ResQ-IOS: An iterative optimization-based simulation framework for quantifying the resilience of interdependent critical infrastructure systems to natural hazards

Abstract

Critical Infrastructure Systems are highly complex and interdependent. Growing complexity and interdependency between infrastructure systems and frequent exposure to extreme events have inevitably increased the probability of cascading failures and the prolonged lack of serviceability in urban communities, especially so for energy systems. The resilience analysis of interdependent infrastructure systems against natural hazards provides stakeholders with a comprehensive outlook on recovery strategies to minimize the damage costs and losses caused by extreme events. This paper introduces the ResQ-IOS, a Resilience Quantification Iterative Optimization-based Simulation (IOS) framework for quantifying the resilience of interdependent infrastructure systems to natural hazards with the capability of considering the real-world conditions for the status of infrastructure systems' components. The ResQ-IOS framework consists of five modules: risk assessment, simulation, optimization, database, and controller. To evaluate the capabilities of this framework, the seismic resilience of interdependent energy infrastructure networks (power, natural gas, and water) in Shelby County (TN), USA, was assessed. The results of the resilience analysis of the case study suggest that the water network is the best candidate for implementing pre-disaster Resilience Enhancement Measures (REMs), like increasing the supply capacity. Due to the controlling role of the power network in the community's recovery process, it is recommended that post-disaster REMs, such as increasing the number of Repair and Maintenance (R&M) teams, should be applied to the power network to speed up the restoration of failed components in that network and consequently, shorten the recovery duration of the community. The ResQ-IOS can be employed as a useful computational tool for planning the resilience-oriented sustainable development of urban communities by, for example, deploying Renewable Energy (RE)-based strategies to enhance their disaster resilience.