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Record W2989863498 · doi:10.1109/ecce.2019.8912850

Design of a PM-Assisted Synchronous Reluctance Motor Utilizing Additive Manufacturing of Magnetic Materials

2019· article· en· W2989863498 on OpenAlexaff
Maged Ibrahim, Fabrice Bernier, Jean-Michel Lamarre

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMagnetic reluctanceMagnetic flux leakageTorqueRotor (electric)LimitingMagnetAutomotive engineeringSynchronous motorInduction motorAC motorPower (physics)Direct torque controlMechanical engineeringLeakage (economics)Materials scienceComputer scienceEngineeringElectric motorElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a novel design for Permanent Magnet (PM) assisted Synchronous Reluctance (SynR) motors, where the rotor consists of alternate layers of PM and Soft Magnetic Composite (SMC) deposited on the rotor shaft using additive manufacturing. The proposed design eliminates the need for the bridges and/or center-posts. These features are essential for the rotor mechanical integrity in laminated SynR motors, but provide a path for performance-limiting leakage flux. Consequently, their elimination in the proposed design led to a superior torque, power and power factor compared to conventional SynR and PM-assisted SynR motors.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.194
Teacher spread0.184 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations19
Published2019
Admission routes1
Has abstractyes

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