Modern engineering structures form complex - often interconnected - assemblies that operate under highly varying loads and adverse environments. To ensure a resource-efficient and resilient operation of such systems, it is imperative to understand their performance as-is; a task which can be effectuated through Structural Health Monitoring (SHM). SHM comprises a hierarchy across levels of increasing complexity aiming to i) detect, ii) localize and iii) quantify damage, and iv) finally offer a prognosis over the system's residual life. When considering higher levels in this hierarchy, including damage assessment and even performance prognosis, purely data-driven methods are found to be lacking. For higher-level SHM tasks, or for furnishing a digital twin of a monitored structure, it is necessary to integrate the knowledge stemming from physics-based representations, relying on the underlying mechanics.

This talk discusses implementation of such a hybrid approach to SHM for tackling the aforementioned challenges for robust monitoring of engineered systems. We offer a view to establishing augmented twin representations, capable of representing the structure as-is, anticipating performance under future stressors, and advising on preventive and remedial actions.

Eleni Chatzi is an Associate Professor and Chair of Structural Mechanics and Monitoring at the Department of Civil, Environmental and Geomatic Engineering of ETH Zurich. Her research interests include the fields of Structural Health Monitoring (SHM), structural dynamics, and intelligent data-driven assessment for engineered systems. She is the current Vice-President of the European Academy of Wind Energy (EAWE). She led the recently completed ERC Starting Grant WINDMIL on the topic of "Smart Monitoring, Inspection and Life-Cycle Assessment of Wind Turbines".

Her work in the domain of self-aware infrastructure was recognized with the 2020 Walter L. Huber Research prize, awarded by the American Society of Civil Engineers (ASCE) and the EASD Junior Research Prize in the area of Computational Structural Dynamics.