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Record W2015846210 · doi:10.1002/cnm.859

A numerical study of primal mixed finite element approximations of Darcy equations

2006· article· en· W2015846210 on OpenAlexafffund
José Urquiza, D. N' Dri, A. Garon, Michel C. Delfour

Bibliographic record

VenueCommunications in Numerical Methods in Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsUniversité de MontréalPolytechnique MontréalUniversité du Québec à Montréal
FundersUniversité Laval
KeywordsFinite element methodMathematicsConvergence (economics)Darcy's lawPiecewisePiecewise linear functionMixed finite element methodApplied mathematicsNumerical analysisExtended finite element methodMathematical analysisPorous mediumPhysics

Abstract

fetched live from OpenAlex

Abstract A numerical study of several finite element approximations for the primal mixed formulation of the Darcy equations is presented. In all cases the pressure is approximated by continuous piecewise‐linear functions. The difference between each scheme is in the choice of the finite element approximation space for the velocity. Numerical tests confirm the theoretical convergence of some of these schemes and we investigate the convergence properties of schemes for which theoretical results are not available. Numerical results for some 2D problems suggest that some of the new schemes provide better convergence properties for the velocity. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.003
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.066
GPT teacher head0.396
Teacher spread0.329 · 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

Citations12
Published2006
Admission routes2
Has abstractyes

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