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Record W4230929265 · doi:10.1109/intmag.2015.7156698

Adaptive meshing for eddy current calculations

2015· article· en· W4230929265 on OpenAlex
Delphine Dupuy, D. Pedreira, Demmy Verbeke, Vincent Leconte, P. Wendling, Loïc Rondot, Vincent Mazauric

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

Venue2015 IEEE Magnetics Conference (INTERMAG) · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsCenter for Diagnosis and Research on Alzheimer's Disease
Fundersnot available
KeywordsEddy currentTransient (computer programming)Computer scienceCurrent (fluid)Power (physics)Energy (signal processing)Electronic engineeringMechanicsEngineeringElectrical engineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Eddy currents are at the origin of losses and signal distorsions in power electrical. In order to address their considerable impacts on both the energy efficiency and the performance requirement, eddy current modeling and its accuraccy are discussed from a thermodynamic approach. Whereas adaptive meshing strategies were extensively used in static cases [1,2], some valuable results are carried out in an induction machine case-study, providing a general validation for transient regimes [3].

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.721
Threshold uncertainty score0.894

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.143
GPT teacher head0.336
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