A review of aeroacoustic shape optimization of micro-UAV rotors
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Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
Published on: August 27, 2021
Chengxi Wang1, Bochun Zhang2, Jianqiang Xia3
1Faculty of Transportation Engineering, Kunming University of Science and Technology, No. 727, Jingming South Road, Chengguan District, Kunming City, Yunnan Province, Kunming, 65050, China.
Abstract:
With the development of micro-unmanned aerial vehicles (micro-UAVs) in more applications, especially the urban areas, the rotor aeroacoustic noise becomes increasingly concerning. Operating mostly within low-Reynolds-number regimes (Re ≈ 104~105), micro rotors encounter complex unsteady flow phenomena like laminar separation and boundary layer transition that heavily influence both aerodynamic efficiency and noise emission. This review systematically examines the generation mechanisms and predictive methodologies of micro-UAV rotor noise, highlighting the reason behind traditional macroscopic geometric optimizations (e.g., chord, twist, and tip modifications) that frequently descend into a zero-sum game between acoustic attenuation and aerodynamic performance. Then the recent advancements in bio-inspired aeroacoustic shape optimization trying to transcend these inherent bottlenecks were summarized. The physical mechanisms underlying owl-inspired serrations, dragonfly-inspired corrugations, and flexible porous materials that otherwise effectively modulate near-wall turbulence and disrupt spanwise coherent structures were paid closely attention. Furthermore, the paradigm shift driven by Multidisciplinary Design Optimization and data-driven machine learning frameworks due to prohibitive costs of high-fidelity simulations can be circumvented during achieving true aeroacoustic-aerodynamic synergistic design were explored prior to outlining a future roadmap emphasizing the critical transition from isolated-rotor tailoring to array-level system aerodynamic interference control with an aim to provide a theoretical foundation for the development of future low-noise micro-UAV platforms.
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