101 citations · 246 across the 14 of their papers we have counts for
6 papers · 1 filter
On an Application of Generative Adversarial Networks on Remaining Lifetime Estimation
G. Tsialiamanis, D. Wagg, N. Dervilis +1
A major problem of structural health monitoring (SHM) has been the prognosis of damage and the definition of the remaining useful life of a structure. Both tasks depend on many par…
On generative models as the basis for digital twins
G. Tsialiamanis, D. J. Wagg, N. Dervilis +1
A framework is proposed for generative models as a basis for digital twins or mirrors of structures. The proposal is based on the premise that deterministic models cannot account f…
On partitioning of an SHM problem and parallels with transfer learning
G. Tsialiamanis, D. J. Wagg, P. A. Gardner +2
In the current work, a problem-splitting approach and a scheme motivated by transfer learning is applied to a structural health monitoring problem. The specific problem in this cas…
On an application of graph neural networks in population based SHM
G. Tsialiamanis, C. Mylonas, E. Chatzi +3
Attempts have been made recently in the field of population-based structural health monitoring (PBSHM), to transfer knowledge between SHM models of different structures. The attemp…
On generating parametrised structural data using conditional generative adversarial networks
G. Tsialiamanis, D. J. Wagg, N. Dervilis +1
A powerful approach, and one of the most common ones in structural health monitoring (SHM), is to use data-driven models to make predictions and inferences about structures and the…
On the application of generative adversarial networks for nonlinear modal analysis
G. Tsialiamanis, M. D. Champneys, N. Dervilis +2
Linear modal analysis is a useful and effective tool for the design and analysis of structures. However, a comprehensive basis for nonlinear modal analysis remains to be developed.…