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Impact of Occupant Modelling on the Prediction of Airflow around Occupants in a Ventilated Room

2007· article· en· W579739242 on OpenAlexafffund
Alireza Shakeri, Ali Dolatabadi, Fariborz Haghighat, Taghi Karimipanah

Bibliographic record

VenueInternational Journal of Ventilation · 2007
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsConcordia University
FundersPublic Works and Government Services Canada
KeywordsAirflowComputational fluid dynamicsThermal comfortSimulationComputationVentilation (architecture)Computer scienceEnvironmental scienceMechanical engineeringEngineeringAerospace engineeringMeteorologyPhysics

Abstract

fetched live from OpenAlex

Localized ventilation systems typically create highly asymmetric or non-isothermal environments around occupants with significant vertical temperature gradient and highly non-uniform airflow regimes that could be directed toward a segment of the body. These effects may have pronounced impact on occupant’s thermal comfort. The airflow field and temperature distribution near the occupant can be determined either by performing full-scale measurements or by simulation methods. Usually, human subjects or manikins are used in field studies involving measurement techniques. However, as an alternative to full-scale measurement, Computational Fluid Dynamics (CFD) has been proven to be a practical and valuable tool for predicting the airflow field. At the same time, the accuracy of the predictions of the local airflow within the microclimate of the occupant is highly dependent on the proper modelling of the occupant itself. The human body not only has a complicated physical shape, but also has complex thermo-physiological properties. Modelling of all these aspects is a formidable challenge and an extremely time-consuming task. Therefore, various simplifications have been made in order to decrease the level of complexity so that the computation may be performed with the available computer resources.This paper reports the results of a detail numerical simulation to study the impact of occupant modelling on the airflow and temperature distribution and their influences on the occupant’s thermal comfort. First, the predictions made by the CFD model were compared with experimental data that were measured in a specially designed experimental chamber. Good agreement was observed. Four type of configuration were used to model the occupant: a conventional block form, three-node, six-node and finally eight-node configurations. Further simulations were carried out to investigate the assumption of uniform heat distribution. An assessment of uniform and non-uniform heat distribution scenarios for various occupant configurations and ventilation systems showed that the assumption of uniform heat distribution is valid for a wide range of operating conditions.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.341
Teacher spread0.300 · 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
GenreEmpirical

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

Citations3
Published2007
Admission routes2
Has abstractyes

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