# Damage Identification

Ultrasonic guided-wave inspection of thin-walled structures usually needs repeated finite-element runs or dense scans to obtain a damage-free baseline. PI-SIREN embeds the coupled elastodynamic equations of Mindlin–Reissner plate theory in the training loss of a sinusoidal-activation network, reconstructing the steady-state wavefield in the frequency domain from sparse measurements without temporal discretization. In the numerical ablation the full optimization pipeline reaches a test error of 0.1037, and in experiment the surrogate serves as the baseline that localizes a back-side milled notch from sparse measurements, whereas comparable plain multilayer-perceptron baselines localize no defect at all.

Ultrasonic guided-wave inspection of thin-walled structures usually needs repeated finite-element runs or dense scans to obtain a damage-free baseline. PI-SIREN embeds the coupled elastodynamic equations of Mindlin–Reissner plate theory in the training loss of a sinusoidal-activation network, reconstructing the steady-state wavefield in the frequency domain from sparse measurements without temporal discretization. In the numerical ablation the full optimization pipeline reaches a test error of 0.1037, and in experiment the surrogate serves as the baseline that localizes a back-side milled notch from sparse measurements, whereas comparable plain multilayer-perceptron baselines localize no defect at all.