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Record W4386126773 · doi:10.1139/cjce-2022-0351

Wind pressure on a 45° gabled roof: verifying code provisions with field measurements and wind tunnel data

2023· article· en· W4386126773 on OpenAlexaffvenueabout
Mauricio Chavez, Angathevar Baskaran, Murad Aldoum, T. Stathopoulos, Tsinuel N. Geleta, Girma Bitsuamlak

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsConcordia UniversityWestern UniversityNational Research Council Canada
Fundersnot available
KeywordsRoofWind tunnelStructural engineeringWind engineeringPressure measurementMerge (version control)EngineeringBuilding codeFull scaleGeotechnical engineeringMarine engineeringComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

The wind load provisions for gabled roofs with a slope of 27° < α < 45° in the National Building Code of Canada (NBCC) were derived from wind tunnel studies conducted in the 1970s. The coefficients have remained basically unchanged until this time. The paper presents the results of full-scale measurements and wind tunnel experiments to verify the necessity to update the current NBCC provisions. A full-scale building with a gabled roof of 45° was instrumented with pressure taps, and the wind load was monitored for 15 months. Special attention is given to the roof overhang by considering the simultaneous pressure contribution from both the upper and lower surfaces. The building and surroundings were replicated at a wind tunnel scale and investigated by Concordia University and Western University. Based on these three sources of data, the study concluded that the corner and edge provisions for both cases—a roof with and without overhang—need to be increased. It is suggested to merge the corner and edge into a single “perimeter” load provision. This code simplification would help the roofing industry to reduce misleading interpretations of the code and minimize failure due to installation errors.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.032
GPT teacher head0.216
Teacher spread0.184 · 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 teacher head, 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
Published2023
Admission routes3
Has abstractyes

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