Correlation Analysis of High Resolution Particle Image Velocimetry Data of Screeching Jets
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The acoustic analogy provides a general framework for predicting broadband jet noise. The accuracy of the noise predictions are strongly dependent on the second- and fourth-order integral time and length scales of the turbulence quantities in the jet. Two low-order models for the second- and fourth-order integral length scales are examined. The low-order models are defined by locally isotropic scales estimated from 2D particle image velocimetry measurements. These measurements are of screeching underexpanded unheated round jets issuing from a purely converging nozzle at conditions, which corresponds to ideally expanded Mach numbers of 1:45 and 1:59. The jets are dominated by the helical C instability screech mode, which is associated with large-scale coherent periodic fluctuations. These fluctuations are filtered using a proper orthogonal decomposition method to assess low-order models that approximate the length scales associated with the broadband noise mechanisms. The length scale model parameters are shown to be insensitive for the two Mach numbers considered. The root-mean-square error associated with the low-order models indicates that either is su cient for approximating the integral length scales required to model equivalent sources of broadband jet noise.