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Record W2125656280 · doi:10.1109/vppc.2007.4544219

Low-Order Dynamic Magnetic Equivalent Circuits of Saturated Steel Laminations

2007· article· en· W2125656280 on OpenAlexaff
Ali Davoudi, Alireza Khaligh, Marco Amrhein, Patrick L. Chapman, Juri Jatskevich

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsInstream Energy Systems (Canada)University of British Columbia
Fundersnot available
KeywordsNonlinear systemLaminationModel order reductionMagnetic circuitEquivalent circuitBandwidth (computing)Computer scienceElectronic engineeringElectronic circuitSaturation (graph theory)Control theory (sociology)AlgorithmElectromagnetic coilEngineeringMaterials scienceMathematicsElectrical engineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

Physics-based modeling of laminated magnetic devices accurately represents underlying dynamic characteristics. However, these models are hard to formulate, oversimplified with crude approximations, and computationally intensive. In this paper, a high-fidelity magnetic equivalent circuit of steel lamination is set forth based on geometrical and material data. The nonlinearity imposed by saturation is also considered. Automated linear and nonlinear order-reduction techniques are introduced to mathematically extract the essential system dynamics in the desired bandwidth, thus preserving both accuracy and computational efficiency. The resulting reduced-order system is validated with hardware measurements and full-order simulation in both time and frequency domains.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations4
Published2007
Admission routes1
Has abstractyes

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