MétaCan
Menu
Back to cohort
Record W2068678170 · doi:10.1063/1.1533754

Thermocapillary convection with moving contact points

2003· article· en· W2068678170 on OpenAlexaff
Yuyan Jiang, H. M. Badr, J. M. Floryan

Bibliographic record

VenuePhysics of Fluids · 2003
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsWestern University
Fundersnot available
KeywordsPhysicsMarangoni effectBiot numberMechanicsConvectionMarangoni numberReynolds numberDissipative systemLaminar flowClassical mechanicsThermodynamicsTurbulence

Abstract

fetched live from OpenAlex

Marangoni convection in a cavity subject to two types of heating, i.e., heating through the sidewalls and heating by a point source from above, has been investigated. The assumed wetting conditions permit motion of the interface along the sidewalls subject to a constant contact angle constraint. The analysis considers complete interface deformation effects. The results determined for large Biot and zero Marangoni numbers show the existence of limit points beyond which steady, continuous interface cannot exist. The limit points define the maximum capillary number Ca and the maximum cavity length L permitted. The permitted values of the Reynolds number may be bounded from below and from above depending on the values of other transport parameters and on the form of the external heating. Interface approaching bottom of the cavity leading, most likely, to the formation of a dry spot, represents the main factor limiting the existence of steady convection. The topology of the flow field is similar to the case when the wetting conditions result in the fixed location of the contact points while the topology of the interface is qualitatively different. The change of the contact conditions from the fixed contact points to the fixed contact angles results in a significant reduction of the range of parameters that guarantee the existence of a continuous interface.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.401

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 head0.006
GPT teacher head0.182
Teacher spread0.176 · 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

Citations6
Published2003
Admission routes1
Has abstractyes

Explore more

Same venuePhysics of FluidsSame topicFluid Dynamics and Thin FilmsFrench-language works237,207