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Record W2334528010 · doi:10.1109/tia.2016.2551683

Design of a Sinusoidally Wound 2-D Rotational Core Loss Setup With the Consideration of Sensor Sizing

2016· article· en· W2334528010 on OpenAlex
John Wanjiku, Pragasen Pillay

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2016
Typearticle
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaHydro-Québec
KeywordsSizingElectrical engineeringCore (optical fiber)Materials scienceElectronic engineeringControl theory (sociology)EngineeringComputer sciencePhysicsAutomotive engineeringOpticsChemistry

Abstract

fetched live from OpenAlex

The design of a two-dimensional rotational core loss setup that considers sensor sizing and the airflux leakage field is presented. The length of the flux density (B) coils is evaluated based on the magnetic degradation caused by holes used to locate the B-coils. The measured core loss is shown to be independent of the planar magnetic field (H) coil size, but depends on the location and the thickness of the enclosed core area. This determines the extent of the airflux leakage field in the measured field. This field links through the air close to the sample surface, and is shown to bias the shape, magnitude, and phase of the measured magnetic field. Core losses measured using three testers show that the airflux leakage field reduces with increasing magnetizer diametrical size. However, it is independent of the stack length in compact magnetizers. Finally, the performance of the proposed magnetizer is assessed at 60 Hz, 400 Hz, and 1 kHz.

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 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: none
Teacher disagreement score0.931
Threshold uncertainty score0.349

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 head0.026
GPT teacher head0.239
Teacher spread0.213 · 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