Quantifying (Community Disaster) Resilience

Božidar Stojadinović

Božidar Stojadinović
Chair of Structural Dynamics and Earthquake Engineering
Swiss Federal Institute of Technology (ETH) Zürich

Professor Božidar Stojadinović is the Chair of Structural Dynamics and Earthquake Engineering at the ETH Zürich, member of the ETH Risk Center, and co-PI of the ETH Future Resilient System program in Singapore. His degrees are in Civil Engineering: PhD from the University of California, Berkeley in 1995, MS from Carnegie-Mellon University in 1990 and BS (Dipl.Ing.) from the University of Belgrade, Serbia in 1988. His main research is in the field of community disaster resilience. In this area, he specializes in performance-based probabilistic resilience evaluation and design of civil infrastructure systems, buildings and bridges. Professor Stojadinović is also working on seismic design methods, earthquake response modification techniques, and on hybrid simulation methods to investigate the response of structures to dynamic loads.

April 18, 2022 Quantifying (Community Disaster) Resilience

Increased emphasis on resilience, specifically disaster resilience of communities, challenges engineers to do something about it. Our approach is one of a design cycle: we assess the current state for acceptability, and iteratively improve the design of actions to change the current state for the better. Making a design cycle work for community disaster resilience poses challenges: in this talk, I will focus on resilience assessment and quantification. Given a community, understood as a stem-of-systems that provide for safety and support the social and economic activities of the inhabitants, our goal is to assess how resilient this community is to disruptions, small and large, common and rare. Huge strides in this direction have been made in the past two decades. We have diverse families of model that reproduce the evolution of a community from damage to its function through the recovery process to its new state, the “swoosh” curve. But, are the numbers on the axes? Turns out they are quite different, depending on the modeling approach, model assumptions, even modelers knowhow. Quantification of community resilience for assessment and design is an urgent priority. I will present my view of the state of the art in this field, and discuss with you how to move forward. My goal is a state when we can use and thrust different models of community disaster resilience to compute comparable (if not identical) resilience metrics that support uniform, method-agnostic, resilience acceptance criteria.

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