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This study aims to investigate mixed lubrication performances of stern bearing in a misaligned state considering turbulence and bearing deformation impacts.

A mixed lubrication model of stern bearing is established. The generalized average Reynolds equation governing the turbulent flow of lubricant is analyzed by considering the interaction of bearing elastic deformation, asperity contact pressure and film pressure. The bearing behaviors including minimum film thickness, hydrodynamic pressure, asperity friction force and frictional coefficient are studied under different models. The correctness of this model is verified by comparing it with that of the published data.

Numerical results indicate that elastic deformation noticeably decreases the maximum film pressure, the asperity contact force and the friction coefficient in the mixed lubrication stage. The effect of elastic deformation and turbulence reduces the transition speed from mixed to liquid lubrication.

This model includes both turbulence and bearing deformation impacts on journal bearing performances. It is expected that the numerical results can provide useful information to establish a stern bearing exposed to mixed lubrication conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2022-0352/

Harmonic gears always work under different operating conditions and may usually break down due to lubrication failures, while its lubrication mechanism is still not clearly understood. This paper aims to present a lubrication model comprehensively considering the influence of contact geometry, lubrication properties and three-dimensional (3D) real surface roughness to analyze the lubrication performance under different conditions.

Based on the discrete convolution-fast Fourier transformation with duplicated padding and quasi-system numerical methods, the lubrication model for harmonic gears is developed, which is verified by comparing results with available lubrication data.

The effects of meshing process, working conditions and 3D roughness on the lubrication characteristics are discussed. From the calculated cases, the increase in rotational speed and decrease of applied torque may increase the film thickness, enhancing the lubrication performance of harmonic gears. It is also observed that proper surface roughness can be used for lubrication design.

The research results can provide theoretical guidance for improving lubrication performance and reducing friction/wear of the harmonic gear interfaces. This study can be promoted to various engineering scenarios of harmonic gears, such as industrial robots, space-driven agencies and precision measuring instruments.

This study aims to use a machine learning (ML) model for the prediction of traction coefficient and asperity load ratio for different surface topographies of non-conformal rough contacts.

The input data set for the ML model is generated using a mixed-lubrication model. Surface topography parameters (skewness, kurtosis and pattern ratio), rolling speed and hardness are used as input features in the multi-layer perceptron (MLP) model. The hyperparameter tuning and fivefold cross-validation are also performed to minimize the overfitting.

From the results, it is shown that the MLP model shows excellent accuracy (R² > 90%) on the test data set for making the prediction of mixed lubrication parameters. It is also observed that engineered rough surfaces with high negative skewness, low kurtosis and isotropic surface patterns exhibit a significant low traction coefficient. It is also concluded that the MLP model gives better accuracy in comparison to the random forest regression model based on the training and testing data sets.

Mixed lubrication parameters are predicted by developing a regression-based MLP model. The machine learning model is trained using several topography parameters, which are vital in the mixed-EHL regime because of the lack of regression-fit expressions in previous works. The accuracy of MLP with random forest models is also compared.

This paper aims to study the startup performance of thrust bearing. The effects of acceleration scenarios, roughness, the area ratio of texture and texture depth on the transient startup performance of the thrust bearing were analyzed.

The lubrication model is solved by the Reynolds equation with the mass-conservation boundary condition. The Greenwood and Tripp contact model is used to predict asperity contact load. The finite volume method is used to discretize the governing equations.

By studying the bearing performance with different acceleration functions, it was found that the higher the acceleration at the beginning of the startup, the faster the thrust bearing operates under the hydrodynamic lubrication regime in the start stage. It appears that the friction and contact time of asperity increase with the increasing roughness. The optimal area ratio of texture is within 30%–50%. The depth of texture ranging from 1 to 2 is the best.

This paper proposes a transient mixed lubrication analysis model of the thrust bearing. This model can be used to analyze the variations of tribological performance and lubrication regime of the thrust bearing under different acceleration scenarios.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2022-0268/

Hydro-viscous drive (HVD) clutches are widely used in equipment requiring soft start, such as fans and pumps, to transmit torque and adjust speed by changing the gap distance between friction pairs. This paper aims to propose a novel two-parameter evaluation method for HVD during the mixed lubrication stage. The objective is to develop an effective model that establishes the relationship between these parameters and the actual surface topography.

In the presented methods, the fractal features of the real manufacturing surface are calculated based on the power spectrum function by the ultra-depth three-dimensional microscope. After that, the hybrid friction model of the friction plate is established based on mixed elasto-hydrodynamic lubrication theory, boundary friction model and fractal theory. Then the torque and load bearing characteristics of the clutch are obtained, and the influences of the surface fractal features are investigated and discussed. Finally, the Weierstrass–Mandelbrot function is adopted for the surface topography characterization and evaluation.

The results indicate that the proposed method exhibits good accuracy, while the speed difference between the friction pair exceeds 2,500 rpm. It is concluded that this paper proposed a way to evaluate the torque and loading capacity of HVD considering the real manufacturing surface topography and is helpful for surface optimization.

The originality and value of this study lie in its development of a novel torque and load bearing capacity evaluation method for HVD in mixed lubrication stage, considering manufacturing surface topography and describing the real manufacturing surface.

This study aims to investigate the effects of irregular groove textures on the friction and wear performance of sliding contact surfaces. These textures possess multiple depths and asymmetrical features. To optimize the irregular groove texture structure of the sliding contact surface, an adaptive genetic algorithm was used for research and optimization purposes.

Using adaptive genetic algorithm as an optimization tool, numerical simulations were conducted on surface textures by establishing a dimensionless form of the Reynolds equation and setting appropriate boundary conditions. An adaptive genetic algorithm program in MATLAB was established. Genetic iterative methods were used to calculate the optimal texture structure. Genetic individuals were selected through fitness comparison. The depth of the groove texture is gradually adjusted through genetic crossover, mutation, and mutation operations. The optimal groove structure was ultimately obtained by comparing the bearing capacity and pressure of different generations of micro-convex bodies.

After about 100 generations of iteration, the distribution of grooved textures became relatively stable, and after about 320 generations, the depth and distribution of groove textures reached their optimal structure. At this stage, irregular texture structures can support more loads by forming oil films. Compared with regular textures, the friction coefficient of irregular textures decreased by nearly 47.01%, while the carrying capacity of lubricating oil films increased by 54.57%. The research results show that irregular texture structures have better lubrication characteristics and can effectively improve the friction performance of component surfaces.

Surface textures can enhance the friction and lubrication performance of metal surfaces, improving the mechanical performance and lifespan of components. However, surface texture processing is challenging, as it often requires multiple experimental comparisons to determine the optimal texture structure, resulting in high trial-and-error costs. By using an adaptive genetic algorithm as an optimization tool, the optimal surface groove structure can be obtained through simulation and modeling, effectively saving costs in the process.

This paper aims to improve the tribological properties of lithium complex greases using nanoparticles to investigate the tribological behavior of single additives (nano-TiO₂ or nano-CeO₂) and composite additives (nano-TiO₂–CeO₂) in lithium complex greases and to analyze the mechanism of their influence using a variety of characterization tools.

The morphology and microstructure of the nanoparticles were characterized by scanning electron microscopy and an X-ray diffractometer. The tribological properties of different nanoparticles, as well as compounded nanoparticles as greases, were evaluated. Average friction coefficients and wear diameters were analyzed. Scanning electron microscopy and three-dimensional topography were used to analyze the surface topography of worn steel balls. The elements present on the worn steel balls’ surface were analyzed using energy-dispersive spectroscopy and X-ray photoelectron spectroscopy.

The results showed that the coefficient of friction (COF) of grease with all three nanoparticles added was low. The grease-containing composite nanoparticles exhibited a lower COF and superior anti-wear properties. The sample displayed its optimal tribological performance when the ratio of TiO₂ to CeO₂ was 6:4, resulting in a 30.5% reduction in the COF and a 29.2% decrease in wear spot diameter compared to the original grease. Additionally, the roughness of the worn spot surface and the maximum depth of the wear mark were significantly reduced.

The main innovation of this study is the first mixing of nano-TiO₂ and nano-CeO₂ with different sizes and properties as compound lithium grease additives to significantly enhance the anti-wear and friction reduction properties of this grease. The results of friction experiments with a single additive are used as a basis to explore the synergistic lubrication mechanism of the compounded nanoparticles. This innovative approach provides a new reference and direction for future research and development of grease additives.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0291/

The purpose of this study is to develop a 3D wheel-rail adhesion model under wet condition, which considers the generated surface roughness topography and the traditional braking procedure for high-speed trains.

Wheel-rail adhesion has an important effect on the braking ability of railway vehicle. Based on the deterministic mixed lubrication approach, the model was solved to get the adhesion characteristics of the train during braking. The elastic deformation was calculated with the discrete convolution and fast Fourier transform method. The simulation results of adhesion coefficient were compared with the experimental values. The wheel-rail adhesion characteristics of train braking at several different initial speeds were investigated. The effects of the time-step length and roughness orientation on the contact load ratio were also discussed.

The results show that the adhesion coefficient of the numerical model is in good agreement with the experimental results. At the instant of braking, the adhesion coefficient drops to a lower adhesion level, the value of adhesion coefficient is lower than 0.06, especially at a higher speed (200, 300 and 400 km/h).

It can provide a better understanding of the low adhesion phenomenon of train braking under wet condition.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0040/

This paper aims to explore the influence of applied pressure on the tribological properties of the friction component in a wet multi-disc clutch during the running-in process.

The running-in evolutionary was explored in terms of global friction performance. The variation of friction torque and mean COF of the initial 300 engagement cycles was obtained by full-scale tests. Finally, an optical microscope was used to detect the wear characteristics of friction surfaces.

The applied pressure showed a significant influence on the tribological behaviors of wet clutches during the running-in process. The mean COF decreased and then increases with the increase of the applied pressure. A higher applied pressure contributed to more asperity summits being sheared, thus resulting in a smoother surface. Considering a suitable wore performance, properly applied pressure is necessary.

The results provide theoretical guidance for selecting the optimal applied pressure in the running-in of wet clutches.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2022-0256/

As the crucial support component of the propeller power system, the reliability of the operation of submersible pumps is influenced by the lubrication performance of water-lubricated thrust bearings. When the water-lubricated thrust bearings are under start-stop or heavy load conditions, the effect of surface morphology is crucial as the mixed lubrication regime is encountered. This paper aims to develop one mixed lubrication model for the water-lubricated thrust bearings to predict the effects of surface skewness, kurtosis and roughness orientation on the loading carrying capacity and tribological behavior.

This paper developed one improved mixed lubrication model specifically for the water-lubricated thrust bearing system. In this model, the hydrodynamic model was improved by using the height of the rough surface and its probability density function, combined with the average flow model. The asperity contact model was improved by using the equation for the Pearson system of frequency curves to characterize the non-Gaussian aspect of surface roughness distribution.

According to the results, negative skewness, large kurtosis and lateral surface pattern can improve the tribological performance of water-lubricated thrust bearings. Optimizing the surface morphology is a reasonable design method that can improve the performance of water-lubricated thrust bearings.

In this paper, one mixed lubrication model specifically for the water-lubricated thrust bearing with the effect of surface roughness into consideration was developed. Based on the developed model, the effect of surface morphology on tribological behavior can be evaluated.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0247/