MétaCan
Menu
Back to cohort
Record W2115425571 · doi:10.1109/epec.2010.5697236

Design of bilateral Switched Reluctance linear generator

2010· article· en· W2115425571 on OpenAlexaff
Hao Chen, Xinyu Wang, Jason Gu, Shengli Lu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSwitched reluctance motorStatorMagnetic reluctanceReluctance motorPrime moverGenerator (circuit theory)Yoke (aeronautics)Control theory (sociology)Air gap (plumbing)EngineeringComputer scienceElectrical engineeringPower (physics)Rotor (electric)PhysicsMagnetMaterials science

Abstract

fetched live from OpenAlex

The paper presented the design objective of three-phase 6/4 structure long-mover bilateral Switched Reluctance linear generator. The structure, the main design parameters include air gap length, unit stator poles numbers, mover poles numbers, mover tooth width, stator tooth width, mover polar distance, stator polar distance, mover width, stator width, mover slot depth, stator slot depth, mover yoke height, stator yoke height and stator unit length are described. The calculation method of electric load and magnetic load are also given. The selection methods and the calculation methods of the main design parameters are also presented. The design procedure and example of a developed prototype with rated output power 200 W, rated velocity 2 m/s, and output voltage for windings 24V are given. The design of Switched Reluctance linear generator is accomplished by analogy analysis between Switched Reluctance rotary generator. The length of air gap of the Switched Reluctance linear generator is bigger than that of Switched Reluctance rotary generator. The mover yoke height in bilateral Switched Reluctance linear generator is twice as same as that in unilateral Switched Reluctance linear generator.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.565
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicElectric Motor Design and AnalysisFrench-language works237,207