A novel approach to scaling experimentally produced downburst-like impinging jet outflows
Bibliographic record
Abstract
Downbursts are intense thunderstorm winds that can be found in most, if not all, regions around the globe. An accurate experimental investigation of downburst winds requires the proper geometric and kinematic scaling between the model downburst (m) created in a wind simulator and the full scale downburst event (p). This study makes a threefold contribution to further understanding of downburst outflows. First, the article introduces a new scaling methodology for downburst outflows based on the signal decomposition techniques of p and m downburst wind records. Second, the study describes a large set of m downbursts produced in the WindEEE Dome simulator at Western University and critically discusses their similarity with a large set of p events detected in the Mediterranean. Third, using the proposed scaling methodology, this paper attempts to partially reconstruct two p downburst events recorded in Genoa and Livorno, Italy. In total, 17 p and 1400 m downburst outflows are investigated herein, which represents the largest database of p and m downbursts combined. The similarity between p and m downbursts is quantitatively demonstrated for both mean and fluctuating components of the flows. The scaling method is verified by accurately predicting the known anemometer height of p events using m downburst measurements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".