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Record W2154632690 · doi:10.1109/ias.1996.559271

Modeling and validation of asynchronous machine taking into account the saturation effects

2002· article· en· W2154632690 on OpenAlexaff
André B. Charette, Jianhong Xu, A. Lakhsasi, Ziwen Yao, V. Rajagopalan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversité du Québec à Trois-RivièresHydro-QuébecNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsInduction motorAsynchronous communicationSaturation (graph theory)Computer scienceSteady state (chemistry)Operating pointWork (physics)Control theory (sociology)Control engineeringEngineeringArtificial intelligenceVoltageMathematicsMechanical engineeringElectronic engineeringChemistry

Abstract

fetched live from OpenAlex

Induction motors play an important role in constant and adjustable speed drives. This paper contributes to the development of a realistic model for an induction machine taking into account saturation. We concentrate on the steady state analysis of a saturated induction machine and present a methodology for the evaluation of the validation of the parameters of a saturated induction machine. The validation of the machine model is presented under steady state conditions. This work provides a good starting point for the evaluation of steady state performance of asynchronous machines under saturated and unsaturated operating conditions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.162

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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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 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

Citations3
Published2002
Admission routes1
Has abstractyes

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