Moving efficiently through a crowd: A nature-inspired traffic rule.

In 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. The traffic rule used in the article is a dipole field which satisfactorily captures the features of the flow fields around a moving intruder. We study the effectiveness of this dipole traffic rule using numerical simulations in a two-dimensional periodic domain, where one self-propelled elite agent tries to move through a crowd of inert agents that prefer to stay in a state of rest. Simulations are carried out for a wide range of strengths of the traffic rule and packing densities of the crowd. We characterize and analyze four regions in the parameter space-free-flow, motion due to cooperation and frozen and collective drift regions-and discuss the consequence of the traffic rule in light of the collective behavior observed. We believe that the proposed method can be of use in a swarm of robots working in constrained environments.

Averaged model for probabilistic coalescence avalanches in two-dimensional emulsions: Insights into uncertainty propagation.

A 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. When this ratio is small, the avalanche grows autocatalytically to destabilize the emulsion. Using a scaling analysis, we unravel the relation between a local characteristic of the system and a global system wide effect. The anisotropic nature of local coalescence results in a system size dependent transition from nonautocatalytic to autocatalytic behavior. By incorporating uncertainty into the parameters in the model, several possible realizations of the coalescence avalanche are generated. The results are compared with the Monte Carlo simulations to derive insights into how the uncertainty propagates in the system.

Coalescence of drops in a 2D microchannel: critical transitions to autocatalytic behaviour.

A 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. We discover that the coalescence propagation dynamics exhibit a critical behavior where two outcomes are favored: no avalanche and large avalanches. Our analysis reveals that this behavior is a result of the inherent autocatalytic nature of the process. The effect of the aspect ratio of the drop assembly on the propagation dynamics is studied. We generate a parametric plot that shows the region of the parameter space where the propagation, averaged over the ensemble, is autocatalytic: where the possibility of near destabilization of the drop assembly appears.