Proper Orthogonal Decomposition Analysis of Numerically Simulated Supersonic Jet flow

Proper Orthogonal Decomposition (POD) is performed on Large Eddy Simulation (LES) data and Particle Image Velocimetry (PIV) data from an underexpanded axisymmetric jet. PIV measures the streamwise and radial velocity components along a streamwise plane while LES provides data for the full domain and includes all flow variables (three velocity components, density, pressure, and temperature). A qualitative comparison between the POD modes from the LES and PIV data shows features similar in wavelength and shape particularly just downstream of the nozzle exit. An energy analysis shows that the biggest difference between the two cases was near the nozzle exit and believed to be the low turbulence level near the nozzle exit in LES data. At downstream positions, both cases have a similar distribution of POD modal energy. The analysis also shows that the large-scale flow features captured by the POD modes are strongly dependent on the domain size. Small domains are good for extracting the smaller-scale and low energy flow features near the nozzle exit. Further downstream the smaller domain spatially filters the largest flow features from the POD modes. The LES data is further post-processed to see if the streamwise and/or radial velocity can be used to estimate the tangential velocity, pressure, or density. It is found that the streamwise velocity can predict the pressure field, the radial velocity can predict the tangential velocity, and neither component does a good job at predicting the density. The prediction of flow variables is most likely due to the under-expanded nature of the jet and shows how PIV data can be used to further estimate other flow variables.