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Record W2989649483 · doi:10.1017/jfm.2019.924

The influence of heating on liquid jet spreading and hydraulic jump

2019· article· en· W2989649483 on OpenAlexaff
Yunpeng Wang, Roger E. Khayat

Bibliographic record

VenueJournal of Fluid Mechanics · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsWestern University
Fundersnot available
KeywordsHydraulic jumpMechanicsJet (fluid)JumpMaterials scienceEnvironmental scienceFlow (mathematics)Physics

Abstract

fetched live from OpenAlex

The free-surface flow and thermal fields formed by an axisymmetric liquid jet impinging on a circular heated disk are examined theoretically. The disk is maintained either at a prescribed heat flux or temperature. The study explores the effect of inertia, wall heat flux and wall temperature on the momentum and thermal boundary layers as well as the film thickness and the location and height of the hydraulic jump. Only non-metallic liquids are considered, for which the kinematic viscosity is generally larger than the thermal diffusivity, causing the thermal boundary layer to remain thinner than the momentum boundary layer. The effect of surface tension resulting in the Marangoni stress at the free surface and the hoop stress at the jump is also explored. Our results corroborate well existing experimental, theoretical and numerical studies. Both the momentum and thermal boundary layers are found to decrease with increased inertia or thermal input at the disk. The thermal boundary layer is found to always reach the free surface for an imposed constant wall heat flux. The two transition locations where the boundary layers reach the free surface move downstream with inertia but move in opposite directions with increasing wall heat flux or wall temperature. Enhanced heating from the wall also tends to increase the jump radius and depress its height. More importantly, the hydraulic jump leads to a shock-type drop in the Nusselt number, confirming existing numerical findings. Finally, we show that the Nusselt number is independent of the wall temperature for a fluid of constant properties.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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 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

Citations20
Published2019
Admission routes1
Has abstractyes

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