14:00
UAS/UAM noise modelling 1
14:00
20 mins
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High-Fidelity Aeroacoustics Analysis of Non-Uniformly Spaced Propellers for Quiet Urban Air Mobility
Hussain Ali Dr Abid, Nick B. Zang, Hulya Dr Biler, Hassan Ali Abid, Igor Solnstev, Sergey Karabasov
Abstract: The deployment of low-noise propulsion systems is essential for the widespread public acceptance of drones and urban air mobility in densely populated environments. Unevenly spaced propeller blades have emerged as a promising passive noise-reduction strategy by redistributing acoustic energy and spreading dominant tonal peaks over a broader frequency range, thereby reducing the overall A-weighted sound pressure level. This study investigates the aerodynamic and aeroacoustic effects of asymmetric blade spacing on four- and six-bladed propellers. High-fidelity numerical methods, including Reynolds-Averaged Navier–Stokes simulations and GPU-accelerated wall-modelled large eddy simulations, are employed and complemented by experimental validation conducted in a dedicated anechoic chamber. Propellers based on the APC
10×7 profile serve as baselines, with tailored non-uniform blade distributions examined for both four- and six-bladed configurations. Preliminary results at 4000 rpm indicate that the six-bladed baseline generates approximately 21% higher thrust than the four-bladed counterpart. Flow-field analysis reveals increased wake velocity and turbulent kinetic energy for the six-bladed configuration, accompanied by a downstream shift and broader spatial distribution of high-energy regions. These aerodynamic characteristics are shown to influence the effectiveness of uneven blade spacing for noise mitigation. The final paper will present a comprehensive aeroacoustic assessment of multiple asymmetric configurations, linking unsteady flow structures to noise directivity and providing design guidance for next-generation quiet drone rotors.
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14:20
20 mins
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Gaussian Process-Based Time-Domain Modeling for Multi-Rotor Noise Prediction
Jeongwoo Ko, Minhyuk Kim
Abstract: A probabilistic modeling framework based on Gaussian Process Regression (GPR) is presented for aeroacoustic noise prediction of multirotor vehicles in forward flight. The framework is designed to directly model aeroacoustic noise signals in the time domain, enabling uncertainty-aware prediction of both deterministic and stochastic signal components. By directly predicting time-domain signals, the proposed approach enables accurate reproduction of time–frequency characteristics and supports psychoacoustic and perceptual noise evaluation. The GPR model is trained using a database of simulated aeroacoustic signals generated with the Comprehensive Multi-rotor Noise Assessment (CONA) framework. To reflect the distinct physical characteristics of the multirotor flight noise, the time-domain signals are decomposed into tonal and broadband components prior to modeling. Tonal contributions are represented using a blade-passage-frequency-informed Fourier kernel, while broadband components are captured through a likelihood formulation. The predictions show good agreement in both time and frequency domains. Furthermore, psychoacoustic metrics are used to assess the model accuracy, with loudness differences not exceeding 4.24 sones (5.55% of the reference loudness). The proposed framework is designed with consideration for application to experimentally measured aeroacoustic noise. In particular, the probabilistic structure of the model is intended to accommodate measurement uncertainty encountered in real-world operating conditions.
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14:40
20 mins
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A numerical study on the aeroacoustics of a propeller at low Reynolds number subjected to vortical gusts
Mario Alì, Andrea Piccolo, Riccardo Zamponi, Daniele Ragni, Francesco Avallone
Abstract: In real flight conditions, drones are typically exposed to turbulent flow arising from the atmospheric boundary layer, upstream obstacles, and temperature gradients. While a substantial body of research has focused on the aeroacoustics of propellers operating in homogeneous and nearly isotropic turbulence, the interaction between a propeller and sudden, directional, and non-chaotic velocity perturbations - namely vortical gusts - has not yet been investigated because of the difficulty in reproducing such conditions in a controlled environment.
The present work investigates, for the first time and through numerical simulations, the effect of sinusoidal, single frequency vortical gusts on the aeroacoustic response of a propeller operating at low Reynolds number in forward flight. The objective of this study is to elucidate the influence of gust frequency, initial phase, and direction on the aeroacoustic performance of the propeller, as well as to identify the underlying noise generation mechanisms under these challenging conditions. A series of Very Large Eddy Simulations (VLES), based on the Lattice Boltzmann Method (LBM), are conducted in a digital environment developed within the PowerFLOW software. The gusts are introduced by imposing an appropriate time-varying boundary condition at the inlet. This ensures the free-divergence condition, preventing the formation of spurious acoustic waves.
Preliminary results show that gust induces tonal components in the noise spectrum at the gust frequency and in the vicinity of the first blade-passing frequency (BPF). This is attributed to a not perfectly balanced loading between the two blades. The additional tones show weak dependence on the phase of the propeller over one revolution.
The study aims to pave the way for further research into propeller aeroacoustics under realistic flight conditions.
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