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Record W4251712681 · doi:10.32920/ryerson.14663127

The Influence of Cavity Ventilation on the Performance of Brick Veneer Panels When Exposed to Wind Driven Rain: an Experimental Analysis

2021· preprint· en· W4251712681 on OpenAlexaff
Graeme Richards

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsVentilation (architecture)SuctionMaterials scienceBrickEnvironmental scienceCavity wallComposite materialStructural engineeringMeteorologyEngineeringPhysics

Abstract

fetched live from OpenAlex

This study investigates the influence of cavity ventilation on the wind driven rain (WDR) performance of brick veneer walls. Two types of walls (type C and D) both bonded with N-type mortar were studied. The volume and frequency of WDR was based on weather station data from York University. Cavity conditions were mocked with a cavity chamber and ventilation was simulated with a fan providing air suction out of the cavity. Ventilation rates were simulated at 0, 5 and 10 ACH. Higher ventilation rates resulted in more efficient drying and lower RH within the cavity chamber. Wall type C exhibited more absorption with increased ventilation rates. Moisture content readings were generally irrelevant due to failure of the prescribed method. Measuring the influence of cavity ventilation on the amount of penetrated water should be further investigated by applying different ventilation rates to the same wall specimens to reduce the impact of physical variations within the same brick type.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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