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Record W4405737963 · doi:10.3390/wind4040021

A Comparison of ASCE/SEI 7–22 Tornado-Induced Load Provisions for Residential Low-Rise Buildings to Those Evaluated Using Physical Simulation

2024· article· en· W4405737963 on OpenAlexafffundabout
Gabriel Narancio, Djordje Romanić, Chowdhury Jubayer, Hanping Hong, Horia Hangan

Bibliographic record

VenueWind · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsOntario Tech UniversityMcGill UniversityWestern University
FundersInstitute for Catastrophic Loss Reduction
KeywordsTornadoLow-riseEngineeringEnvironmental scienceArchitectural engineeringCivil engineeringForensic engineeringStructural engineeringMeteorologyGeography

Abstract

fetched live from OpenAlex

In this study, the loads induced by tornado-like vortices on scaled models of eight low-rise residential buildings with real-world shapes in a typical North American community are quantified and compared to the provisions provided by ASCE/SEI 7–22. Physical simulations of the interaction between translating tornado-like vortices representative of EF1-, EF2- and EF3-rated tornadoes and the scaled models were performed in the WindEEE Dome at the University of Western Ontario. Three internal pressure scenarios were numerically simulated. The tornado velocity gust factor was identified as a critical parameter when translating loads from the model to full-scale. The uplift forces on the whole roof in the internal pressure scenarios with one dominant opening are between 44% and 63% higher than the distributed leakage scenario, highlighting the importance of keeping the integrity of the envelope. Revised values of the internal pressure coefficients and external pressure coefficients or correction factors may be used to improve the ability of the standard to provide safer design loads.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.057
GPT teacher head0.395
Teacher spread0.338 · 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
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

Citations1
Published2024
Admission routes3
Has abstractyes

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