On the coalescence of models with data for infrastructure assessment

The life-cycle management of structural systems operating under diverse loads involves the tasks of simulation (forward engineering), identification (inverse engineering) and maintenance/control actions. The efficient and successful implementation of these tasks is however non-trivial, due to the ever-changing nature of these systems, the variability in their interactive environment, and the polymorphic uncertainties involved. Structural Health Monitoring (SHM) attempts to tackle these challenges by exploiting the Value of Information stemming from sensor networks. SHM comprises a hierarchy across levels of increasing complexity aiming to i) detect damage, 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 first principles. This talk discusses implementation of such a hybrid approach to SHM for tackling the aforementioned challenges. Among other topics, we will discuss the potential and limitations of purely data-driven schemes, and the benefits stemming from infusion of data with models relying on first principles, in support of efficient management of engineered systems throughout their life-cycle.

This talk will be given in the frame of the SWICCOMAS General Assembly. The planning is:
14h – 15h Seminar by Eleni Chatzi, ETHZ
15h – 16h General Assembly
1.     SWICCOMAS board
2.     New ECCOMAS constitution
3.     SWICCOMAS price
4.     WCCM 2020, Paris
5.     Budget approval
6.       Short update by Prof. Eleni Chatzi, ECCOMAS Young Investigators.
16 – 17h Aperitif