Multi-fidelity physics-informed machine learning for probabilistic damage diagnosis

S. Miele, Pranav Karve, Sankaran Mahadevan

Abstract: Highlights•Developed PIML-based classification models for damage localization.•Combined data from physics models of different fidelities for training.•Laboratory experiments for hidden crack localization in slabs.•Investigated training data generation cost vs. model performance.