MétaCan
Menu
Back to cohort
Record W1989567918 · doi:10.1063/1.1527044

Air bubble entrapment under an impacting droplet

2002· article· en· W1989567918 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysics of Fluids · 2002
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMechanicsBubblePhysicsHeptaneSolid surfaceVolume (thermodynamics)Volume of fluid methodAir bubbleContact angleSurface (topology)Flow (mathematics)ThermodynamicsGeometryChemical physics

Abstract

fetched live from OpenAlex

We simulated impact of water, n-heptane, and molten nickel droplets on a solid surface. A numerical code was developed to model the motion of both the liquid in the droplet and the surrounding air. The model used a volume-of-fluid method to track the droplet surface and assumed that only one flow field governed the motion of all the fluids present. Predicted droplet shapes during impact agreed well with photographs. When a droplet approached another surface, air in the gap between them was forced out. Increased air pressure below a droplet created a depression in its surface in which air was trapped. The magnitude of pressure rise could be predicted using a simple analysis of fluid between two solid planes moving closer together. The air bubble formed at the solid–liquid interface remained attached to the solid surface in a water droplet. In an n-heptane droplet the bubble moved away from the surface and broke into two or three smaller bubbles before escaping through the droplet surface. This difference in behavior was attributed to the contact angle of water being much larger than that of n-heptane.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.551

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 head0.018
GPT teacher head0.217
Teacher spread0.198 · 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