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Record W2952152147 · doi:10.1109/tmtt.2019.2919630

Ka-Band 3-D-Printed Wideband Groove Gap Waveguide Orthomode Transducer

2019· article· en· W2952152147 on OpenAlexaff
Mohamed A. Abdelaal, Ahmed A. Kishk

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsWidebandBandwidth (computing)TransducerGroove (engineering)Impedance matchingExtremely high frequencyWaveguideEngineeringInsertion lossMaterials scienceAcousticsElectrical engineeringOpticsElectrical impedanceOptoelectronicsPhysicsTelecommunicationsMechanical engineering

Abstract

fetched live from OpenAlex

An orthomode transducer (OMT) that falls into the twofold symmetry category is designed at the Ka-band with 33.33% bandwidth. Groove gap waveguide (GGWG) technology is adapted to implement the design due to its suitability for millimeter-wave (mm-wave) frequencies as electrical contacts between different parts are not necessary. Moreover, two transitions are deployed to broaden the operating bandwidth. The first transition is GGWG to WR-28 standard waveguide, which also acts as a power combiner. The second transition is placed between two layers of GGWGs. This new OMT consists of two main sections, the OMT core section, and the assembly section of different parts. Each section is investigated and simulated separately; then the whole structure is simulated to validate the performance. A prototype is built using 3-D-printing technology with copper-electroplated surfaces. A back-to-back measurements technique indicated matching and isolation level better than 12.5 and 25 dB, respectively, for both polarizations over the entire band. Nevertheless, the insertion loss has an acceptable level over such bands.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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.

Study designBench or experimental
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

Citations36
Published2019
Admission routes1
Has abstractyes

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