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Record W2320280295 · doi:10.7227/ijmee.38.3.3

Use of Linear Graphs and Thevenin/Norton Equivalent Circuits in the Modeling and Analysis of Electro-Mechanical Systems

2010· article· en· W2320280295 on OpenAlex

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

VenueInternational Journal of Mechanical Engineering Education · 2010
Typearticle
Languageen
FieldComputer Science
TopicEvolutionary Algorithms and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThévenin's theoremEquivalent circuitMechanical systemComputer scienceNetwork analysisDomain (mathematical analysis)Electronic circuitCoupling (piping)Nonlinear systemLinear systemControl engineeringMathematicsEngineeringMechanical engineeringElectrical engineeringPhysicsMathematical analysisArtificial intelligenceVoltage

Abstract

fetched live from OpenAlex

This paper presents a unified approach for the modeling and analysis of electro-mechanical systems. First, the need for a unified approach is justified in view of the presence of electro-mechanical dynamic coupling. Next, linear graphs are promoted as a useful tool for unified modeling of multi-domain systems, where the existing analogies across domains can be exploited. Finally, Thevenin's theorem is extended to mechanical systems. Specifically, equivalent circuits of Thevenin and Norton are integrated with linear graphs, in the frequency domain, to facilitate analytical modeling. The choice of a particular equivalent circuit is shown to depend on the problem objective. Worked examples are provided throughout to illustrate the approaches presented in the paper.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.272
Teacher spread0.252 · 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