Numerical thermal analysis of grease-lubrication in limited line contacts considering asperity contact

Grease lubrication is widely used for rolling element bearing due to its special rheological characteristics. While there have been many related studies based on experiments, the corresponding numerical simulation method is much less developed. This article presents the numerical simulation for finite line contacts for grease lubrication whose rheological behavior follows the Ostwald model. Neural network and genetic algorithms are used for the prediction of film thickness and asperity contact load ratio based on the results of the numerical simulation, and it shows that the predictive of the well trained neural network has a good agreement with the simulation results. This provides a simple way for the prediction of the film thickness and asperity contact load ratio for grease lubrication.