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Record W2258150847 · doi:10.1063/1.4949267

The effect of Prandtl number on mixing in low Reynolds number Kelvin-Helmholtz billows

2016· article· en· W2258150847 on OpenAlexafffund
Mona Rahmani, Brian R. Seymour, Gregory A. Lawrence

Bibliographic record

VenuePhysics of Fluids · 2016
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsWestern Canada Research Grid
KeywordsPrandtl numberTurbulent Prandtl numberReynolds numberPhysicsMixing (physics)TurbulenceMechanicsMagnetic Prandtl numberClassical mechanicsThermodynamicsNusselt numberConvection

Abstract

fetched live from OpenAlex

The effect of Prandtl number on mixing in temporally evolving Kelvin-Helmholtz (KH) instabilities at low to moderate Reynolds numbers is studied through direct numerical simulation. We distinguish between the mixing induced by the primary billow and the mixing generated by three-dimensional motions by performing each simulation in two and three dimensions. The results indicate that the time evolution of the rate of two- and three-dimensional mixing through different stages of the life cycle of KH flow is significantly influenced by the Prandtl number. As the Prandtl number increases, the final amount of mixing increases for Reynolds that are too low to support active three-dimensional motions. This trend is the opposite in sufficiently high Reynolds number KH flows that can overcome viscous effects and develop significant three-dimensional instabilities. While the mixing generated in the two-dimensional flows, uniform in the span-wise direction, is not significantly dependent on the Prandtl number, the turbulent mixing induced by three-dimensional motions is a function of the Prandtl number. We observe a steady increase in the total amount of mixing for buoyancy Reynolds numbers above 7, consistent with the results of Shih et al. [“Parameterization of turbulent fluxes and scales using homogeneous sheared stably stratified turbulence simulations,” J. Fluid Mech. 525, 193-214 (2005)]. Both maximum instantaneous and cumulative mixing efficiencies exhibit a decreasing trend with increasing Prandtl number. We compare the dependence of the mixing efficiency on Prandtl number to previous studies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.503

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 head0.004
GPT teacher head0.213
Teacher spread0.209 · 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 designBench or experimental
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

Citations21
Published2016
Admission routes2
Has abstractyes

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