Complex Network Model for Characterizing Hazards and Risks Associated with Mine-tailings Facility

Abstract

If not well-managed, a mine-tailings facility may become a major source of risks, endangering the community and environment, and damaging the reputation of the minerals industry regarding sustainability. Identifying, characterizing, and mitigating the hazards and risks associated with tailings facilities have been critical to the maintenance of community-safe and environmentally sound mine-tailings facilities. Herein, a complex network model for characterizing the hazards and risks associated with the lifecycle of tailings facilities is presented. In this approach, the hazards are modeled as vertices of the complex network, and the interactions among the hazards are modeled as edges of the complex network. The complex network for modeling the hazard and risk spreading of mine-tailings impoundments is analyzed and characterized by using network metrics such as the network density, geometrical characteristics, characteristic path length, network efficiency, and clustering coefficient. The degree distribution of the network obeys a power-law distribution, indicating that the network for characterizing the risk spreading associated with a tailings facility is scale-free. According to the results of calculations and existing research results, the network is ultrasmall-world. By analyzing the change of the global network efficiency under four kinds of different methods to remove network nodes and edges, network nodes with higher between centrality (BC) are identified as critical. The removal of those critical nodes helps mitigate risks associated with a tailings facility and reveals the vulnerabilities to BC attacks.