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Record W2031642755 · doi:10.1109/iemdc.2013.6556152

The influence of rotating field direction on core losses in electrical machine laminations

2013· article· en· W2031642755 on OpenAlexaff
Natheer Alatawneh, Pragasen Pillay

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsConcordia University
Fundersnot available
KeywordsStatorElectrical steelExcitationFixtureCore (optical fiber)Magnetic fieldAcousticsMagnetMaterials scienceElectrical engineeringReversingTest fixtureRotating magnetic fieldField (mathematics)Nuclear magnetic resonancePhysicsMechanical engineeringEngineeringOpticsMathematics

Abstract

fetched live from OpenAlex

The measurements of rotational core loss in machine laminations show significant differences in losses when the rotating field reverses its direction from clockwise (CW) to counterclockwise (CCW) direction of excitation. A novel design of a magnetizing test fixture based on an electromagnetic Halbach array is used to perform measurements on a non oriented silicon steel sample of M36G29 at three different frequencies of interest to the industry 60 Hz, 400 Hz, and 1 kHz. The experimental results are fed to three types of electrical machine models, 2-pole induction machine (IM), 6-4 switched reluctance motor (SRM), and 2-pole brushless DC machine (BLDC) to investigate the effect of reversal of the rotating field direction on the delivered core loss in the stator. Results reveal that the IM experiences the highest effect of field reversing followed by the BLDCM, and then the SRM which is the least affected.

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 score0.323
Threshold uncertainty score0.444

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 head0.011
GPT teacher head0.248
Teacher spread0.238 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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