Community Detection of Force-Chain Network Evolution During Particle Migration in Granular Packings Under Fluid Action

Force chains, which transmit and distribute loads through networks of interparticle contacts, largely determine the mechanical response of granular materials. However, automatically identifying force chains and quantifying their evolution remain difficult, especially for three-dimensional granular systems under fluid action. In this work, a coupled computational fluid dynamics and discrete element method (CFD-DEM) is combined with community detection to extract and characterize the force chain network of a granular packing during particle migration. The inter-particle contact forces are encoded as a weighted network, and an improved Louvain algorithm based on modularity optimization is employed to partition the force network into sub-communities. The evolution of the community structure is quantified in terms of community size, average contact force, centrality and coordination number at different fluid pressures and dynamic viscosities. The results show that strong force chains assemble into compact and highly branched communities located mainly in the central region of the packing, and that increasing fluid pressure promotes the recombination of strong and weak chains into more branched structures, enhancing the stability of the granular system under high pressure. The community size distributions display a linear decay in the complementary cumulative distribution function without a characteristic scale, and the coordination number distributions of different communities respond to pressure in opposite ways. Higher fluid viscosity retards particle migration and favors more compact and stable community structures. The proposed framework provides a quantitative link between the mesoscale organization of force chains and the macroscopic stability of granular materials under fluid action. Beyond the specific packing studied here, the framework relies only on the interparticle contact forces and can therefore be transferred directly to any numerical or experimental dataset in which such forces are accessible; it thus offers a globally applicable tool for diagnosing fines migration, permeability impairment and sand production in deeply buried reservoirs, as well as internal erosion in dams, filters and embankments and the handling of particulate beds in the chemical and pharmaceutical industries.