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Record W4410090398 · doi:10.1063/5.0272456

Design and test of a waveguide filter for reflected electromagnetic waves

2025· article· en· W4410090398 on OpenAlexaff
C. Fransoo, M. Nishiura, S. Kubo

Bibliographic record

VenueAIP Advances · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsUniversity of British Columbia
FundersJapan Society for the Promotion of Science
KeywordsElectromagnetic radiationOpticsWaveguidePhysicsAcousticsMaterials science

Abstract

fetched live from OpenAlex

A high power gyrotron system is used for plasma production and sustainment by electron cyclotron resonance heating (ECRH) in fusion reactors. An ECRH system in the Large Helical Device uses gyrotrons with megawatt output power. This megawatt electromagnetic wave transmitted through a circular corrugated waveguide is partially reflected back to the gyrotron and can be a cause of unstable gyrotron oscillations. The reflected beam may also propagate at an angle relative to the waveguide axis. To reduce the reflected beam while retaining as much of the forward-propagating gyrotron beam as possible, we aim to optimize the length of a filter consisting of a gap with absorbing walls between waveguide sections in a transmission line. A semi-analytical model is developed using diffraction theory to calculate the transmitted power of the HE11 mode as a function of filter gap distance for a wide range of beam angles, including a perfectly aligned beam to approximate the forward gyrotron beam. Before implementing this filter, we use a vector network analyzer to measure the scattering parameters for an experimental mock-up of this filter with 88.9 mm inner diameter waveguides, gap distances between 0 and 600 mm, and beam angles between 0° and 4°. These sophisticated models are used to inform the gap filter design and length optimization.

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 score0.444
Threshold uncertainty score0.345

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 head0.016
GPT teacher head0.327
Teacher spread0.311 · 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
Published2025
Admission routes1
Has abstractyes

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