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Record W2032441158 · doi:10.1080/08916150600977358

Experimental Study of Natural Convection in a Window with a Between-Panes Venetian Blind

2007· article· en· W2032441158 on OpenAlexaff
David Naylor, B. Y. Lai

Bibliographic record

VenueExperimental Heat Transfer · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceNatural convectionWindow (computing)Natural (archaeology)ConvectionOpticsMechanicsComputer scienceGeology

Abstract

fetched live from OpenAlex

An experimental study has been conducted on natural convective heat transfer in an idealized double-glazed window with a between-panes louvered blind. A Mach-Zehnder interferometer has been used to obtain full-field temperature visualization, as well as local and average convective heat transfer rates. A blind, consisting of 17 horizontal aluminium slats, was mounted inside a tall vertical enclosure formed by two aluminium plates and two acrylic end spacers. Temperature field visualization and measurements were obtained for three plate spacings and three blind slat angles over a Rayleigh number range (based on the enclosure width) of 4.6 × 104 ≤ Ra ≤ 1.3 × 105. Air was the fill gas. The results show that the inter-pane blind has a strong influence on the local and average convective heat transfer rates. In general, a between-panes blind was found to reduce the average convective heat transfer rate across the window, relative to an empty enclosure. At the three plate spacings studied, a closed blind was found to yield the lowest average convective heat transfer rates.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.266
Teacher spread0.251 · 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

Citations26
Published2007
Admission routes1
Has abstractyes

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