Im Rahmen der "Ruzena Bajcsy Lectures on Communications and Resilience", die der Sonderforschungsbereich 1053 MAKI gemeinsam mit dem LOEWE-Zentrum emergenCITY ausrichtet, hält


June 23, 2023, 13:00-15:00


Rundeturmstraße 10, 64283 Darmstadt

S3/20/18 , Rundeturmstraße 10, 64283 Darmstadt


LOEWE Zentrum emergenCITY in Kooperation mit dem SFB MAKI


Prof. Dr. Eleni Chatzi, Chair of Structural Mechanics & Monitoring, ETH Zürich

am Freitag, 23.6.2023 um 13:00 Uhr

einen Vortrag über "Augmented Twins: Monitoring for Resilience and Data-driven Decision Support"

Die Veranstaltung ist öffentlich; interessierte Besucher*innen sind herzlich willkommen.

Im Anschluss an den Vortrag werden die diesjährigen Female Student Travel Awards vergeben.

Zur besseren Planung bitten wir um eine kurze Anmeldung per Mail an


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). Structural Health Monitoring 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 i) integrate knowledge stemming from physics-based representations, and ii) assimilate experience garnered from expert operators. This talk discusses implementation of such a hybrid approach to treating cyber physical systems for tackling the aforementioned challenges and improving our oversight on the operation of critical systems and structures. 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.


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