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Record W2021990876 · doi:10.1109/tpel.2012.2216901

Design, Analysis, and Optimization of Ironless Stator Permanent Magnet Machines

2012· article· en· W2021990876 on OpenAlex
I. Stamenkovic, Nikola Milivojević, N. Schofield, Mahesh Krishnamurthy, Ali Emadi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2012
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStatorDimensioningRotor (electric)MagnetFinite element methodElectromagnetic coilMechanical engineeringMagnetic fluxGenerator (circuit theory)EngineeringComputer sciencePower (physics)Control engineeringElectrical engineeringStructural engineeringMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

This paper presents a methodology for the design, analysis, and graphical optimization of ironless brushless permanent magnet machines primarily for generator applications. Magnetic flux in this class of electromagnetic machine tends to be 3-D due to the lack of conventional iron structures and the absence of a constrained magnetic flux path. The proposed methodology includes comprehensive geometric, magnetic and electrical dimensioning followed by detailed 3-D finite element (FE) modeling of a base machine for which parameters are determined. These parameters are then graphically optimized within sensible volumetric and electromagnetic constraints to arrive at improved design solutions. This paper considers an ironless machine design to validate the 3-D FE model to optimize power conversion for the case of a low-speed, ironless stator generator. The machine configuration investigated in this paper has concentric arrangement of the rotor and the stator, solenoid-shaped coils, and a simple mechanical design considered for ease of manufacture and maintenance. Using performance and material effectiveness as the overriding optimization criteria, this paper suggests optimal designs configurations featuring two different winding arrangements, i.e., radial and circumferentially mounted. Performance and material effectiveness of the studied ironless stator designs are compared to published ironless machine configurations.

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.

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: none
Teacher disagreement score0.960
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.209
Teacher spread0.203 · 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