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Record W2160411724 · doi:10.1109/tmag.2009.2022742

A Novel Superposition RBF Collocation Method to Solve Moving Conductor Eddy Current Problems

2009· article· en· W2160411724 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Magnetics · 2009
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEddy currentSuperposition principleConductorCollocation methodMagnetic fieldEquations of motionPhysicsRadial basis functionCurrent (fluid)Electromagnetic fieldComputer scienceMathematical analysisMechanicsClassical mechanicsDifferential equationMathematicsGeometryArtificial neural network

Abstract

fetched live from OpenAlex

This paper presents a novel radial basis function (RBF) collocation method to solve the moving conductor eddy current problem. The magnetic field is considered an addition of two fields generated respectively by the excitation current and the eddy current according to the source superposition principle. The corresponding governing equations are decoupled and solved with the RBF. Moving coordinate systems in which the separate fields are computed are also constructed to avoid the model reconfiguration caused by the motion. Electromagnetic field equations are analyzed with kinetic equations and circuit equations together to simulate the motion process. A practical engineering problem is computed to verify the method.

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.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.279
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
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.292
Teacher spread0.266 · 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