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Record W4417428258 · doi:10.1016/j.jweia.2025.106314

An aerodynamic database of wind loads on gable and hip roof buildings

2025· article· en· W4417428258 on OpenAlexafffund
Timothy John Acosta, Stefano Brusco, Yitian Guo, Jin Wang, Gregory A. Kopp

Bibliographic record

VenueJournal of Wind Engineering and Industrial Aerodynamics · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaDepartment of Science and Technology, Republic of the Philippines
KeywordsGableRoofAerodynamicsStiffnessWind tunnelDeckBuilding modelTerrain

Abstract

fetched live from OpenAlex

Experimental wind tunnel databases are essential for determining design wind loads on buildings for a range of applications, including building code development and database-assisted design. Such databases have played a key role in developing data-driven methods and validating numerical simulations in recent years. Despite their importance, there are limited publicly available databases. This paper presents wind tunnel data obtained at Western University, which aims to address the gap for data on low-to mid-rise gable and hip-roof buildings. The database encompasses 154 different cases, examining the impacts of non-dimensional building geometry parameters and roof shape on the resulting aerodynamic loads. Notably, it includes 74 gable and 80 hip roof-shaped building cases, all with a roof slope 6/12 across open and suburban terrain categories. The paper examines the geometric aspect ratio limits as to when the gable or hip roof can be considered aerodynamically flat with respect to the total base shear. For gable-roofed buildings, the contribution of the mean and the variance of the base shear loads of the walls and roof collapse relatively well with respect to the mean roof height-to-length ( h / L ) ratio, where the length, L , is the plan dimension parallel to the wind direction. The contribution of the roof reduces to less than 3 % when h / L > 2 . For uplift, the contribution of the windward roof and leeward roof to the total uplift was examined. For h / L < 2 , the leeward roof contributes more to the total uplift. As for the hip roof, the contributions of the walls and roof collapse are observed to be a function of the height-to-breadth ( h / B ) ratio, where the breadth, B , is the plan dimension perpendicular to the wind direction. The contribution of the hip roof to the total base shear is less than 1 % when h / B > 1.25 for the L / B ratios considered in the database. The controlling geometric aspect ratios are different for a gable and hip roof due to how these parameters alter the projected roof area that contributes to the total base shear. Generally, when the hip or gable roof contributes to the total base shear, the peak design base shear is smaller than a case with a flat roof.

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)0.002
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.009
GPT teacher head0.215
Teacher spread0.205 · 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
GenreDataset

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

Citations1
Published2025
Admission routes2
Has abstractyes

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