Drag coefficient and plant form response to wind speed in three plant species: Burning Bush (<i>Euonymus alatus</i>), Colorado Blue Spruce (<i>Picea pungens</i> glauca.), and Fountain Grass (<i>Pennisetum setaceum</i>)
Bibliographic record
Abstract
Whole‐plant drag coefficients (Cd) for three plant species: Burning Bush (Euonymus alatus), Colorado Blue Spruce (Picea pungens glauca.), and Fountain Grass (Pennisetum setaceum) in five different porosity configurations were developed from force versus wind speed data collected with a force balance in a recirculating wind tunnel. The average Cd for the Burning Bush, Colorado Spruce, and Fountain Grass in their untrimmed forms were 0.42 (±0.03), 0.39 (±0.04), and 0.34 (±0.06), respectively. Drag curves (Cd versus flow Reynolds number (Re) function) for the Burning Bush and Colorado Spruce were found to exhibit, for the lower porosity configurations, a rise to a maximum around flow Reynolds numbers (Re = ρuhh/ν) of 2 × 105. Fountain Grass Cd was shown to be dependent upon Re to values >5 × 105. The Burning Bush and Colorado Spruce plants reduced their drag, upon reaching their maxima, by decreasing their frontal area and increasing their porosity. Maximum Cd for these plants occurred at optical porosities of ∼0.20. The Fountain Grass reduced drag at high Re by decreasing frontal area and porosity. The mechanism of drag reduction in Fountain Grass was continual reconfiguration to a more aerodynamic form as evidenced by continual reduction of Cd with Re.
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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 | 0.000 |
| 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 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".