A<scp>ERODYNAMICS OF</scp>S<scp>MALL</scp>V<scp>EHICLES</scp>
Bibliographic record
Abstract
▪ Abstract In this review we describe the aerodynamic problems that must be addressed in order to design a successful small aerial vehicle. The effects of Reynolds number and aspect ratio (AR) on the design and performance of fixed-wing vehicles are described. The boundary-layer behavior on airfoils is especially important in the design of vehicles in this flight regime. The results of a number of experimental boundary-layer studies, including the influence of laminar separation bubbles, are discussed. Several examples of small unmanned aerial vehicles (UAVs) in this regime are described. Also, a brief survey of analytical models for oscillating and flapping-wing propulsion is presented. These range from the earliest examples where quasi-steady, attached flow is assumed, to those that account for the unsteady shed vortex wake as well as flow separation and aeroelastic behavior of a flapping wing. Experiments that complemented the analysis and led to the design of a successful ornithopter are also described.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".