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Computational aeroacoustics of aerofoil leading edge noise using the volume penalization-based immersed boundary methods

Broadband noise due to the turbulence-aerofoil interaction, which is also called the leading edge noise, is one of the major noise sources of aircraft (including the engine). To study the noise properties numerically is a popular approach with the increasing power of computers. Conventional approach...

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Published in:International journal of aeroacoustics 2022-03, Vol.21 (1-2), p.74-94
Main Authors: Ying, Wei, Fattah, Ryu, Cantos, Sinforiano, Zhong, Siyang, Kozubskaya, Tatiana
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Language:English
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description Broadband noise due to the turbulence-aerofoil interaction, which is also called the leading edge noise, is one of the major noise sources of aircraft (including the engine). To study the noise properties numerically is a popular approach with the increasing power of computers. Conventional approaches of using body-fitted grids at the boundaries would be convoluted due to the complex geometries, which can constrain the efficiency of parametric studies. A promising approach to tackle this issue is to use the immersed boundary method (IBM). Among various IBM variants, the volume penalization (VP) approach employs a masking function to identify the immersed solid boundary, and continuous forcing terms are added to the original flow governing equations to account for the boundary conditions. It is, therefore, efficient and easy to implement into the existing computational aeroacoustics solvers. In this work, the VP-based IBM is used to simulate the leading edge noise by combining with the advanced synthetic turbulence method. The simulations are conducted for both the isolated aerofoils and cascade, and the results are compared with the well-validated body-fitted grid solutions. The viscosity effect is also highlighted by comparing the results obtained by solving both Euler and Navier–Stokes equations.
doi_str_mv 10.1177/1475472X221079557
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title Computational aeroacoustics of aerofoil leading edge noise using the volume penalization-based immersed boundary methods
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