Evaluation of Acoustic Frequency Methods for the Prediction of Propeller Noise

Herniczek, Mark Kotwicz; Feszty, Dániel; Meslioui, Sid-Ali; Park, Jong; Nitzsche, Fred

doi:10.2514/1.j056658

Cited by 18 publications

(4 citation statements)

References 19 publications

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“…7. The presented results indicate the dipole nature of the noise emission of the propeller [17,18]. The maximum noise levels are observed in the direction of the azimuth angle of 90, which is consistent with the directional pattern of the first BPF tone of the studied propeller obtained under static conditions when the maximum was observed in the direction of 105 [13].…”

Section: Acoustic Resultssupporting

confidence: 88%

Simulation of Isolated Propeller Noise Using Acoustic-Vortex Method

2023

JSFI

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The widespread development of unmanned aerial vehicles and light propeller-driven aircraft poses the task of reducing the community noise of such vehicles. To solve this problem, tools are needed to calculate the noise of such devices. The paper presents the results of the numerical simulation of the noise of an AV-2 propeller mounted on an AN-2 light propeller-driven aircraft. The authors use the acoustic-vortex method to solve the problem of aeroacoustic modeling of propeller noise in the presence of an incoming flow. The paper shows a good agreement of computed data with the in-flight experiment results and the calculation by the semi-empirical method. For the flight mode with an airspeed of 180 km/h, the deviation of the numerical simulation results from the experimental data does not exceed 2 dB.

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Section: Acoustic Resultssupporting

confidence: 88%

Simulation of Isolated Propeller Noise Using Acoustic-Vortex Method

2023

JSFI

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“…As the most dominant excitation is provided in the first three harmonic frequencies of the BPF, these are investigated in the following section. A comprehensive overview of calculation methods for propeller noise in the frequency domain is given by Kotwicz-Herniczek et al [28].…”

Section: Propeller Excitationmentioning

confidence: 99%

Knowledge-based model generation for aircraft cabin noise prediction from pre-design data

Hesse,

Allebrodt,

Teschner

et al. 2024

Preprint

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The climate targets set out in the "European Green Deal" call for the consideration and implementation of climate-friendly propulsion concepts and sustainable fuels in future aircraft configurations. This puts the use of very efficient propeller engines into the focus of aircraft design. However, these pose major challenges, especially to cabin acoustics, due to high, tonal sound pressure levels on the fuselage. The design of noise control measures requires the competence to predict the resulting interior noise as early as possible in the design process of the vehicle. This requires a high level of geometric and structural detail regarding the fuselage structure and cabin components. With increasing frequency range, the necessary structural details also increase, which have to be resolved in the simulation models due to the associated decreasing structural wavelength. Especially in the context of aircraft pre-design, there is usually not enough information available for a detailed vibro-acoustic modeling of the fuselage and cabin components, which allows a meaningful prediction of the vibrations and thus the cabin noise. Therefore, the knowledge-based tool FUGA (Fuselage Geometry Assembler) is developed for the targeted enrichment of preliminary design data with knowledge for detailed numerical analyses. This paper describes the knowledge-based geometry and model generation in FUGA, which can consider the necessary (increasing) level of detail for the vibro-acoustic prediction already in the preliminary design. For this purpose, aircraft data sets in the preliminary design data format CPACS (Common Parametric Aircraft Configuration Schema) form the modeling basis. Originating from the aircraft preliminary design, these initially describe the outer shell of the vehicle and are extended by detailed structural information that defines the geometric boundary conditions for component placement in cabin design. For the cabin components, the open-source geometry kernel OCCT (Open Cascade Technology) is used to provide geometries at the level of detail required for subsequent analyses. The geometry models are then discretized in open source (e.g. Gmsh) or commercial meshers and further used for numerical analysis. Finally, the prediction of cabin noise is demonstrated as a Proof of Concept using the example of a short-haul propeller-driven aircraft and the sensitivity of resulting simulation models to the fuselage skin thickness is investigated.

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“…Lastly, Bessel functions are used to improve far-field noise prediction. The equations for the Barry-Magliozzi formulation are summarized in these references [87][88][89].…”

Section: Aeroacoustics Analysismentioning

confidence: 99%