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Record W1966011011 · doi:10.1063/1.3234398

Capturing transition features around a wing by reduced-order modeling based on compressible Navier–Stokes equations

2009· article· en· W1966011011 on OpenAlexaff
Rémi Bourguet, Marianna Braza, A. Sévrain, A. Bouhadji

Bibliographic record

VenuePhysics of Fluids · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicModel Reduction and Neural Networks
Canadian institutionsBallard Power Systems (Canada)
Fundersnot available
KeywordsMach numberNavier–Stokes equationsReynolds numberMathematicsCompressibilityFlow (mathematics)Compressible flowGalerkin methodWingProjection (relational algebra)Mathematical analysisPhysicsMechanicsGeometryFinite element methodAlgorithmTurbulence

Abstract

fetched live from OpenAlex

The three-dimensional transition in the flow around a NACA0012 wing of constant spanwise section at Mach number 0.3, Reynolds number 800, and incidence 20° is investigated by direct numerical simulation and reduced-order modeling. The interaction between the von Kármán and the secondary instabilities is analyzed. Irregular events in the flow transition modulating the spanwise undulation are highlighted and quantified. These transition features, including “local intermittencies” in the secondary instability pattern, are efficiently captured by a reduced-order model derived by means of the Galerkin projection of the compressible flow Navier–Stokes equations onto a truncated proper orthogonal decomposition basis.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 head0.023
GPT teacher head0.267
Teacher spread0.244 · 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

Citations24
Published2009
Admission routes1
Has abstractyes

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