Coarse-grained descriptions of collective motion of flocking systems are often derived for the macroscopic or the thermodynamic limit. However, the size of many real flocks falls within 'mesoscopic' scales (10 to 100 individuals), where stochasticity arising from the finite flock sizes is important. Previous studies on mesoscopic models have typically focused on non-spatial models.
View Article and Find Full Text PDFIn this article, we propose a traffic rule inspired from nature that instructs how a crowd made up of inert agents should respond to an elite agent to facilitate its motion through the crowd. When an object swims in a fluid medium or an intruder is forced through granular matter, characteristic flow fields are created around them. We show that if inert agents made small movements based on a traffic rule derived from these characteristic flow fields, then they efficiently reorganize and transport enough space for the elite to pass through.
View Article and Find Full Text PDFDroplets, as they flow inside a microchannel, interact hydrodynamically to result in spatio-temporal patterns. The nature of the interaction decides the type of collective behaviour observed. In this context, we study the application of droplet microfluidics in the area of complex-shape particle synthesis.
View Article and Find Full Text PDFA two-dimensional concentrated emulsion exhibits spontaneous rapid destabilization through an avalanche of coalescence events which propagate through the assembly stochastically. We propose a deterministic model to explain the average dynamics of the avalanching process. The dynamics of the avalanche phenomenon is studied as a function of a composite parameter, the decay time ratio, which characterizes the ratio of the propensity of coalescence to cease propagation to that of propagation.
View Article and Find Full Text PDFA single coalescence event in a 2D concentrated emulsion in a microchannel can trigger an avalanche of similar events that can destabilize the entire assembly of drops. The sensitive dependence of the process on numerous parameters makes the propagation dynamics appear probabilistic. In this article, a stochastic simulation framework is proposed to understand this collective behavior in a system employing a large number of drops.
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