Physics-enhanced neural operator for predicting hydrodynamic lubrication in slipper pairs
The transient dynamics of the micrometer-scale slipper-pair oil film in axial piston pumps are governed by multi-factor coupling effects, rendering traditional numerical methods inadequate for real-time simulation and rapid design optimization. This paper proposes a physics-enhanced neural operator (PENO) to predict tr...