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Record W1485086738 · doi:10.1063/1.4922388

Study of coherent structures of turbulence with large wall-normal gradients in thermophysical properties using direct numerical simulation

2015· article· en· W1485086738 on OpenAlexafffund
Shawn K. Reinink, M. I. Yaras

Bibliographic record

VenuePhysics of Fluids · 2015
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsCarleton University
FundersAtomic Energy of Canada LimitedCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsTurbulencePhysicsMechanicsDirect numerical simulationVorticityConvectionVortexHeat transferBaroclinityBoundary layerThermodynamicsClassical mechanicsReynolds number

Abstract

fetched live from OpenAlex

Forced-convection heat transfer in a heated working fluid at a thermodynamic state near its pseudocritical point is poorly predicted by correlations calibrated with data at subcritical temperatures and pressures. This is suggested to be primarily due to the influence of large wall-normal thermophysical property gradients that develop in proximity of the pseudocritical point on the concentration of coherent turbulence structures near the wall. The physical mechanisms dominating this influence remain poorly understood. In the present study, direct numerical simulation is used to study the development of coherent vortical structures within a turbulent spot under the influence of large wall-normal property gradients. A turbulent spot rather than a fully turbulent boundary layer is used for the study, for the coherent structures of turbulence in a spot tend to be in a more organized state which may allow for more effective identification of cause-and-effect relationships. Large wall-normal gradients in thermophysical properties are created by heating the working fluid which is near the pseudocritical thermodynamic state. It is found that during improved heat transfer, wall-normal gradients in density accelerate the growth of the Kelvin-Helmholtz instability mechanism in the shear layer enveloping low-speed streaks, causing it to roll up into hairpin vortices at a faster rate. It is suggested that this occurs by the baroclinic vorticity generation mechanism which accelerates the streamwise grouping of vorticity during shear layer roll-up. The increased roll-up frequency leads to reduced streamwise spacing between hairpin vortices in wave packets. The density gradients also promote the sinuous instability mode in low-speed streaks. The resulting oscillations in the streaks in the streamwise-spanwise plane lead to locally reduced spanwise spacing between hairpin vortices forming over adjacent low-speed streaks. The reduction in streamwise and spanwise spacing between hairpin vortices causes them to interact more frequently by merging together and by breaking apart into smaller turbulence structures.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.469

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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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

Citations12
Published2015
Admission routes2
Has abstractyes

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