Abstract

In order to study the effect of surface roughness on lubrication performance of an elastic support water-lubricated tilting pad thrust bearing, a mixed lubrication (ML) deterministic model is hereby presented based on a unified Reynolds equation model. This very model incorporates the elastic–plastic deformation of asperities and polymer matrix of the thrust pad, as well as the elastic deformation of the rubber support. The randomly distributed surface roughness of the thrust pad is generated by a mathematical model and shares the same distribution characteristics as the measured surface roughness. The Greenwood and Williamson asperity contact model and thin plate deformation model are combined to solve the asperities contact stress and deformation. Meanwhile, the bearing ML performance is compared with the results calculated by a thermohydrodynamic (THD) lubrication model and a thermo-elasto-hydrodynamic (TEHD) lubrication model, while the film thickness is also compared with measurements. The results show that the water film thickness calculated by the ML model is smaller than that by the THD model and the TEHD model, but the water film temperature is higher. The roughness has a great influence on the contact area ratio and the lubrication state, but little effect on the average film thickness. A higher roughness indicates a higher rotational speed required for the bearing to achieve full hydrodynamic lubrication. The film thickness calculated by the mixed lubrication model is closer to the measured results. Overall, it is proved that the mixed lubrication model can more accurately predict the lubrication performance of bearings. Compared to the thin plate deformation model, the elastic deformation simulation based on the half-infinite space model severely overestimates the elastic deformation of the pad surface, making it unsuitable for calculating the elastic deformation of the polymer matrix of the thrust pad under contact force or water film pressure. This ML deterministic model provides an effective means for high-precision prediction of the lubrication performance of the elastic supported water-lubricated thrust bearings coupled with multi-layer soft materials.

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