Friction最新文献

A timely trend in gear transmission involves the replacement of steel with polymers. Nevertheless, the absence of fundamental durability data for polymer gears impedes their reliable application during power transmission. The expensive and time-consuming gear fatigue experiments make it impossible to rely merely on experimental data. In this study, a strategy for contact fatigue life prediction of polymer gears via an experimental-simulated hybrid data-driven model is presented. The hybrid data are established with a certain mixture ratio of experimental and simulation data and are augmented by the conditional tabular generative adversarial network (CTAB-GAN) algorithm. This specific algorithm was combined with the extreme gradient boosting (XGBoost) algorithm to predict the contact fatigue life of gears made from different polymer materials, with the prediction accuracy controlled within a 3-fold scatter band. Moreover, an empirical predictive formula for contact fatigue life was developed. The hybrid data-driven model, which merges experimental and simulated data, allows for efficient estimation of fatigue life and material selection strategies, generating insight into the anti-fatigue design of polymer gears.

Rolling contact fatigue (RCF) damage is the critical damage form faced by rails, especially under rainy and humidity conditions. In order to deeply explore the mechanisms of RCF damage under such conditions, a novel wet-dry alternation testing method (D/W-A test) was proposed, and rail RCF damage evolution tests were conducted in this study. Detailed comparisons between the novel testing method and three widely used rail RCF methods were analyzed. The results show that under wet-dry alternating conditions, the crack growth rate and wear rate were initially low, with cracks predominantly located in the region near the rail surface. Thus, there was a significant competitive relationship between crack propagation and wear in this period. Then, with the increase in cycling number, RCF damage was gradually dominated by crack propagation, which extended deeper into the material along its deformation orientation. Meanwhile, the severe material spalling led to a rapid increase in wear rate. Through comparative analysis of the accuracy, repeatability, evaluability, rationality, and practicability of the four testing methods, it was found that the novel method proposed in this study had significant advantages in rationality and accuracy compared with traditional RCF testing methods, providing a more effective tool for systematic studies on RCF performance of rail materials.

Lubricants are widely employed in mechanical systems to reduce energy loss and the wear induced by friction. With increasing concern for environmental protection, the development of eco-friendly lubricants has become increasingly significant. Nanocellulose, a natural material derived from cellulose, attracts increasing research attention in the field of lubrication due to its renewable, non-toxic, and biodegradable properties. Focusing on this emerging research topic, this state-of-the-art review first analyzes the theoretical basis of applying nanocellulose as a thickening agent in eco-friendly lubricating formulations. The following presents an overview of research advances in cellulose nanocrystals (CNCs) and cellulose nanofibrils (CNFs), categorized by their applications as additives or thickeners in aqueous, oil, and grease lubricants. This study also highlights the challenges associated with eco-friendly lubricants based on nanocellulose and offers suggestions for future investigations in this field. It is hoped that this review will inform the research direction of eco-friendly lubricants and promote the development of nanocellulose materials for industrial lubrication applications.

Sustainable lubrication of biomedical hydrogels with high stability is important for their application in dry eye disease (DED) treatment but remains a challenge. We report a novel strategy to achieve sustainable superlubricity under ocular conditions on the basis of the degradation of a thermosensitive P-C_nPEG (polyethylene glycol (PEG)) hydrogel. First, by adjusting the composition and chemical structure of the P-C_nPEG complex, its aqueous solution undergoes an adaptive sol‒gel transition at 25.1 °C during heating, resulting in a gel state upon injection onto the ocular surface (35 °C). In addition, the P-C_nPEG hydrogel obtained at 35 °C also shows superior performance, such as shear resistance, high transmittance (> 80%), rapid swelling, self-healing, and Ca²⁺ responsiveness, making it suitable for ocular applications. In the tear environment of DED patients with high reactive oxygen species (ROS) content, the P-C_nPEG hydrogel degrades within 6 days through the breakage of crosslinking sites. The degradation solution of each day presents ultralow coefficients of friction (COFs) under ocular conditions through the hydration effect. Finally, the excellent biocompatibility of the hydrogel demonstrates its potential for ocular applications. This study systematically discusses the mechanism of sustainable degradation-induced superlubricity of P-C_nPEG hydrogels, introducing a novel and promising strategy for DED treatment.

The persistent economic and environmental challenges arising from friction-induced energy losses underscore the critical need for innovative lubrication technologies. Two-dimensional transition metal dichalcogenides (2D TMDs), characterized by their layered architecture and weak interlayer van der Waals (vdW) interactions, have emerged as promising nanolubricants due to their well-documented shear properties and ability to form low-friction tribofilms. However, practical applications of TMDs are hindered by inherent limitations, including insufficient load-bearing capacity and high sensitivity to environmental conditions. Accordingly, extensive research efforts have been directed toward the rational design and structural modification of TMD-based lubricants. This review outlines recent advances in TMD-based tribological systems, beginning with their structural characteristics and synthesis routes, followed by an in-depth discussion of lubrication mechanisms and key performance-influencing factors. This paper explores modulation strategies for TMD-based lubricants, from conventional methods to emerging approaches, along with their applications across diverse environments. Finally, the review identifies prevailing challenges and suggests promising research directions to guide the development of next-generation high-performance TMD-based lubricants.

Hydrostatic oil grooves in the friction pair are responsible for guiding, storing, and distributing lubricating oil, widely applied to ultra-high-power hydraulic motors of tunnel boring machines, aerospace variable pumps, and hydrostatic precision guideways/spindles of high-end industrial mother machines, etc. The traditional design methods for oil groove patterns highly rely on the designer's experience and size optimization of preset shapes, making it difficult to achieve optimal lubrication. For that, this study proposes the intelligent self-evolving design method of oil grooves, in which the AI-assisted generalized pattern search algorithm (GPS+AI) is designed to make an oil groove pattern self-evolve towards maximizing load-bearing capacity according to the friction pair’s contact force feedback from a lubrication model. The designed oil groove pattern is machined onto the piston of a hydraulic motor and is experimentally evaluated for its lubrication load-bearing capacity through the home-made quasi-actual roller-piston pair testing rig. Comparing two traditional oil grooves, the new oil groove can reduce the friction torque (contact force) by a maximum of 88%, which is very significant for improving efficiency and lifespan of ultra-high power hydraulic motors (power > 10⁶ W), especially under the dual-carbon target. 

This paper presents a NURBS-based isogeometric analysis framework for modeling both hard and soft elastohydrodynamic lubrication (EHL) contacts under the fully flooded condition. Unlike conventional approaches, the framework incorporates nonlinear solid deformation within a unified weak formulation and employs a mortar method to flexibly couple the fluid and solid domains with independent discretizations. Benchmark tests show excellent agreement with reference ANSYS FSI simulations while reducing the computational time by about 99% for both hard and soft EHL line contacts. The framework is further applied to a soft EHL point contact between a hyperelastic hemisphere and a rigid plane, confirming that nonlinear solid deformation strongly affects the film thickness and frictional response. Finally, the influence of surface roughness is investigated, revealing that transversely oriented topographies yield superior lubrication performance, as indicated by a higher transition load and a lower friction coefficient.

This study proposes a numerical methodology based on the application of first, second, and third-order derivatives to analyze the evolution of the coefficient of friction (CoF) obtained from ball-on-disc (BoD) wear tests. The approach aims to provide an objective and quantitative identification of mechanisms, wear stages, and transition points, overcoming the subjectivity commonly associated with conventional friction curve interpretation. Before derivative computation, the CoF signal was smoothed to reduce experimental noise while preserving the morphological features of the friction curve. The methodology was applied to a newly developed multicomponent Al80Mg10Si5Cu5 HPDC alloy tested under dry sliding at room temperature (RT). The derivative-based analysis enabled the identification of successive wear stages, from the initial settling and running-in to transient and quasi-stationary regimes, and the determination of characteristic transition points, correlated with wear mechanisms through surface and microstructural analyses. The results demonstrate that the proposed methodology enables an objective determination of the duration and sequence of wear stages, reveals that the transition to stable sliding does not coincide with the maximum CoF value, and improves the identification of highly dynamic early wear regimes that are often underestimated by visual analysis. Due to its low computational cost and reliance on signals commonly available in tribological systems, the proposed derivative-based methodology shows strong potential for real-time friction and wear monitoring, predictive maintenance, and the automation of tribological control systems, although further validation under industrial operating conditions is required.

Due to the outstanding tribological and wear properties at cryogenic temperatures, Diamond-Like Carbon (DLC) materials are widely used in fields such as deep space exploration and superconducting magnets. Wherein, the temperature dependent frictional behavior of DLC is expected to follow the conventional thermally activated process. In this article, the frictional properties of DLC are scrutinized in the temperature range of 300 to 100 K by reciprocally scanning a DLC coated atomic force microscopy (AFM) tip against a DLC substrate in ultra-high vacuum (UHV) conditions. The results reveal a remarkable monotonical temperature dependence of frictional behavior, which remains robust under varying normal loads and sliding velocities. Specially, the overall friction force raises as temperature decreases, with a distinct friction peak at T_max = 215 ± 10 K. While a logarithmic dependence of friction on velocity is observed at temperatures far from T_max, friction becomes nearly velocity-independent in the vicinity of T_max. This non-monotonically temperature dependence of friction beyond conventional thermally activated framework is well interpreted involving the formation/rupture of interfacial bonds. This work provides new insights into the interfacial bonding mechanisms affecting the tribological properties of DLC materials at cryogenic temperatures.

The Johnson-Kendall-Roberts (JKR) theory remains the most cited model of adhesive contact. It was demonstrated that the JKR theory can be substantially extended, allowing adhesive JKR-type contact problems to be solved through an explicit transformation of the corresponding non-adhesive Hertz-type load-displacement curve. This framework enables application of the extended JKR theory to non-classical scenarios where analytical non-adhesive solutions are unavailable, and therefore numerical methods can be employed. However, the transformation formulae involve the first and second derivatives of the load-displacement curve, posing challenges when applied to discrete numerical data. This study presents a straightforward and effective numerical approach that converts a numerically obtained data series of load – displacement – contact radius for a non-adhesive contact problem into the corresponding JKR-type adhesive solution. While any appropriate numerical method can be used to generate these data, the finite element method is employed here. The proposed approach is validated by comparing numerical results with established analytical solutions for adhesive contact problems involving an elastic half-space and a thin elastic layer bonded to a rigid substrate, as well as with experimental data. These comparisons demonstrate excellent agreement between the numerical and analytical solutions. It is argued that the proposed method offers significant potential for solving many important practical problems, e.g., adhesive contact analysis for coated or multi-layered media.