Acoustic Modeling of Compressible Jet from Chevron Nozzle: A Comparison of URANS, LES and DES Models

Murugu, Sakthi Prakash; Srikrishnan, A R; Krishnaraj., Bharath Kumar; Jayaraj, Anguraj; Mohammad, Akram; Velamati, Ratna Kishore

doi:10.3390/sym14101975

Cited by 6 publications

(2 citation statements)

References 36 publications

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“…The LES_WALE and Ffowcs William Hawking models are versatile and widely used in aeroacoustics simulation. They can be applied in various applications such as aircraft noise [32,33], wind turbine [34][35][36], automotive noise [37], and underwater acoustic [38][39][40][41].…”

Section: Methodsmentioning

confidence: 99%

Co-simulation approach for computational aero-acoustic modeling: Investigating wind-induced noise within two-way radio microphone ports cavity

Hairudin,

Mat,

Ooi

et al. 2024

J. Mech. Eng. Sci.

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Wind-induced noise (aeroacoustic) can cause problem with any outdoor microphone applications, notably impacting the performance of telecommunication mobile. One prominent source in two way radios is the microphone port cavity. In this article, the noise characteristics behaviour is studied at scale-up of microphone port cavity through computational aero-accoustics (CAA) numerical simulation and experimental test. This research aims to investigate the wind-induced noise (aeroacoustic) generated inside the microphone port cavity at various wind orientation angles (wind direction) and distance radii, r. A direct-hybrid co-simulation CAA method, utilizing the LES-WALE (Wall-Adapting Local Eddy-viscosity) and Ffowcs William-Hawking (FW-H) models, is employed to obtain the near-field noise source and far-field noise patterns inside a microphone port cavity. The simulations are conducted using the scFLOW2Actran software. Richardson extrapolation and Grid Convergence Index (GCI) are applied to evaluate the accuracy of the grid independency in numerical simulations.The findings reveal that the leading edge, centre and trailing edge are the primary noise sources and generations inside a microphone port. The study indicates that the noise level in the microphone port cavity is characterized by low frequency noise.The results indicates that at an observation of angles of 0° and distance radii of 0.2 m, the wind noise level is higher compared to other orientation angle and distance radii. This can be attributed to the proximity to the noise source at this location. The directivity pattern of noise propagation exhibits a typical dipole pattern observed at observation angles of 0° to 45°. Numerical results align well with the experimental results from the wind tunnel test, demonstrating the feasibility of the proposed approach for flow-acoustic coupling application. This research holds significant value for engineers as it provides a comprehensive understanding of the physical phenomena involved in microphone port design.

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Section: Methodsmentioning

confidence: 99%

Co-simulation approach for computational aero-acoustic modeling: Investigating wind-induced noise within two-way radio microphone ports cavity

Hairudin,

Mat,

Ooi

et al. 2024

J. Mech. Eng. Sci.

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“…Numerous research using numerical simulations have attempted to explain the phenomena that causes the chevrons to operate, reduce noise, and change the flow field. Additionally, the difference in pressure between the top and bottom surfaces of chevrons and the presence of the triangular shape in the chevron design, generates vortices that extend downstream of the nozzle acting as sound barriers that disrupt the coherent sound waves produced by the jet and reduce the overall sound pressure level (OASPL [19][20][21][22]).…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of a Micro Turbojet Engine Chevrons Nozzle by Means of the Schlieren Technique

Cican,

Gall,

Bogoi

et al. 2023

Inventions

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In connection with subsonic jet noise production, especially regarding the hot jet from a micro turbojet engine, we encountered a lack of recent high-resolution data in the literature describing the flow field using experimental validation through optical diagnoses. The objective of this paper is to examine and compare the influence on shear layers of the exhaust plug nozzle of a micro turbojet engine with and without chevrons mounted, using a high-speed camera used in Schlieren-type optical system diagnosis. Three different operating regimes are examined for both the baseline configuration and the configuration with 16 triangular-shaped chevrons. In conjunction with the image captures, the sound pressure level was recorded with the help of a microphone placed perpendicular to the flow, 0.4 m from the exhaust of the nozzle which was further processed. In quantitative terms, we found that the OASPL decreases by more than 1% when the engine is operating at higher regimes. Moreover, we found that the average exhaust jet angle, which is a measure of the quality of the fluid mixing layer is increased by 5% with respect to the baseline nozzle. By using the “darkest pixel” technique in Schlieren imaging, we can verify experimentally, for all working regimes, the theory that asserts that subsonic jet noise is a consequence of fine-scale homogeneous turbulence. Additionally, the potential novelty lies in the specific observations related to consistent dispersion of fine-scale eddies and how the presence of chevrons amplifies this uniformity within the turbulent field.

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Airfoil Self Noise Prediction Using Machine Learning and Explainable AI

Pandey,

Gupta

2024

2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS)

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Acoustic Modeling of Compressible Jet from Chevron Nozzle: A Comparison of URANS, LES and DES Models

Cited by 6 publications

References 36 publications

Co-simulation approach for computational aero-acoustic modeling: Investigating wind-induced noise within two-way radio microphone ports cavity

Co-simulation approach for computational aero-acoustic modeling: Investigating wind-induced noise within two-way radio microphone ports cavity

Experimental Investigation of a Micro Turbojet Engine Chevrons Nozzle by Means of the Schlieren Technique

Airfoil Self Noise Prediction Using Machine Learning and Explainable AI

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