Leonardo Ferreira | PhD Candidate, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil
December 7, 2022 | 11h00-12h00 | Room U.0.6 | https://videoconf-colibri.zoom.us/j/93285885760 | Lusófona University, Lisbon, Portugal
Abstract: Structural health monitoring (SHM) of composite plates has been implemented to automatic detect structural damage. The Lamb Waves have been used to measure the structural response. In this type of approach, temperature effects are particularly critical and they are always present in real structures, which challenges the applicability of SHM. Therefore, this talk presents recent advances in the development of a probabilistic numerical model to quantify temperature effects on Lamb Wave propagation, capable to perform data augmentation for the training of machine learning algorithms.