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Record W2089778738 · doi:10.1063/1.1683151

Four dynamical regimes for a starting plume model

2004· article· en· W2089778738 on OpenAlexaff
Catherine A. Hier Majumder, David A. Yuen, Alain Vincent

Bibliographic record

VenuePhysics of Fluids · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPrandtl numberInviscid flowPhysicsNusselt numberPlumeMechanicsTurbulent Prandtl numberRayleigh numberBoundary layerRayleigh scatteringConvectionNatural convectionReynolds numberThermodynamicsTurbulenceOptics

Abstract

fetched live from OpenAlex

The growth of two-dimensional plumes was modeled numerically to study the dynamics of plumes with Rayleigh numbers in the range of 104 to 108 and Prandtl numbers in the range of 0.025 to 10 000. In this study we deal with a geometry driven by a heated line source, which is different from the basally heated Rayleigh–Bénard convection between two horizontal plates. We found four different regimes for plume growth: a diffusive-viscous regime characterized by both thick thermal and velocity boundary layers; an inviscid-diffusive regime with thin velocity and thick temperature boundary layers; a viscous nondiffusive regime with thick velocity boundary layers and thin thermal ones; and an inviscid nondiffusive regime with both thin velocity and narrow thermal boundary layers. We also studied the dependence of the Nusselt number on height for various Rayleigh and Prandtl numbers. We found that plumes with Prandtl numbers as high as 104 grown at a high Rayleigh number (108) are significantly different from plumes developed in an infinite Prandtl number 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 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 score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.243
Teacher spread0.221 · 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

Citations29
Published2004
Admission routes1
Has abstractyes

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