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Record W2076296677 · doi:10.1063/1.4717954

Spatial linear disturbances in a plane wall jet

2012· article· en· W2076296677 on OpenAlexafffund
Lars-Uve Schrader, Catherine Mavriplis, Luca Brandt

Bibliographic record

VenuePhysics of Fluids · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsInstabilityJet (fluid)Plane (geometry)Linear stabilityMechanicsLaminar flowZonal flow (plasma)MaximaAmplitudeFlow (mathematics)Classical mechanicsGeometryOpticsPlasmaTokamak

Abstract

fetched live from OpenAlex

A two-dimensional direct numerical simulation study of the linear instability in a laminar plane wall jet is presented. The evolution of the wall jet disturbances is in reasonable agreement with predictions by spatial linear stability theory only with regard to the wavelength and the amplitude shape of the disturbance, whereas significant differences in the linear growth rate are noticed. As a consequence, the “stable island” on the instability map based on linear stability theory turns out to be connected with the outer stable region in the simulations, thus taking the form of a “stable peninsula”. The failure of the theory is attributed to the rapid streamwise spread and decay of the wall jet, which is incompatible with the assumption of parallel flow. We also assess the maximum possible transient linear amplification of two-dimensional disturbances in the plane wall jet, using the concept of optimal initial disturbances. The transient energy growth relies on the Orr mechanism, and the upper bound of the disturbance energy increases linearly in time for the present flow configuration. The optimal disturbances exhibit local maxima near the edge of the jet and close to the wall, where sites of effective receptivity are hence expected. We find that the outer region of the plane wall jet is more receptive to time periodic forcing than the inner region.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.427

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 head0.010
GPT teacher head0.211
Teacher spread0.202 · 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.

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

Citations3
Published2012
Admission routes2
Has abstractyes

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