Nogal, M., O’Connor, A., Martinez-Pastor, B., and Caulfield, B., (2017), ‘Novel probabilistic resilience assessment framework of transportation networks against extreme weather events’, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems: Part A Civil Engineering. 3(3).
The occurrence of severe weather events appears to have become more frequent, more widespread, and more intense during the last century. One of the results of this phenomenon is that vital transport networks are increasingly exposed to disruption or disablement, leading to important societal risk. In this present-day context, tools and guidelines to enhance the security of infrastructure networks under extreme climatological hazards become necessary. With this aim, this paper presents an innovative probabilistic framework to estimate the resilience of a traffic network impacted by extreme weather events. The proposed methodology takes into account important aspects such as the cost increment, the user stress level, and the system impedance to alter its previous state. Moreover, the uncertainty involved in the variables (1) traffic demand; (2) local vulnerability to a given hazard; and (3) capacity of response of users is considered. Probabilistic curves of the system response are defined using the Monte Carlo method and Latin hypercube sampling. There are multiple benefits to using this novel framework because it will allow early warning response, will support the decision-making process, and will permit the improvement of existing networks and the generation of more efficient designs.