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Record W2074492088 · doi:10.1063/1.4773538

Design and development of 3 dB patch compensated tandem hybrid coupler

2013· article· en· W2074492088 on OpenAlexfundno aff
Rana Pratap Yadav, Sunil Kumar, S. V. Kulkarani

Bibliographic record

VenueReview of Scientific Instruments · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory Health
KeywordsReturn lossTandemCapacitorCompensation (psychology)Materials scienceComputer scienceWidebandHybrid couplerElectrical impedanceImpedance matchingElectronic engineeringPower dividers and directional couplersElectrical engineeringVoltageTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Design and development procedure of the strip line based 3 dB patch compensated tandem hybrid coupler at 91.2 ± 15 MHz and 2.5 kW is presented. The coupled strip-line structure is designed and electromagnetic analysis software is used for accurate modelling and optimization of parameters. Coupled strip lines are well known for poor impedance matching and poor isolation due to discontinuities, fabrication tolerance constraints, and theoretical approximations in design. These effects are realized and compensated or taken into consideration. The conventional methods of compensation like open stubs or lumped capacitors are useful in the low rf power applications only. In the present paper, patch compensation technique is explored, explained, applied, and incorporated in the development of a 3 dB tandem hybrid coupler. This newly explored patch compensation technique is found substantially effective in improving the overall performance in terms of return loss and isolation. A prototype tandem coupler rated for 2.5 kW at 91.2 ± 15 MHz, has been developed, fabricated, tested, and the effect of patch compensation technique is found to be quite effective.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.221
Teacher spread0.200 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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