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Record W2071060730 · doi:10.1063/1.3058706

Finite element method based on a minimization theorem to obtain unique magnetization distribution

2009· article· en· W2071060730 on OpenAlexaff
A.V. Farahani, J.D. Lavers, A. Konrad

Bibliographic record

VenueJournal of Applied Physics · 2009
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMagnetizationFinite element methodMagnetostaticsMagnetic fieldInternal energyMathematical analysisPhysicsPolarization (electrochemistry)MinificationMathematicsQuantum mechanicsMathematical optimizationThermodynamicsChemistry

Abstract

fetched live from OpenAlex

A new approach to obtain unique magnetization distribution M and the corresponding internal magnetic field H inside magnetic materials subject to an applied field is introduced. The proposed finite element method obtains M directly by finding the minimum of a given mathematical function WM(M) that can be interpreted as the sum of the internal free energy of polarization, and internal and external magnetic energies. According to a theorem in magnetostatics, the magnetization state that satisfies the constitutive equation minimizes WM(M) and is unique. It is shown that the numerical solution satisfies both the condition for a minimum state and the constitutive equation. Therefore there is theoretical confidence that the proposed method yields the unique distributions M and H.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.360

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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 designSimulation or modeling
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
Published2009
Admission routes1
Has abstractyes

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