Aeroacoustic Analysis of Urban Air Operations Using the LB/VLES Method

Casalino, Damiano; Velden, Wouter C. van der; Romani, Gianluca; Gonzalez-Martino, Ignacio

doi:10.2514/6.2019-2662

Cited by 19 publications

(17 citation statements)

References 10 publications

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“…19 However, in some particular situations, such as in confined environments, these perturbations might be due to the rotor wakes recirculating in the domain and are within reach of modern unsteady flow simulations. 20 These unsteady sources are not modelled in the optimization process as their prediction requires significant computational resources. Thus, only trailing edge noise, which can be estimated with statistical models given a few flow assumptions, is added to the steady loading noise prediction.…”

Section: Numerical Methodology For Mav Blade Noise Reductionmentioning

confidence: 99%

Towards silent micro-air vehicles: optimization of a low Reynolds number rotor in hover

Serré

Gourdain

Jardin

et al. 2019

International Journal of Aeroacoustics

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The demand in micro-air vehicles is increasing as well as their potential missions. Either for discretion in military operations or noise pollution in civilian use, noise reduction of micro-air vehicles is a goal to achieve. Aeroacoustic research has long been focusing on full scale rotorcrafts. At micro-air vehicle scales however, the hierarchization of the numerous sources of noise is not straightforward, as a consequence of the relatively low Reynolds number that ranges typically from 5000 to 100,000 and low Mach number of approximately 0.1. This knowledge, however, is crucial for aeroacoustic optimization and blade noise reduction in drones. This contribution briefly describes a low-cost, numerical methodology to achieve noise reduction by optimization of micro-air vehicle rotor blade geometry. Acoustic power measurements show a reduction of 8 dB(A). The innovative rotor blade geometry allowing this noise reduction is then analysed in detail, both experimentally and numerically with large eddy simulation using lattice Boltzmann method. Turbulence interaction noise is shown to be a major source of noise in this configuration of low Reynolds number rotor in hover, as a result of small scale turbulence and high frequency unsteady aeroadynamics impinging the blades at the leading edge.

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Section: Numerical Methodology For Mav Blade Noise Reductionmentioning

confidence: 99%

Towards silent micro-air vehicles: optimization of a low Reynolds number rotor in hover

Serré

Gourdain

Jardin

et al. 2019

International Journal of Aeroacoustics

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show abstract

“…Future work is needed to correlate this engineering parameter to human perception via psycho-acoustic methods. Once this parameter deemed viable in assessing aspects of annoyance, it can facilitate the assessment of the noise impact (by for instance applying it to data of high-fidelity numerical computations of rotor noise 29,30 or even to noise data of complete UAM vehicles in urban environments 31,32 ). A modulation parameter can also form a cost function in a design optimization for low-noise rotor technologies.…”

Section: B Present Contribution and Outlinementioning

confidence: 99%

Quantifying modulation in the acoustic field of a small-scale rotor using bispectral analysis

Baars

Bullard

Mohamed

2021

AIAA Scitech 2021 Forum

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This paper describes a methodology to quantify inter-frequency modulation in the acoustic field of a small-scale rotor. How the blade passing frequency modulates the intensity of the higher-frequency (broadband) noise content is of specific interest, as this modulation is a major factor in the human perception of rotor noise from advanced air mobility vehicles and drones. A proposed modulation-parameter is based on post-processing steps that are applicable to a single acoustic time series. First, an auto-bispectral analysis assesses the dominant nonlinear, quadratic inter-frequency coupling between the blade passing frequency and the higher-frequency noise content. Secondly, the degree of modulation is determined using a robust parameter: a correlation parameter between the (low-frequency) modulating BPF signal and an envelope of the (higher-frequency) carrier signal. Provided that a single parameter is obtained for a given acoustic time series, the directivity pattern of the modulation strength can be inferred from data available from standard acoustic measurement campaigns. For illustration, an 11 inch diameter single-rotor in hover is considered, with acoustic data taken at 420 microphone positions within a plane perpendicular to the rotor disk. It is revealed that modulation is confined to a sector θ ≈ (10 • , −45 • ), where θ = 0 • is the rotor plane and negative angles are in the direction of the rotor-induced flow. The strongest modulation appears around θ ≈ −15 • . This work aids in quantifying the phenomenological description of modulation, namely that it results from the periodic advance and retreat of certain rotor blade's noise sources, relative to a stationary observer.

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“…Apart from source modeling issues, assessing the noise impact in the environment also involves realistic propagation models that are beyond the scope of the present study. This aspect is addressed for instance by Bian et al [11] and Casalino et al [5].…”

Section: Introductionmentioning

confidence: 99%

“…It must be kept in mind that very accurate flow and noise predictions are only achievable with numerical simulation strategies, once all geometrical details and operational regimes are defined. For the moderate subsonic Mach numbers of interest, a practical approach succeeding in UAV noise prediction is the Lattice-Boltzmann Method (LBM), as already reported by, for instance, Nardari et al [4] and Casalino et al [5]. However, the price to pay for accuracy is a higher computational cost.…”

Section: Introductionmentioning

confidence: 99%

Tonal-Noise Assessment of Quadrotor-Type UAV Using Source-Mode Expansions

Roger

Moreau

2020

Acoustics

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The present work deals with the modeling of the aerodynamic sound generated by the propellers of small-size drones, taking into account the effects of horizontal forward flight with negative pitch and of installation on supporting struts. Analytical aeroacoustic formulations are used, dedicated to the loading noise. The fluctuating lift forces on the blades are expanded as circular distributions of acoustic dipoles, the radiated field of which is calculated by using the free-space Green’s function. This provides descriptions of the sound field, valid in the entire space. The stationary mean-flow distortions responsible for the lift fluctuations and at the origin of the sound are estimated from existing numerical flow simulations and from ad hoc models. Installation and forward-flight effects are found to generate much more sound than the steady loading on the blades associated with thrust. Therefore, the models are believed reliable fast-running tools that could be used for preliminary low-noise design through repeated parametric calculations, or for noise-impact estimates corresponding to prescribed urban traffic.

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Aeroacoustic Analysis of Urban Air Operations Using the LB/VLES Method

Cited by 19 publications

References 10 publications

Towards silent micro-air vehicles: optimization of a low Reynolds number rotor in hover

Towards silent micro-air vehicles: optimization of a low Reynolds number rotor in hover

Quantifying modulation in the acoustic field of a small-scale rotor using bispectral analysis

Tonal-Noise Assessment of Quadrotor-Type UAV Using Source-Mode Expansions

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