Simulation and analysis of flow around tilting asymmetric ducted fans mounted at the wing tips of a vertical take-off and landing unmanned aerial vehicle
Bibliographic record
Abstract
Tilting ducted fans attached to the wing tips of vertical take-off and landing unmanned aerial vehicles define new applications for these types of aerial vehicles. This new configuration gives vertical take-off and landing unmanned aerial vehicles the ability to hover like helicopters and fly forward like airplanes, which results in using any arbitrary location for take-off and landing combined with increasing range and speed. Furthermore, generating additional lift using asymmetrical shape for the external body of the ducted fans can lead to reducing the wing area and related overall drag, which results in saving more energy. This research provides experimental results from wind tunnel tests in addition to computational fluid dynamics simulations to investigate the advantages of using an asymmetrical tilting ducted fan instead of a symmetrical one. “actuator disk model” combined with the assumption of “constant delivered power” to the propeller were used successfully to calculate the induced velocity to the rotor plane of the ducted fan in the computational fluid dynamics simulations. The effects of the stall and flow separation on the aerodynamic coefficients were also studied and compared for the symmetrical and asymmetrical ducted fans. Both computational fluid dynamics and experimental results showed noticeable improvement in the lift coefficient using an asymmetrical shape for the external body of the tilting ducted fans.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".