Towards self-aware infrastructure
Engineers are today faced with a conundrum. On one hand an ageing building stock and on the other novel materials and digital building technologies reshaping the landscape of construction. The life-cycle management of both existing and new structural systems operating under diverse loads demands a better understanding of how these systems respond. This involves the tasks of simulation (forward engineering), identification (inverse engineering) and the organization of maintenance/control actions. The efficient and successful implementation of these tasks is however non-trivial, due to the ever-changing nature of these systems, and the variability in their interactive environment. Two defining factors in understanding and interpreting such large-scale systems are nonlinear behavior and structural uncertainty. The former is related to the external dynamic loading that might shift the structural response from purely linear to nonlinear regimes, while the latter is related to erroneous modeling assumptions, imprecise sensory information, ageing effects, and lack of a priori knowledge of the system itself.
This talk discusses implementation of methods and tools able to tackle the aforementioned challenges. Among other topics, the use of parametric surrogate representations and Bayesian-type filters for the reduced representation and identification of uncertain and time-varying or nonlinear structural systems is discussed. It is further demonstrated how construction of data-driven performance indicators (PIs) stemming from the previous analysis may be exploited to support decisions on optimal management of infrastructure.
Eleni Chatzi received her PhD from the Department of Civil Engineering and Engineering Mechanics at Columbia University, New York. She is currently an Associate Professor and Chair of Structural Mechanics at the Institute of Structural Engineering of the Department of Civil, Environmental and Geomatic Engineering of ETH Zürich. She leads an international team of researchers working on data-driven monitoring, automated condition assessment and intelligent decision support for engineered systems, with applications spanning across civil, mechanical and aerospace infrastructure. She serves as editor of numerous peer reviewed journals, and as scientific committee member of international conferences in the field of SHM. Her research has been supported by the European Commission, the Swiss National Science Foundation, and the ETH Research Foundation. She is currently leading the ERC Starting Grant WINDMIL on Smart Life-Cycle Assessment of Wind Turbines. She serves as director of the Computational Science Zurich PhD Program, and a Core Group member of COST Actions TU1402, TU1406 focusing on assessment of infrastructure.