Particle-fluid two-phase flow system is widely used in many kinds of industrial processes , which has a significant influence on our life and living environment. In particular, the mesoscale structure such as particle clusters makes the two-phase flow system have unique physical properties, which has brought a great challenge to the experimental and theoretical research. Thus, it is very important to study the mechanism of particle clusters. We propose a parameterless algorithm for particle cluster identification from the view of microstructure, which also gives a strict definition of particle clusters. Based on the definition of particle clusters and the method of parameterless identification, a kinetic model of clusters based on stochastic process is proposed, where the evolution of the clusters is regarded as a stochastic process. The dynamic model of cluster evolution is established at mesoscopic scale with the mathematical tool of stochastic process.
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