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Record W3000427222 · doi:10.1063/1.5132350

Small droplet bouncing on a deep pool

2020· article· en· W3000427222 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 · 2020
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsWestern University
FundersHigher Education Discipline Innovation ProjectFoundation for Innovative Research Groups of the National Natural Science Foundation of China
KeywordsPhysicsPenetration (warfare)MechanicsOscillation (cell signaling)Weber numberPenetration depthClassical mechanicsOpticsTurbulenceReynolds number

Abstract

fetched live from OpenAlex

Droplet bouncing on liquid surfaces frequently occurs for low-Weber-number impacts. Previous studies typically used large droplets with oscillation initiated by their creation process but without determining the effects of these oscillations. Here, we use small droplets, providing the means to reduce oscillations to show that the probability of the droplet bounce does not depend on the droplet oscillations. The time from the moment of contact to the maximum penetration depth was found to be independent of the Weber number for droplets of fixed diameter but increased with an increase in diameter. Both the maximum penetration depth and the maximum rebound height increased monotonically with the Weber number. A simple model predicting the maximum penetration depth was proposed and validated through comparison with experimental data.

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 score0.789
Threshold uncertainty score0.518

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 head0.023
GPT teacher head0.197
Teacher spread0.174 · 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