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Record W2893997903 · doi:10.1115/1.4041557

A New Approach to Delay or Prevent Frost Formation in Membranes

2018· article· en· W2893997903 on OpenAlexaff
Pooya Navid, Shirin Niroomand, Carey J. Simonson

Bibliographic record

VenueJournal of Heat Transfer · 2018
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsFrost (temperature)MembraneSaturation (graph theory)MoistureHumidityMass transferMechanicsCondensationRelative humidityThermodynamicsMaterials scienceEnvironmental scienceChemistryComposite materialPhysicsMathematics

Abstract

fetched live from OpenAlex

Saturation of the water vapor is essential to form frost inside a permeable membrane. The main goal of this paper is to develop a numerical model that can predict temperature and humidity inside a membrane in order to show the location and time of saturation. This numerical model for heat and mass transfer is developed to show that frost formation may be prevented or delayed by controlling the moisture transfer through the membrane, which is the new approach in this paper. The idea is to simultaneously dry and cool air to avoid saturation conditions and thereby eliminate condensation and frosting in the membrane. Results show that saturation usually occurs on side of the membrane with the highest temperature and humidity. The numerical model is verified with experimental data and used to show that moisture transfer through the membrane can delay or prevent frost formation.

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)0.000
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.041
GPT teacher head0.277
Teacher spread0.235 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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