Fundamental approach to the design and optimization of static mixers

Abstract

Mixing in the Kenics

Simulation of gas–liquid flow in a helical static mixer

“…For singlephase flow this approach has been carried out with some success already (e.g. Rauline et al, 1998, Byrde and Sawley, 1999, Szalai and Muzzio, 2003, Wageningen et al, 2004, Song and Han, 2005, Paglianti, 2008, Coroneo et al, 2012. For multiphase flow, in contrast, hardly any computational study has been performed.…”

On the performance of static mixers: A quantitative comparison

“…Also the standard Kenics geometry allowed for numerical analyses, starting in 1995, see [33][34][35][36]. Dynamical system techniques were applied to understand and optimize mixing, see [31][32][33][34][35][36][37][38], and applied to the Kenics geometry [39], in the low [40], and high [41,42], Reynolds number regime, all the way to turbulent flows [43][44][45][46], and the use of the Kenics as reactor [47][48][49]. The group of Muzzio developed analytical and numerical methods to quantify stretching distributions in these types of mixers, which is far from trivial since interfaces grow exponentially in time.…”

Spectral characterization of static mixers. The S‐shaped micromixer as a case study

“…This is particularly true whenever localized approaches such as finite differences, finite volumes, or finite elements are used. As this shortcoming is associated with all numerical simulations of advection‐diffusion processes in the high Pe range, independently of both the scale (micro vs macro) and the nature (open vs closed) of the mixing domain, a number of strategies aimed at avoiding the direct solution of the Eulerian advection‐diffusion equation have been proposed 10, 11. The crudest version of these approaches consists of analyzing only the convective aspect of mixing and assess mixing efficiency on the basis of purely kinematic (Lagrangian) indexes.…”

“…Beyond Poincaré sections, which provide a global view of the trajectories in the mixing domain, relevant indexes that account for the local and global deformation process of the kinematic interface are stretch factor distributions, Lyapunov exponents, and topological entropy 12, 13. The kinematic approach has encountered a favorable response among researchers dealing with laminar mixing in micro‐14 and ordinary lengthscale motionless mixers11 in view of numerical evidence that in globally chaotic conditions, a sensible estimate of mixing and reaction efficiency can be derived a posteriori by superimposing the action of diffusion (and, possibly, of chemical reactions) to the kinematic picture (see, e.g., Szalai et al,15 and therein cited references).…”