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Record W4210250784 · doi:10.1109/ted.2022.3144122

Multiport Relativistic Magnetron for Phased Array Application

2022· article· en· W4210250784 on OpenAlexaff
Renjie Cheng, Tianming Li, Jiaoyin Wang, Haiyang Wang, Hao Li, Yihong Zhou, Meiling Ou, Chaoxiong He, Fadhel M. Ghannouchi, Biao Hu

Bibliographic record

VenueIEEE Transactions on Electron Devices · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsPhase shift modulePhysicsPhased arrayElectrical engineeringPower (physics)Phase (matter)MicrowaveElectronic engineeringAmplitudeEngineeringTopology (electrical circuits)Antenna (radio)Optics

Abstract

fetched live from OpenAlex

A preliminary investigation on S-band multiport relativistic magnetron (RM) is carried out, which is targeted at the application of high-power microwave (HPM) phased array system. For such system, the phase synchronization and stabilization of sources are crucial. In the proposed multiport RM, the HPMs in four independent output ports are extracted from the same resonant system, thus having the same amplitude and phase naturally. Moreover, the output mode of such multiport RM is fundamental mode, which can achieve Gaussian radiation in the far field directly. Since mode convertors and phase-locked units are no longer necessary, it is beneficial to the miniaturization of HPM phased array system. To further control the phase of output signals, a wide side dimension adjustable phase shifter used for this multiport RM is designed, which could achieve 180° phase shift with a power handling capacity of 568 MW. Particle-in-cell (PIC) simulation of such multiport RM combined with phase shifters applied a diode voltage of 450 kV is carried out. When all output signals are adjusted to be in- phase, an average output power of 265 MW in each port can be obtained, corresponding to a power conversion efficiency up to 65%, and the relative phase differences are controlled within ±2.4%.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.001

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 head0.015
GPT teacher head0.303
Teacher spread0.287 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

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