Application of data mining into acoustic waves from a rocket plume

Flow and acoustic fields of a supersonic jet impinging on an inclined flat plate are investigated by applying data mining techniques. The data of flow and acoustic fields obtained in the previous study are used. The self-organizing map (SOM) and k-means method are applied to this dataset based on the normalized sound pressure level spectra. The results of SOM and k-means method show the clear characterization of the regions based on the frequency characteristics of acoustic waves. Some of clustered regions correspond to the region at which three kinds of aeroacoustics wave are (i) Mach wave from the main jet, (ii) acoustics waves from impinging, and (iii) Mach waves from the supersonic flow downstream of impinging region. The results of SOM and k-means method validate the relationship among these three kind of aeroacoustic waves which is clarified in the previous study, i.e. lower frequency components are stronger for Mach/acoustic waves with the higher index.