Properties of Tornado Wind Speed Profiles Used in the Development of the ASCE 7-22 Tornado Provisions
Bibliographic record
Abstract
Significant tornado events have prompted a push for the development of design standards that consider tornado loading for conventional buildings and structures. One important loading parameter in the design standards is the variation in the horizontal wind speed with the height (i.e., wind speed profile) as manifested in a velocity pressure profile. Different from the atmospheric boundary layer (ABL) in which the wind speed monotonically increases with height, the average wind speed profile in tornadoes exhibits a “nose-like” profile for which the wind speed increases from the surface to a local maximum at “nose” height and then decreases above that height. A tornado task committee (TTC) was convened through the ASCE 7 Wind Load Subcommittee, in part to report on the collection, review, and analysis of tornado wind speed profile data and to propose a “design” tornado velocity pressure profile for inclusion in the new tornado load chapter of the ASCE 7-22 standard. A total of 36 tornado profiles were evaluated independent of terrain exposure or surface roughness and collected from mobile radar data. Significant variability was noted in the profiles, but many showed a peak horizontal wind speed relatively close to surface, with a median height of approximately 164 ft (50 m). A proposed tornado velocity pressure profile and associated velocity pressure exposure coefficient, KzTor, was then developed for ASCE 7-22. The proposed nominal tornado profile closely followed the median radar profile. Values of the new KzTor=1.0 between ground level and 200 ft (61 m) decrease linearly to 0.9 at a height of 328 ft (100 m) then remain constant above that height.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".