A Probabilistic Reliability and Risk Framework for Flood Control in Multi-Structure Complexes: Mining Site Design

This paper developed a probabilistic framework for system level reliability and risk assessment that coupled hydraulic loading with structural response and explicitly modelled cascading interactions and statistical dependence between components. The contribution is a system-level reliability and risk modelling methodology that integrates dynamic cascading interactions, non-stationary design-life reliability accumulation, and system-level optimisation within a unified Monte Carlo architecture. Dynamic Monte Carlo simulation was used to evaluate individual, joint, conditional, and system-scale probabilities of failure across varying flood magnitudes and design lives. Model verification confirmed that discretisation and sampling errors were small relative to parameter-driven variability. Results showed that long-term system reliability arose from the combined influence of flood frequency, exposure duration, and the strength of interaction between interdependent structures. Frequent loading accelerates the accumulation of failure probability through repeated events, whereas rare events contribute more slowly but dominate extreme outcomes, indicating that cumulative reliability cannot be inferred by the linear extrapolation of annual probabilities. In an examined diversion–levee–basin configuration, strong structural coupling amplified vulnerability by contracting joint stability margins and increasing conditional failure probabilities. The system-level optimisation of structural parameters over the examined design life reduced cumulative system failure probability from 0.305 to 0.153, whereas single-component optimisation redistributed risk within the system without reducing total system risk. The framework advances beyond static risk analysis by integrating time-dependent reliability, cascading dependencies, and design-life optimisation for system-scale mitigation.