Characterization of coherent structures in a turbulent mixing layer by digital image analysis

Digital image analysis has been applied to a shadowgraph motion picture of a helium nitrogen mixing layer in order to characterize the coherent vortex structures in the flow. Both the primary spanwise coherent vortices and secondary streamwise vortices are considered. Pattern recognition algorithms were designed to take advantage of the more pronounced features of the vortices and of their temporal coherence to isolate them and to measure their characteristics. The resulting data base permits a deterministic description of the evolution of primary and seconary vortices.