Integrating life-cycle analysis into civil infrastructure resilience decision making: Illustrative application to seismic resilience modeling of US communities

This paper aims to integrate life-cycle analysis into civil infrastructure resilience modeling and decision-making in seismic-prone communities. To achieve this aim, the authors present a methodology for modeling seismic life-cycle resilience of interdependent buildings and lifeline systems and subsequently informing resilience decisions directly related to the maintenance and retrofit of interdependent infrastructure to enhance a community’s physical, social, and economic systems. The methodology consists of 1) community data collection, 2) seismic hazard analysis, 3) physical damage analysis, and 4) system-level functionality and restoration analysis, 5) socio-economic impact analysis, 6) life-cycle optimization and retrofit decision-making. The methodology begins by developing geospatial datasets to characterize a community’s interdependent civil infrastructure. Subsequently, ground motion prediction models are employed to simulate scenario earthquakes and obtain spatial intensity measures within the community. A fragility-based computational model of the networked infrastructure is then developed using graph theory to perform physical damage analysis using Monte Carlo simulations by accounting for structural aging and degradation. The damage estimates are used as input to an input-output model to perform functionality and restoration analysis by accounting for infrastructure networks’ cascading failure and interdependency. An illustrative case study is presented to demonstrate the implication of the methodology to perform seismic life-cycle resilience in US communities, including Shelby County, TN. The methodology will assist engineers and urban planners in assessing the vulnerability of critical buildings and lifeline systems and developing life-cycle resilience-informed mitigation strategies to improve the seismic resilience of communities.