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Record W4392452218 · doi:10.1063/5.0196888

Mixed finite element method in 3D for a nonlinear eddy current problem

2024· article· en· W4392452218 on OpenAlexaff
Montasser Hichmani, Marc Laforest, El Miloud Zaoui

Bibliographic record

VenueAIP conference proceedings · 2024
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsFinite element methodEddy currentNonlinear systemCurrent (fluid)Computer sciencePhysicsMechanicsElectrical engineeringEngineeringThermodynamics

Abstract

fetched live from OpenAlex

The purpose of this paper is to demonstrate the convergence of a mixed finite element formulation in 3D for a nonlinear eddy current problem encountered in the modelling of Type II superconductors. The eddy current problem models the magnetic field in a material with a power law magnetic resistivity which makes it an analogue of the p-Laplacian. Yet in contrast to the p-Laplacian, the resulting time-transient degenerate parabolic problem includes a divergence constraint and requires non-conforming elements. Numerical discretizations of this problem, sometimes referred to as the p-curl, have been studied by many, but the well-posedness of mixed formulations has only been established in 2D by Prigozhin and Barrett. This research extends earlier work of Farhloul on the p-Laplacian and discusses well-posedness both for the continuous and the discrete formulation using first-order Nédélec elements.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.950
Threshold uncertainty score0.732

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 science0.0000.000
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 head0.042
GPT teacher head0.329
Teacher spread0.287 · 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 designOther design
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
Published2024
Admission routes1
Has abstractyes

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