Use of Stochastic Turbulence Models in Jet Acoustics

Authors

A. Ahmadzadegan Corresponding Author, Department of Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran. Center of Excellence in Computational Aerospace Engineering (AeroExcel) (e-mail: [email protected])

M. Bayati Corresponding Author, Department of Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran. Center of Excellence in Computational Aerospace Engineering (AeroExcel) (e-mail: [email protected])

M. Tadjfari Corresponding Author, Department of Aerospace Engineering, Amirkabir University of Technology, Tehran, Iran. Center of Excellence in Computational Aerospace Engineering (AeroExcel) (e-mail: [email protected])

Abstract:

There are many approaches to determine the sound propagated from turbulent flows. In hybrid methods, the turbulent noise source field is computed or modeled separately from the far-field calculations. To have an initial and quick estimation of the sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations. In this paper, turbulent mean flow of a two dimensional, compressible, cold-jet at Mach 0.56 is computed using RANS with 2 equation k-ε RNG model. The above mean-flow quantities are then used in a stochastic model to generate the details of the turbulent velocity fluctuations. This method is based on the use of classical Langevin equation to model the details of fluctuating flow field superimposed on the averaged computed quantities. The resulting sound field due to the generated unsteady flow is then evaluated using Lighthill's acoustic analogy. Our results are validated by comparing the directivity and the overall sound pressure level (OASPL) magnitudes with the available experimental data. Numerical results show reasonable agreement with the experiments, both in maximum directivity and the magnitude of the OASPL.

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