Ensemble-averaging and correlation techniques for flow visualization images

Flow visualization using marking techniques such as timelines provides a basis for quantitative analysis of macroscale features of unsteady flows by global ensemble-averaging and correlation techniques. In the visual-ensemble-averaging technique described herein, the timeline positions are tracked and averaged in successive images. The phase reference for the averaging process can take the form of an analog pressure, velocity, or displacement signal, or a recurring coherent portion of the image. Global correlations of the timeline patterns are obtained using the same timelines defined for the ensemble-averaging process. A new type of visual correlation function, giving the correlation between two timelines in a given image or successive images, is proposed. Preliminary results are given.