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Fluid mixing usually involves the interplay between advection and diffusion, which together cause any initial distribution of passive scalar to homogenize and ultimately reach a uniform state. However, this scenario only holds when the velocity field is nondivergent and has no normal component to the boundary. If either condition is unmet, such as for active particles in a bounded region, floating particles, or for filters, then the ultimate state after a long time is not uniform, and may be time dependent. We show that in those cases of nonuniform mixing it is preferable to characterize the degree of mixing in terms of an f-divergence, which is a generalization of relative entropy, or to use the $L^1$ norm. Unlike concentration variance ($L^2$ norm), the f-divergence and $L^1$ norm always decay monotonically, even for nonuniform mixing, which facilitates measuring the rate of mixing. We show by an example that flows that mix well for the nonuniform case can be drastically different from efficient uniformly mixing flows.
In this fluid dynamics video, we demonstrate the microscale mixing enhancement of passive tracer particles in suspensions of swimming microalgae, Chlamydomonas reinhardtii. These biflagellated, single-celled eukaryotes (10 micron diameter) swim with
We study numerically joint mixing of salt and colloids by a chaotic velocity field $mathbf{V}$, and how salt inhomogeneities accelerate or delay colloid mixing by inducing a velocity drift $mathbf{V}_{rm dp}$ between colloids and fluid particles as p
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The mixing of binary fluids by stirrers is a commonplace procedure in many industrial and natural settings, and mixing efficiency directly translates into more homogeneous final products, more enriched compounds, and often substantial economic saving