MétaCan
Menu
Back to cohort
Record W1999448470 · doi:10.1080/19401490903528147

A simplified model of heat transfer at an indoor window glazing surface with a Venetian blind

2010· article· en· W1999448470 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Building Performance Simulation · 2010
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsQueen's UniversityToronto Metropolitan University
Fundersnot available
KeywordsGlazingHeat transferConvectionMechanicsRadiative transferWindow (computing)Convective heat transferMaterials scienceSolar gainFenestrationThermalThermodynamicsOpticsPhysicsComputer scienceComposite material

Abstract

fetched live from OpenAlex

In this article, a simplified model is developed to predict the radiative and convective heat transfer in a complex fenestration system consisting of a Venetian blind located adjacent to an indoor window glazing. Empirical correlations for natural convection in an asymmetrically heated channel and an isolated flat plate are used in this one-dimensional simplified model. In this simplified model, an energy balance is performed at the blind surface using a mean blind temperature. The radiative heat exchange between the blind, window and room is calculated using a four surface grey-diffuse model, which is coupled to the convective heat transfer. The simplified model has been developed using experimental and numerical data from the literature. Sample results are presented that illustrate the effect of blind slat angle, blind-to-window spacing and absorbed solar heat flux on the heat transfer at the window surface.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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