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Record W2161262962 · doi:10.1115/1.3000970

Mixed Convection in an Impinging Laminar Single Square Jet

2008· article· en· W2161262962 on OpenAlexaff
L.B.Y. Aldabbagh, A. A. Mohamad

Bibliographic record

VenueJournal of Heat Transfer · 2008
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsReynolds numberNusselt numberJet (fluid)Richardson numberLaminar flowMechanicsPhysicsVortexTurbulence

Abstract

fetched live from OpenAlex

The effect of Richardson number (Ri=Gr/Re2=Ra/Pr Re2) in a confined impinging laminar square jet was investigated numerically through the solution of Navier–Stokes and energy equations. The simulations were carried out for Richardson number between 0.05 and 8 and for jet Reynolds number between 50 and 300. The jet-to-target spacings were fixed to 0.25B, 0.5B, and 1.0B, respectively, where B is the jet width. The calculation results show that for the jet-to-target spacing of 0.25B, the flow structure of a square single jet impinging on a heated plate is not affected by the Richardson number. For such very small jet-to-target distances the jet is merely diverted in the transverse direction. The wall jet fills the whole gap between the plates with a very small vortex motion formed near the corners of the jet cross section close to the upper plate. In addition, the effect of the Richardson number on the variation in the local Nusselt number is found to be not significant. For higher jet-to-target spacing, the Nusselt number increased as the Richardson number increased for the same Re. In addition, the heat transfer rate increased as the jet Reynolds number increased for the same Richardson number.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.219
Teacher spread0.184 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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