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Record W2006633249 · doi:10.1115/ht2013-17165

Numerical Study of the Effect of Cold Air Vent Flow on the Convective Heat Transfer Rate From a Hot Window Covered by a Top-Down, Bottom-Up Plane Blind System

2013· article· en· W2006633249 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsQueen's University
Fundersnot available
KeywordsMechanicsTurbulenceLaminar flowHeat transferBuoyancyFlow (mathematics)Reynolds numberConvective heat transferConvectionPlane (geometry)Vertical planeMeteorologyPhysicsMaterials scienceGeometryEngineeringMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

In summer when the air-conditioning system is in use cool air from a floor-mounted vent located beneath a window often flows over the warm window. The presence of a blind system over the window will, in general, influence the effect of the vent flow on the convective heat transfer rate from the window. The effect of a Top-Down, Bottom-Up plane blind system and a cool air vent flow on the heat transfer rate from a recessed window has therefore been numerically studied here. The actual situation considered in this study is an approximate model of real situations. The window is represented by a plane isothermal section recessed into the wall, this window section being hotter than the room air far from the window. The floor-mounted vent is assumed to be located against the wall and to have a uniform discharge velocity which is normal to the vent surface. The flow has been assumed to be two-dimensional, i.e., the effect of the window and vent width has not been considered. The flow has been assumed to be steady and situations involving both laminar and turbulent flow have been considered. The fluid properties have been assumed constant except for the density change with temperature that gives rise to the buoyancy forces, this being dealt with using the Boussinesq approach. The governing equations have been solved using the commercial CFD code ANSYS FLUENT©, the k-epsilon turbulence model having been used. The solution has the following parameters: the Rayleigh number, the Reynolds number based on the vent discharge velocity, the dimensionless depth that the window is recessed, the Prandtl number, the dimensionless top and bottom blind opening, the dimensionless size of the air vent, and the dimensionless vent discharge temperature to undisturbed air temperature difference. Results have only been obtained for a Prandtl number of 0.74 and for fixed values of the dimensionless depth that the window is recessed, the dimensionless size of the air vent, and the dimensionless vent discharge temperature difference. The effects of the other dimensionless variables on the window Nusselt number have been numerically studied.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.571

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 communication0.0000.000
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 head0.005
GPT teacher head0.176
Teacher spread0.171 · 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

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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