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Record W4400726877 · doi:10.1109/tte.2024.3430201

Modal Characterization of a 12/8 Switched Reluctance Motor Stator-Housing Assembly

2024· article· en· W4400726877 on OpenAlexfundno aff
Ashish Kumar Sahu, Moien Masoumi, Francisco Juarez-Leon, Christopher J. Sensor, Scott MacDonald, Berker Bilgin

Bibliographic record

VenueIEEE Transactions on Transportation Electrification · 2024
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsSwitched reluctance motorModalStatorReluctance motorAutomotive engineeringStructural engineeringEngineeringMaterials scienceMechanical engineeringRotor (electric)Composite material

Abstract

fetched live from OpenAlex

There is an increasing research focus on computationally evaluating the acoustic noise and vibration of switched reluctance motors (SRMs) using finite element (FE) tools. The accuracy of the calculated acoustic behavior of an electric motor relies heavily on the fidelity of the FE model. The FE model of a stator-housing assembly poses a challenge due to the orthotropic behavior of electrical steel and the nonuniform geometry of the windings. This article introduces an experimental modal analysis approach to calculate the modal characteristics of a 12/8 SRM stator-housing assembly, investigating the effects of winding and housing on these characteristics. Additionally, the study involves analytical calculation and FE modeling, correlating the results with experimental values to enhance understanding and accuracy in predicting acoustic behavior. It also presents a polynomial function to calculate modal damping parameters and investigates the applicability of the analytical equations commonly used in the literature to the tested SRM.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.658
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.214
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 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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