Improvement and validation of a propeller slipstream model for small unmanned aerial vehicles
Why this work is in the frame
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Bibliographic record
Abstract
Airflow from the propeller, called the propeller slipstream or propwash, plays an important role in the aerodynamics of small unmanned aerial vehicles (UAVs). In fact, flights at low forward speeds or extreme angle of attack (AoA) maneuvers of small fixed-wing UAVs are possible only because the propeller slipstream provides the airflow necessary to maintain lift and control under these conditions. Almost all related works in the literature consider propeller slipstream effect on the UAV's aerodynamics by means of simple theories such as the momentum theory, classical lifting line theory etc. However, these theories take into account only the acceleration of air within the slipstream while failing to account for its diffusion, thereby limiting their applicability to the region near the propeller where acceleration is dominant; far downstream of the propeller, these theories predict unreasonably high induced velocities since diffusion of the slipstream is not accounted for. A propeller slipstream model that considers both acceleration and diffusion within the slipstream has already been presented in a previous work by the authors. The main objective of the current work is to present improvements made to the model in light of detailed experimental measurements of the induced velocity downstream of the propeller. Thereafter, validity of the propeller slipstream model is also demonstrated via additional experiments. The model is shown to be accurate up to an axial distance of ~5 propeller diameters from the propeller plane, with a root mean square error of 0.45 m/s at 1750 rpm and 1.21 m/s at 6425 rpm.
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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 | 0.000 | 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 it