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Record W1970776482 · doi:10.1002/ceat.200800290

Simultaneous Aerodynamic and Thermal Analysis during Cooling of Stacked Spheres inside Ventilated Packages

2008· article· en· W1970776482 on OpenAlexafffund
Jalal Dehghannya, Michael Ngadi, C. Vigneault

Bibliographic record

VenueChemical Engineering & Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsAgriculture and Agri-Food CanadaMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAirflowAerodynamicsMechanicsHeat transferThermalConvectionAerodynamic heatingMaterials scienceForced convectionEnvironmental scienceNatural convectionMeteorologyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract Aerodynamic and thermal analysis during forced convection cooling of produce was conducted by modeling coupled airflow and heat transfer. Air velocities and heterogeneity indexes were predicted for different configurations of package openings at an airflow rate of 0.022 m3/s. Predicted temperature profiles were compared with experimental data for model validation. Good agreement between model prediction and measured data was obtained. The results showed that airflow distribution during the process was not homogeneous. More uniform airflow distribution was obtained by increasing the vent area from 2.4 to 12.1 %. The highest cooling heterogeneity index (108 %) was recorded at 2.4 % vent area whereas the lowest heterogeneity index (0 %) was detected in a package with 12.1 % vent area. Proper package vent design is necessary to provide more uniform cooling operation during the forced convection cooling process.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.171
Teacher spread0.167 · 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

Citations43
Published2008
Admission routes2
Has abstractyes

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