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Record W2291215841 · doi:10.1109/iemdc.2015.7409079

Free vibration analysis of a large hydroelectric generator and computation of radial electromagnetic exciting forces

2015· article· en· W2291215841 on OpenAlexaff
Hind Chit Dirani, Samuel Cupillard, Arezki Merkhouf, Sylvain Bélanger, A. Tounzi, Anne-Marie Giroux, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsHydro-QuébecÉcole de Technologie Supérieure
Fundersnot available
KeywordsStatorMultiphysicsModal analysisVibrationRotor (electric)Generator (circuit theory)Transient (computer programming)Normal modeElectromagnetic fieldElectromagneticsModalAcousticsEngineeringComputationFinite element methodComputer sciencePhysicsMechanical engineeringStructural engineeringElectronic engineeringPower (physics)Materials science

Abstract

fetched live from OpenAlex

Major causes of vibration in electrical machines come from electromagnetic sources. A serious problem may arise when the frequencies of the periodic exciting force are identical with, or close to, one of the natural frequencies of the machine. This paper presents a 2D modal analysis which calculates the natural frequencies and mode shapes of the stator and rotor of a large hydroelectric generator. The structural model takes into account the shape of the stator teeth and rotor poles. Moreover, a 2D electromagnetic transient simulation is performed in order to predict the frequencies and mode shapes of the electromagnetic exciting force. This advanced electromagnetic numerical simulation takes into account the winding sequence and the geometry of the rotor and stator given by the manufacturer. The purpose of this work is to validate a multiphysics tool for the future and recognize its advantages over the classical method.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.213
Teacher spread0.204 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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