Finite-Element-Informed Neural Surrogates for Elastic Site Characterization from Sparse Data: A Feasibility and Sensitivity Study
Data-driven site characterization in geotechnical engineering increasingly relies on high-dimensional waveform data and computationally intensive inverse modeling. Full waveform inversion and finite element model updating typically rely on gradient-based or Bayesian optimization, requiring many serial forward simulatio...