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Record W2134844427 · doi:10.5539/cis.v3n3p158

Development of Design and Analysis Tool for Switched Reluctance Drive System

2010· article· en· W2134844427 on OpenAlexvenueno aff
Shoujun Song, Weiguo Liu

Bibliographic record

VenueComputer and Information Science · 2010
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSwitched reluctance motorComputer scienceMATLABGraphical user interfaceDesign toolBasis (linear algebra)Nonlinear systemInterface (matter)Control engineeringMagnetic reluctanceDevelopment (topology)Programming languageMechanical engineeringOperating systemEngineering

Abstract

fetched live from OpenAlex

Switched reluctance drive (SRD) system has been used in many applications. However, because of its inherent nonlinearity, the design and analysis of SRD system is relatively difficult. In this paper, the development of design and analysis tool for SRD system based on MATLAB/GUIDE is studied. Firstly, the steps for the development of graphical user interface (GUI) by MATLAB/GUIDE are summarized. Then, two tools, namely switched reluctance machine (SRM) design tool and converter thermal analysis tool, are presented as examples. The theoretical basis, structure and functions of both tools are presented. Results from each tool are given as well.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.178

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 communication0.0000.001
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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2010
Admission routes1
Has abstractyes

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