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Record W2333953388 · doi:10.2514/6.2013-3088

Code Verification of an unsteady RANS finite-element solver

2013· article· en· W2333953388 on OpenAlexaff
Alexander Hay, Stéphane Étienne, Dominique Pelletier, André Garon

Bibliographic record

Venue21st AIAA Computational Fluid Dynamics Conference · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceFinite element methodReynolds-averaged Navier–Stokes equationsSolverCode (set theory)Programming languageComputational scienceComputational fluid dynamicsStructural engineeringEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

We present a Code Verification procedure for unsteady turbulent flow solvers based on the URANS equations. Code Verification is performed using the Method of the Manufactured Solution with a physically realistic unsteady wall-bounded turbulent flow solution. Our Code Verification procedure is based on the separation of the spatial and temporal components in the numerical errors and aims at providing a practical and feasible procedure without resorting to the use of extremely intensive computational resources. We present the application of this procedure to our finite-element URANS solver with wall-functions.

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)0.010
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.024
GPT teacher head0.276
Teacher spread0.251 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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Same venue21st AIAA Computational Fluid Dynamics ConferenceSame topicAdvanced Numerical Methods in Computational MathematicsFrench-language works237,207