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Record W2146958116 · doi:10.1109/ccece.2009.5090309

A new approach to minimize the cogging torque of axial flux pmg for under water applications

2009· article· en· W2146958116 on OpenAlexaff
Sanjida Moury, M. Tariq Iqbal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCogging torqueTorqueRotor (electric)Generator (circuit theory)TurbinePermanent magnet synchronous generatorWater turbineMagnetControl theory (sociology)Shunt generatorAutomotive engineeringMechanical engineeringComputer scienceEngineeringPhysicsPower (physics)

Abstract

fetched live from OpenAlex

The rotor of a typical water current turbine rotates below 100 rpm. In conventional hydro installation the generator is coupled to the turbine via a gear box, so that it can typically rotate at a speed of 1500 or 1800 rpm. The water current turbine can be simplified by eliminating the gear box and by using a low-speed generator, the rotor of which rotates at the same speed as the rotor of the turbine. The main design challenge for a direct driven Permanent Magnet Generator (PMG) is to minimize the cogging torque. Cogging torque is an inherent characteristic of PMGs and is caused by the geometry of the generator. In this paper a new approach to minimize the PMG cogging torque is proposed. Basic design of a low cogging torque generator is also provided.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.223
Teacher spread0.208 · 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
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

Citations2
Published2009
Admission routes1
Has abstractyes

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