Flow and acoustics of unmanned vehicles

There is a growing interest in unmanned vehicles (UVs) across applications. An improved understanding of fluid dynamics and acoustics of UVs and their components (e.g., propulsion systems) is crucial for optimal energy efficiency, maneuverability, and a low acoustic footprint. This special collection of articles presents the state-of-the-art research in the above field. The studies performed by the authors of these papers cover experimental and computational techniques and a range of applications, including air and underwater vehicles.

Huang et al.¹ conducted detached eddy simulations to study the vortex dynamics of a pre-swirl pumpjet propulsor (PJP) in an oblique inflow. They showed high hydrodynamic efficiency loss for this PJP system operating in a drift mode. The authors quantified the local flow properties of the different observed vortical structures and shed light on the hub rotation frequency in oblique flow conditions. Wu et al.,² for the first time, investigated both experimentally and numerically the tonal noise (near- and far-fields) of an unmanned aerial vehicle (UAV) propeller. Their UAV operated with a circular strut mounted just downstream. They measured pressure signals and observed the presence of a strong impulse caused by the propeller–strut interaction. The magnitude of the impulse is reduced with distance and increased between the propeller and the strut. Wu et al.² also developed analytical models to estimate the unsteady loading on the propeller and strut, which they compared with computational fluid dynamics (CFD) predictions and experimental measurements.

Wang et al.³ numerically studied the aerodynamic performance of a bio-inspired flapping wing with local weep morphing. They discussed the aerodynamic forces and unsteady vortex structures and showed that combined flapping and local sweep morphing could significantly enhance the aerodynamic performance. Moreover, they shed light on the local kinematics of combined flapping and local sweep morphing, which can be optimized if the outer wing captures the mid-span vortices. Fenyvesi et al.⁴ presented a new automated method to identify tone noise sources' interaction of counter-rotating rotors. They analyzed a series of beam-forming noise source maps by employing principal component analysis-based methods. This method quantifies the dominant noise generation mechanisms in frequency bins associated with interaction tones.

Xu et al.⁵ numerically studied the training of a self-propelling agent to migrate in an unsteady flow environment. They utilized the back-flow structure in agent controlling, employing a reinforcement learning algorithm to minimize energy consumption. Xu et al.⁵ investigated agent migration under two flows: (i) a simple periodical double-gyre flow and (ii) a complex turbulent Rayleigh–Bénard convection. They revealed important findings that impact many migration problems, such as energy-efficient trajectories of unmanned aerial vehicles flying in a turbulent convective environment.

Yucel et al.⁶ employed particle image velocimetry and CFD to investigate the vortical structures' local behavior in a biplane configuration of plunging airfoils. The authors aimed to disclose the vortex shedding and interaction mechanisms for various values of frequency and amplitude of the plunging motion and the effect of phase difference on vortex structures and propulsive characteristics, such as thrust and Froude efficiency. They found that the opposed plunge (180°) is the most efficient among all the phase angles investigated, where 90° is beneficial in lift production.

Faure et al.⁷ validated low-order models for cetacean propulsion generated by a periodic flapping motion of their fluke. They shed light on the discrete vortex method, where the viscous drag modeling method should be added to obtain reliable thrust results for all Garrick frequencies below 2. They proposed a modification of the method that considers the wing dihedral that results from the spanwise flexibility. They produced local vorticity fields, which were then compared to previously published data from the literature. The choice of deformation parameters applied to a highly flexible wing revealed how the discrete vortex method could produce more reliable results.

Wang et al.⁸ developed an acoustic observation application of the Petrel acoustic Autonomous Underwater Vehicles (AUV) in marine monitoring, focusing on AUV self-noise in a passive acoustic monitoring mode. They evaluated the self-noise characteristics of Petrel acoustic AUVs using simulation and testing. Wang et al.⁸ showed how ideal these AUVs are when used as an acoustic observation platform for multiple diverse observation tasks.

Using a two-fluid model in three dimensions, Hou et al.⁹ investigated the high-pressure zones and near-field pressure evolution of shock waves between two detonation tubes. These tubes have an important place in several applications of underwater propulsion systems. They shed light on the performance of dual-tube detonation as affected by the pressure evolution under different factors, such as tube intervals, ignition delays, and filling conditions. Hou et al.⁹ found that shock waves' directivity and intensity levels are sensitive to these factors.

Ko et al.¹⁰ developed a multirotor noise assessment framework for noise prediction in rotational-speed-real-time-controlled rotor configurations for the first time. The method intends to extract the frequency-modulated multirotor noise from the frequency modulation (FM) characteristics. The latter is identified by a synchrosqueezing-based high-resolution TFA (very non-stationary signals). Ko et al.¹⁰ showed how their framework could facilitate noise assessment at the early stages of multirotor configuration design.

Usually, numerical studies neglect the fluctuating rotational speed of the rotors—in revolutions per minute (RPM)—due to the high computational cost involved. Therefore, Jeong et al.¹¹ studied the acoustic characteristics of a multirotor through a stochastic numerical analysis that considers the RPM fluctuations. They showed how the proposed stochastic analysis method could efficiently predict the multirotor noise in the presence of RPM fluctuations.

Wang et al.¹² numerically investigated the power factor that measures the efficiency of a gliding wing with spanwise oscillation to support a unit weight. The spanwise oscillation could provide an alternative to flapping motion toward high-efficiency bio-inspired flight. They found that the spanwise oscillation can enhance the power factor of the rectangular wing by 1.97 times compared to the case without spanwise oscillation. Moreover, the authors introduced an effective reduced frequency to account for the spanwise velocity oscillations encountered by the wing. They also analyzed the vortex structures and the Lamb vector field, showing that enhanced power factor results from the interaction between the stable leading-edge vortex and side-edge vortices associated with the spanwise oscillation.

Dbouk and Drikakis¹³ investigated the acoustic noise induced by drone swarms. They developed a high-resolution computational methodology for predicting the aeroacoustic footprints of an overall swarm of six multi-copter drones (four rotors for each drone). For the first time, Dbouk and Drikakis¹³ addressed the aerodynamics and the acoustic noise footprints showing how a V-flight formation of multi-copter drones can emit less sound pressure level noise than a U-shape (or rectangular) formation. They also revealed how the V-shape flight formation induces a reduced drag compared to the U-shape formation, thus reducing the overall energy consumption.

Liu et al.¹⁴ simulated a full-scale submarine propelled by a high-skew propeller. They employed a dynamic overset grid approach to simulate the local rotation of the propeller. They predicted and analyzed the self-propulsion performance and then investigated the influence of different parameters on the accuracy of simulation results, such as the addition of a skin friction correction factor. Finally, after comparison with results from the literature, they made detailed discussion on the discrepancies between the sub-scale and full-scale models/approaches to predict accurate self-propulsion indicators, e.g., propeller performance, boundary layer, pressure distribution, and wake flow.

We hope that the developments and scientific and engineering challenges reported in the aforementioned studies will stimulate further research in the fluid dynamics and acoustics of UVs.