Observations on a Hurricane Wind Hazard Model Used to Map Extreme Hurricane Wind Speed
Bibliographic record
Abstract
The hurricane hazard modeling requires a hurricane wind field model and a hurricane track model, that are generally developed based on historical wind speed and track records. Several hurricane hazard models have been proposed for engineering applications; the model used to map the hurricane wind hazard shown in several editions of a U.S. national standard is extensively documented in open literature. A term, which is expressed as the product of the hurricane translation velocity and gradient of the wind velocity relative to the moving center of the vortex in the governing equation (i.e., fluid momentum equation) to model hurricane wind field, is neglected in various publications. However, the effect of using this approximation on the calculated wind field has not been elaborated. In the research reported in this paper, the effect of this approximation on the wind field is investigated through numerical analysis. Also, a possible simplification of the track model used to estimate the extreme hurricane wind for the U.S. national standard is explored. The use of different wind field models and track models to estimate the extreme hurricane wind is carried out. Comparison of the estimated return period values of hurricane wind speeds is presented.
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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 | 0.000 | 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".