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Modeling of Buoyancy-Driven Natural Ventilation in Workshop: Optimization of Distance between Heat Source and Ground

2012· article· en· W1981225780 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

VenueApplied Mechanics and Materials · 2012
Typearticle
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsLa Cité Collégiale
FundersNatural Science Foundation of Shanghai
KeywordsNatural ventilationBuoyancyCeiling (cloud)Environmental scienceVentilation (architecture)Computational fluid dynamicsWaste heatMechanicsMeteorologyEngineeringMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Natural ventilation is suitable for application to workshops with heat sources to keep good indoor air quality at lower energy cost. In this paper, the authors numerically investigated the buoyancy-driven natural ventilation in a workshop with heat source based on computational fluid dynamics (CFD) method. The effect of the distance between heat source and ground on the air flow and temperature distribution was examined. Results showed that the average air temperature at operation zone could be effectively reduced when the distance between heat source and ground increased. The temperature field in the upper zone of the workshop was improved by diminishing the hot air zone near the ceiling and the waste heat directly going into the operation zone decreased when the distance between heat source and ground increased.

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 score0.419
Threshold uncertainty score0.282

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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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