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Record W2233604321 · doi:10.3970/fdmp.2010.006.203

Effects of Flow Pulsing on Passive Scalar Mixing in a Turbulent Round Jet

2010· article· en· W2233604321 on OpenAlexaff
A. Benaïssa, Ibrahim Yimer

Bibliographic record

VenueFDMP: Fluid Dynamics & Materials Processing · 2010
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsStrouhal numberMechanicsTurbulenceJet (fluid)PhysicsScalar (mathematics)Mixing (physics)InletOpticsReynolds numberMathematicsGeology

Abstract

fetched live from OpenAlex

This work presents a study on the effect of pulsing on a jet flow. Puls- ing is used to modify jet inlet conditions with the objective of improving mixing. In this experimental work, a jet was slightly heated so that temperature could be considered as a passive scalar. The spectral behaviour of velocity and the passive scalar temperature was analyzed along the jet axis with and without pulsing. Low frequency pulsing (f/fS < 0.05 fS the Strouhal frequency) modifies the spectral com- position of the velocity at the jet exit, but it does not affect the asymptotic profile reached in the fully developed region of the jet at approximately x/d = 30. The lower frequency pulsations travel far downstream and stay visible in the fully de- veloped region on both the velocity and temperature spectra. This pulsing affects slightly the scalar spectral composition at the jet exit for only the highest frequency used (f/fS = 0.04 (40 Hz) to 0.05 (80 Hz)). This indicates that mixing is improved since the change reflects mixing the main flow with the surrounding airflow. Also, the presence of low pulsing frequencies far downstream indicates the effect pro- duced at the jet exit lasts into the far field.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.003
GPT teacher head0.198
Teacher spread0.195 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

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