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Record W3118789260 · doi:10.1063/5.0033640

The planar spread of a liquid jet and hydraulic jump on a porous layer

2021· article· en· W3118789260 on OpenAlexafffund
Yunpeng Wang, Roger E. Khayat

Bibliographic record

VenuePhysics of Fluids · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHydraulic jumpMechanicsPorosityBoundary layerJumpJet (fluid)PhysicsPlanarFlow (mathematics)Materials scienceComposite material

Abstract

fetched live from OpenAlex

The flow of a planar liquid free surface jet impinging on a porous layer is theoretically examined, with particular emphasis on the influence of porosity ϕ, stress jump coefficient χ, and depth of the porous layer on the super- and sub-critical regions. Despite the numerous studies in the literature on the flow over a porous medium, the jet impingement on a porous layer has not been studied. An averaging integral approach is adopted to capture the flow in the developing boundary-layer and fully viscous regions upstream of the hydraulic jump. Asymptotic analyses for small distance from impingement, small porosity, and small porous layer depth are also conducted, elucidating the various mechanisms behind the behavior predicted numerically. We find a domain of validity for the stress jump coefficient χ in which numerical and experimental values of χ from the literature seem to fall. The transition point, where the outer edge of the boundary layer intersects the film surface, moves downstream with increasing porosity and stress jump coefficient accompanied by a drop in the film thickness. While the height of the hydraulic jump generally decreases with increasing ϕ for any permeability, the jump location decreases for small χ and increases for large χ.

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 score0.028
Threshold uncertainty score0.340

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 head0.016
GPT teacher head0.223
Teacher spread0.208 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

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