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Record W2988665433 · doi:10.1017/jfm.2019.164

An empirical expression for on the axis of a slightly heated turbulent round jet

2019· article· en· W2988665433 on OpenAlexaff
Jean Lemay, L. Djenidi, R. A. Antonia, A. Benaïssa

Bibliographic record

VenueJournal of Fluid Mechanics · 2019
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsRoyal Military College of CanadaUniversité Laval
Fundersnot available
KeywordsUnicodePhysicsComputer science

Abstract

fetched live from OpenAlex

Self-preservation analyses of the equations for the mean temperature and the second-order temperature structure function on the axis of a slightly heated turbulent round jet are exploited in an attempt to develop an analytical expression for $\unicode[STIX]{x1D716}_{\unicode[STIX]{x1D703}}$ , the mean dissipation rate of $\overline{\unicode[STIX]{x1D703}^{2}}/2$ , where $\overline{\unicode[STIX]{x1D703}^{2}}$ is the temperature variance. The analytical approach follows that of Thiessetet al.(J. Fluid Mech., vol. 748, 2014, R2) who developed an expression for $\unicode[STIX]{x1D716}_{k}$ , the mean turbulent kinetic energy dissipation rate, using the transport equation for $\overline{(\unicode[STIX]{x1D6FF}u)^{2}}$ , the second-order velocity structure function. Experimental data show that complete self-preservation for all scales of motion is very well satisfied along the jet axis for streamwise distances larger than approximately 30 times the nozzle diameter. This validation of the analytical results is of particular interest as it provides justification and confidence in the analytical derivation of power laws representing the streamwise evolution of different physical quantities along the axis, such as: $\unicode[STIX]{x1D702}$ , $\unicode[STIX]{x1D706}$ , $\unicode[STIX]{x1D706}_{\unicode[STIX]{x1D703}}$ , $R_{U}$ , $R_{\unicode[STIX]{x1D6E9}}$ (all representing characteristic length scales), the mean temperature excess $\unicode[STIX]{x1D6E9}_{0}$ , the mixed velocity–temperature moments $\overline{u\unicode[STIX]{x1D703}^{2}}$ , $\overline{v\unicode[STIX]{x1D703}^{2}}$ and $\overline{\unicode[STIX]{x1D703}^{2}}$ and $\unicode[STIX]{x1D716}_{\unicode[STIX]{x1D703}}$ . Simple models are proposed for $\overline{u\unicode[STIX]{x1D703}^{2}}$ and $\overline{v\unicode[STIX]{x1D703}^{2}}$ in order to derive an analytical expression for $A_{\unicode[STIX]{x1D716}_{\unicode[STIX]{x1D703}}}$ , the prefactor of the power law describing the streamwise evolution of $\unicode[STIX]{x1D716}_{\unicode[STIX]{x1D703}}$ . Further, expressions are also derived for the turbulent Péclet number and the thermal-to-mechanical time scale ratio. These expressions involve global parameters that are most likely to be influenced by the initial and/or boundary conditions and are therefore expected to be flow dependent.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.257
Teacher spread0.242 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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