MétaCan
Menu
Back to cohort
Record W2158923164 · doi:10.1109/ias.1991.178147

Modeling and performance of linear induction motor with saturable primary

2002· article· en· W2158923164 on OpenAlexaff
K. Idir, G.E. Dawson, A.R. Eastham

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsYoke (aeronautics)Linear induction motorRepresentation (politics)ComputationInduction motorComputer sciencePrimary (astronomy)Saturation (graph theory)Topology (electrical circuits)Electronic engineeringAlgorithmEngineeringPhysicsMathematicsSimulationElectrical engineering

Abstract

fetched live from OpenAlex

A two-dimensional electromagnetic field analysis of the single-sided linear induction motor (LIM) is presented, taking into account saturation in both primary and secondary cores. An analytical layer model has been developed in which the primary core is modeled by two different layers representing the yoke and teeth-slot regions. Such representation facilitates the evaluation of the magnetic state of the primary yoke and teeth separately. A generalized mathematical formulation of a multilayer model is presented. The analytical computation results from a seven-layer model correlate very well with experimental results obtained from an intermediate capacity transit system LIM. The model is well suited for sensitivity analysis and design studies.>

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.162
Teacher spread0.151 · 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

Citations24
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicElectric Motor Design and AnalysisFrench-language works237,207