Abstract
Modeling the multiagents cooperative systems inspired from biological self-organized systems in the context of swarm model has been under great considerations especially in the field of the cooperation of multi robots. These models are trying to optimize the behavior of artificial multiagent systems by introducing a consensus, which is a mathematical model between the agents as an intelligence property for each member of the swarm set. The application of this novel approach in the modeling of nonintelligent multi agents systems in the field of cohesion and cluster formation of nanoparticles in nanofluids has been investigated in this study. This goal can be obtained by applying the basic swarm model for agents that are more mechanistic by considering their physical properties such as their mass, diameter, as well as the physical properties of the flow. Clustering in nanofluids is one of the major issues in the study of its effects on heat transfer. Study of the cluster formation dynamics in nanofluids using the swarm model can be useful in controlling the size and formation time of the clusters as well as designing appropriate microchannels, which the nanoparticles are plunged into.
Highlights
Swarming, as a novel approach in modeling the dynamics of multiagent systems, inspires from the behavior of biological self-organized and decentralized systems that cooperate to do a special task
First attempts to describe the behavior of such biological systems from the mathematical points of view belong to Breder [1] who developed the motion equation of schools of fish and claimed that the motion of each member is the resultant of a long-range attraction and short-range repulsion components
He modeled the near field force with a linear combination of an attraction and repulsion components just as what is considered in the swarm model
Summary
As a novel approach in modeling the dynamics of multiagent systems, inspires from the behavior of biological self-organized and decentralized systems that cooperate to do a special task. Many efforts have been investigated to introduce the behavior of multiagent systems whose members have mechanical interaction with each other It means they may collide to one another and exchange some momentum or arrange in special configurations that can be seen in cluster formations from multiphase and granular flows to nanofluids. Zohdi [8] proposed the idea of breaking all of the interactions between particles in a multiphase flow into four major forces, for example, thermal force, drag force, inter particle contact force, and near field force He modeled the near field force with a linear combination of an attraction and repulsion components just as what is considered in the swarm model. By knowing the cluster size of the swarm set as well as the diameter of the vessel, one can compute the number of nano robot probes participating in the cohesion task
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