A dynamic Bayesian network approach to characterize multi-hazard risks and resilience in interconnected critical infrastructures

A new paradigm for risk assessment has emerged, recognizing the escalating frequency and severity of disasters associated with natural hazards. Conventional risk assessments often fail to capture the dynamic and interconnected nature of disruptions within infrastructure systems during failure scenarios. This study introduces a Dynamic Bayesian Network (DBN) framework, designed to assess risk in interconnected infrastructure systems under complex hazard scenarios. The framework addresses the limitations of static models by dynamically capturing the progression of disruptions during failure and the restoration process during recovery. Using a case study in Saint Lucia, a Caribbean Island susceptible to natural…

• WU
  Western University