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Record W4309211396 · doi:10.3390/eng3040033

A Novel Planar Power Divider/Combiner for Wideband High-Power Applications

2022· article· en· W4309211396 on OpenAlexaff
Hamed Tadayon, Mansoor Dashti Ardakani, Reza Karimian, Shahrokh Ahmadi, Mona Zaghloul

Bibliographic record

VenueEng—Advances in Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsWilkinson power dividerPower dividers and directional couplersWidebandHFSSBandwidth (computing)Current dividerElectronic engineeringFrequency dividerElectrical engineeringRadarEngineeringPlanarComputer sciencePower (physics)TelecommunicationsPhysics

Abstract

fetched live from OpenAlex

This manuscript presents a novel wideband power divider with high power handling capability. The power handling capacity of the power divider is increased through the use of grounded 50 ohm loads. The full circuit analysis of a single section of the proposed structure is presented utilizing even and odd modes and ABCD matrices. The final designed sections are cascaded and extended to achieve a high bandwidth response for the target of X-band. The structure was designed and optimized with the method of moments based on ADS software and simulated in HFSS for 3D full-wave analysis. A prototype module was fabricated and measured for experimental validation. The simulation results were confirmed by through measurements for the frequency band of 7–12 GHz (more than 52% fractional bandwidth). A divider such as the proposed one has a significantly higher power handling capacity than Wilkinson, as well as a wider frequency bandwidth than Gysel power dividers. As a wideband high-power power divider, the proposed device is ideal for high-data rate radar or satellite applications.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.965
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 integrity0.0000.000
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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations13
Published2022
Admission routes1
Has abstractyes

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