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In this study a numerical analysis of the elastohydrodynamic lubrication point contact problem in the unsteady state of reciprocating motion is presented. The effects of frequency, stroke length and load on film thickness and pressure variation during one operating cycle are discussed. The general tribological behavior of elastohydrodynamic lubrication during reciprocating motion is explained.

The system of equations of Reynolds, film thickness considering surface deformation and load balance equations are solved using the Newton-Raphson technique with the Gauss-Seidel iteration method. Numerical solutions were performed with a sinusoidal contact surface velocity to simulate reciprocating elastohydrodynamics. The methodology is validated using historical experimental measurements/observations and numerical predictions from other researchers.

The numerical results showed that the change in oil film during a stroke is controlled by both wedge and squeeze effects. When the surface velocity is zero at the stroke end, the squeeze effect is most noticeable. As the frequency increases, the general trend of central and minimum film thickness increases. With the same entraining speed but different stroke lengths, the properties of the oil film differ from one another, with an increase in stroke length leading to a reduction in film thickness. Finally, the numerical results showed that the overall film thickness decreases with increasing load.

General tribological behaviors of elastohydrodynamic lubricating point contact, represented by pressure and film thickness variations over time and profiles, are analyzed under reciprocating motion during one working cycle to show the effects of frequency, stroke length and applied load.

This paper aims to reveal the influence of the grooved texture parameters on the lubrication performance of circular pocket-roller pairs in cylindrical roller bearings.

In this paper, the thermal elastohydrodynamic lubrication mathematical model of the grooved texture circular pocket-roller pair was established, the finite difference method and successive over-relaxation method were used to solve the model, the influence of texture quantity, texture depth and texture area ratio on circumferential bearing capacity, friction coefficient, maximum temperature rise, stiffness and damping of the circular pocket-roller pairs were analyzed.

The results show that texture quantity, texture depth and texture area ratio significantly influence the static and dynamic characteristics of circular pocket-roller pairs. The suitable surface groove texture parameters can dramatically improve the circumferential bearing capacity, reduce the friction coefficient, inhibit the maximum temperature rise and increase the stiffness and damping of the circular pocket-roller pairs.

The research in this paper can provide a theoretical basis for the optimization design of pockets in cylindrical roller bearings to reduce friction and vibration.

The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal bearing (MHJB) system.

To simulate the behaviour of PVP lubricant in clearance space of the MHJB system, the modified form of Reynolds equation is numerically solved by using finite element method. Galerkin’s method is used to obtain the weak form of the governing equation. The system equation is solved by Gauss–Seidal iterative method to compute the unknown values of nodal oil film pressure. Subsequently, performance characteristics of bearing system are computed.

The simulated results reveal that the location of pressurised lubricant inlets significantly affects the oil film pressure distribution and may cause a significant effect on the characteristics of bearing system. Further, the use of PVP lubricant may significantly enhances the performance of the bearing system, namely.

The present work examines the influence of pocket orientation with respect to loading direction on the characteristics of PVP fluid lubricated MHJB system and provides vital information regarding the design of journal bearing system.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0241/

The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.

This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.

The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.

Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/

The purpose of this paper is to investigate the friction and wear mechanisms in lubricated sliding conditions of additively manufactured SS316L parts. The different viscous oils 5W30, 15W40, 20W50 and SAE140 are used. These investigations provide a theoretical basis for the high performance of printed and postheattreated SS316L.

Tribological tests were carried out on selective laser melting-made SS316L printed specimens and heat-treated specimens. The parameters in 15 min of test duration are 20 N of load, 200 rpm, 8 mm of pin diameter, 25 mm length, 80 mm of track diameter and EN31 counter disc body. This work presented the phenomena of lubrication regimes and their characterization, as identified by the Stribeck curve, and these regimes affect the tribological properties of additively manufactured SS316L under the influence of industrial viscous lubricants. The results are observed using Scanning electron microscope (SEM), X-ray diffraction (XRD) and wear tests.

The observations indicate that additively manufactured SS316L shows a reduced coefficient of friction (COF) and specific wear rate (SWR). This is credited to the utilization of different viscous lubricants.

This exclusive research demonstrates how various viscous lubricants affect the COF and SWR of printed and post-heat-treated SS316L parts. Lambda (λ), lubricant film thickness (h₀), surface roughness and wear mechanisms are studied and reported.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0110/

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/

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.

Inspired by the high-friction performance of the soft toe pads of tree frogs, this study aims to investigate the effect of elastic deformation on the lubrication properties of squeezing films inside soft tribocontacts with microstructured surface under wet conditions.

A one-dimensional hydrodynamic extrusion model was used to study the film lubrication characteristics of conformal contact. The lubrication characteristics of the extruded film, including load-carrying capacity, liquid flow and surface elastic deformation, were obtained through the simultaneously iterative solution of the fluid-governing and deformation equations.

The results show that the hydrodynamic pressure is approximating parabolically and symmetrically distributed in the contact area, and the peak value appears in the center of the extrusion surface. Elastic deformation increases the thickness of the liquid film, weakens the bearing capacity and homogenizes the liquid flow rate of inside soft friction contact. The magnitude of this effect greatly increases as the initial liquid film thickness decreases. Moreover, the elastic deformation directly affects the average film thickness of the extrusion contact. Narrow and shallow microchannels are found to result in a more prominent elastic deformation on the microstructured soft surface.

These results present a design for soft tribocontacts suitable for submerged or wet environments involving high friction, such as wiper blades, in situ flexible electrons and underwater robots.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0049/

Liquid-assisted laser surface texturing technology was used to create composite microtextures on triangular guide rail surfaces to enhance their tribological properties.

Numerical simulations were used to investigate the impact of various microtextures on fluid dynamic lubrication. Reciprocating friction and wear tests, followed by mechanistic analysis, examined the combined tribological effects of microtextured surfaces and lubricants.

The numerical simulation outcomes reveal a significant augmentation in the influence of fluid dynamic pressure due to composite microtextures, consequently amplifying the load-bearing capacity of the oil film. The average friction coefficient of composite microtextured samples was approximately 0.136 in reciprocating pin-on-disk friction tests, representing approximately 17% decrease compared to polished samples. Triangular guide rails with composite microtextures demonstrated the lowest average coefficient under conditions of high-speed and heavy-loading in the reciprocating friction and wear tests. Additionally, the presence of composite microtextures was found to promote the formation of adsorbed and friction films during friction, potentially contributing to the enhancement of tribological properties.

Triangular guide rails face high friction and wear, limiting their stability in demanding applications like machine tool guideways. This paper proposes a novel approach for steel triangular guide rails, involving composite microtexturing, numerical fluid simulations, liquid-assisted laser surface texturing and friction-wear testing. By implementing composite microtextures, the method aims to reduce friction coefficients and extend guideway service life, thereby saving energy and reducing maintenance costs. Enhancing the antifriction and antiwear properties of machine tool guideways is crucial for improving performance and longevity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0183/

This study aims to explore the thermal energy diffusion and flow features of a hybrid nanofluid in a thin film. In particular, the focus is to elicit the impact of shape factor in the backdrop of a magnetic field. The hybrid nanofluid is the amalgamation of various shaped nanoscale particles of copper and alumina in water.

The equations of motion and energy are modeled using the Tiwari–Das model. The differential equations governing the physics of the designed model have been obtained by the application of scaling analysis. To achieve quantitative outcomes, Runge–Kutta–Fehlberg numerical code along with shooting techniques is used. Validation of the derived outcomes with available data in literature reveals a greater accuracy of the numerical procedure used in this investigation.

The dynamics of the slender nano liquid film is explored eliciting the impact of various flow parameters. The rate of energy transport of the Cu-Al₂O₃/ water with blade-shaped nanoparticle, at a fixed Prandtl number (=2) is enhanced by 14.7% compared to that evaluated with spherical particles. The presence of hybrid nanoparticles has an affirmative impact in boosting the rate of heat transfer (RHT). The temperature and the rate of thermal diffusion of the hybrid nanofluid are more prominent than those of the Cu-H₂O case. The numerical outcomes of this investigation are collated with the already published works as a limiting case and are found to be in good agreement.

The adopted methodology helped to obtain the results of the present problem. To the best of authors’ knowledge, it can be shown that the originality of the work with the table of comparison. There is a good agreement between present outcomes with the existed results.