Probabilistic Seismic Multi-hazard Risk and Restoration Modeling for Resilience-informed Decision Making in Railway Networks

Abstract

ABSTRACT Transportation systems, such as railways, are considered critical infrastructure. It is essential to identify potential hazards that can affect the functionality of these systems and quantify metrics that can be used for resilience-informed decision-making. This paper develops an integrated probabilistic model for seismic multi-hazard risk and restoration assessment of railway systems by accounting for the effects of seismic waves propagation, liquefaction and landslide as main phenomena affecting the integrity of distributed networked infrastructure; this is done via a GIS-based user interface. An illustrative case study is then presented to assess the seismic risk and restoration of the Tehran-Sari railway in Iran. The implementation results demonstrate the capability of the presented methodology to quantify physical metrics (including combined damage state of network components, component- and system-level functionality and restoration) and economic loss. These metrics can assist officials with implementing retrofit plans to reduce loss and improve the resilience of railway system segments.