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Record W3152121954

Optimal L~∞ analysis of non-singular finite element methods/finite volume methods for the stationary 3D Navier-Stokes equations

2015· article· en· W3152121954 on OpenAlexaff
Li Jia

Bibliographic record

VenueScientia Sinica(Mathematica) · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFinite element methodMathematicsFinite volume methodRate of convergenceMixed finite element methodhp-FEMNorm (philosophy)Mathematical analysisExtended finite element methodFinite element limit analysisApplied mathematicsPhysicsMechanicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

In this paper,we develop and analyze the L~∞ stability and convergence analysis for non-singular finite element and finite volume solutions for the stationary 3D Navier-Stokes equations.We obtain optimal estimates for the gradient of velocity and the pressure in the L~∞-norm by applying the stabilization of a macro-element and technical lemmas including weighted L~2-norm estimates for the regularized Green's functions associated with the Stokes problem.Moreover,using the finite element solutions as interpolations,the relationship between the finite element method and the finite volume method is used to obtain the interesting super-close convergence rate with O(h~(3/2)) in the L~2-norm and the optimal rate with 0(h) in the L~∞-norm between the finite element method and the finite volume method for the velocity gradient and the pressure.Furthermore,optimal error estimates in the L~∞-norm are derived for the first time for the velocity gradient and pressure without a logarithmic factor O(|logh|) for the stationary 3D Naiver-Stokes equations.

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)0.008
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-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: Methods
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.092
GPT teacher head0.442
Teacher spread0.350 · 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.

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
Published2015
Admission routes1
Has abstractyes

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