Network Analysis of The Brazil Nut Effect Phenomenon with a Single Intruder

9th Annual Basic Science International Conference 2019

自然科学（总论）

Rahmadhan Putra, Muhammad Iqbal^1 ; Rudiawan, Aufa^1 ; Andariwulan, Wahyuni^1 ; Berasategui, Rubén García^2 ; Viridi, Sparisoma^1

Department of Physics, Faculty of Mathematics and Natural Sciences, Bandung Institute of Technology, Bandung, Indonesia^1

STIE Jakarta International College, Jakarta, Indonesia^2

关键词: Betweenness centrality;    Clustering coefficient;    Community detection;    Community structures;    Large-size particles;    Network extractions;    Optimization method;    Two dimensional model;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/546/5/052057/pdf
DOI  :  10.1088/1757-899X/546/5/052057

学科分类：自然科学（综合）

来源: IOP

【 摘 要 】

One phenomenon that can be observed in granular systems is the Brazil Nut Effect (BNE), that is, a phenomenon in which large-size particles lift up when vibrated vertically. In this experiment, structural changes in a pseudo-two-dimensional model of a granular system experiencing BNE were observed from the perspective of network analysis. The system consisted of 199 granular beds of 0.68 cm of diameter with a 2.5 cm diameter intruder placed in a 3mm wide double-window box that was slightly larger than the thickness of the bed and the intruder. The system was subjected to vibrations with a frequency of 13.33 Hz and an amplitude of 0.75 cm, so the BNE could be observed. For the purpose of the analysis, the granular beds were considered the nodes of a network and the relationships between adjacent beds (were contact force occurred) represented its edges. The analysis, consisting of image processing, network extraction, network parameters calculation and community detection, was performed using Wolfram Mathematica v. 11.3. The experiment was able to calculate the change in the network parameters including degrees, clustering coefficients, betweenness centrality, and modularity for the system with intruders and systems without intruders. The parameter values corresponding to each system were markedly different, clearly showing the influence of the intruder. The authors were also able to successfully map the evolution of the community structure in both types of granular systems one step at a time using a modularity optimization method.