Surface Friction Research Articles

Mo2Ti2C3 and PTFE synergistically functionalized corrosion-resistant, thermally conductive, super abrasion-resistant epoxy resin composite coating

Epoxy resin (EP) matrix composites are a widely used polymer-based protective coating material. However, the low lubricity leads to frictional wear problems that make their large-scale development and application a serious challenge. Based on this, a multifunctional composite coating (MPT-EP) with low wear, high lubricity, high thermal conductivity, and corrosion resistance was prepared by introducing polytetrafluoroethylene (PTFE) and lamellar Mo2Ti2C3 as a composite lubricant into epoxy resin matrix using a simple solvent dispersion method. The results showed that the introduction of the composite lubricant resulted in enhanced hardness and mechanical properties of the composite coating. Compared with the single epoxy resin coating (0.31), the friction coefficient (COF) of the composite coating was only 0.22, and the friction surface did not show obvious abrasion marks. The surface temperature of the composite coating was up to 51.4 °C when it was placed on a hot bench at 60 °C for 60 s. In addition, the COF of the composite coating did not change significantly after being immersed in acid, alkali and salt solutions. Therefore, the Mo2Ti2C3-induced multifunctional epoxy resin matrix composites have important application potential and research value in the field of ultra-wear-resistant and high lubrication protective coatings.

The vertical loading tests of single and group piles by centrifuge modelling

ABSTRACT Pile foundations are widely used for tall buildings, but determining their capacity and behavior under load often involves expensive and lengthy field tests or imprecise numerical models. This research employed a centrifuge to perform vertical loading tests on single and grouped piles in dry sand, subjected to 100 times gravitational acceleration, to investigate pile capacity and load transfer mechanisms. The results from centrifuge modeling, numerical simulations, and field tests were consistent. The total pile capacity for a single pile was 5800 kN/m², while short and long pile groups had capacities of 6800 kN/m² and 9200 kN/m², respectively. End-bearing accounted for 40% of the capacity in single and short pile groups, and 13% in long pile groups. Surface friction was 95 kN/m² for single piles and 140 kN/m² for grouped piles. A method for estimating total pile capacity based on soil properties showed good agreement with empirical results.

INFLUENCE OF GRAPHITED DUST ON THE ABRASION PROCESSES OF COMPOSITE MATERIAL BASED ON POLYTETRAFLUOROETHYLENE

Purpose. Study of the influence of graphitized dust on abrasive wear of polytetrafluoroethylene-based composites. Research methods. Experimental studies were performed using modern methods of physical and mechanical tests, which ensures the reliability of the results. A laboratory mixer with a rotating electromagnetic field and a hydraulic table press TU 10003 TORIN were used for the production of samples. Weighing of samples for experiments was carried out on a VLR-200 scale, abrasion assessment was carried out on a HECKERT machine. The friction surfaces were studied using a BIOLAM-M microscope. Results. The conducted studies showed that the index of abrasive wear of the composite with a polytetrafluoroethylene matrix decreases from 2.974 mm3/m to 2.539 mm3/m with a content of 10 % of graphitized dust. This helps to increase the service life of parts, which will reduce the frequency of their replacement, as well as reduce production costs. Given that graphitized dust is a waste of metallurgical production, its secondary use as a filler for composite materials allows to partially solve the environmental problem of disposal of production waste. Scientific novelty. Today, the production of products from composite materials is one of the promising directions of production, because the combination of a polymer matrix with various fillers makes it possible to obtain more economically profitable materials, forming the necessary physical properties. The possibility of using production waste as a filler allows solving the current problem of recycling and disposal of environmentally harmful substances. Therefore, the conducted research opens up new ways to solve a complex of environmental and economic problems. Practical value. The obtained results are important in the further process of manufacturing composite materials. The ability to increase the resistance of the material to abrasive abrasion allows the production of parts that work in friction conditions.

Friction and Wear Mathematical Modeling and Optimization Design of Surface Microstructure Parameters of Unfolding Wheel based on Experiment and Numerical Simulation

Objective: In order to improve the friction-increasing and wear-reducing performance of the unfolding wheel surface, the surface microstructure of the unfolding wheel used in the detection of 8 kinds of steel balls was optimized by parameter matching. Method: Firstly, based on Hertz's theory, the contact area between steel balls of different sizes and the unfolding wheel are analyzed. The wear depth model is established based on Archard adhesive wear model. Secondly, the appropriate microstructure parameters for friction and wear experiments were selected. The finite element analysis software is used to simulate the stress on the surface of the microstructure unfolding wheel and calculate the wear depth. According to the experimental results, the relationship between friction coefficient, wear depth and microstructure parameters is obtained by data fitting, and the objective function of optimization design is established. Finally, based on the genetic algorithm DNSGA-II and Python, the parameters are optimized, and the optimal solution is obtained by using the TOPSIS method. Results: The feasibility of the simulation method is verified by friction and wear experiments, and the correctness of the optimization method is verified. Some existing patents on friction and wear of microstructure surfaces are introduced, and the future development of this field is prospected Conclusion: The research shows that the optimal parameters matching of microstructure for steel ball diameters of Ф16.6688 mm~Ф22.2250 mm: the shape is rhombus; the area of a single pit is close to the contact area, which is 0.0319 mm2 ~ 0.0554 mm2; the pit depth is 145 μm~150 μm, and the surface density of microstructure is (5.4~5.6) /mm2.

Transferable machine learning model for the aerodynamic prediction of swept wings

With their development, machine learning models can be used instead of computational fluid dynamics simulations to predict flow fields in aerodynamic optimization. However, it is difficult to construct a prediction model for swept wings with various planform geometries because too many samples are required to cover the parameter space. In the present paper, a new model framework is proposed to predict wing surface pressure and friction distributions with fewer samples. The distributed geometry parameters along spanwise are used as model inputs instead of the global planform parameters, and processors are designed to help the model better learn the local effect of geometric variation. The model is trained and tested on simple swept wings with single segment and linear twist distribution, where it outperforms the global input model by 57.6% in terms of lift coefficient prediction errors on small dataset sizes. The distributed input also enables the model to be transferred from single wings to more engineering-practical yet complex kink wings. After fine-tuning with a few samples, model accuracy for kink wings can be similar to that of simple wings, which proves the model for wings with complex planform geometries can be efficiently built with the proposed method.

Microstructural transformation impact on mechanical and tribological performance of different temperature heat-treated carbon/carbon composites

Due to the harsher application environments of C/C composites, optimizing the internal structure of C/C materials through high-temperature treatments (HTT), specifically above 2300 °C, has become an effective method to enhance their properties. The current study investigates the influence of microstructural evolution on the mechanical and tribological behavior of carbon/carbon composites after heat treatments at 2300 °C and 2700 °C. The C/C composites experience a reduction in mechanical properties as the heat treatment temperature is raised. This may be due to the rearrangement of carbon atomic layers at high temperatures, resulting in increased orientation in pyrolytic carbon. However, fibers parallel to the friction surface are relatively less affected, while fibers perpendicular to the friction surface and PyC are more significantly affected. The average coefficient of friction increases from 0.19 to 0.42 as heat treatment temperature from 2300 °C to 2700 °C under the brake pressure of 1 MPa with 25 m/s brake speeds. This phenomenon is attributed to the samples with high graphitization degree (2700 °C) producing a large number of flaky chips under shear stress during friction, which can be easily ground and compacted to form a complete friction film. Additionally, the more easily deformable z-axis fiber asperities increase the contact area, resulting in an increase in the coefficient of friction and friction stability.

Laser cladding Ni60 @ WC/ Cu encapsulated rough MoS2 self-lubricating wear resistant composite coating and ultrasound-assisted optimization

This research aims to broaden the scope of self-lubricating wear-resistant coatings for applications in diverse industries such as automotive, metallurgy, power, and aerospace. Employing laser cladding technology, we successfully fabricated high-performance self-lubricating ceramic composite coatings. A comprehensive investigation was conducted to understand the inhibitory effect of Cu on the thermal decomposition of MoS2, and the study systematically explored the relationship between powder composition, coating structure, and organizational properties. The mechanisms behind friction reduction and wear resistance were unveiled, shedding light on the formation of the MoS2 self-lubricating protective film. Research findings reveal that during the laser cladding process, Cu and Ni undergo solid solution, resulting in the formation of the Cu–Ni alloy phase and crystal refinement. The MoS2 aggregation area exhibits a fine dendritic structure, while the dispersion area showcases coarse dendritic and cellular crystals. The addition of Cu and MoS2 influences the content of the MxCy phase and the thermal decomposition of MoS2. The incorporation of Cu increases the average coating hardness, whereas MoS2 addition decreases it; nevertheless, the Cu/MoS2 coating hardness is enhanced by at least 6.4 %. Cu significantly improves the coating's wear resistance, with a relatively smaller impact on friction reduction. MoS2 functions as a friction-reducing phase during wear, effectively preventing the peeling of hard phases and reducing the friction coefficient. Cu is uniformly distributed in the coating, experiencing solid solution strengthening, reducing adhesive region areas, and minimizing wear debris generation. MoS2, although unevenly distributed, forms intermittent lubricating films on the surface. The lubricating film of the Cu/MoS2 coating remains stable, preventing mutual contact of the friction surface and concurrently reducing the friction coefficient and wear amount. While the study successfully prepared a self-lubricating ceramic coating with excellent wear resistance, some surface quality defects persist. Further optimization of the preparation method was achieved through ultrasound-assisted technology.

Wind direction and speed calculation model with deep learning

Abstract In view of the problems of complex process and weak representation in regular atmospheric wind field detection, this paper adopts deep learning method, uses global high-altitude meteorological detection data, and establishes a deep learning model for calculating wind direction and speed with different altitudes and temperatures by using keras software package. The model is verified by using third-party independent sounding data from a meteorological observatory in Shanghai. The calculation accuracy of the model above 2000 m is 0.9830 and the value of loss function is 0.0482. The accuracy under 2000 m is 0.9164 and the value of loss function is 0.0377. There are significant differences in the performance of the model between under 2000 meters and above 2000 meters due to surface friction. The model shows that wind direction and speed of different height layers can be calculated by using only height and temperature at the same height. This model can also be used to check whether the quality of regular wind detection work is good or not with big old data.

Controlling the Surface Friction of Rotating Rods by Laser Surface Engraving

Controlling the Surface Friction of Rotating Rods by Laser Surface Engraving

Aerodynamic performance optimization of a UAV's airfoil at low-Reynolds number and transonic flow under the Martian carbon dioxide atmosphere

Unmanned aerial vehicles (UAV) on Mars operate in a thin atmosphere of carbon dioxide, where the flow Reynolds number and local sound velocity are significantly reduced compared to the Earth's atmosphere because of low gas density and temperature. Therefore, a Mars UAV with a rotary-wing design can operate in a state of low-Reynolds number (Re = 1-5 × 104) and transonic flow (Matip = 0.7–1.2), where flow separation and shock waves occur simultaneously. The interaction between flow separation and shock waves not only makes the entire flow field more complex but also seriously affects the aerodynamic performance of the airfoil, thereby reducing the payload of UAVs, which previous aircraft designs based on the thick atmospheric environment of the Earth have not considered. Therefore, in this study, a numerical simulation method is used to conduct airfoil optimization research on a characteristic airfoil under low-Reynolds number transonic flow (Re = 33200, Ma = 0.85) conditions to acquire additional insight, improve aerodynamic performance of the airfoil, and enhance the payload. The results were compared with the optimization results of subsonic flow (Re = 19500, Ma = 0.50). The Hicks-Henne bump functions method was selected for airfoil parameterization, and non-dominated sorting genetic algorithms (NSGA)-Ⅱ were used for optimization. Through an analysis of the pressure coefficient (Cp), surface friction coefficient (Cf), and density gradient, the number and intensity of oblique shock waves on the upper and lower surfaces were observed to significantly affect the aerodynamic performance of airfoils under low-Reynolds number flow. The changes in flow separation and transition positions do not directly affect the aerodynamic performance but weaken the oblique shock wave intensity induced by the separation point or directly transform strong shock waves into weaker compression waves because of the absence of flow separation. The optimization results for both subsonic and transonic flow point to a thinner overall shape with a flatter surface with the drag greatly reduced due to the disappearance of shock waves on the lower surface, which significantly improves aerodynamic performance. Compared with the original airfoil, at Ma = 0.85, this design can increase the lift coefficient (Cl) by at least 124 % and lift drag ratio (Cl/Cd) by 177 %.

Enhanced prediction of thermomechanical systems using machine learning, PCA, and finite element simulation

This research paper presents a comprehensive methodology for analyzing wet clutches, focusing on their intricate thermomechanical behavior. The study combines advanced encoding techniques, such as Principal Component Analysis (PCA), with metamodeling, to efficiently predict pressure and temperature distributions on friction surfaces. By parametrically varying input parameters and utilizing Finite Element Method (FEM) simulations, we generate a dataset comprising 200 simulations, divided into training and testing sets. Our findings indicate that PCA encoding effectively reduces data dimensionality while preserving essential information. Notably, the study reveals that only a few PCA components are required for accurate encoding: two components for temperature distribution and pressure, and three components for heat flux density. We compare various metamodeling techniques, including Linear Regression, Decision Trees, Random Forest, Support Vector Regression, Gaussian Processes, and Neural Networks. The results underscore the varying performance of these techniques, with Random Forest excelling in mechanical metamodeling and Neural Networks demonstrating superiority in thermal metamodeling.

Kansei Drives Sustainable Material Innovation—An Approach to Enhance the Added Value of Biomass Materials

Abstract: In this study, we discovered that the physical composition of materials can significantly affect users’ psychological and physiological responses. Materials research constantly offers novel materials as better alternatives to convention. However, the functionality of a material no longer ensures its commercial success and widespread use. Additionally, the material should provide significant added value beyond its practical evaluation. Kansei, a concept derived from the Japanese language, pertains to the psychological perception of a product’s functionality and has attracted considerable attention in both industry and academia. This study proposes a Kansei-driven sustainable material method to enhance materials’ added value. We quantified users’ Kansei of tea waste materials via experiments. Specifically, we first measured the physical qualities of the materials, such as their color, surface roughness, and odor index. Next, we used semantic differential and pairwise comparison methods to measure users’ impressions and preferences toward the materials. We also employed wearable physiological measurement devices to capture users’ reactions to the materials, including the skin conductance level (SCL) and heart rate (HR). Finally, we conducted correlation analysis using the Statistical Package for the Social Sciences (SPSS) on the collected physical, psychological, and physiological data. This study found strong correlations between the materials’ frictional coefficients and surface roughness and people’s psychological evaluations, such as sensory and safety factors. In addition, we also found that these physical qualities affect people’s HR and SCL, leading to changes in people’s emotions. These findings carry significant implications for enhancing the added value of materials.

The effect of friction block hole configurations on the brake tribological performance of high-speed trains

Three triangular friction block configurations are commonly employed in high-speed train brake systems, namely, unperforated, perforated configuration with one circular hole, and perforated with three circular holes. In this study, we adopted these friction block types to investigate the effect of perforated friction block configurations on the brake performance of high-speed trains based on a self-developed brake test rig. The results indicate the significant impact of the number of the holes on the wear behavior, temperature distribution, and vibration characteristics of the brake interface. The friction surface of the unperforated block is covered by wear debris, while the perforated blocks produce less wear debris. Furthermore, the one-hole block exhibits a more uniform temperature distribution and better vibration behavior than that with three holes. The friction brake is a dynamic process, during which separation and attachment between the pad and disc alternatively occur, and the perforated structure on the friction block can both trap and expel the wear debris.

IMPACT OF LOADS ON LOCOMOTIVE MOTOR AXLE BEARINGS ON THE CONDITIONS OF FORMATION OF OIL FILM ON FRICTION SURFACES

During the active operation of locomotives, a significant portion of failures (up to 20 %) is attributed to the malfunction of motor-axial bearings. This is due to the imperfection of the lubrication system of the motor-axial bearings, the proper functioning of which largely depends on various factors such as climatic conditions, the level of wear of lubricating oil, and lubrication devices, among others. There is a need to improve the existing lubrication systems for motor-axial sliding bearings. One of the methods to address this issue involves examining the factors influencing the lubrication process of the friction surfaces of motor-axial bearings and the conditions of lubricant material supply. The article provides calculations of the loading forces on the motor-axial bearings, their action vectors, and analyzes the impact of these parameters on the ability to form an oil film on the friction surfaces of motor-axial bearings. To determine the magnitude of the load, technical specifications of the locomotive were used, and the relationship between power usage and locomotive speed was analyzed. The study involved an analysis of recent publications regarding the generation of contact pressure force between the contact surfaces of friction pairs, the magnitude of which exceeds permissible limits, considered one of the primary factors leading to bearing failure. Additionally, the existing bearing lubrication system used on the locomotive was analyzed, its shortcomings were identified, and methods for addressing these issues were discussed. The calculations were performed for the 2TE116 locomotive with traction electric motors ED-118B, based on the operational characteristics of the locomotive in the speed range of 0-80 km/h.

Numerical simulation of Darcy–Brinkman oscillatory flow of dissipative fluid: Utilization of finite difference method

This study investigates viscous flow behavior in a Darcy–Brinkman porous medium, considering the effects of porous dissipation and frictional heating. The fluid is flowing over a flat plate, oscillating in its plane. The velocity and temperature profiles are simulated using a mathematical model that includes linear convection and considers the effects of porous and viscous dissipation. After performing mathematical transformations, the governing equations are modified into coupled and nonlinear dimensionless PDEs. The forward time centered space method numerically solves the modeled dimensionless equations. The acquired results are explicitly validated against the findings of the literature in a situation where limits are considered. The numerical results are presented graphically, providing a comprehensive analysis of the variables impacting fluid characteristics, including temperature and velocity. Interestingly, this work shows that a rise in the porosity parameter causes temperature profiles to rise and velocity to decrease. Moreover, a drop in velocity is linked to a rise in the Prandtl number. Furthermore, the influence of surface friction is diminished by including the porosity parameter. Moreover, a rise in the heat transmission rate at the surface can be observed.

Fluorine-free Superhydrophobic Stearic Acid Modified Kaolin Nanoparticles for Self-cleaning Silicone Rubber Surface

This study introduces fluorine-free nanoparticles to innovate superhydrophobic surfaces for self-cleaning applications, addressing environmental concerns linked to fluorine-based compounds. The method involves modifying kaolin nanoparticles with stearic acid and integrating them into silicone. The surface of stearic acid-kaolin nanoparticles exhibits a contact angle of 149.4° ± 3.3, while the resulting composite film exhibits a contact angle of 113.9° ± 5.8. The surface roughness of the silicone rubber surfaces increases proportionally with higher concentrations of stearic acid-modified kaolin nanoparticles. Field Emission Scanning Electron Microscopy (FESEM) analysis demonstrates the successful coverage of kaolin nanoparticles-stearic acid on resulting film. Self-cleaning performance is evaluated by simulating the deposition of graphite powder onto the surfaces and subsequently observing the behaviour when water is dropped on them revealing their remarkable self-cleaning properties.

Tribological Properties of Nano-Scale Al2O3 Particles with Different Shapes as Lubricating Oil Additives

Enhancing lubrication across various tribological systems in the maritime industry is essential for improving safety, efficiency, and environmental sustainability. Al2O3 nanoparticles, employed as additives in lubricating oils, demonstrate favorable tribological properties including anti-wear and anti-friction characteristics. In this work, nano-scale γ-Al2O3 particles with different shapes, i.e., nanosheet, nanorod, nanosphere, and irregular-shaped nanoparticles, were prepared and calcinated forming the same crystalline phase with nanoscale size, which dispersed well in lubricating oil. The tribological properties of Al2O3 nanoparticles as lubricating oil additives were examined using block-on-ring wear tests, and the effects of the particle shape and particle concentration were investigated. The results indicated that the frictional properties are largely influenced by the particle shape and the concentration of the Al2O3 additives, with the optimal concentration being around 0.1 wt% for each shape. The lubricating oil with nanosheet additives presented the best tribological performance, followed by those with nanorod, nanosphere, and irregular-shaped Al2O3 nanoparticle additives. Al2O3 nanosheets as the lubricating oil additives reduced the stress effect on the friction surface because of their larger bearing area and are inter-particle-sheared during sliding due to the movement of friction pairs, which can further improve the tribological properties compared to other shapes.

In-situ surface modified water-soluble Cu nanoparticles as lubrication additives in water-based cutting fluids

Water-based lubricants are essential in the field of tribology, and the application of nanoparticles as additives in water-based lubricants shows promise and significant practical importance. In this study, water-soluble Cu nanoparticles modified with methoxypolyethyleneglycol xanthate long-chain polymers were fabricated by a in-situ surface modification method. The tribological behavior of the Cu nanoparticles synthesized as additives in a water-PEG system was evaluated using a universal micro-tribotester. It was found that the synthesized nanoparticles could be stably dispersed in the water-PEG system and could enhance the tribological properties and load-carrying capacity of the system significantly. For example, the coefficient of friction could be reduced to 0.052, and the PB value increased to 588 N when the Cu nanoparticles were added at a mass fraction of 1.5 %. This was mainly attributed to the formation of a boundary lubrication film consisting of Cu, Fe2O3, Fe2(SO4)3, and FeS throughout the entire friction process. The boundary film effectively prevents direct contact between the friction surfaces, thereby improving the tribological properties. The incorporation of Cu nanoparticles as additives into commercial cutting fluids resulted in a lower coefficient of friction and significantly enhanced the extreme pressure performance of the cutting fluids, demonstrating promising application prospects.

High temperature/low speed sliding wear behavior of Ni-Cr-W matrix composites against IC10 pin

Ni-Cr-W matrix cermet composites were prepared using powder metallurgical technology, and their microstructures, phase compositions, and mechanical properties were determined. Specifically, the tribological performances of the Ni-Cr-W composites were evaluated at a speed of 0.5 mm/s from room temperature to 800 °C, and their friction-reducing mechanism was clarified. The results showed that the NiCrW/Al2O3/Ag composite had the highest mechanical strength, with a 94.5 % increase in tensile strength compared to NiCrW/Al2O3. The NiCrW/Al2O3/SrCO3 composite exhibited the best high-temperature tribological performance because the chemical reaction on the friction surface generated new lubricating phases consisting of NiO, WO2, WO3, and Sr2CrO4. These acted synergistically lubricate and anti-wear with the Al2O3, Cr2O3, and NiCr2O4, and formed a continuous glaze layer on the wear surface. Furthermore, the multiple roles of nano-alumina in the obtained composite and its service in friction were discussed.

Synergistic Effects of Graphene-added Lubricants and Surface Micro-texturing on the Tribological Behavior of Thrust Roller Bearings

The synergistic effects of graphene additive and surface micro-texturing on the friction and wear properties of rolling bearings are still a research gap. To this end, the tribological behavior of dimples textured thrust roller bearings (81107TN) are investigated under starved lubrication. The lubricants contained different mass fractions (0.06 %, 0.10 % and 0.14 %) of graphene. The evenly distributed dimples (diameter: 60 µm or 250 µm; depth: 1 µm or 8 µm) were manufactured only on the raceways of the shaft washers. By comparing the coefficients of friction (COF), wear losses and worn surfaces, the influence of various dimples dimensions and mass fractions of graphene on the tribological behavior of rolling bearings is discussed. The results show that appropriate dimple parameters and a suitable mass fraction of graphene can synergistically have a positive effect on the tribological properties of bearings. In this work, the textured group, with a dimple-diameter of 60 µm and a dimple-depth of 1 µm, can provide the best comprehensive friction-reducing and wear-reducing performance for the mass fraction of graphene with 0.10 wt%. Compared to the smooth bearings lubricated with base oil, its mean COF is reduced by 31 % and its wear loss by 35 %. This work can be a valuable reference for the improvement of rolling bearings and lubricants.