Recent studies on distributed electric propulsion systems suggest phase synchronization between rotors as a noise reduction strategy. However, the aerodynamic interactions between propellers' near fields and their influence on far-field tonal noise remain poorly understood, partly due to experimental limitations in microphone placement. This paper addresses this gap through lattice Boltzmann very large eddy simulations of three adjacent, co-rotating rotors, spaced radially at 2% of their diameter, to investigate how relative phase angle affects tonal noise directivity. Results reveal that proximity-induced aerodynamic interactions generate dominant tonal noise in most spatial directions, driven by two mechanisms: time-averaged inflow distortion from nearby propellers and impulsive local effects at blade tips, with the latter influenced by phase angle. While the directivity pattern of the blade-passing frequency harmonic tone remains consistent across phase angles, comparing cases with zero relative phase (blades aligned) and opposite-phase conditions shows sound pressure level shifts of up to 4.5 dB along the primary noise axis, namely, along the inflow direction. Conversely, acoustic interference significantly alters noise directivity, especially in opposite-phase conditions where sound is nearly canceled in specific directions. These findings highlight rotor synchronization as a promising strategy for reducing noise emissions toward sensitive areas.

With the rapid proliferation of unmanned aerial vehicles, understanding the aeroacoustics of drones in operating conditions is essential to mitigate perceived annoyance. Performing these measurements in a large indoor test hall is particularly attractive, as it allows the execution of complex drone maneuvers under controlled atmospheric conditions, with high-precision trajectory tracking provided by motion capture systems. Yet, not being acoustically treated, these facilities present challenging reverberant conditions for acoustic measurements. This research work focuses on investigating a maneuvering quadcopter drone inside an indoor test hall and proposes a methodology based on phased-array techniques to decontaminate the recorded noise from the reverberation effects using a tailored Green's function. The results indicate that the tonal contributions of the noise spectrum are significantly influenced by drone operation and orientation, with distinct changes in the blade pass frequencies linked to the varying speeds of the front and back rotors during different flight phases. By filtering out spurious broadband noise due to sound reflections, the proposed dereverberation methodology facilitates the tracking of these tonal components, which can be more clearly visualized in the noise spectrum. The study eventually highlights the importance of analyzing the drone trajectory when interpreting the corresponding noise radiation.

The low-speed fans used for automotive engine cooling contribute to a significant part of the global noise emitted by the vehicle. A low-order sound-prediction methodology is developed considering the blade sweep-angle effect on the acoustic predictions of the turbulence-impingement and the trailing-edge noise-generating mechanisms. We modeled these through the application of a semianalytical method based on Amiet’s airfoil theory, appropriately adapted via a strip-theory approach accounting for rotation and modified to include the blades forward curvature. Sweep was already shown in the literature to reduce the noise emitted by isolated airfoils, but its effect on rotating machines was not yet well understood. In this study, we show that the effect of the sweep-angle is to globally reduce the emitted noise by the fan and to change the sound distribution of the sources along the blade span. Thus, the sweep-angle must be considered not only because it yields a better comparison with experimental results but also because wrong conclusions on the dominating noise-generating mechanisms can be drawn when this effect is not taken into account. The investigation is finally complemented by a sensitivity analysis focusing on some of the key parameters characterizing the acoustic prediction.