Faculty Candidate for the Zhejiang-University of Illinois at Urbana-Champaign Institute (ZJUI)
Quantifying and Managing Infrastructure Resilience: A Structural Health Monitoring Solution
Binbin Li, University of Liverpool,
Wednesday, April 11, 2018
2312 Newmark Civil Engineering Laboratory
205 N. Mathews, Urbana
Civil infrastructures, e.g., water, energy, waste and transportation systems, are essential to modern life and central to the security and stability of the nation. Modern societies demand civil infrastructures to be ‘resilient’ to disasters – natural and man-made hazards, e.g., earthquakes, floods, storms, terrorist attacks. Resilience measures the vulnerability and adaptability of infrastructures to extreme events. There are methodologies to quantify the vulnerability and adaptability of civil infrastructures. However, they are mainly based on empirical procedures due to lack of sufficient data. With integrated sensor networks in structures and infrastructures, structural health monitoring has shown its applicability in operation maintenance and emergency management, taking advantage of both the engineering knowledge and field data. This talk summarizes recent research and proposes approaches to resolve challenges of quantification and management of infrastructural resilience from the perspective of structural health monitoring to envision a promising future with resilient and intelligent civil infrastructures.
Dr. Binbin Li is currently a research associate in the Institute of Risk and Uncertainty at the University of Liverpool, UK, working on quantifying and managing uncertainties in ambient vibration test. He obtained his Ph.D. (2016) in Civil Engineering from the University of California-Berkeley and his B.S. (2009) in Civil Engineering and M.S. (2012) in Structural Engineering both from Dalian University of Technology, China. His research focuses on developing innovative statistical methods to address safety, resilience and sustainability issues of the built civil infrastructures. His specific interests include operational modal analysis, Bayesian system identification, infrastructural network modeling and field test, for structure and infrastructure health management and resilience assessment.