Year: 2019
Author: Tian Tian, Han Wang, Wei Ge, Pingwen Zhang
Communications in Computational Physics, Vol. 26 (2019), Iss. 5 : pp. 1617–1630
Abstract
In this paper, the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) method is proposed to detect particle clusters in particle-fluid systems. The particles are grouped in one cluster when they are connected by a dense environment. The parameters that define the dense environment are determined by analyzing the structure of the system, therefore, our approach needs little human intervention. The method is illustrated by identifying the clusters in two kinds of simulation trajectories of different particle-fluid systems. The robustness of cluster identification in terms of statistical properties of clusters in the steady state is demonstrated.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/cicp.2019.js60.09
Communications in Computational Physics, Vol. 26 (2019), Iss. 5 : pp. 1617–1630
Published online: 2019-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 14
Keywords: Particle-fluid system cluster DBSCAN method.
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