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


23. Juni 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 office@emergencity.de.


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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