MS 16

Reliability and Resilience of Critical Infrastructure Systems and Networks


Michael Beer,

Institute for Risk and Reliability, Leibniz University Hanover, Germany

Konstantin Zuev,

Department of Computing and Mathematical Sciences, California Institute of Technology, USA

Edoardo Patelli,

Department of Civil and Environmental Engineering, Strathclyde University, Glasgow, UK

Matteo Broggi,

Institute for Risk and Reliability, Leibniz University Hannover, Germany

Frank Coolen,

Department of Mathematical Sciences, Durham University, UK


Complex infrastructure systems and networks are a pervasive feature of modern society. They provide critical services for everyday life, such as water, food, energy, transport, communication, banking, and finance. Reliability and resilience of our infrastructure are thus of utmost importance. However, most of our critical infrastructures are interconnected, interact with one another and depend on social networks, as well. In this respect, cascading failures, where external perturbations trigger some initial local failures that lead to eventual global system failure, are especially hazardous. A deep understanding of complex failure mechanisms and of the capabilities to withstand natural hazards and man-made threats is crucial. In particular, the degree to which an infrastructure system subjected to internal or external stresses is capable of keeping or recovering the service demanded needs to be quantitatively estimated. Quantitative assessment of system and network reliability and associated risks and uncertainties is therefore a key aspect of system design, optimization, and operation.

The main objective of this Mini-Symposium is to bring together experts working in the interdisciplinary area of reliability and resilience of infrastructure systems and networks to discuss the latest developments in the field. Some relevant topics include reliability, risk, vulnerability and resilience analyses of critical infrastructures, multi-sector interdependencies of infrastructure networks, common cause failure, and cascading failures.