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Record W2958563140 · doi:10.1109/access.2019.2928993

Solar-Panel Integrated Circularly Polarized Meshed Patch for Cubesats and Other Small Satellites

2019· article· en· W2958563140 on OpenAlexafffund
Symon K. Podilchak, Davide Comite, Brendan K. Montgomery, Yuepei Li, Victoria Gómez‐Guillamón Buendía, Yahia M. M. Antar

Bibliographic record

VenueIEEE Access · 2019
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsRoyal Military College of CanadaLockheed Martin (Canada)
FundersSamsungHorizon 2020 Framework ProgrammeNatural Sciences and Engineering Research Council of CanadaEuropean CommissionQueen's UniversitySapienza Università di Roma
KeywordsMicrostrip antennaBandwidth (computing)OpticsMaterials sciencePatch antennaAntenna (radio)Computer scienceOptoelectronicsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

This paper presents the design of a circularly polarized (CP) meshed patch antenna fully integrated within a solar panel for operation on CubeSats and other microsatellites. The structure has been designed to ensure optimal antenna performance at S-band as well as to minimize any shadowing effects that can reduce the received power at the solar cells. To generate CP, the antenna is driven by two orthogonal feed points, penetrating through a transparent borosilicate glass layer, as well as a silicon and PCB substrate. Simulated and measured performances, on both a preliminary FR4 design and a fully integrated prototype, demonstrate a good impedance bandwidth, satisfactorily axial ratio, as well as stable radiation patterns and minimum shadowing levels. The proposed antenna can be useful for communications between satellites as well as with the ground station, and since the structure is compact and completely integrated, the design can be an alternative approach to new-phased arrays on solar panels and other beam-steering systems.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.040
GPT teacher head0.250
Teacher spread0.210 · 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 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

Citations60
Published2019
Admission routes2
Has abstractyes

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