Three statistical jet noise prediction models are compared for a representative set of single-stream jet cases, which include cold and hot jets of the Strategic Investment in Low-Carbon Engine Technology experiment at an acoustic Mach number of 0.875 as well as the cold jets of the NASA small hot jet acoustic rig experiment at acoustic Mach numbers of 0.5 and 0.9. The implemented models are those proposed by Tam and Auriault (Jet Mixing Noise from Fine-Scale Turbulence,” AIAA Journal, Vol. 37, No. 2, 1999, pp. 145–153), Khavaran and Bridges (“An Empirical Temperature Variance Source Model in Heated Jets,” NASA TM 2012-217743, 2012), and the Goldstein’s “A Generalized Acoustic Analogy,” Journal of Fluid Mechanics, Vol. 488, July 2003, pp. 315–333) generalized acoustic analogy (GAA) model. By virtue of reduced-order modeling, which is based on the single-point mean flow and turbulence statistics, all of these implementations use a number of empirical dimensionless source parameters for far-field noise spectra predictions. In comparison with the Tam and Auriault model, the Khavaran and GAA model implementations use several dimensionless parameters, which are available from previous literature and assumed to be more or less universal for a class of single-stream jets. These parameters include the fluctuating enthalpy function and the dimensionless amplitudes of autocovariances of turbulent fluctuating stresses and velocities available from the literature. The comparison of the three models is aimed at not only assessing their accuracy for a range of jet conditions, observer angles, and frequencies but also to examine their robustness outside of a reference jet experiment for which their source models were calibrated. For the input to each model, the mean flow, turbulence kinetic energy, and dissipation rate extracted from Large Eddy Simulations and Reynolds-averaged Navier–Stokes solutions are considered.


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    Title :

    Robustness of Reduced-Order Jet Noise Models


    Contributors:

    Published in:

    AIAA Journal ; 61 , 1 ; 315-328


    Publication date :

    2023-01-01




    Type of media :

    Conference paper , Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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