High-Fidelity Simulations of Noise Generation in a Propeller-Driven Unmanned Aerial Vehicle

Mankbadi, Reda R.; Afari, Samuel; Golubev, Vladimir V.

doi:10.2514/1.j059117

Cited by 28 publications

(35 citation statements)

References 28 publications

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“…The library has been used to simulate compressible free jets, and the results have been compared favorably to the experimental data using the FWH method [ 29 , 30 ]. It has also been used to simulate the marine propeller noise [ 31 ] and the rotor noise from unmanned arial vehicles [ 32 , 33 ]. Airfoil-generated noise and jet noise has been successfully simulated utilizing the libAcoustics implementation of the FWH method.…”

Section: Methodsmentioning

confidence: 99%

Validating Confined Flame Noise Simulation Using External Sensor

Williamson

Srivastava²,

Sallam

2022

Sensors

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Advancements in lean premixed combustion have increased the efficiency and reduced the amount of greenhouse gas emissions, but they have led to increased noise emissions due to higher turbulence and mixing fluctuations. This study used an external sensor (microphone) to validate the simulation of the combustion noise of a confined space. An experimental facility with a laboratory-scale furnace was used to carry out the measurement, and the simulation of the confined flame noise was conducted in OpenFOAM. The simulation utilized the Partially Stirred Reactor (PaSR) and a hybrid computational aeroacoustics (CAA) approach using the large eddy simulation (LES)/the Ffwocs Williams–Hawkings (FWH) method. Additionally, unsteady Reynolds-averaged Navier–Stokes (URANS)/the FWH method was tested for a comparison with the LES prediction. A sensor which was placed outside the enclosure for ease of access was then used to validate the results of the numerical model. The sensor data agreed with the LES/FWH results including the amplitude and frequency of the primary combustion peak and the overall sound pressure level (OASPL). This suggested that a sensor which was placed outside the enclosure could serve as a validation tool for the simulation of the confined flames despite the sound reflections from the walls.

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Section: Methodsmentioning

confidence: 99%

Validating Confined Flame Noise Simulation Using External Sensor

Williamson

Srivastava²,

Sallam

2022

Sensors

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“…The minimal differences in the broadband noise spectrum for solid and permeable surfaces implies the expected insignificance of quadrupole source for propellers with low blade-tip Mach number [37]. This being said, quadruple source is posited [7] to be significant component for multi-propeller configurations due to wake interactions. The broadband in the range of 0.7 -1.4 kHz is not observed in the either numerical spectra.…”

Section: Far-field Characteristicsmentioning

confidence: 99%

“…Although noise generation mechanisms in classical propeller based applications such as helicopters are well researched in the literature, noise generation in DEP propellers could be significantly different due to deviations in the size and operational parameters (rotational speed, Reynolds number, Mach number). For instance, Mach numbers for helicopter propeller tips are usually [7] between 0.7 ≤ ≤ 0.8 while DEP propellers are in the range of 0.1 ≤ ≤ 0.2. This puts the acoustic signature of DEP propellers closer to small unmanned aerial vehicles (UAVs) propellers than the classical helicopter propellers.…”

Section: Introductionmentioning

confidence: 99%

“…Diaz and Yoon [8], Perez and Lopez [9], Zawodny et al [10], Afari et al [11] and Mankbadi et al [7] numerically investigated aerodynamic and acoustic aspects of small commercial UAVs. Diaz and Yoon [8] used a higher-order accurate code with detached eddy simulation (DES) based turbulence formulation to model aerodynamic aspects of single rotor and multi-rotor commercial drones while the acoustic aspects were not deliberated.…”

Section: Introductionmentioning

confidence: 99%

“…Perez and Lopez [9] also investigated flow field of a small UAV without solving for the acoustic parameters. Zawodny et al [10] used unsteady Reynolds-averaged Navier-Stokes (RANS) coupled with the Ffowcs-Williams and Hawkings (FW-H) acoustic analogy to study broadband noise propagation for a small UAV while Afari et al [11] and Mankbadi et al [7] employed the DES turbulence formulation along with the FW-H formulation to investigate the propagation of both tonal and broadband noise generated by a small UAV to the far-field. Several experimental campaigns to acoustically characterise small UAVs include the work of Lu et al [12] and Intaratep et al [13] while aerodynamic interaction between the propellers of a DEP system is explored by Vries et al [14].…”

Section: Introductionmentioning

confidence: 99%

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Numerical characterisation of noise generated by a distributed-propulsion propeller

Sharma

Ambrose

Jefferson-Loveday

2022

28th AIAA/CEAS Aeroacoustics 2022 Conference

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The shift towards sustainable and eco-friendly future of aviation is further catalysed by the aggressive targets set by administrative and industrial stakeholders. It has emerged as one of the solutions with the potential to increase overall efficiency and improve noise emissions. This paper characterises the flow and acoustic field associated with a DEP propeller. A hybrid methodology using scale-resolving turbulence formulation and an acoustic analogy is used to predict aerodynamic noise generation and acoustic wave propagation to the far-field for an isolated DEP propeller. The numerical predictions are observed to be in reasonable agreement with the measured values for both aerodynamic and aero-acoustic attributes. The sensitivity of far-field acoustic spectra to the integration surface is also presented. The results are further analysed to identify dominant noise sources in the system including propeller and wake flows. I. Nomenclature= density RANS = Reynolds-averaged Navier-Stokes LES = Large eddy simulation WALE = Wall-adopted local eddy-viscosity DEP = Distributed electric propulsion

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Study of an aviation opposed piston engine noise

Moshkov

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High-Fidelity Simulations of Noise Generation in a Propeller-Driven Unmanned Aerial Vehicle

Cited by 28 publications

References 28 publications

Validating Confined Flame Noise Simulation Using External Sensor

Validating Confined Flame Noise Simulation Using External Sensor

Numerical characterisation of noise generated by a distributed-propulsion propeller

Study of an aviation opposed piston engine noise

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