Sheng-Bo Li

A comparative study of preprocessing methods for physics-informed neural networks in fluid mechanics

This study systematically compares PINNs preprocessing methods, with particular focus on three universal approaches (the non-dimensionalization, inner normalization layers, and synergistic normalization method for data and equation), and provides a practical reference for selecting preprocessing methods in different physical scenarios.