Wind Tunnel Testing of Buildings Subjected to Atmospheric Wind Loads And Thunderstorm Gust Fronts
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".