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Modularity-based community detection in quasi-static granular shear

Author

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  • Jha, Prashant Kumar
  • Kishore, Raj
  • Sahu, Kisor Kumar

Abstract

Quasi-static shear in granular sphere packing have been reported with intermittent peaks in the unbalanced force (UBF) index, which is attributed to the release of stored elastic energy, but the microscopic mechanisms underlying these events have remained unclear. In this work, we examine these events using a network-based analysis of particle interactions. The granular system is represented as a contact network, and modularity-based community detection is applied to identify groups of interacting particles at discrete time steps, without using predefined thresholds or labels. By following the evolution of these communities, we observe that large UBF peaks tend to follow the changes in local community organization. The study aims to perform data-driven analysis of UBF peak anomaly linking community-level dynamics to the UBF fluctuations. These results suggest that modularity-based community analysis can be a useful tool for studying collective effects in quasi-static granular systems.

Suggested Citation

  • Jha, Prashant Kumar & Kishore, Raj & Sahu, Kisor Kumar, 2026. "Modularity-based community detection in quasi-static granular shear," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 697(C).
    • Handle: RePEc:eee:phsmap:v:697:y:2026:i:c:s0378437126004577
    DOI: 10.1016/j.physa.2026.131721
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