Mechanical and Civil Engineering Seminar

Civil infrastructure systems, like electric power supply, water supply and distribution and cellular communication systems, provide valuable services to modern communities. Resilient civil infrastructure systems are crucial to maintain the living standards of contemporary societies. Most systems are, however, fragile when subjected to demands imposed by natural hazards (e.g. earthquakes, floods, storms), or threats like terrorist- and cyber-attacks. Major changes in the post-disaster service demand of the community can put supplementary burden on their performance. Additionally, a once damaged system may require a substantial amount of time and resources to adapt or recover. To assess and quantify the resilience of a civil infrastructure system in a holistic demand/supply approach, a multitude of information and input on the vulnerability and recoverability of its demand and supply is needed. This leads to a two-fold problem: dealing, on the one hand, with a lack of knowledge and data, and, on the other hand, with big data problems. This talk summarizes recent research and proposes approaches to resolve these challenges in resilience engineering, making use of tools like machine learning and uncertainty quantification, to draw a possible path toward a more resilient 21st century.

Max Didier is a doctoral student at the Chair of Structural Dynamics and Earthquake Engineering at the Institute of Structural Engineering (IBK) of the Swiss Federal Institute of Technology (ETH) Zurich. He received his B.Sc. and M.Sc. degrees in Civil Engineering from ETH Zurich in 2012 and 2014, respectively. He was awarded with the Willi Studer Price for the best Master's degree and the ETH medal for an outstanding Master's thesis. His research interests are in design and evaluation of resilient civil infrastructure systems and communities.