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Record W4389541004 · doi:10.17118/11143/20992

Frost formation over a cold plate with icephobic coatings

2023· article· en· W4389541004 on OpenAlexafffund
Mouna Rahal, Alexandre Coulombe, Reza Jafari, Sébastien Poncet, Hachimi Fellouah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec à ChicoutimiUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaMitacsNatural Resources CanadaHydro-QuébecUniversité de Sherbrooke
KeywordsFrost (temperature)Materials scienceComposite materialCold climateMeteorologyPhysics

Abstract

fetched live from OpenAlex

Abstract: In this study, a new experimental set-up has been developed to investigate by flow visualizations the frost formation and growth on a cold plate. Seven environmental conditions, varying the air temperature, relative humidity, and velocity and the plate temperature, are considered. For the uncoated plate, the experimental data on the temporal evolution of the frost layer thickness enable to validate a pseudo 1D model formerly developed. Three bioinspired icephobic surfaces including superhydrophobic, SLIPS and self-lubricant coatings are then compared to the base case without coating for five environmental conditions. Superhydrophobic coating provides the highest retardation time for the formation and growth of frost compared to the SLIPS and self-lubricant coatings whatever the environmental conditions. It appears as a valuable way to delay the formation of frost and improve the performance of refrigeration systems based on eutectic plates, used for the transport of food products.

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 score0.520
Threshold uncertainty score0.326

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 head0.009
GPT teacher head0.192
Teacher spread0.183 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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