Research on the Application of Physical Information Neural Network in Multiscale Fluid Dynamics Simulation - Liu, Jinyu; Yan, Yinxiao; Wang, Junhui (International Journal of Computer Science and Information Technology, 2025)
In this paper, a multi-scale fluid dynamics simulation framework based on physical information neural network (PINN) is proposed, which achieves efficient simulation of multi-scale flow characteristics by means of a multi-resolution network structure, physical constraints on scale decomposition and adaptive sampling strategy. Experimental results show that the framework outperforms traditional methods in microscale flow, turbulence and multiphase flow problems, with a 37% improvement in the average prediction accuracy and a 75% reduction in the computational resource requirement. In particular, it shows excellent generalisation performance when dealing with complex flows with large scale spans, providing a new method for fluid dynamics simulation with both accuracy and efficiency.