A user-friendly graphical user interface (GUI) of wall jet analytical and semi-empirical models of downbursts
Bibliographic record
Abstract
Downbursts are intense, often damaging, winds produced by downdrafts from storms that strike the ground and spread outward in all directions. Near the surface, the flow characteristics of downburst outflows closely resemble those of an impinging jet spreading over a flat surface, a well-known phenomenon in experimental fluid mechanics. Key features such as high wind speeds, nose-shaped vertical profiles of mean velocity, abrupt shifts in wind direction, and non-Gaussian velocity distributions make downbursts a significant hazard to certain structures. Owing to their resemblance to impinging jets, downbursts have been modeled using various analytical and semi-empirical formulations, which are now commonly used in wind engineering to evaluate structural loads and environmental impacts. This short communication introduces a simple and intuitive MATLAB® software tool that integrates nine well-documented models of downburst-like impinging jets. The tool allows users to visualize radial and vertical profiles of the mean wind components and to export both plots and data in multiple formats. Its interactive interface enables easy adjustment of key model parameters, enhancing usability for research and engineering applications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.054 | 0.015 |
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".