On the high-lift characteristics of a bio-inspired, slotted delta wing
Bibliographic record
Abstract
A bio-inspired, slotted delta wing was abstracted from a multi-vane propulsor geometry ubiquitous in nature, and analysed to investigate aerodynamic performance during acceleratory and steady-state motions. Evolutionary convergence of slotted geometries in nature suggests an aerodynamic benefit in manoeuvrability, as exemplified in the fins and wings of a broad range of extant and extinct swimmers and flyers, respectively. Through direct force measurements and stereoscopic particle image velocimetry, it was found that the abstracted, slotted geometry exhibited a region of steady-state lift and drag enhancement at angles of attack greater than 25° when compared to a reference profile based on a delta-wing plate. At an angle of attack of 30°, the lift and drag measured on the abstracted model were 15.3% and 17.0% higher than the delta-wing model, respectively. In contrast, these shapes showed little difference in performance during an acceleration-from-rest manoeuvre. It was found that the secondary and tertiary vanes of the abstraction encouraged the formation of additional leading-edge vorticity. The formation of these additional leading-edge vortices was confirmed by an increase in streamwise circulation measured near each effective leading edge along the length of the chord. As such, this configuration provides lift augmentation appropriate for the development of high-performance control surfaces.
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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".