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Newmark-\b{eta}-DGN is introduced, a graph neural network-based framework that combines two structures inspired by computational mechanics that links coarse-step prediction to the inference of mechanical quantities that were never observed during training.
Guided-wave structural health monitoring enables damage localization in composite plates using sparse networks of bonded piezoelectric transducers. However, supervised localization remains weakly constrained when measurements are available from only a limited set of damage locations. Because exhaustive spatial coverage...
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