Measuring the scale of segregation in mixing data

Abstract

Four methods were used to extract length scales from mixing data: the maximum striation thickness, point-to-nearest-neighbour (PNN) distributions, the correlogram and the variogram. Four test data sets were analysed: blending in a micromixer; particle dispersion in a stirred tank; dispersion of a smoke plume and a pulse tracer test in a reactor. The maximum striation thickness captures the largest length scale. The PNN method quantifies differences between clustered, random and regular spatial distributions. The correlogram calculation cannot be consistently used for all types of mixing data and has therefore been rejected. The variogram reveals both large-scale segregation and periodicity. Sub-sampling is needed to isolate smaller structures. The variogram, PNN and transect methods all successfully extracted mixing length scales from large 2D data sets.