MétaCan
Menu
Back to cohort
Record W4402186180 · doi:10.32920/26871442.v1

Wind Tunnel Testing of Buildings Subjected to Atmospheric Wind Loads And Thunderstorm Gust Fronts

2024· preprint· en· W4402186180 on OpenAlexaffabout
Moustafa Aboutabikh

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsWind tunnelThunderstormEnvironmental scienceMeteorologyWind engineeringWind speedAtmospheric sciencesEngineeringGeologyAerospace engineeringGeography

Abstract

fetched live from OpenAlex

The limited land in urban areas has pushed people to build tall, and slender buildings, where the wind is the governing design load. However, current design codes have a variety of limitations when it comes to the evaluation of wind loads on buildings. Moreover, thunderstorms are considered in design codes as regular synoptic events. Downbursts (or strong downdrafts) are associated with thunderstorms and result in a very damaging outflow when touching the ground. To overcome the design limitations associated with codes, experimental testing of atmospheric boundary layer wind (ABL) and downburst outflows in the Wind Tunnel at Toronto Metropolitan University (TMU) was conducted to evaluate loads on buildings. This was achieved by designing and calibrating a multi-louver system that allows for modeling downbursts outflows. The accuracy of the louver system and optimization was confirmed by conducting CFD simulations and experimental wind tunnel testing and achieving a reasonable match to full-scale events. Moreover, a low-cost expandable synchronous multi-pressure sensing system (SMPSS) was developed and validated at TMU wind tunnel. The pressure system consists of expandable 128 pressure sensors connected to a compact data acquisition and a host workstation. The developed system was examined and validated to be used for buildings by comparing mean, root mean square (RMS), and power spectral density (PSD) for the base moments coefficients with the available data from the literature. Using the two developed systems (the downburst generating system and the multipressure system) an extensive wind tunnel study was performed to study the characteristics of ABL and downburst loads on buildings. Wind forces on buildings were investigated in terms of mean, RMS force coefficients, and power spectral density. Moreover, downburst forces on buildings were presented in terms of max, min, RMS force coefficients, and power spectral density. Results have confirmed the importance of considering higher modes when designing tall buildings.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same topicWind and Air Flow StudiesFrench-language works237,207