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Record W4293115954 · doi:10.11159/htff22.153

Influence of Contact Angle on the Internal Flow in a Freezing Water Droplet

2022· article· en· W4293115954 on OpenAlexvenueno aff
Erik Fagerström, Anna‐Lena Ljung

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicFreezing and Crystallization Processes
Canadian institutionsnot available
Fundersnot available
KeywordsContact angleFlow (mathematics)MechanicsMaterials scienceEnvironmental scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

Ice accretion upon a surface is of interest in areas such as wind power, electric power transmission and vehicles in cold climate.Ice assimilation appears when humid air or water droplets impacts and freezes on a cold surface.In the study presented in this paper, droplets are deposited onto aluminium plates constructed to generate a specific contact angle between the droplet and substrate.Five contact angles are investigated and Particle Image Velocimetry (PIV) is used to analyse the internal flow.The droplets are studied along the vertical centerline and at horizontal lines at distances of 50% and 75% of the total height of the droplet.From the results it is found that a lower contact angle will increase the magnitude of the internal flow close to the edges.A larger contact angle will instead increase the magnitude of the flow in the center of the droplet.For a droplet with lower contact angle it was furthermore found that there is a triangular area inside the droplet with close to zero velocity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.172
Teacher spread0.168 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicFreezing and Crystallization ProcessesFrench-language works237,207