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cs.CE2026
Reduced-Order Physics-Informed Neural Network with Adaptive Basis Refinement for Structural Identification
Rui Zhang, Konstantinos Vlachas, Eleni Chatzi
Physics-informed neural networks (PINNs) provide a flexible framework for solving forward and inverse problems. However, their direct application to structural dynamics remains lim…
cs.CE2024
A Reduced Order Model conditioned on monitoring features for estimation and uncertainty quantification in engineered systems
Konstantinos Vlachas, Thomas Simpson, Anthony Garland +3
Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Alt…