New Approaches for Analysis of Jet Noise Data

Abstract

Despite the significant advances in Computational Aeroacoustics for predicting jet noise, there is still a considerable need for experimental data. However, traditional measures of the directivity of Overall Sound Pressure Levels or the spectral distribution of the acoustic energy yield limited understanding of the nature of the sources. There is hence a need to use different approaches to the analysis of jet acoustics, among them applications of statistical methods such as auto correlation, self-correlation etc to understand the noise sources. In this paper, the acoustic characteristics of supersonic and high subsonic jets from nozzles of different exit geometries are measured and analyzed using these methods. The results show that these statistical methods of analysis can reveal the presence of two distinct noise sources in the flow and are applicable to both subsonic and supersonic flows. The information can be used to determine the appropriate model for the data and is useful for forming new theories about the noise generation mechanism in turbulent jets.