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Record W4240212334 · doi:10.32920/ryerson.14664336

An interferometric study of free convective heat transfer at an indoor glazing with an insect screen attachment

2021· preprint· en· W4240212334 on OpenAlexafffund
Daniel Zalcman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicGreenhouse Technology and Climate Control
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlazingHeat transferMaterials scienceConvectionConvective heat transferInterferometryOpticsWindow (computing)MechanicsIsothermal processThermodynamicsPhysicsComposite materialComputer science

Abstract

fetched live from OpenAlex

Free convective heat transfer from an idealized window with an insect screen attachment was studied using a Mach-Zehnder interferometer. An experimental model was set up with an isothermal plate, two commercially available screens (KHP=8.74×10-9 m2, tHP=0.29 mm and KLP=3.40×10-9 m2, tLP=0.65 mm) and window to screen spacings of b=2 cm and b=1 cm. Heat transfer measurements using finite fringe interferograms were taken at a Rayleigh number of Ra=5.30×107 based on window height. Infinite fringe interferograms were taken for temperature field visualization. Screen temperature was also measured. Experimental results were compared to a preliminary CFD model developed with SolidWorks Flow Simulation and show good agreement. The results show that an insect screen produces a reduction in the convective heat transfer from the indoor glazing. The current measurements show that the effect of window to screen spacing is small. Results from this study are expected to be used for the validation of CFD models and for the development of correlations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.256
Teacher spread0.218 · 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 designObservational
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
Published2021
Admission routes2
Has abstractyes

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