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Record W2062212804 · doi:10.1115/ht2013-17219

Analytical Modeling of Mist Condensation by Natural Convection Over Inclined Flat Surfaces

2013· article· en· W2062212804 on OpenAlexaff
M.A. Fayazbakhsh, Majid Bahrami

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDewMistCondensationMass transferMechanicsHeat transferDew pointConvectionNatural convectionWork (physics)Materials scienceThermodynamicsMeteorologyPhysics

Abstract

fetched live from OpenAlex

Dew formation on a transparent surface creates a pattern that can cause blurred view over it. This fogging phenomenon should be avoided in many applications. Mist condensation of water on a cold surface exposed to humid air is studied in this work. In order to analyze the misting process, the fluid flow and heat transfer of humid air as well as the heat transfer across the solid surface are considered. A dew formation model is used to predict the shape and size of the droplets. Analytical models have been proposed to solve the heat and mass transfer for the simple arrangement of a vertical flat surface. The analytical model is then combined with the dew formation model to introduce an analytical model for mist condensation over vertical and inclined surfaces. Due to the proposed method, complex numerical calculations can be avoided for solving the heat and mass transfer equations.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations3
Published2013
Admission routes1
Has abstractyes

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