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Record W2113812915 · doi:10.1109/tec.2002.805227

Use of a permeance model to predict force harmonic components and damper winding effects in salient-pole synchronous machines

2002· article· en· W2113812915 on OpenAlexaff
Andrew M. Knight, Haran Karmaker, K. Weeber

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2002
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsGeneral Electric (Canada)University of Alberta
Fundersnot available
KeywordsPermeanceDamperHarmonicsFinite element methodSalientHarmonicHarmonic analysisControl theory (sociology)Electromagnetic coilShock absorberSynchronous motorEngineeringStructural engineeringComputer sciencePhysicsElectronic engineeringAcousticsElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents a combined finite-element and analytical modeling technique for the prediction of force-density harmonics in salient-pole synchronous machines. The model calculates the induced currents in the damper winding cage and includes their effect on force-density components in the solution. Use of a combined analytical and finite-element approach considerably reduces simulation times compared to full time-stepping finite-element solutions, while including the effects of design changes on air-gap force harmonics. Results of the model predictions are presented together with measured data from two different machines.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.211
Teacher spread0.187 · 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
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

Citations52
Published2002
Admission routes1
Has abstractyes

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