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Record W2106310544 · doi:10.1109/pac.1993.308756

Cavity RF mode analysis using a boundary-integral method

2002· article· en· W2106310544 on OpenAlexaff
M.S. de Jong, F.P. Adams

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsMatrix (chemical analysis)Mathematical analysisEigenvalues and eigenvectorsIntegral equationMagnetic fieldFinite element methodBoundary value problemSurface (topology)PhysicsRadio frequencyBoundary (topology)MathematicsMaterials scienceGeometryQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

A 3-dimensional boundary-integral method has been developed for RF cavity mode analysis. A frequency-dependent, homogeneous linear matrix equation is generated from a variant of the magnetic field integral equation (MFIE) where the domain of integration is a closed surface specifying the RF envelope of the cavity. Frequencies at which the MFIE has nonzero solutions are mode frequencies of the cavity, and the solutions are the corresponding surface magnetic field distributions. The MFIE can then be used to calculate the electric and magnetic field at any other point inside the cavity. Forward iteration is used to find the largest complex eigenvalue of the matrix at a specific frequency. This eigenvalue is 1 when the frequency corresponds to a cavity RF resonance. The matrix equivalent of the MFIE is produced by approximating the cavity surface by a set of perfectly conducting surface elements, and assuming that the surface magnetic field has constant amplitude on each element. The method can handle cavities with complex symmetries, and be easily integrated with finite-element heat-transfer and stress analysis codes.>

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.019
GPT teacher head0.300
Teacher spread0.282 · 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 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

Citations3
Published2002
Admission routes1
Has abstractyes

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