A Numerical and Analytical Approach of the Sound-Scattering Effects in Rotor-Strut Interaction Noise of Small-Size Drones
Bibliographic record
Abstract
This paper addresses various aspects of the aerodynamic noise radiated by small-size drone rotors, emphasizing on a simplified generic configuration, including a rotor and a diametrically and radial aligned downstream cylinder. In this configuration, as the rotor-cylinder distance is reduced, three intricate mechanisms are expected, namely sound generation by the rotor operating in the potential distortion of the cylinder, noise generation by the cylinder because of impinging wakes from the rotor blades, and scattering of each emitted sound by the complementary body. Some focus is put on the possible amplification of rotor noise by the cylinder scattering at the lowest frequencies. The study is both theoretical and numerical, complemented with experimental data. The scattering of rotor noise is modeled analytically, by associating a potential-interaction noise model and the exact Green’s function for the rigid cylinder. Lattice-Boltzmann simulations are performed for the selected configuration in its complete experimental set-up, capturing unsteady aerodynamics and acoustic features of the problem. A direct noise propagation, and the noise obtained form applying FW-H acoustic analogy are compared with the results measured in a previous work. Results obtained from the performed simulations are used as input parameters for the analytical model to perform preliminary predictions and comparisons.The outcomes are believed to provide guidelines for the future design of quieter drones.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".