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Record W1930118061

Design of low scattering struts for center-fed reflector antennas

2010· article· en· W1930118061 on OpenAlexaff
Mathieu Riel, Y. Brand, Y. Cassivi, Y. Demers, Peter de Maagt

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsTransCanada (Canada)
Fundersnot available
KeywordsScatteringReflector (photography)OpticsRadar cross-sectionBandwidth (computing)Center frequencyAntenna measurementAntenna height considerationsAntenna (radio)Periscope antennaPolarization (electrochemistry)PhysicsEngineeringElectrical engineeringTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

The struts supporting the feed in a center-fed antenna are known to generate scattered fields, therefore causing degradations in antenna performance such as increased sidelobe levels and peak gain reductions. In this paper, two different configurations of low scattering struts using hard electromagnetic surfaces have been designed and fabricated for Ku-band operation in a center-fed reflector antenna configuration. Compared to conventional metallic triangular rooftop cross-section struts, these two low scattering strut designs significantly improve the forward scattering performance in TM polarization over a large relative bandwidth. Measurements performed on a Ku-band center-fed reflector antenna with four hard surface low scattering struts show significant sidelobe level reductions, compared to the same antenna measured with four conventional metallic triangular rooftop cross-section struts. Detailed comparisons between measurements and predictions are presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.040
GPT teacher head0.259
Teacher spread0.218 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2010
Admission routes1
Has abstractyes

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