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Record W2093958118 · doi:10.1541/ieejias.129.1048

A Description of a Design Method of a Claw Teeth Motor on the Basis of Three-Dimensional Reluctance Network Analysis

2009· article· en· W2093958118 on OpenAlex
T. Mizuguchi, K. Nakamura, Takayuki Koyama, O. Ichinokura

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

VenueIEEJ Transactions on Industry Applications · 2009
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsClawTorqueSwitched reluctance motorSpace (punctuation)IsotropyEngineeringStructural engineeringComputer scienceRotor (electric)Mechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Soft magnetic composites (SMCs) have the following advantages: three-dimensional magnetic isotropy, high resistivity, and recyclability. By using SMC, therefore, a new concept motor with a three-dimensional structure can be developed. Its power-to-space ratio and efficiency can be improved since the space factor of winding and the space utilization factor of the motor is increased. This paper describes a design method of a claw teeth motor made of SMC by reluctance network analysis (RNA)-based experimental design. First, a three-dimensional RNA model of the claw teeth motor is presented. Next, the RNA-based experimental design of the claw teeth motor is presented. As a result, the average torque is improved by approximately 50%. In addition, the calculation time required for the design is significantly reduced by the proposed design 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.

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: Methods · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.248
Teacher spread0.217 · 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