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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/

The purpose of this paper is to study the correlation between different topographies and the reaction of Ulva Linza fouling species.

In this research, topographies with a different method, such as hot embossing and hot pulling, were achieved, and biological analyses were done with macroalgae Ulva Linza cells. The effect of topography via local binding geometry (honeycomb size gradients) and Wenzel roughness on the settling of Ulva microorganisms was tested.

As a result, Ulva spores confirmed different reactions to a similar set of tapered microstructures that was in agreement with the results on distinct honeycombs. The local binding geometry and the Wenzel roughness factor “r” were dominant on settling of Ulva Linza spores.

The reaction of an organism at the interface of vehicles’ substrate is powerfully affected by surface topographies.

The best embedment occurred on structures with bigger sizes than Ulva Linza’s spores. The density of settled spores was proportional to Wenzel roughness and the spores favour to attach to “kink sites” positions.

Unfortunately, unpleasant aggregation of marine biofouling on marine vehicles’ surfaces, generate terrific difficulties in the relevant industry.

There was a sharp relationship between Wenzel roughness and settle of Ulva Linza spores. The local binding geometry and the Wenzel roughness factor “r” were dominant on settling of Ulva Linza spores.

The purpose of this study is to reveal the friction reduction performance and mechanism of granular flow lubrication during the milling of difficult-to-machining materials and provide a high-performance lubrication method for the precision cutting of nickel-based alloys.

The milling tests for Inconel 718 superalloy under dry cutting, flood lubrication and granular flow lubrication were carried out, and the milling force and machined surface quality were used to evaluate their friction reduction effect. Furthermore, based on the energy dispersive spectrometer (EDS) spectrums and the topographical features of machined surface, the lubrication mechanism of different granular mediums was explored during granular flow lubrication.

Compared with flood lubrication, the granular flow lubrication had a significant force reduction effect, and the maximum milling force was reduced by about 30%. At the same time, the granular flow lubrication was more conducive to reducing the tool trace size, repressing surface damage and thus achieving better surface quality. The soft particles had better friction reduction performance than the hard particles with the same particle size, and the friction reduction performance of nanoscale hard particles was superior to that of microscale hard particles. The friction reduction mechanism of MoS₂ and WS₂ soft particles is the mending effect and adsorption film effect, whereas that of SiO₂ and Al₂O₃ hard particles is mainly manifested as the rolling and polishing effect.

Granular flow lubrication was applied in the precision milling of Inconel 718 superalloy, and a comparative study was conducted on the friction reduction performance of soft particles (MoS₂, WS₂) and hard particles (SiO₂, Al₂O₃). Based on the EDS spectrums and topographical features of machined surface, the friction reduction mechanism of soft and hard particles was explored.

Gears are prone to instantaneous failure when operating under extreme conditions, affecting the machinery’s service life. With numerous types of gear meshing and complex operating conditions, this study focuses on the gear–rack mechanism. This study aims to analyze the effects and optimization of biomimetic texture parameters on the line contact tribological behavior of gear–rack mechanisms under starvation lubrication conditions.

Inspired by the microstructure of shark skin surface, a diamond-shaped biomimetic texture was designed to improve the tribological performance of gear–rack mechanism under starved lubrication conditions. The line contact meshing process of gear–rack mechanisms under lubrication-deficient conditions was simulated by using a block-on-ring test. Using the response surface method, this paper analyzed the effects of bionic texture parameters (width, depth and spacing) on the tribological performance (friction coefficient and wear amount) of tested samples under line contact and starved lubrication conditions.

The experimental results show an optimal proportional relationship between the texture parameters, which made the tribological performance of the tested samples the best. The texture parameters were optimized by using the main objective function method, and the preferred combination of parameters was a width of 69 µm, depth of 24 µm and spacing of 1,162 µm.

The research results have practical guiding significance for designing line contact motion pairs surface texture and provide a theoretical basis for optimizing line contact motion pairs tribological performance under extreme working conditions.

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/

This paper aims to investigate the effect of solder composition and roughness on early wetting behavior and interfacial reaction under atmospheric conditions.

High-speed photography is used to observe the early wetting and spreading process of the solder on the substrate in real time. The morphology of intermetallic compounds (IMCs) was observed by scanning electron microscopy, and the composition of IMCs micro bumps was determined by energy dispersive spectroscopy.

With a roughness range of 0.320–0.539 µm, the solder is distributed in an elliptical trilinear pattern along the grinding direction. With a roughness range of 0.029–0.031 µm, the solder spreads in the direction of grinding and perpendicular, forming a perfect circle (except in the case of Sn63Pb37 solder). The effect of three types of solder on early wettability is Sn63Pb37 > Sn96.5Ag3Cu0.5 > Sn. The wetting behavior is consistent with the Rn∼t model. The rapid spreading stage (Stage I) is controlled by the interfacial reaction with n1 values between 2.4 and 4. The slow spreading stage (stage II) is controlled by diffusion with n2 values between 4 and 6.7. The size of Cu6Sn5 formed on a rough substrate is greater than that produced on a smooth substrate.

Investigating the effect of solder composition and roughness on early wettability. This will provide a powerful guide in the field of soft brazing.

The purpose of this paper is to propose a fractal model of thermal contact conductance (TCC) of rough surfaces based on cone asperity.

A detailed numerical study is conducted to examine the effects of contact load, fractal dimensional, fractal roughness and material properties on the TCC of rough surfaces.

The results indicate that when the fractal dimension D is less than 2.5, the TCC of rough surfaces increases nonlinearly with the increase of the contact load. However, when the fractal dimension D is greater than or equal to 2.5, the TCC of rough surfaces increases linearly with the increase of the contact load; the TCC of the rough surfaces increases with the increase of the fractal dimension D and the decrease of the fractal roughness G; the material parameters also have an influence on the TCC of the rough surfaces, and the extent of the effect on the TCC is related to the fractal dimension D.

A fractal model of TCC of rough surfaces based on cone asperity is established in this paper. Some new results and conclusions are obtained from this work, which provides important theoretical guidance for further study of TCC of rough surfaces.

The purpose of this study is to establish a fractal model of thermal contact conductance (TCC) of micro-segment gear considering friction coefficient.

The influences of friction coefficient, fractal dimension, fractal roughness and contact type on the TCC of the rough surface were studied by using numerical simulation.

The results show that with the increase of the friction coefficient, the TCC of the rough surface will decrease. As the fractal dimension increases or the fractal roughness decreases, the rough surface becomes smoother and the TCC becomes larger. Under the same load conditions, the TCC of the internal contact type is greater than that of the external contact type. In engineering practice, the desired TCC can be achieved by changing the contact type.

A fractal model of TCC of micro-segment gear considering friction coefficient was established in this study. The achievements of this study provide some theoretical basis for the investigation of the TCC of the gear.

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 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.