Qingkai Zhao

PRCT-Net: A Transfer-Learning Physics-Informed Convolutional Transformer for Fast Surrogate Prediction of Confined Dual-Cylinder 3D Free-Surface Two-Phase Flow

The results demonstrate that the proposed PRCT-Net substantially enhances computational efficiency while maintaining high prediction accuracy for two-phase flow problems, and supports single-stage training and sustained deployment, enabling robust inference across a wide range of unseen operating conditions.