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Record W2546868444 · doi:10.1109/icelmach.2016.7732578

Performance of a high torque density induction motor with an integrated magnetic gear

2016· article· en· W2546868444 on OpenAlexaff
Dalia Zaky Abdelhamid, Andrew M. Knight

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMagnetic gearTorque densityTorqueMagnetInduction motorProcess (computing)Automotive engineeringComputer scienceEngineeringControl engineeringMechanical engineeringElectrical engineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

There have been a number of recent advancements in magnetic gears and pseudo direct drive permanent magnet (PM) machines with integrated magnetic gears. Despite these advances, there are a number of applications where induction machine drives are preferable. This paper investigates the feasibility of a pseudo direct drive induction machine with an integrated magnetic gear, and presents some of the difficulties in the design process as compared to the design process for PM machines. The performance of an induction machine with an integrated magnetic gear is investigated. This paper presents some of the loading characteristics of the proposed machine. A prototype design at small scale is developed, and simulation results demonstrate the potential for high torque density with good loading characteristics.

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 score0.302
Threshold uncertainty score0.256

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 head0.005
GPT teacher head0.164
Teacher spread0.158 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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