[Archimedes Talks Series]Machine-learning for structural dynamics and structural health monitoring

Dr. Tsialiamanis completed his MEng at the Civil Engineering School of the National Technical University of Athens. He then joined the DRG of the University of Sheffield as a PhD student and a Marie Skłodowska-Curie early stage researcher of the Dynamic Virtualisation (DyVirt) project. He has been a visiting researcher at ETH Zurich and has acquired funding from the non-destructive evaluation division of the Engineering Institute of the Los Alamos National Laboratory and for an extended research visit. Dr. Tsialiamanis is also a member of the steering board committee of the Welsh Digital Twin Network, which aims at developing a functional digital twin of Wales to improve the everyday life of people in the region.

The research of the DRG is focused on modelling structural dynamics. A great part of the research is conducted on the structural health monitoring of structures which is inseparably connected to the acquisition and exploitation of data. The group employs machine-learning algorithms to deal with situations where physical knowledge is absent and the formalisation of the physics is challenging because of the presence of uncertainties. A great deal of research is also conducted on the Verification and Validation of models, which is based on performing experiments to confirm the accuracy and robustness of models. For this purpose, the Laboratory of Verification and Validation (LVV) is used, where equipment is available to test structures under varying environmental conditions, such as varying temperatures, wind loadings, wave loading, etc.