MétaCan
Menu
Back to cohort
Record W2238970585 · doi:10.1049/iet-est.2015.0028

Double‐rotor switched reluctance machine design, simulations, and validations

2015· article· en· W2238970585 on OpenAlexafffund
Yinye Yang, N. Schofield, Ali Emadi

Bibliographic record

VenueIET Electrical Systems in Transportation · 2015
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
FundersCanada Excellence Research Chairs, Government of CanadaCanada Research Chairs
KeywordsSwitched reluctance motorRotor (electric)Reluctance motorMagnetic reluctanceComputer scienceMachine designControl theory (sociology)Control engineeringAutomotive engineeringEngineeringMechanical engineeringMagnetArtificial intelligence

Abstract

fetched live from OpenAlex

Double‐rotor switched reluctance machine (DRSRM) is a new type of switched reluctance machine that is composed of two rotors and one stator integrated in one machine housing, which is potentially more compact, lower cost, and enables two mechanical outputs suitable for hybrid electric transmissions. This study presents detailed design and simulation procedures of a DRSRM. Various electromagnetic design aspects are investigated to comprehensively analyse the DRSRM design. Loss analysis and thermal simulations are performed to evaluate the thermal loading, and a DRSRM drive model is built to simulate the DRSRM performance. Then a DRSRM prototype is manufactured and tested. The test results confirmed the design and simulations with good agreements.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.243
Teacher spread0.215 · 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 designSimulation or modeling
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

Citations21
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueIET Electrical Systems in TransportationSame topicElectric Motor Design and AnalysisFrench-language works237,207