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Record W4417438838 · doi:10.1109/access.2025.3645202

Experimental Characterization and Finite Element Correlation of Rotor Stress\Strain for a High-Speed Permanent Magnet Synchronous Machine

2025· article· W4417438838 on OpenAlexfundno aff
Harsh Dipakkumar Patel, Ashish Kumar Sahu, Robert J. Sluban, Sudesh V. Pathirannahalage, Reemon Z. Haddad, Dhafar Al-Ani, Berker Bilgin

Bibliographic record

VenueIEEE Access · 2025
Typearticle
Language
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRotor (electric)Finite element methodStrain gaugeMagnetStress (linguistics)Synchronous motorControl theory (sociology)Wound rotor motorModal analysis

Abstract

fetched live from OpenAlex

A higher machine speed is an enabling factor in achieving a higher power density. However, higher speed poses a challenge to the structural integrity of the rotor, as the centrifugal force acting on the rotor increases quadratically with speed. This high stress may lead to failure in the rotor ribs and bridges of an Interior Permanent Magnet Synchronous Machine (IPMSM). This paper presents a high-speed rotor strain measurement experimental setup that uses strain gauges and a telemetry system to measure strain at critical locations of the IPMSM rotor up to 18,000 rpm. Strain measurements are conducted at both room and high temperature to emulate the operating conditions of a high-speed machine. The measured strain is then correlated with the results of the finite element analysis strain to evaluate the fidelity of the rotor stress model. Also, the effect of anisotropic mechanical properties of electric steel on rotor strain is investigated.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.255
Teacher spread0.246 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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