Review and challenges for a realistic numerical SHM benchmark - View source for Marafini et al 2024a - Scipedia

9th European Congress on Computational Methods in Applied Sciences and Engineering

F. Marafini, G. Zini, A. Barontini, M. Betti, G. Bartoli, N. Mendes, A. Cicirello

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==Abstract==

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== Full Paper ==
<pdf>Media:Draft_Sanchez Pinedo_873022164pap_838.pdf</pdf>

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Document information

Published on 29/10/24
Submitted on 29/10/24

Volume Physics-Informed Machine Learning for Structural Health Monitoring: Emerging Trends and Open Issues, 2024
DOI: 10.23967/eccomas.2024.245
Licence: CC BY-NC-SA license

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Keywords

Sensor Fault • Numerical benchmark • Environmental and Operational Variability • Data generation • Damage detection

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