A new definition of mixing and segregation: Three dimensions of a key process variable

Although a number of definitions of mixing have been proposed in the literature, no single definition accurately and clearly describes the full range of problems in the field of industrial mixing. An alternate approach is proposed which defines segregation as being composed of three separate dimensions. The first dimension is the intensity of segregation quantified by the normalized concentration variance (CoV); the second dimension is the scale of segregation or clustering; and the last dimension is the exposure or the potential to reduce segregation. The first dimension focuses on the instantaneous concentration variance; the second on the instantaneous length scales in the mixing field; and the third on the driving force for change, i.e. the mixing time scale, or the instantaneous rate of reduction in segregation. With these three dimensions in hand, it is possible to speak more clearly about what is meant by the control of segregation in industrial mixing processes. In this paper, the three dimensions of segregation are presented and defined in the context of previous definitions of mixing, and then applied to a range of industrial mixing problems to test their accuracy and robustness

Mixing performance of viscoelastic fluids in a kenics km in-line static mixer

AbstractThe mixing of ideal viscoelastic (Boger) fluids within a Kenics KM static mixer has been assessed by the analysis of images obtained by Planar Laser Induced Fluorescence (PLIF). The effect of fluid elasticity and fluid superficial velocity has been investigated, with mixing performance quantified using the traditional measure of coefficient of variance CoV alongside the areal method developed by Alberini et al. (2013). As previously reported for non-Newtonian shear thinning fluids, trends in the coefficient of variance follow no set pattern, whilst areal analysis has shown that the >90% mixed fraction (i.e. portion of the flow that is within ±10% of the perfectly mixed concentration) decreases as fluid elasticity increases. Further, the >90% mixed fraction does not collapse onto a single curve with traditional dimensionless parameters such as Reynolds number Re and Weissenberg number Wi, and thus a generalised Reynolds number Reg=Re/(1+2Wi) has been implemented with data showing a good correlation to this parameter

Measuring the scale of segregation in mixing data

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