Mixed Elastohydrodynamic Lubrication in a Partial Journal Bearing—Comparison Between Deterministic and Stochastic Models

The analysis of the mixed lubrication phenomena in journal and axial bearings represents nowadays the next step towards a better understanding of these devices, subjected to more and more severe operating conditions. While the theoretical bases required for an in-depth analysis of the mixed-lubrication regime have long been established, only small-scale numerical modeling was possible due to computing power limitations. This led to the appearance of averaging models, thus making it possible to generalize the trends observed in very small contacts, and to include them in large-scale numerical analyses. Unfortunately, a lack of experimental or numerical validations of these averaging models is observed, so that their reliability remains to be demonstrated. This paper proposes a deterministic numerical solution for the hydrodynamic component of the mixed-lubrication problem. The model is applicable to small partial journal bearings, having a few centimeters in width and diameter. Reynolds’ equation is solved on a very thin mesh, and pad deformation due to hydrodynamic pressure is taken into account. Deformation due to contact pressure is neglected, which limits the applicability of the model in those cases where extended contact is present. The results obtained with this deterministic model are compared to the stochastic solution proposed by Patir and Cheng, in both hydrodynamic and elastohydrodynamic regimes. The rough surfaces used in this study are numerically generated (Gaussian) and are either isotropic or oriented, having different correlation lengths. It is shown that the stochastic model of Patir and Cheng correctly anticipates the influence of roughness over the pressure field, for different types of roughness. However, when compared to the smooth surface solution, the correction introduced by this model only partially compensates for the differences observed with a deterministic analysis.