3 papers
physics.flu-dyn2026
Large-eddy simulation nets (LESnets) based on physics-informed neural operator for wall-bounded turbulence
Sunan Zhao, Yunpeng Wang, Huiyu Yang +2
Accurate and efficient prediction of three-dimensional (3D) wall-bounded turbulent flows poses a significant challenge for machine learning methods, particularly in scenarios where…
physics.flu-dyn2026
Physics-Informed Transformer operator for the prediction of three-dimensional turbulence
Zhihong Guo, Sunan Zhao, Huiyu Yang +2
Data-driven turbulence prediction methods often face challenges related to data dependency and lack of physical interpretability. In this paper, we propose a physics-informed Trans…
physics.flu-dyn2025
LESnets (Large-Eddy Simulation nets): Physics-informed neural operator for large-eddy simulation of turbulence
Sunan Zhao, Zhijie Li, Boyu Fan +3
Acquisition of large datasets for three-dimensional (3D) partial differential equations (PDE) is usually very expensive. Physics-informed neural operator (PINO) eliminates the high…