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Record W2059367477 · doi:10.1109/tmag.2011.2172783

Rotational Core Loss and Permeability Measurements in Machine Laminations with Reference to Permeability Asymmetry

2012· article· en· W2059367477 on OpenAlexafffund
Natheer Alatawneh, Pragasen Pillay

Bibliographic record

VenueIEEE Transactions on Magnetics · 2012
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsConcordia University
FundersHydro-Québec
KeywordsPermeability (electromagnetism)Eddy currentNuclear magnetic resonanceMaterials scienceMechanicsMagnetic fluxMagnetic hysteresisElectrical steelMagnetic fieldMagnetizationRelative permeabilityRotating magnetic fieldAsymmetryPhysicsComposite material

Abstract

fetched live from OpenAlex

Rotational core loss and vector magnetization in electrical steel laminations are investigated under the circular 2D rotating field. The loss under a rotating field is compared with the loss under a pulsating field, and the behavior of the dynamic hysteresis loops in both cases are explained with reference to permeability asymmetry. The permeability of the magnetic material under the rotating field tends to change based on the flux direction. Experimental data is obtained using a new test fixture based on an electromagnetic Halbach array, which is capable of measuring rotational and pulsating losses in circular steel laminations. The measurements were performed for M15 gauge 29 electrical steel material at three typical frequencies of industrial interest (60 Hz, 400 Hz, and 1 kHz), and results are presented and discussed. It is found that there is a relation between the direction of applied field and the permeability, in addition to a strong effect on the permeability in the case of rotational flux when compared to pulsating flux.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.279
Teacher spread0.224 · 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.

Study designObservational
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

Citations5
Published2012
Admission routes2
Has abstractyes

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