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Record W2332010370 · doi:10.3934/dcdsb.2001.1.495

Meshless method for the stationary incompressible Navier-Stokes equations

2001· article· en· W2332010370 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

VenueDiscrete and Continuous Dynamical Systems - B · 2001
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMathematicsNavier–Stokes equationsConvergence (economics)CompressibilityMathematical analysisIncompressible flowKernel (algebra)Applied mathematicsRegularized meshless methodHagen–Poiseuille flow from the Navier–Stokes equationsNumerical analysisFlow (mathematics)PhysicsSingular boundary methodGeometryFinite element methodMechanics

Abstract

fetched live from OpenAlex

Mathematical analysis is achieved on a meshless method for thestationary incompressible Stokes and Navier-Stokes equations. In particular,the Moving Least Square Reproducing Kernel (MLSRK) method is employed.The existence of discrete solution and its error estimate are obtained. As anumerical example for convergence analysis, we compute the numerical solutionsfor these equations to compare with exact solutions. Also we solve thedriven cavity flow numerically as a test problem.

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 categoriesnone
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 score0.933
Threshold uncertainty score0.573

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 head0.013
GPT teacher head0.285
Teacher spread0.272 · 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