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Record W2980656354 · doi:10.1063/1.5118891

Path to turbulence in a transitional asymmetric planar wake

2019· article· en· W2980656354 on OpenAlexafffund
Jean-Pierre Hickey, Khaled Younes

Bibliographic record

VenuePhysics of Fluids · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsWakePhysicsLaminar flowTurbulenceBoundary layerMechanicsSplitter plateFlow separationReynolds numberIntermittencyLaminar sublayerClassical mechanics

Abstract

fetched live from OpenAlex

We report on a transitional, high-resolution direct numerical simulation of a temporally developing planar asymmetric wake at Re = 4000 based on the mass flux deficit. The asymmetric wake is formed by a Blasius and a fully turbulent boundary layer on either side of an infinitely thin splitter plate. Such a setup has direct relevance in low-Reynolds number aeronautics where pressure gradients on an airfoil can relaminarize transitional wall-bounded flows, thus generating a half-laminar/half-turbulent wake. The spreading and normalized turbulence intensity of the asymmetric wake are lower than the initially fully laminar wake but greater than the initially turbulent wake. In the far-field, the flow reaches a fully symmetric and nearly self-similar state with a high level of structural organization, originating from the transition of the laminar side. The structures are generated by the mutual interaction of the turbulent/laminar half-wakes. A forcing from the turbulent side accelerates the development of spanwise-organized structures on the laminar side, which evolve and develop a high-level of spanwise coherence. Unlike the classical transitioning wakes, the pairing of the roller is bypassed. Instead, the spanwise-aligned bulges appear from the initially turbulent half-wake. Under the local shear of the Blasius boundary layer, these bulges undergo a “kinking-and-stretching” mechanism similar to that of the mixing layer. The spanwise organization of the structures is maintained far downstream.

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)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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