Physics-informed neural networks (PINNs) represent a burgeoning paradigm in computational science, whereby deep learning frameworks are augmented with explicit physical laws to solve both forward and ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Patient digital twins aim to create computational replicas of an individual’s physiology that can predict disease trajectories and treatment response.