MS041C Physics-Informed Machine Learning for Structural Health Monitoring: Emerging Trends and Open Issues III
MS Corresponding Organizer: Dr. Alberto Barontini (University of Minho, ISISE, ARISE)
Chaired by:
Dr. Alberto Barontini (University of Minho, ISISE, ARISE , Italy)
Dr. Alberto Barontini (University of Minho, ISISE, ARISE , Italy)
Scheduled presentations:
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Simulation of ground penetrating radar data for railway condition assessment via Physics-Informed Neural Networks
T. Rigoni, G. Arcieri, M. Haywood-Alexander, D. Haener, E. Chatzi* -
Structural Stress Estimation using Digital Image Correlation and Machine Learning
W. Mucha*, G. Kokot -
Dynamic identification of structures by means of stochastic subspace identification method.
S. Scalisi*, M. Cuomo -
Sensor Integrity Assessment and Spatio-Temporal Interpolation using Graph Neural Networks for Radioactive Waste Repository Monitoring
P. Hembert*, C. Ghnatios, J. Cotton, F. Chinesta -
Review and challenges for a realistic numerical SHM benchmark
F. Marafini*, G. Zini, A. Barontini, M. Betti, G. Bartoli, N. Mendes, A. Cicirello