No Arabic abstract
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 a breaststroke pulling motion of their flagella at speeds of about 100 microns/s and exhibit heterogeneous trajectory shapes. Fluorescent tracer particles (2 micron diameter) allowed us to quantify the enhanced mixing caused by the swimmers, which is relevant to suspension feeding and biogenic mixing. Without swimmers present, tracer particles diffuse slowly due solely to Brownian motion. As the swimmer concentration is increased, the probability density functions (PDFs) of tracer displacements develop strong exponential tails, and the Gaussian core broadens. High-speed imaging (500 Hz) of tracer-swimmer interactions demonstrates the importance of flagellar beating in creating oscillatory flows that exceed Brownian motion out to about 5 cell radii from the swimmers. Finally, we also show evidence of possible cooperative motion and synchronization between swimming algal cells.
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 proposed in recent experiments cite{Deseigne2013}. We demonstrate that because the drift velocity is no longer divergence free, small variations to the total velocity field drastically affect the evolution of colloid variance $sigma^2=langle C^2 rangle - langle C rangle^2$. A consequence is that mixing strongly depends on the mutual coherence between colloid and salt concentration fields, the short time evolution of scalar variance being governed by a new variance production term $P=- langle C^2 abla cdot mathbf{V}_{rm dp} rangle/2$ when scalar gradients are not developed yet so that dissipation is weak. Depending on initial conditions, mixing is then delayed or enhanced, and it is possible to find examples for which the two regimes (fast mixing followed by slow mixing) are observed consecutively when the variance source term reverses its sign. This is indeed the case for localized patches modeled as gaussian concentration profiles.
Recent numerical results show that if a scalar is mixed by periodically forced turbulence, the average mixing rate is directly affected for forcing frequencies small compared to the integral turbulence frequency. We elucidate this by an analytical study using simple turbulence models for spectral transfer. Adding a large amplitude modulation to the forcing of the velocity field enhances the energy transfer and simultaneously diminishes the scalar transfer. Adding a modulation to a random stirring protocol will thus negatively influence the mixing rate. We further derive the asymptotic behaviour of the response of the passive scalar quantities in the same flow for low and high forcing frequencies.
We consider self-propelled droplets which are driven by internal flow. Tracer particles, which are advected by the flow, in general follow chaotic trajectories, even though the motion of the autonomous swimmer is completely regular. The flow is mixing, and for P{e}clet and Batchelor numbers, which are realized e.g. in eucaryotic cells, advective mixing can substantially accelerate and even dominate transport by diffusion.
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 savings in energy and input ingredients. Enhancements in mixing efficiency can be accomplished by unorthodox stirring protocols as well as modified stirrer shapes that utilize unsteady hydrodynamics and vortex-shedding features to instigate the formation of fluid filaments which ultimately succumb to diffusion and produce a homogeneous mixture. We propose a PDE-constrained optimization approach to address the problem of mixing enhancement for binary fluids. Within a gradient-based framework, we target the stirring strategy as well as the cross-sectional shape of the stirrers to achieve improved mixedness over a given time horizon and within a prescribed energy budget. The optimization produces a significant enhancement in homogeneity in the initially separated fluids, suggesting promising modifications to traditional stirring protocols.