Similarity scaling of jet noise sources for low-order jet noise modelling based on the Goldstein generalised acoustic analogy

Abstract

As a first step towards a robust low-order modelling framework that is free from either calibration parameters based on the far-field noise data or any assumptions about the noise source structure, a new low-order noise prediction scheme is implemented. The scheme is based on the Goldstein generalised acoustic analogy and uses the Large Eddy Simulation database of fluctuating Reynolds stress fields from the CABARET MILES solution of Semiletov et al. corresponding to a static isothermal jet from the SILOET experiment for reconstruction of effective noise sources. The sources are scaled in accordance with the physics-based arguments and the corresponding sound meanflow propagation problem is solved using a frequency domain Green’s function method for each jet case. Results of the far-field noise predictions of the new method are validated for the two NASA SHJAR jet cases, sp07 and sp03 from and compared with the reference predictions, which are obtained by applying the Lighthill acoustic analogy scaling for the SILOET far-field measurements and using an empirical jet-noise prediction code, sJet.