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Record W2044560838 · doi:10.1109/antem.2010.5552501

Reflect-array study with shorted slotted ground plane using microtrip patches or rings as cell elements

2010· article· en· W2044560838 on OpenAlexaff
Saeed I. Latif, Cyrus Shafai, L. Shafai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGround planeAperture (computer memory)OpticsSTRIPSHFSSAntenna apertureMicrostripReflection (computer programming)Antenna (radio)Plane (geometry)Microstrip antennaPhysicsAcousticsComputer scienceRadiation patternGeometryTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Reflect-array antenna was introduced to replace parabolic reflectors, as they offer many advantages including beam steering, ease of fabrication, lightweight, etc.. The electromagnetic energy should reflect back when it hits the reflect-array surface. It has become very popular due to the advancement of printed antennas because of low surface profile, small mass and low cost. We have been studying microstrip rings as the cell element to obtain a reflect-array. When there is an aperture on the ground plane, the distance of the rings can be adjusted to obtain appropriate phases so that the electromagnetic energy can propagate through the ground plane or reflect back. The aperture size is another important parameter to obtain the reflection. When the aperture on the ground plane is partially shorted using a micrsotrip, the length of the aperture is essentially reduced, and the reflection from the structure can be achieved. In this paper, simulation results of the unit cell of a reflect-array are discussed, which is based on square rings with an aperture on the ground plane. The effects of the aperture size and the use of shorting strips are presented. The cell is in an infinite array environment. Simulations were carried out in Ansoft HFSS, version 12.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.749

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 integrity0.0000.000
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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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