonstrates an output return loss and isolation levels better than 12.5 dB with a 0.8 dB insertion loss and power handling up to 6 KW.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.065
GPT teacher head0.390
Teacher spread0.326 · 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 designTheoretical or conceptual
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

Citations5
Published2024
Admission routes1
Has abstractyes

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