TY - JOUR
T1 - Detecting Particle Clusters in Particle-Fluid Systems by a Density Based Method
AU - Tian , Tian
AU - Wang , Han
AU - Ge , Wei
AU - Zhang , Pingwen
JO - Communications in Computational Physics
VL - 5
SP - 1617
EP - 1630
PY - 2019
DA - 2019/08
SN - 26
DO - http://doi.org/10.4208/cicp.2019.js60.09
UR - https://global-sci.org/intro/article_detail/cicp/13278.html
KW - Particle-fluid system, cluster, DBSCAN method.
AB - <p style="text-align: justify;">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.</p>