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Infrastructure Resilience Conference 2018

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Natural Hazard Resilience Assessment for Transportation Infrastructure: A State of the Art Case Study

Infrastructure networks such as transportation, water and power are critical lifelines to society. Manager, of those infrastructures, plan and execute interventions to guarantee their operational state under various circumstances, including after the occurrence of (natural) hazard events. Creating an intervention program demands knowing the probable network-related consequences (i.e. risk) of the various stochastic hazard events that could occur. This paper describes a study to investigate flood and mudflow hazards with the potential to cause severe damage to parts of the E43 highway, Switzerland's second most important north-south road link. This work include the modeling of (1) the propagation of hazard effects throughout the transportation network, (2) the functional interdependencies between multiple objects in the network, including physical, functional, and geographic dependencies, and (3) impacts and consequences in terms of their expected frequency of occurrence, costs of restoration, and duration of road closure. The risk assessment was based on the following scenario: Heavy rainfall caused an increase in river discharge which led to a flood event. Additionally, the rainfall increase the probability that mudflow events were triggered. Both, the flood and the mudflow events affected the physical and functional properties of the infrastructure objects in the network (e.g. the structural performance of a bridge was jeopardized by local pier scour due to flooding). The functional losses and the effects of road closures on traffic flow patterns were assessed using a traffic assignment model, with and without allowing for the elasticity of travel demand. Finally, the resilience of the transportation network was determined by the execution of restorations works that would enable the network to provide an adequate level of service again by changing the state of damaged infrastructure objects.

Jürgen Hackl
ETH Zürich
Switzerland

Juan Carlos Lam
ETH Zürich
Switzerland

Magnus Heitzler
ETH Zürich
Switzerland

Bryan T. Adey
ETH Zürich
Switzerland

Lorenz Hurni
ETH Zürich
Switzerland

 

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