Maximum Friction Coefficient Research Articles

Structure analysis of friction layer of copper matrix composites reinforced by composite ceramic (TiC-B4C) powder

To alleviate the issues of matrix softening and excessive wear faced by copper-based composites matched with C/C–SiC disc during high-speed braking, the research was conducted to investigate the impact of composite ceramic (TiC–B4C, TB) powder on copper matrix composites prepared through conventional powder metallurgy method. TiC–B4C powder was produced using the high-energy ball milling method, and a suitable milling time (48 h) was established to obtain the maximum disorder degree. The results revealed that TB2 (6% TB) had the highest densification and the best mechanical and thermal performance, as compared to other composites. However, there were differences in tribological properties, with TB4 (10% TB) achieving the maximum friction coefficient, while TB2 (6% TB) exhibited more stable friction performance. As the TB powder content increased, larger tribo-films were formed on the worn surface. However, the influence of TB powder content (less than 10% TB) on friction performance was mainly due to mechanical strength and structural tightness, rather than the formation of tribo-films. The friction layer consisted of three parts: the top nanostructure layer composed of nanoparticles (C, Cu, Fe, B, O, and Ti), the middle tribo-film composed of graphite and B2O3, and the lower elastic deformation zone.

Study on the shear-slip process and characteristics of fracture in shale

To clarify the shear-slip process and characteristics of fault, we conducted triaxial shear tests driven by displacement on shale samples with prefabricated sawcut and natural fractures, and the acoustic emission (AE) technology was used to monitor the shear-slip process in real-time. According to the test results, the shear-slip process and mechanical characteristics of sawcut and natural fractures were analyzed. The test results indicate that the shear-slip process of fractures can be divided into four stages, improving the confining pressure will cause more serious plastic failure in the shear-slip process, and the increase of roughness will make the phenomenon of “stress drop” more obvious, which is closely related to the earthquake occurrence. Confining pressure and roughness all have implications for the stress thresholds of each stage. With the transition of shear-slip stages, the effects of confining pressure and roughness on the shear-slip of fractures are more drastic. The maximum static friction coefficient μ0 increases with initial roughness increasing and is independent of confining pressure. Due to the strain-strengthening effect of fracture slip, the average value of dynamic friction coefficient μd under simple shear deformation is greater than the maximum static friction coefficient μ0. Based on AE response characteristics, microcracks development, and rupture scale during the shear-slip process were also explored. AE events are mainly distributed along the inclined fracture. The AE response in different shear-slip stages displays pronounced differences, and the AE evolution and macro mechanical characteristics of fractures show significant time-synchronization. The variation of peak frequency can reflect the rupture scale transformation and the influence of confining pressure and roughness. Additionally, the differences in the morphological evolution of sawcut and natural fractures are mainly reflected in the wear pattern, degree and the rock debris attach amount. Finally, we also discussed the micro-deformation mechanism of asperities during the shear-slip process. This work may provide a reference for the research of fault activation and slip in shale reservoirs.

Einfluss der Stillstandszeit auf das Losreißmoment nasslaufender Lamellenkupplungen

Detailed knowledge of the influences on the frictional behavior is crucial for reliable operation of safety-relevant, wet-running multi-plate clutches. The breakaway torque is of particular interest for safety-critical applications such as safety brakes and clutches. While influences of the tribological system by variation of friction partners, lubricant and operating conditions are usually the focus of current investigations, the influence of the time of standstill between a preceding tribological load and a subsequent breakaway of the wet disk clutch is not considered. To determine this influence, experimental investigations are carried out on a component test rig. For this purpose, the time of standstill of the clutch is systematically varied after preceding load shifts and the clutch is then broken away. During these investigations, it is shown that the downtime of multi-plate clutches with sinter friction lining has considerable influence on the frictional behavior in the first switching operations after actuation. An influence can already be clearly seen at a standstill time of approximately 15 minutes. An increase in the maximum friction coefficient occurring at the start of the slip switching operation compared with subsequent slip switching operations was observed, which can be attributed to the downtime after a defined preload. Influences of the disk temperature are considered by measuring the outer disk temperature. The influence is attributed to the change of the boundary layer during the standstill. The results provide a contribution to the transferability of investigations of the friction behavior of component test rigs to real applications in which the friction system is exposed to relevant times of standstill and expand the existing knowledge base on test methods.

Effect of Chamfer Form and Parameters on the Characteristics of Finite Length Journal Bearing under Impact Load

Journal bearings in typical applications are subjected to misalignment due to several causes, such as shaft deformation under load and errors related to the installation and manufacturing processes. Misalignment has well-known severe negative consequences on the performance of the bearings. This paper deals with the bearing chamfer to reduce these consequences of misalignment, and two forms of bearing edge modification are considered in the analysis. These forms are linear and curved chamfering of the bearing edges, where the height of the chamfer in the circumferential direction and the length of the modification in the longitudinal direction are considered as geometrical design parameters. The investigation includes a numerical solution of the hydrodynamic lubrication problem of finite length journal bearing, considering 3D misalignment cases using the finite difference method. This includes the assessment of the chamfer forms and their effects on the bearing performance in terms of the main bearing design parameters. Furthermore, the stability of the chamfered bearings is also investigated under impact load. Results showed that both chamfer forms are beneficial for a certain limit of the design parameters in reducing the maximum pressure and coefficient of friction and in elevating the film thickness levels, extending the range of misalignment in which the journal bearing can operate safely. In addition, the chamfered bearings in both forms showed more stability range in terms of the critical speed and shaft center trajectories under impact load. The bearings with the curved chamfer, where the slope is continuous at the start of modification, showed more uniform film thickness levels, and their shaft center trajectories were closer to the perfectly aligned bearing in the stable operating range of the system.

Insight into Unsteady Separated Stagnation Point Flow of Hybrid Nanofluids Subjected to an Electro-Magnetohydrodynamics Riga Plate

The main objective of this work is to analyze and compare the numerical solutions of an unsteady separated stagnation point flow due to a Riga plate using copper–alumina/water and graphene–alumina/water hybrid nanofluids. The Riga plate generates electro-magnetohydrodynamics (EMHD) which is expected to delay the boundary layer separation. The flow and energy equations are mathematically developed based on the boundary layer assumptions. These equations are then simplified with the aid of the similarity variables. The numerical results are generated by the bvp4c function and then presented in graphs and tables. The limitation of this model is the use of a Riga plate as the testing surface and water as the base fluid. The results may differ if another wall surfaces or base fluids are considered. Another limitation is the Takabi and Salehi’s correlation of hybrid nanofluid is used for the computational part. The findings reveal that dual solutions exist where the first solution is stable using the validation from stability analysis. Graphene–alumina/water has the maximum skin friction coefficient while copper–alumina/water has the maximum thermal coefficient for larger acceleration parameter. Besides, the single nanofluids (copper–water, graphene–water and alumina–water) are also tested and compared with the hybrid nanofluids. Surprisingly, graphene–water has the maximum skin friction coefficient while alumina–water has the maximum heat transfer rate. The findings are only conclusive and limited to the comparison between graphene–alumina and copper–alumina with water base fluid. The result may differ if another base fluid is used. Hence, future study is necessary to investigate the thermal progress of these hybrid nanofluids.

Friction and Road Condition Estimation using Bayesian Networks

Knowledge about the maximum tire-road friction potential is an important factor to ensure the driving stability and traffic safety of the vehicle. Many authors proposed systems that either measure friction related parameters or estimate the friction coefficient directly via a mathematical model. However these systems can be negatively impacted by environmental factors or require a sufficient level of excitation in the form of tire slip, which is often too low under practical conditions. Therefore, this work investigates, if a more robust estimation can be achieved by fusing the information of multiple systems using a Bayesian network, which models the statistical relationship between the sensors and the maximum friction coefficient. First, the Bayesian network is evaluated over its entire domain to compare the inference process to all possible road conditions. After that, the algorithm is applied to data from a test vehicle to demonstrate the performance under real conditions.

Determination of engineering properties of selected animal feed and fodder materials

The traditional ways of handling feed and fodder in a commercial dairy farm are labour intensive, tiresome and also leads to huge expenses as labour charges. Therefore, there is a need of mechanised feed and fodder distribution unit in order to reduce the human drudgery and other expenses. Thus, an attempt was made to determine the engineering properties (moisture content, bulk density, angle of repose and coefficient of internal friction) of feed which would be affecting the design of a mechanised feed and fodder unit. Three feed materials viz., oat green, wheat straw and concentrate mixture were selected for study. The angle of repose varied from 24.78±0.34 to 37.79±0.76°,the coefficient of friction from 0.187±0.024 to 2.628±1.612depending on the moisture content and the bulk density of the selected materials. The coefficient of external friction was determined for different fabrication materials including wooden/ply board, galvanized iron, aluminium, mild steel and stainless steel and the maximum coefficient of external friction was offered to the feed materials by ply board followed by mild steel.

INTERFACIAL BOND STRENGTH BETWEEN MICRO-SYNTHETIC FIBER-REINFORCED PATCH REPAIR MORTAR AND CONCRETE SUBSTRATE BASED ON PUSH-OFF TEST

A micro synthetic fiber-reinforced mortar has been developed as a patch repair material. The bond strength of this material is a crucial parameter for successful repair applications. The state of stress occurring at the interfacial plane between the repair material and the concrete substrate influences the bond strength requirements of patch repair material. Therefore, bond strength envelope criteria should be established using, among others, the interfacial adhesion and friction coefficient parameters. This research aims to determine the composite’s interfacial bond strength parameters (adhesion and friction coefficient) between micro-synthetic fiber-reinforced patch repair mortar (MSFRPRM) and concrete substrate by push-off tests. At this stage, the smooth joint texture limits the investigation. The fiber volume fraction and age of repair are considered. The tests were conducted at the age of 1, 3, 7, and 28 days. In addition to the laboratory experiment, this research used ATENA Science GiD to numerically simulate the push-off test and study the influence of the fiber volume on the adhesion and friction coefficient. The results show that at a fiber volume of 0.06%, the adhesion and friction coefficients increase from 1.15 to 2.33 MPa and 0.74 to 0.85, respectively, corresponding to age. Numerical simulation indicates that the maximum adhesion and friction coefficient occurs at the fiber volume fraction of 0.06%. Thus, the overall simulation results can be used in the future as a parameter to establish MSFRPRM and concrete substrate bond strength envelopes that will be useful for evaluating the suitability of MSFRPRM as repair materials under various states of stress. Keywords: Bond Strength, Concrete Patch Repair, Concrete Substrate, Micro-Synthetic Fiber-Reinforced Repair Mortar, Push-Off Test DOI： https://doi.org/10.35741/issn.0258-2724.58.1.20

Neural Network based Tire-Road Friction Estimation Using Experimental Data

Knowledge of the maximum friction coefficient µmax between tire and road is necessary for implementing autonomous driving. As this coefficient cannot be measured via existing serial vehicle sensors, µmax estimation is a challenging field in modern automotive research. In particular, model-based approaches are applied, which are limited in the estimation accuracy by the physical vehicle model. Therefore, this paper presents a data-based µmax estimation using serial vehicle sensors. For this purpose, recurrent artificial neural networks are trained, validated, and tested based on driving maneuvers carried out with a test vehicle showing improved results compared to the model-based algorithm from previous works.

Contact and Tribological Study of Micro/Nano Groove Texture on the Surface of Gas Bearing Materials Based on Nanoscale

As a kind of sliding bearing, the gas bearing is widely used in high-speed rotating machinery. It realizes energy cleaning in the field of high-speed rotating machinery. In order to solve the problem of reducing the service life of gas bearings due to friction during startup and shutdown, we use micromachining technology to process groove textures with different groove widths on the surface of 0Cr17Ni7Al, a common material for gas bearings. A ball-disc friction contrast test is conducted under dry friction conditions with and without texture. The experiment shows that the lowest average friction coefficient of 0.8 mm texture is σ = 0.745. When the friction radius is 22.5 mm, the wear rate of 1.0 mm texture is the lowest at ω = 3.118 × 10-4mm3/N·mm. However, the maximum friction coefficient reached is σ = 0.898. Under the nanometer scale, the contact between friction pairs is fully analyzed. The influence mechanism of different groove widths, friction impacts and climbing heights on the friction and wear properties of the micromechanical groove texture on the surface of 0Cr17Ni7Al stainless steel is studied at the nano-fractal scale. The effects of different width grooves on the surface texture and tribological properties of the micromachine are studied.

Effects of fly ash introduction on friction and wear characteristics of brake pads

Fly ash is a waste matter generally emitted abundantly from chimneys of the production facilities and should mostly be recycled. In this context, this study reveals the tribological effects of fly ash on brake pad components by doping the fly ash in basic brake pad matrix with various weight fractions of 30% (S30), 35% (S35) and 40% (S40) by reducing aluminum powder in the pad matrix. According to the results, as the fly ash concentration increases in the matrix, density and hardness of the structure were prone to decrease to an extent. Water immersion technique was used to determine density values and specially modified pin-on-disc tribotester was utilized to measure coefficient of friction (CF) and specific wear rate (SWR) values between brake pad samples and the cast iron rotating disc. Among prepared samples, maximum average reduction in density and hardness were observed to be by 3.97% and 10.67%, respectively. S30 depicted the minimum CF of 0.32 and maximum CF of 0.43 was performed by S40. Maximum specific wear rate was observed for S40 subtending to an increase of 8.67% from that of S30 to S40. Results showed that, though higher escalation in CF as the fly ash fraction elevates in the matrix, wear rates did not show a dramatic increase which is an indication of effectiveness of fly ash in brake pads in terms of braking performance and long term durability.

Integrated Estimation Strategy of Brake Force Cooperated with Artificial Neural Network Based Road Condition Classifier and Vehicle Mass Identification Using Static Suspension Deflections

Brake forces and maximum static road friction coefficients for each wheel of the vehicle are essential information for vehicle safety systems including adaptive cruise control, electronic stability control (ESC), and collision avoidance system, etc. Many studies have been performed to estimate brake force and road friction using well-known model-based approaches, but none have unambiguously guaranteed an accurate performance in all ranges of driving conditions and road ones. In addition, the investigation of the integrated estimation approach of road friction and brake force including mass estimation has not been clearly addressed so far. Therefore, in this study, a novel integrated estimation strategy based on a data-driven technique and artificial neural network (ANN) classifier along with a compact mass identification has been proposed to acquire the accurate road friction and brake force of individual wheel. Specifically, it includes an instant mass estimation by monitoring static suspension deflections, an artificial neural network (ANN) classifier for road friction coefficient based on the average data set from available standard sensors, and a brake force estimation using the data-driven technique. The performance of the proposed technique is validated by a co-simulation environment between Carsim and MATLAB/Simulink. It is found that the integrated estimation strategy guaranteed an accurate estimation of brake forces and road friction for a wide range of variations of road frictions, vehicle velocities, and masses. This work will be a valuable asset for those who wish to develop an integrated estimation system for such crucial parameters of the vehicle system.

Design of bionic tire tread compounds with pit structures and the improvement mechanism of wear and wet grip resistance

Design of bionic tire tread compounds with pit structures and the improvement mechanism of wear and wet grip resistance

Экспериментальное исследование коэффициента трения фрикционных болтовых соединений

In order to confirm the slip factor, a series of experiments carried out on models of slip critical joints with contact surfaces subjected to shot blasting. The dependence of the slip factor on the technology of preparation of contact surfaces and the presence of a protective coating is established. The data obtained suggest that achieving the maximum guaranteed coefficient of friction of 0.58 requires careful control over the preparation of the contact surface. The absence of regulatory requirements for the technology of abrasive blasting and quality control of the friction surface is noted. Differences in approaches to the determination of the coefficient of friction between domestic and foreign methods are given. The expediency of revising the values of slip factor for various methods of surface treatment adopted in SP 16.13330.2017 for slip critical joints is substantiated.

Evaluation and prediction of frictional behavior of AA 2024 based hybrid composites using ANN model

The paper investigates the frictional behavior of AA 2024 hybrid aluminum matrix composites reinforced with Zirconium dioxide (ZrO2) and Graphite (Gr). The hybrid composite is fabricated by stir casting technique by using fixed 6 wt. % of ZrO2 and varying 1.5, 3.0 and 4.5 wt. % of Gr reinforcement. The test specimens were fabricated in the form of pins to carryout frictional testing by using Pin-on-disc tribometer under dry and lubricated conditions. Tests were conducted at 15 N load corresponding to 2000 m sliding distance and varying sliding speed of 1 m/s, 2 m/s, 3 m/s and 4 m/s. Coefficient of Friction (COF) increased with the increase in sliding speed for both dry and lubricated conditions but hybrid composite with 3.0 and 4.5 wt. % showed a decrease in COF at 4 m/s sliding speed under lubricated conditions. At higher sliding speed, greater amount of frictional heat is developed which leads to the softening of Gr particles and a solid lubricant layer of Gr along with Polyalphaolefin(PAO) oil reduces the metal-to-metal contact and thus reduces the COF. Maximum COF was observed for 1.5 wt. % Gr reinforcement under dry condition whereas under lubricated conditions pure AA 2024 resulted in maximum COF. Artificial Neural Network (ANN) technique was used for predicting the friction behavior and the confirmatory tests were also performed corresponding to sliding speed of 5 m/s. From the investigations it was revealed that the error in predicted and experimental results is in the acceptable range.

Tribological behavior of thermal- and pH-sensitive microgels under steel/CoCrMo alloy contacts

The tribological behavior of 316L stainless steel/CoCrMo alloy contacts under aqueous lubrication was investigated in this work. Three types of microgels including poly(N-isopropylacrylamide) (PNIPAM), polyacrylic acid (PAA), and poly(N-isopropylacrylamide-co-acrylic acid) (PNIPAM-co-PAA) were prepared and used as lubricant additives in aqueous solutions. Tribological tests were conducted using a ball-on-disk reciprocating tribometer, over a range of temperatures, pH, and concentrations of the microgels. The PNIPAM-co-PAA microgels were proven to have excellent anti-friction and anti-wear properties, depending on the temperature and pH values of the solutions. The maximum friction coefficient coincided with the lower critical solution temperature of the PNIPAM-co-PAA microgels at 32 °C. At the same time, the friction coefficient increased with the increase in pH value of the lubricant solution with the PNIPAM-co-PAA microgels. The unique thermal- and pH-sensitive properties of the PNIPAM-co-PAA microgels provided a new strategy for controlling the friction and wear of steel/CoCrMo alloy contacts under aqueous lubrication.

Microstructure analysis, tribological correlation properties and strengthening mechanism of graphene reinforced aluminum matrix composites

In this paper, graphene reinforced aluminum matrix composites are successfully prepared by high-energy ball milling. The results show that no graphene agglomeration is found in the mixed powder. The complex composites prepared by high energy ball milling and powder metallurgy have approximately 4–5 layers of graphene and the thickness of single-layer graphene is approximately 0.334 nm. The final experimental results confirm the formation of compound AlC3 in the microstructure, and its diffraction spot index is (overline{2 }00), (overline{1 }1overline{1 }) and (11overline{1 }). The maximum friction coefficient is 0.126, and the average friction coefficient is 0.027, suggesting good wear resistance and corrosion resistance. Additionally, the friction corrosion mechanism of the material is deeply analyzed. The results of strengthening mechanism analysis show that the main strengthening mechanism of the materials designed in this experiment is thermal mismatch strengthening. It can be concluded that the yield strength of the material calculated by the modified model is 227.75 MPa. This value is slightly lower than the calculated value of the general shear lag model (237.68 MPa). However, it is closer to the yield strength value of the actual material (211 MPa).

Combinatorial Effects of Clay-Type Silicate and MgO on Friction Braking Performance of Hybrid Phenolic Composites

Abstract Halloysite (tubular), montmorillonite (platy), and wollastonite (acicular) type clay silicate morphologies-based magnesium oxide (MgO) filled compression-molded hybrid friction composites were fabricated followed by their mechanical (compressive), thermal (onset of degradation), thermo-mechanical (loss modulus), and tribological performance (CoF, fade, recovery, wear) evaluation. The friction-fade and friction-recovery due to braking-induced heating and cooling cycles vis-a-vis the instantaneous braking performances were evaluated following SAEJ661, on a chase-type friction tester. The combination of halloysite–MgO in the friction composite led to minimum fade (∼2.2%), whereas that of wollastonite–MgO showed a maximum friction coefficient (∼0.47) with enhanced rotor friendliness as indicated from optical surface profilometry. Montmorillonite–MgO-based composites showed a maximum wear resistance along with a greater extent of friction stabilization as supported by ID/IG data from Raman spectra. The performance attributes remained governed by the compressive stiffness of the friction composites, hardness, thermal stability, and morphological aspects of the clay-type silicates, and their induced contact dynamics as evident from scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM–EDX) studies. The heat dissipation mechanism, the disc temperature rise, and friction coefficient under instantaneous braking condition were found to be controlled by MgO in the composites. The study demonstrates that clay-type silicate morphologies in combination with MgO as a mild abrasive may lead to synergistic fade–recovery performance without compromising the compressive stiffness response of the braking surface, enabling increased wear resistance.

Effects of Automotive Test Parameters on Dry Friction Fiber-Reinforced Clutch Facing Surface Microgeometry and Wear-Part 2.

Coefficient of friction values, wear and surface roughness differences are revealed using pin-on-disc test apparatus examinations under three pv loads, where samples are cut from a reference, unused, and several differently aged and dimensioned, used, dry friction fiber-reinforced hybrid composite clutch facings. Tests are characterized by surface activation energy and separated into Trend 1, ‘clutch killer’, and 2, ‘moderate’, groups from our previous study. The results reveal that acceptable, 0.41–0.58, coefficient of friction values among Trend 1 specimens cannot be reached during high pv tests, though the −0.19–−0.11 difference of minimum and maximum pv results disappears when activation energy reaches 179 MJ. The maximum pv friction coefficient can decrease by up to 30% at working diameter due to clutch killer test circumstances, as 179 MJ surface activation energy is applied, while by moderate tests such losses can only be detected close to 2000 MJ energy values among small-sized facings. Besides that, Trend 2 specific wear values are the third of trend 1 results at inner diameter specimens. Compared to reference facing values, specific wear results at working diameter under maximum pv decrease by 47–100%, while increasing specific wear during lifetime can only be detected at the inner diameter of facings enduring clutch killer tests or that are small-sized facings. Among Trend 1 radial and tangential Ra delta results, inner diameter samples provide more decreasing surface roughness data, while by Trend 2 values, the opposite relation is detected. Apart from the effects of activation energy, mileage and driver profile, facing size and friction diameter influence is also revealed.

Neural Network Based Model for Friction Potential Estimation under Longitudinal and Lateral Excitations

Information about the maximum tire-road friction coefficient secures safety, increases the performance of ADAS functions, and enables higher levels of automation. An important parameter representing the relation between maximal longitudinal or lateral forces and normal force is friction potential. This paper presents a new approach for friction potential estimation based on Neural Networks by using data of 4WD vehicle. The regression model built in this paper can estimate the friction potential under both, longitudinal and lateral excitations. The goal was to build an estimation model, which does not require a tire model and can work under different types of excitations. Furthermore, this paper confirms, that the neural network approach requires lower excitations for friction potential estimation in comparison to traditional approaches. Data for training and validation was collected using a research vehicle called FlexCar, which was designed, built, and automated in the project with the same name. Experiments were conducted on three different friction levels.