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Record W6991273508

Field comparison study of indoor environment quality in office buildings with underfloor and overhead ventilation systems

2014· article· en· W6991273508 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2014
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsASHRAE 90.1Thermal comfortVentilation (architecture)Indoor air qualityAir quality indexThermal
DOInot available

Abstract

fetched live from OpenAlex

The use of UFAD (Underfloor Air Distribution) systems is increasing rapidly and reported advantages of UFAD include energy savings and improved indoor air quality. At present few publications documenting measurements of ventilation effectiveness and indoor environment quality in occupied buildings with UFAD have been identified. In this field comparison study we measured several aspects of the thermal environment in two buildings with different ventilation systems (underfloor air distribution and mixing) located in Montreal (Quebec). The results are presented in terms of thermal stratification, predicted thermal comfort indices (VATD , limit to air speed and PMV/ PPD), and IAQ index (CO2 level and stratification). The aim of the study was to determine whether UFAD in practice results in improved ventilation effectiveness compared to typical overhead air distribution without affecting the thermal comfort. The study found that there was little stratification for UFAD under operating conditions and it performed as a mixing system, thus no improvement in ventilation effectiveness was identified in the occupied zone, in comparison to the reference mixing system. In addition the predicted thermal comfort in term of VATD, air speed and PMV/PPD was similar to those obtained for mixing ventilation and was within the acceptable limits set by ASHRAE 55-2010.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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 designObservational
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

Citations0
Published2014
Admission routes2
Has abstractyes

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