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Record W2162068517

Parallel Analysis of Electrothermal Phenomena in a Dry Type Distribution Transformer

2002· article· en· W2162068517 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

VenueParallel Computing in Electrical Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec
Fundersnot available
KeywordsConjugate gradient methodTransformerSolverJoule heatingHeat transferMechanicsTopology (electrical circuits)Computer scienceApplied mathematicsElectrical engineeringMechanical engineeringMathematicsMathematical optimizationPhysicsEngineeringVoltage
DOInot available

Abstract

fetched live from OpenAlex

In this paper we describe the steps taken to solve electrothermal problems on distributed configurations. For that purpose, we computed the 3D temperature distribution in a dry type transformer, by solving the Poisson equation with source terms specific to the topology under scope, that is heat generation by Joule losses and Eddy currents, as well as natural cooling on the outside of the metal casing. Our approach is based on the assumption that the heat transfer in the electrical device is diffusion predominant. The solver used for this problem is the well-know BICCG (Block Incomplete Choleski Conjugate Gradient).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.758
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
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 head0.016
GPT teacher head0.257
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