In this study, a structural optimization method driven by tribo-dynamic mechanism is proposed for the staved water-lubricated bearings (SWLBs). To this end, a tribo-dynamic model considering mass conservation cavitation is established, and the accuracy of this model is verified by comparing it with the experimental and numerical results in published literature studies. The comparative studies emphasize the significant role of mass conservation cavitation on the tribo-dynamic responses of SWLBs under the mixed lubrication regime. Based on numerical simulations, the optimal stave structure for a specific working operation under heavy load condition is identified from the perspective of the tribo-dynamic mechanism. Furthermore, in order to evaluate the applicability of the proposed optimization method, the influences of key parameters, including the rotational speed, the radial clearance, and the surface roughness, on the optimization results are comparatively analyzed. The comparative results reveal that the optimal stave structure is highly dependent on the mentioned key parameters, and the optimal method is effective for a wide range of working conditions. Moreover, the effects of the stave parameters, including stave width and number, on tribo-dynamic characteristics of SWLBs are also investigated, suggesting a more comprehensive optimization scheme for SWLBs.

The purpose of this study is to assess the role of turbulence on the lubrication performances of coupled journal-thrust water-lubricated bearing with micro grooves using a numerical model. The results of the simulation model are compared to the published experimental data to verify the validity of the numerical model. The load capacity, maximum film pressure, and local Reynolds number variations with the rotating speed, eccentricity, radial clearance, axial geometric gap, and micro groove depth for coupled journal-thrust water-lubricated bearing are examined. Furthermore, the calculated results under the turbulent flow are compared with those under laminar flow for coupled and separate bearings. The results show that the turbulence effect can improve the lubrication performances by enlarging fluid pressure and load capacity of the coupled journal-thrust bearing and the laminar flow assumption is no longer applicable to the actual operating conditions of the water-lubricated bearings at a high rotation speed. In addition, optimal micro groove depths for both journal bearing and thrust bearing exist to reach the peak of the load capacity while the optimal micro groove depths for journal bearing and thrust bearing are not the same.

The present study aims to establish a mixed lubrication model for staved stern tube bearings lubricated with water, in which the average Reynolds equation and a KE elastic–plastic contact model are introduced to calculate the hydrodynamic pressure and contact pressure, respectively. The difference in the mixed lubrication behaviors between circular- and flat-staved bearings is compared; moreover, the effects of the number of staves on the mixed-lubrication performance of these two kinds of staved bearing are investigated. The mechanism of action of the number of staves in staved bearings on the mixed-lubrication performance is revealed. The numerical results show that the number of staves has a significant effect on the mixed-lubrication performance in circular- and flat-staved bearings. Furthermore, there is an optimal value for the number of staves, shown to be 30 in the current simulation, for improving the mixed-lubrication performance of flat-staved stern tube bearings lubricated with water.

Rail transportation has dramatically improved travel convenience, but it has also led to environmental pollution and energy consumption issues. These challenges can be partially addressed by reducing friction loss in the mechanical transmission of rail systems. This paper examines the tribological properties of bionic-textured surfaces inspired by snake- and sharkskin. This study focuses on generating bionic textured surfaces with randomly distributed peaks through numerical simulation and connecting them to a transient Reynolds equation and friction fatigue model. The bionic surface wear lubrication model considers the lubricating film’s thickness and contact pressure obtained from the GT model. The results reveal that the existence of a bionic texture can reduce the friction coefficient and wear amount on the contact surface. The findings of this study not only offer a potential solution for reducing energy consumption and emissions in intelligent rail transit systems but also hold promise for providing further insights into the numerical simulation of bionic weaving and the investigation of tribological characteristics.