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This paper aims to study the influence of cylindrical texture parameters on the lubrication performance of static and dynamic pressure thrust bearings (hereinafter referred to as thrust bearings) and to optimize their lubrication performance using multiobjective optimization.

The influence of texture parameters on the lubrication performance of thrust bearings was studied based on the modified Reynolds equation. The objective functions are predicted through the BP neural network, and the texture parameters were optimized using the improved multiobjective ant lion algorithm (MOALA).

Compared with smooth surface, the introduction of texture can improve the lubrication properties. Under the optimization of the improved algorithm, when the texture diameter, depth, spacing and number are approximately 0.2 mm, 0.5 mm, 5 mm and 34, respectively, the loading capacity is increased by around 27.7% and the temperature is reduced by around 1.55°C.

This paper studies the effect of texture parameters on the lubrication properties of thrust bearings based on the modified Reynolds equation and performs multiobjective optimization through an improved MOALA.

This study aims to improve the tribological properties of hydrodynamic journal bearing via surface texture, as well as the wear and antifriction mechanisms of textured bearing were represented. It provides a design direction for solving the tribological problem of rotor-bearing system.

In this paper, the variation of surface texture parameters (e.g. texture diameter, d; area density, sp; and depth, hp) were analyzed based on finite difference method. The optimal surface texture parameters were obtained by designing orthogonal experiments, and the relationship between friction and wear properties and microstructure was studied via combining electron probe microanalyzer, scanning electron microscope, X-ray diffractometer and friction and wear testing machine.

Dimensionless film pressure P increased as the d increased, whereas P first increased and then decreased as the sp and hp increased, and the maximum P was got as sp = 15% and hp = 25 µm, respectively. The friction coefficient of textured surface with suitable parameters was effectively reduced and the textured surface with the best antifriction effect was 5#. Orthogonal experimental design analysis showed that the influence order of factors on friction coefficient was as follows: sp > sp × d > d > d × hp > hp > sp × hp and the friction coefficient first decreased and then increased as the sp, d and hp increased. In addition, the friction and wear mechanism of textured bearing were three body friction and abrasive wear as the matrix structure and hard phase were a single β phase and Mn5Si3, respectively. While the antifriction mechanism of textured surface was able to store abrasive particles and secondary hydrodynamic lubrication was formed.

The sample with reasonable texture parameter design can effectively reduce friction and wear of hydrodynamic journal bearing without reducing the service life, which can provide a reference for improving the lubrication performance and mechanical efficiency of rotor-bearing system.

Micro-texture is processed on the surface to reduce the friction of the contact surface, and its application is more and more extensive. The purpose of this paper is to create a texture function model to study the influence of surface parameters on the accuracy of the simulated surface so that it can more accurately reflect the characteristics of the real micro-textured surface.

The microstructure function model of rough surfaces is established based on fractal geometry and polar coordinate theory. The offset angle θ is introduced into the fractal geometry function to make the surface asperity normal perpendicular to the tangent of the surface. The 2D and 3D contour surfaces of the surface groove texture are analyzed by MATLAB simulation. The effects of fractal parameters (D and G) and texture parameter h on the curvature of the surface micro-texture model were studied.

This paper more accurately characterizes the textured 3D curved surface, especially the surface curvature. The scale coefficient G significantly affects curvature, and the influence of fractal dimension D and texture parameters on curvature can be ignored.

The micro-texture model of the rough surface was successfully established, and the range of fractal parameters was determined. It provides a new method for the study of surface micro-texture tribology.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2023-0298/

The purpose of this paper is to investigate the effects of surface texture with roughness orientation considered on tribological properties under a mixed lubrication state numerically and experimentally.

Based on the average Reynolds equation and asperity contact model, the impacts of surface texture parameters and roughness orientation on lubrication properties have been calculated using finite difference method. Tin–bronze samples with various prescribed surface texture geometric parameters and roughness orientation were fabricated by laser surface texturing technique, and the tribology performance of the textured surface was studied experimentally.

The effects of surface geometric parameters and roughness orientation parameters have been discerned. The experimental observations are in good agreement with the numerical prediction, which suggests that the numerical scheme adopted in this work is suitable in capturing the surface texture and roughness effect under mixed lubrication state.

By meticulously controlling the surface roughness and surface texture geometric characteristics based on the laser surface texturing process, samples with prescribed surface texture parameters and roughness orientation consistent with that in theoretical studies were fabricated and the theoretical model and results were verified experimentally.

The purpose of this study is to establish a friction coefficient prediction model using texture parameters and then using the optimal texture parameters to obtain the minimum friction coefficient.

Based on texture technology and the cavitation phenomenon conditions, a test scheme based on two-factor and five-level texture parameters is designed using central composite design and then the response surface methodology and hybrid back-propagation genetic algorithm (BP-GA) models are used to establish a friction coefficient prediction model and optimize the friction coefficient.

The result indicates that the values predicted using two methodologies agree well with the experimental data, but the hybrid BP-GA model is superior to the response surface methodology model in both prediction and optimization.

Two methodologies are used to study the influence of the texture parameters on the friction coefficient under the cavitation condition. It is expected that the result can be used to obtain optimum texture parameters to reduce the friction coefficient.

This paper aims to present an analysis of several 3 D texture parameters for the entire wear scars obtained in severe regime, on a four-ball tester. The aim of this analysis is to correlate the tribological parameter as wear scar diameter to texture parameters.

Tested lubricants were rapeseed oil, rapeseed oil additivated with 1% Wt nano TiO₂ and rapeseed oil additivated with 1%Wt nano ZnO. The severe regime was applied for 1400 rpm and for loads increasing in steps of 50 N, from 500 to 900 N. Several analyzed roughness parameters (height parameters and functional ones) could be related to the evolution of a wear parameter, the wear scar diameter. Comparing the values for neat rapeseed oil and additivated variants, the texture parameters allow for evaluating if the additives protect or not the worn surfaces.

Measurements pointed out two groups of roughness parameters: one that has an evolution depending on wear scar diameter (WSD) and load (Sa, St, functional parameters) and one including Ssk that has shown no dependence on load and WSD. Also, the functional parameters Spk and Svk follow in a similar manner the wear parameter, WSD, but Sk is the least dependent on load. For the highest load, amplitude parameters such as Sa and St are following the tendency of WSD. Each lubricant has its particular correlation between wear parameters and texture quality, expressed by the help of a set of roughness parameters.

Such studies help tribologists to rank lubricants based on a combined analysis with wear parameters and texture parameters.

The results allow for evaluating new formulated lubricants.

The study on the quality on worn surfaces introduces the original idea of analyzing the entire wear scar surface (approximated by an ellipse with the axes as those experimentally measured) by the help of a set of 3 D roughness parameters.

This paper aims to enhance lubrication performance of the pitcher plant–like textured surface with various parameters.

A pitcher plant–like structure surface is fabricated on the copper alloy, and the lubrication performance of the pitcher plant–like structure with various parameters is evaluated. In addition, the pressure distribution and oil film load capacity of the pitcher plant–like surface are simulated based on Navier–Stokes equations.

When the direction of motion aligns with the pitcher plant–like structure, the friction coefficient remains lower than that of the nontextured surface, and it exhibits a decreasing trend with the increasing of the texture width and spacing distance; the lowest friction coefficient (0.04) is achieved with B = 0.3 mm, L = 1.0 mm and θ = 45°, marking a 75% reduction compared to the nontextured surface. Simulation results demonstrate that with the increase in texture width and spacing distance, the oil film load-bearing capacity demonstrates an increasing trend.

Bionic pitcher plants are prepared on the copper alloy to improve the lubrication performance and wear resistance.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0119/

Surface textures have been widely used in thrust bearings as a means of enhancing the tribological performance. The effect of textures with a spiral distribution on the lubrication characteristics of thrust bearings has not been fully covered. This paper aims to investigate and find the optimal structure and distribution parameters of textures with the maximum loading capacity and minimum friction force as goals.

Combining the multi-objective optimization method based on the non-dominated sorted genetic algorithm-II with response surface methodology, the key textured parameters are optimized. Local sensitivity analysis is used to evaluate the impact level of each parameter.

Spiral distribution of textures can effectively improve the lubrication performance of the thrust bearing compared with the linear distribution. The distribution with high amplitudes and high cycle numbers will weaken the spiral effect and destroy the high-pressure region. Through the multi-objective optimization of the textured structure and distribution parameters, the loading capacity demonstrates a 55.05per cent improvement compared to the basic model. Textured width is the most sensitive parameter for both loading capacity and friction force.

Present research provides a fundamental design guide for textured thrust bearings.

This paper aims to find the best method to predict the friction coefficient of textured 45# steel by comparing different machine learning algorithms and analytical calculations.

Five machine learning algorithms, including K-nearest neighbor, random forest, support vector machine (SVM), gradient boosting decision tree (GBDT) and artificial neural network (ANN), are applied to predict friction coefficient of textured 45# steel surface under oil lubrication. The superiority of machine learning is verified by comparing it with analytical calculations and experimental results.

The results show that machine learning methods can accurately predict friction coefficient between interfaces compared to analytical calculations, in which SVM, GBDT and ANN methods show close prediction performance. When texture and working parameters both change, sliding speed plays the most important role, indicating that working parameters have more significant influence on friction coefficient than texture parameters.

This study can reduce the experimental cost and time of textured 45# steel, and provide a reference for the widespread application of machine learning in the friction field in the future.

The purpose of this study is to investigate the influence of surface texture on the subsurface characteristics of contact interfaces under elastohydrodynamic lubrication condition. As a typical contact form of gears and bearings, the optimization of friction characteristics at the elastohydrodynamic lubrication (EHL) interface has attracted the attention of scholars. Laser surface texturing is a feasible optimization solution, but there have been concerns about whether the surface texture of high-pair parts will affect their fatigue life.

To examine the impact of texture preparation on the subsurface characteristics of high-pair interfaces under EHL conditions, a point contact EHL model is developed that takes into account the effect of textured surface topography. The pressure and thickness of the oil film are calculated as input parameters under different loads and entrainment velocities. The finite element method is used to simulate the impact of textures with varying diameters, densities and depths on the subsurface characteristics of the elastohydrodynamic interface. According to ISO 25178, analyze the relationship between 3D topography parameters and subsurface characteristics and study the trend of friction characteristics and subsurface characteristics based on the results of the ball on disc friction tests.

The outcomes suggest that under different rotational velocity and load conditions, the textured surfaces exhibit improved friction reduction effects; however, the creation of textures can result in significant subsurface plastic deformation and local peeling. The existence of texture makes the larger stress zone in the subsurface layer closer to the surface, leading to fatigue failure near the surface. Reasonable design parameters can help enhance the attributes of the subsurface. A smaller Sa and a Str greater than 0.5 can achieve ideal subsurface properties on the textured surface.

This paper investigates the influence of surface texture on the friction and subsurface characteristics of EHL interfaces and analyzes the impact of surface texture on interface contact performance while achieving lubrication improvement functional characteristics. The results provide theoretical support for the optimization design and functional regulation of surface texture in EHL interfaces.

The peer review history for this article is https://publons.com/publon/10.1108/ILT-10-2023-0324/