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The prediction of jet mixing noise from a stochastic realization based on the Tam & Auriault model was previously studied for cold jet configurations. To generate the acoustical sources the Random Particle M esh method (RPM) was applied, which uses turbulence statistics from RANS data. The generated stochastic sound sources closely realize twopoint cross-correlation functions of the fine-scale jet mixing noise model. In this work the RPM method is extended to realize besides the cross-correlations of the cold jet noise model of Tam & Auriault also those of the hot jet noise model proposed by Tam, Pastouchenko and Viswanathan. For the stochastical realization of the latter model, a recently proposed three-parameter Langevin procedure is utilized to reproduce the cross-correlation functions. The RPM code is combined with the DLR CAA solver PIANO. Similarly to the cold jet noise computations, for hot jet noise computations we use the azimuthal-modal decomposed Linearized Euler Equations (LEE). The combination of stochastic source modeling with an azimuthal formulation allows to predict efficiently in the near-field the fine-scale jet noise spectra at any position. For the prediction of far-field noise spectra the modal Ffowcs-Williams and Hawkings method is conducted subsequently to the CAA computations. In the second part of this paper, the ability to simulate large scale noise by means of linearized Euler equations, including mean-flow gradient terms that allow for the onset of hydrodynamic instabilities, will be discussed. Finally, the CAA results of dual-stream jet computations with nozzle geometry variations are discussed. |
