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Effects of Pressure Equalization on the Performance of Residential Wall Systems under Extreme Wind Loads

2011· article· en· W2034553541 on OpenAlexafffund
Gregory A. Kopp, Eri Gavanski

Bibliographic record

VenueJournal of Structural Engineering · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWestern University
FundersCanada Research ChairsOntario Innovation TrustState Farm
KeywordsEavesEqualization (audio)Structural engineeringWind engineeringEngineeringMarine engineeringChannel (broadcasting)Telecommunications

Abstract

fetched live from OpenAlex

During strong windstorms, sheathing and siding on residential, wood-framed, wall systems have commonly failed. In the current study, a clear difference is observed in the rate of failure occurrence for wall sheathing above or below the eaves. This observation can be explained from tests examining ultimate capacities and pressure equalization of both single- and multilayer residential, wood-framed, wall systems using realistic fluctuating loads. The results indicate that pressure equalization is a critical parameter in the performance of both the cladding and exterior sheathing. With interior sheathing included, significant pressure equalization was observed to occur across the exterior sheathing, because pressure equalization is observed to increase with load (and damage) levels. This substantially increases the ultimate capacity of these wall systems; however, the construction details of the various exterior layers play an important role in the levels of pressure equalization across each layer.

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)0.002
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.185
Teacher spread0.172 · 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

Citations17
Published2011
Admission routes2
Has abstractyes

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