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Zonal Models for Indoor Air Flow - A Critical Review

2004· review· en· W2219525229 on OpenAlex
E.J. Teshome, Fariborz Haghighat

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

VenueInternational Journal of Ventilation · 2004
Typereview
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputational fluid dynamicsFlow (mathematics)MechanicsAirflowPower lawNatural convectionThermalConvectionEnvironmental scienceMeteorologyThermodynamicsPhysicsMathematics

Abstract

fetched live from OpenAlex

A zonal model is an intermediate approach between computational fluid dynamics (CFD) and single–room models. It can give results faster than CFD and be more accurate than single–zone models. It has been used to provide some global information regarding thermal and flow parameters within a room. In this review, due emphasis is given to the commonly used pressurized zonal model – the power law. Qualitative validations show that the power law model reasonably predicts well for natural convection. Nevertheless, for the case of forced convection it was found that zonal models fail to predict the recirculation loop reasonably. This is due to the fact that the power law model employs a constant flow coefficient throughout the flow field. A validated room CFD simulation was employed to illustrate the variability of the flow coefficient in the flow field.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.059
GPT teacher head0.363
Teacher spread0.304 · 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