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Record W4235199316 · doi:10.32920/ryerson.14665767

A Simplified Technique for Thermal Analysis of a Fenestration system with a Venetian Blind

2021· preprint· en· W4235199316 on OpenAlexaff
Hidayat Ullah Shahid

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsGlazingFenestrationWindow (computing)ThermalConvectionHeat transferConvective heat transferComputer scienceMaterials scienceAcousticsMechanicsMeteorologyPhysicsComposite material

Abstract

fetched live from OpenAlex

A simplified 1-D numerical model of a window and horizontal Venetian blind assembly has been developed. This model provides a realistic estimate of the advantage of using blinds to control the window heat gain or loss. The free convective heat transfer rate from an isothermal vertical surface adjacent to a set of horizontal louvres has been studied numerically. This configuration is an approximate model of an indoor window glazing with a Venetian-type blind. Knowledge of the effect of blinds on the free convection at the indoor window surface is important for understanding and predicting the impact of shading devices on the overall thermal performance of a window. The convective heat transfer results are used in the one-dimensional model of the complete fenestration system to study the effect on key performance parameters. The results show that louvred blinds can have a significant beneficial effect on window thermal performance.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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
GenreMethods

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

Citations4
Published2021
Admission routes1
Has abstractyes

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