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Record W4412068278 · doi:10.3390/fluids10070177

Experimental Investigation of the Entrainment Mechanism in Circular and Lobed Hemispherical Jets

2025· article· en· W4412068278 on OpenAlexaff
Saad Aldossary, Mouhammad El Hassan, Nikolay Bukharin, Kamel Abed-Meraïm, Anas Sakout

Bibliographic record

VenueFluids · 2025
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsSAIT Polytechnic
Fundersnot available
KeywordsEntrainment (biomusicology)Mechanism (biology)MechanicsPhysicsOpticsAcoustics

Abstract

fetched live from OpenAlex

Better mixing in the near-field region of jets with their surrounding fluid is of high interest for several industrial applications. Passive control that involves jet geometry modifications as compared to the traditional circular design is used in the present work. An analysis of the entrainment mechanism in the near jet-exit field is proposed for innovative hemispherical nozzles (circular and six-lobed). High-speed Time-Resolved Particle Image Velocimetry (TR-PIV) measurements are used to experimentally characterize the entrainment mechanism in these jets. The distributions of mean entrainment rates, shear layer growth, and momentum flux are investigated along the longitudinal direction within the near-field region of both circular and lobed hemispherical jets. Significant entrainment enhancement is found using the hemispherical geometry as a passive-control method. By comparing both investigated hemispherical nozzle geometries, it has been demonstrated that the lobed nozzle provides higher mixing rates compared to the circular jet. This enhancement in mixing can be attributed to the stronger streamwise vortex structures generated by the lobed nozzle geometry, which promote increased entrainment of the surrounding fluid.

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 score0.470
Threshold uncertainty score0.197

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 head0.194
Teacher spread0.190 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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