Search Results (1,530)

Ionic liquids (ILs) are molten organic salts consisting of organic cations and weakly coordinating organic/inorganic anions at room temperature. ILs have excellent physical and chemical properties such as high thermal stability, high combustible temperature, high miscibility with organic compounds and so on, making them good candidates for high performance lubricants and lubricant additives. The functional designability of ILs makes them novel lubrication materials that can break through the bottleneck of the active control of friction and lubrication. This paper firstly briefly introduces how to design the physical and chemical properties of the ILs required for different friction conditions by bonding specific cations with anions. Then, the lubrication mechanisms of ILs as base lubricants and additives for oils and water are focused on. The correlation between the structure of ILs and the lubrication results are established, which can guide the structural design of ILs in different applications. The response behaviors of friction characteristics under external electric fields are analyzed, which can provide a theoretical basis for the intelligent control of friction based on ILs. Full article

The importance of skid resistance performance assessment in pavement engineering and management is crucial due to its direct influence on road safety features. This paper provides a new approach to skid resistance predictive model definition based on experimentally obtained texture roughness parameters. The originally developed methodology is based on a photogrammetry technique for pavement surface data acquisition and analysis, named the Close-Range Orthogonal Photogrammetry (CROP) method. Texture roughness features were analyzed on pavement surface profiles extracted from surface 3D models, obtained by the CROP method. Selected non-standard roughness parameters were used as predictors in the skid resistance model. The predictive model was developed by the partial least squares (PLS) method as a feature engineering procedure in the regression analysis framework. The proposed model was compared to the simple linear regression model with a traditional texture parameter Mean Profile Depth as the predictor, showing better predictive strength when multiple non-standard texture parameters were used. Full article

Laser surface texturing has proven beneficial in improving tribological performance in different lubrication regimes. However, the interaction between plateau roughness and surface texture remains to be further investigated, even though rough surfaces are common in engineering applications. In the present study, we investigated the frictional influence of surface texturing of ground surfaces under different lubrication conditions. Channel textures with different depths and area ratios were fabricated on ground surfaces, and their friction was tested in reciprocating tests. The experimental findings indicate that the textures caused increased friction for ground surfaces under boundary or mixed lubrication when the interface is well lubricated. Nevertheless, when the oil supply was limited, an up to 40% friction reduction was observed under test conditions. Full article

Laser cladding is a new technology to fabricate a coating on the surface of a metal substrate. The properties on copper substrates are usually not very good due to the high thermal conductivity and reflectivity. The appropriate preheating temperature is helpful to fabricate coatings with good quality and properties, especially for copper substrates. In order to investigate the effect of different preheating temperatures, four coatings with different preheating temperatures (100, 200, 300 and 400 °C) were fabricated via a laser on a copper substrate. The microstructures and properties of four coatings were investigated using SEM, XRD, EDS, a Vickers microhardness meter, a wear tester and an electrochemical workstation. The results show that the elements from Ni-based alloy powder were uniformly distributed among the binding region, which obtained a good metallurgical bonding. The microstructure was mainly composited of cellular, dendrite and plane crystals, and the main reinforced phases were γ (Fe, Ni), Cr_0.09Fe_0.7Ni_0.21, WC and Ni₃B. The values of average microhardness of the four coatings were 614.3, 941.6, 668.1 and 663.1 HV_0.5, respectively. The wear rates of the four coatings were 9.7, 4.9, 12.5 and 13.3 × 10⁻⁵ mm³·N⁻¹·m⁻¹, respectively, which were less than that of the copper substrate (4.3 × 10−3 mm³·N⁻¹·m⁻¹). The decrease in wear rate was due to the existence of the reinforced phases, such as WC, Ni₃B, M₇C₃ (M=Fe, Cr) and Cr_0.09Fe_0.7Ni_0.21. The fine crystals in the coating preheated at 200 °C also improved the wear resistance. Additionally, the minimum values of corrosion current density were 3.26 × 10⁻⁵, 2.34 × 10⁻⁷, 4.02 × 10⁻⁶ and 4.21 × 10⁻⁶ mA·mm⁻², respectively. It can be seen that the coating preheated at 200 °C had higher microhardness, lower wear rates and better corrosion resistance due to the existence of reinforced phases and fine and uniform crystals. Full article

Friction behaviour is an important characteristic of dynamic seals. Surface texturing is an effective method to control the friction level without the need to change materials or lubricants. However, it is difficult to put the manual prediction of optimal friction reducing textures as a function of operating conditions into practice. Therefore, in this paper, we use machine learning techniques for the prediction of optimal texture parameters for friction optimisation. The application of pneumatic piston seals serves as an illustrative example to demonstrate the machine learning method and results. The analyses of this work are based on experimentally determined data of surface texture parameters, defined by the dimple diameter, distance, and depth. Furthermore friction data between the seal and the pneumatic cylinder are measured in different friction regimes from boundary over mixed up to hydrodynamic lubrication. A particular innovation of this work is the definition of a generalised method that guides the entire machine learning process from raw data acquisition to model prediction, without committing to only a few learning algorithms. A large number of 26 regression learning algorithms are used to build machine learning models through supervised learning to evaluate the suitability of different models in the specific application context. In order to select the best model, mathematical metrics and tribological relationships, like Stribeck curves, are applied and compared with each other. The resulting model is utilised in the subsequent friction optimisation step, in which optimal surface texture parameter combinations with the lowest friction coefficients are predicted over a defined interval of relative velocities. Finally, the friction behaviour is evaluated in the context of the model and optimal value combinations of the surface texture parameters are identified for different lubrication conditions. Full article

To conduct an in-depth investigation of the impact of various operating parameters on mulching device wear during the operation of full-film dual-row ridging and mulching machine mulching, this paper employed EDEM software to create a 3D discrete element model of how a mulching device interacts with the soil on the seed bed and simulated the dynamic process of the interaction between the mulching device and the soil during the mulching operation. We analyzed the cladding wear process between the cladding device and the cladding sand particles, and two areas of impact wear on the overburden conveyor housing and areas of wear on the chute deflector scratches were detected. A three-factor, three-level Box–Behnken experimental design approach was used, with mathematical modeling of the relationship between the scraper conveyor lifting line speed, seed bed cover, scraper spacing, and wear of the cover device, finding the optimal combination of operating parameters for mulching devices. The results of the simulation test indicated that the mulching device experienced a minimum wear of 0.958 × 10⁻³ mm at a lifting line speed of 0.7 m·s⁻¹ for the scraper conveyor, a mulching volume of 2.55 kg·s⁻¹ for the seed bed, and a scraper spacing of 98 mm. The results of the field trial validation showed that, in a comparison between simulated wear parts and a mulching operation prototype of the same two wear parts, the established discrete element model appeared reasonable concerning the structural parameters, with a feasible abrasion mechanism process of sand particles on the soil-covering devices, demonstrating the model’s reliability and validity. It can serve as a guide for optimizing the design of mechanized full-film dual-furrow seed bed mulching operation. Full article

A composite lubricating system that combines solid and liquid lubrication can create a synergistic effect by leveraging the strengths of both types of lubricants. Solid lubrication coatings possess advantageous load-bearing abilities and exhibit low volatility. By adopting this approach, the system retains the merits of solid lubrication while simultaneously harnessing the advantages of liquid lubrication. The unique properties of diamond-like carbon coatings (DLCs) offer the potential to create binding locations for lubricant additives by introducing dopant elements that have a high affinity with additives. In the present work, the combined use of europium-doped diamond-like carbon (Eu-doped DLC) with varying atomic concentrations of the dopant element (1.7 at. % and 2.4 at. %) and gadolinium-doped diamond-like carbon (Gd-doped DLC) with different atomic concentrations of the dopant element (1.7 at. % and 2.3 at. %) was studied alongside a pure DLC coating and the incorporation of an ionic liquid (IL) additive in a tribological block-on-ring system. The focus was on the 1-Ethyl-3-methylimidazolium diethylphosphate ionic liquid with a concentration of 1 wt. % in polyalphaolefin (PAO) 8. Among the investigated pairs, the coefficient of friction (CoF) of 1.7 at. % Eu-doped DLC coupled with the IL was the smallest in boundary, mixed, and elastohydrodynamic lubrication regimes. Quantification of wear was challenging due to minimal and localized wear on the DLC coating surfaces. The decrease in friction within the boundary lubrication regime underscores the promise of mechanical systems that integrate 1.7 atomic percent Europium-doped diamond-like carbon coatings with ionic liquids (IL). This study presents a compelling avenue for future scholarly exploration and research efforts focused on reducing friction and improving the efficiency of moving components, particularly in situations where tribological properties exert a substantial influence Full article

With decreasing clearance between the protrusion of a slider and a disk interface, there is a higher likelihood of contact occurring during shock or vibration experienced by hard disk drives (HDDs), which may induce lubricant depletion. Based on the molecular dynamics (MD) model of perfluoropolyether lubricant with a coarse-grained beads spring approach, we compared the slider configurations’ influence on the lubricant transfer volume quantitatively. By further investigating the parameters of the cylindrical asperities, including the width and depth, as well as considering the asperity amounts of the slider, we successfully observed the lubricant depletion process during slider and disk contact. The results demonstrate that the penetration depth was reduced as the asperity amount increased, mainly owing to the increased contact area between the surfaces. The decreasing depth of the asperity and the increasing width of the asperity helped to reduce the depletion volume. In addition, the utilization of a cylindrical slider configuration can contribute to a reduction in lubricant depletion resulting from contact between the head and disk. Full article

Due to the low viscosity of water, water-lubricated bearings are susceptible to significant wear and noise in demanding operating conditions. It has been demonstrated that a small quantity of secondary lubricating medium can improve the lubrication performance of water-lubricated contact surfaces and achieve the purpose of temporary risk aversion. As a further step, the feasibility of the proposed idea is experimentally validated on a water-lubricated bearing test bench. A numerical model that couples the N–S equation and the VOF model is then developed to investigate the behavior of the flow field lubricated by pure water and water with a small quantity of the secondary lubricating medium. This model provides the predictions of important quantities such as the load-carrying capacity, the secondary lubricating medium volume fraction and the contact pressure under different lubricated conditions. The results show that the secondary lubricating medium can enter into the contact region and improve the lubrication performance of water-lubricated bearings, especially at lower shaft rotational speeds. Therefore, the feasibility of our proposed idea is verified, which provides a promising approach to reduce the wear and friction of water-lubricated bearings when they encounter short-time severe working conditions. Full article

Metal seals play a crucial role in ensuring the dependable functioning of the bearing system in roller cone bits. Due to the intricate nature of downhole conditions, the microstructure design of sealing end faces, specifically the surface texture, is rarely used in metal seals. This study focuses on examining the applicability of surface texture technology in metal seals for cone bits to enhance the lubrication characteristics and friction and wear properties of liquid film between end faces. A multi-field coupling model of surface-textured metal seals was established and experimentally verified. The liquid film carrying the capacity and sealing performance of five different shapes of surface-textured end faces (circle, ellipse I (horizontal), ellipse II (vertical), triangle, and chevron) were investigated under varying rotational speeds and environmental pressures. The influences of texture parameters, including depth and area ratio, on the lubrication characteristics and friction reduction effects of surface-textured metal seals were investigated, and the microscopic wear morphology characteristics of the sealing end faces were analyzed. The results show that surface textures can effectively improve the liquid film state and comprehensive performance of metal seals. Specifically, triangle textures significantly enhance the hydrodynamic pressure effect and weaken the abrasive wear and adhesive wear of the end faces. However, when the environmental pressure is p ≥ 30 MPa, the surface textures gradually lose the advantages of dynamic lubrication but can still reduce friction. The proper texture depth and area ratio can achieve zero leakage (obtained theoretically) and minimal friction in metal seals. Full article

This study presents a theoretical and experimental analysis to quantify the power losses generated by an oil jet lubricated angular contact ball bearing. The analysis is conducted for a moderate speed range (N∙dm product less than ${10}^6$) and a limited applied load (<5% of the static capacity). The lubrication regime of each ball is studied through a theoretical model and varies from Iso-Viscous Rigid to Elasto-Hydrodynamic. Therefore, the hydrodynamic effects are considered in the power loss calculation. An experimental campaign is carried out and the influence of several parameters (applied load, oil injection temperature, speed, etc.) is studied. A good agreement is found between the developed model and the measurements. It is shown that the radial applied load has no influence on power losses, unlike speed and axial load. This can be explained by the load distribution and the hydrodynamic rolling contribution on the low loaded balls. Full article

Grease-lubricated rolling bearings transition from the churning phase to the channeling phase. This transition property affects grease life and torque properties. Therefore, the relationship between grease yield stress and grease degradation during operation, which affects this transition, has been investigated. However, there have been few studies on grease flow that affects the transition. In this study, the mechanism of grease reduction on the races was investigated for small bearings operated at low speeds, where thermal degradation and softening of the grease are less likely to occur. It was inferred that the grease transfer to the cage affects the channeling transition and that the amount of transfer varies depending on the initial grease viscosity. These findings can be applied to grease composition and cage design and are useful in providing bearings with excellent low-torque characteristics, such as in industrial motor applications. Full article

The use of synthesis gas (SYNGAS) from waste gasification has been pointed out as a key strategy to help the energy transition. However, SYNGAS’ low calorific power is considered a difficult obstacle to its technological use in internal combustion engines. To overcome this, a novel free-piston linear motor has been proposed to pave the way for the use of SYNGAS in the mobility sector. Surface texturing has vast potential to reduce friction losses in this system. This study utilizes a deterministic numerical model to investigate the mixed lubrication performance of a textured piston ring/cylinder liner conjunction in a free piston engine. The model considers the simultaneous solution of the lubrication and asperity contact problems at the roughness scale, including texturing features on the cylinder surface. The numerical model employs the Reynolds equation with mass-conserving cavitation to calculate the inter-asperity fluid pressure. The rough contact model utilizes the Hertz theory for elastic contact to calculate the contact pressure at each asperity between the piston liner surface and the admitted smooth and rigid ring surface. Surface texturing demonstrated remarkable effectiveness, particularly in the hydrodynamic lubrication regime, with a maximum friction reduction of 38.5% observed for an area coverage of 50%. This was accompanied by a notable shift in the transition from the boundary to the mixed lubrication regime. The textured surfaces exhibited consistent efficiency in reducing fluid pressure and shear stress as the coverage of the textured areas increased. The incorporation of dimples on these surfaces played a crucial role by augmenting the lubricant storage capacity while concurrently reducing the real shear and contact areas. This study offers valuable insights into the nuanced friction-reducing mechanisms of surface textures, illuminating their influence on the coefficient of friction and the formation of lubricant films across various lubrication regimes. Full article

An accurate power loss prediction in the gearbox is desirable for improving vehicle efficiency. To achieve this objective, evaluating the power loss is necessary. However, power loss is influenced by factors such as the gearbox structure, operating conditions, and gear oil formulation, making power loss evaluation a bottleneck in practice. Therefore, a systematic modeling methodology was developed to evaluate the gearbox power loss in an E-Axle that focuses on the influence of the gear oil factors in the load and no-load cases. The gearbox used in a light-duty truck E-Axle was tested to verify the proposed model. The test was performed under various operating speeds, input loads, and oil temperatures, and four types of gear oil with different formulations were also included to quantify their influence on the power loss. The results showed that the gearbox power loss was significantly influenced by the E-Axle operating conditions, oil temperatures, and different gear oil formulations, promoting different power losses. The comparison results showed good consistency between the predicted power loss and the measured data. The proposed methodology can be utilized to effectively predict the power loss of the E-Axle gearbox and further improve the E-Axle efficiency by selecting suitable oil formulations and adjusting oil temperatures. Full article

To improve the accuracy of gear fault diagnosis and overcome the low diagnostic accuracy of the model caused by manual parameter selection, a combined diagnostic model based on time-frequency fusion features is combined with the improved global search whale optimization algorithm (GSWOA) to optimize the fault diagnosis capability of the kernel extreme learning machine (KELM). First, the time-domain and frequency-domain features of the gear fault state are extracted separately, and feature vectors are constructed through feature fusion, which overcomes the limitations of single features. Second, the GSWOA based on three strategies is used to optimize the regularization coefficient C and kernel function parameter γ of KELM, and a GSWOA-KELM fault diagnosis model is built to avoid the problem of low fault diagnosis accuracy caused by the manual selection of KELM parameters. Finally, the public dataset from Southeast University is taken to verify the performance of the proposed model by comparing it with KELM, SSA-KELM, and WOA-KELM models. The experimental results demonstrate that the improved time-frequency fusion features-based GSWOA-KELM model shows faster convergence speed and stronger global search ability. Compared with KELM, SSA-KELM, and WOA-KELM models, the performance of the proposed model has been improved by 11.33%, 8.67%, and 1.33%, respectively. Full article