Friction Coefficient Data Research Articles

Tribological Properties of Nitrate Graphite Foils.

This study investigates the tribological properties of graphite foils (GF) with densities of 1.0, 1.3, and 1.6 g/cm3, produced from purified natural graphite of different particle sizes (40-80 μm, 160-200 μm, >500 μm). Surface roughness was measured after cold rolling and friction testing at static (0.001 mm/s) and dynamic conditions (0.1 Hz and 1 Hz). Results showed that static friction tests yielded similar roughness values (Sa ≈ 0.5-0.7 μm, Sq ≈ 0.5-1.0 μm) across all densities and particle sizes. Dynamic friction tests revealed increased roughness (Sa from 0.7 to 3.5 μm, Sq from 1.0 to 6.0-7.0 μm). Friction coefficients (µ) decreased with higher sliding speeds, ranging from 0.22 to 0.13. GF with 40-80 μm particles had the lowest friction coefficient (µ = 0.13-0.15), while 160-200 μm particles had the highest (µ = 0.15-0.22). Density changes had minimal impact on friction for the 40-80 μm fraction but reduced friction for the 160-200 μm fraction. Young's modulus increased with density and decreased with particle size, showing values from 127-274 MPa for 40-80 μm, 104-212 MPa for 160-200 μm, and 82-184 MPa for >500 μm. The stress-strain state in the graphite foil samples was simulated under normal and tangential loads. This makes it possible to investigate the effect of the anisotropy of the material on the stress concentration inside the sample, as well as to estimate the elasticity modulus under normal compression. Structural analyses indicated greater plastic deformation in GF with 40-80 μm particles, reducing coherent-scattering region size from 28 nm to 24 nm. GF samples from 160-200 μm and >500 μm fractions showed similar changes, expanding with density increase from 18 nm to 22 nm. Misorientation angles of GF nanocrystallites decreased from 30° to 27° along the rolling direction (RD). The coherent scattering regions of GF with 40-80 μm particles increased, but no significant changes in the coherent scattering regions were observed for the 160-200 μm and >500 μm fractions during dynamic friction tests. Microstrains and residual macrostresses in GF increased with density for all fractions, expanding under higher friction-induced loads. Higher values of both stresses indicate a higher level of accumulated deformation, which appears to be an additional factor affecting the samples during friction testing. This is reflected in the correlation of the results with the roughness and friction coefficient data of the tested samples.

Tribological behavior of TiN, AlTiN, and AlTiCrN coatings in atmospheric and vacuum environments

In this study, the tribological characteristics of TiN, AlTiN, and AlTiCrN coatings sliding against a SUS420J1 stainless steel pin were investigated in atmospheric and vacuum environments. The coatings were deposited on SUS440C substrates using the arc-physical vapor deposition technique. The friction and wear behavior of the coatings were evaluated based on the systematic analyses of the friction coefficient data as well as the physical and chemical state of the wear track. The results revealed that the friction coefficients of the SUS440C specimen and AlTiCrN coatings increased, whereas those of the TiN and AlTiN coatings decreased when the environment was changed from atmospheric to vacuum. It was confirmed that the formation of an oxide layer and adsorption of oxides on the surface were dominant factors that influenced the tribological behavior in the atmospheric environment. On the other hand, the compatibility, oxidation inhibition, and droplets of the surface mainly affected the frictional characteristics in the vacuum environment. The results of this work are expected to aid in the selection of proper coating materials for tribological systems operating in a vacuum.

Pavement preventive maintenance decision-making for high antiwear and optimized skid resistance performance

Insufficient pavement skid resistance due to traffic loads and environmental factors is a major cause of vehicular accidents. Hence, continually monitoring the pavement skid resistance has great theoretical significance and is crucial for practical maintenance. A pavement accelerated abrasion system developed by the research team, a high-precision 3D layer scanner, and a pendulum tribometer are used for lab testing. Forty-eight sets of asphalt pavement texture and friction coefficient data for 11 abrasion stages were collected, each comprising 20,000 abrasion cycles. Afterward, a model of asphalt pavement skid resistance deterioration was formulated by analyzing the downward trajectory of the asphalt pavement texture and friction coefficient indexes. The developed deterioration model had a high prediction accuracy with an R2 value of 91.64%, and the corresponding curve met engineering requirements. Subsequently, four pavement maintenance techniques, namely synchronous gravel sealing, microsurfacing, ultrathin overlaying, and thermal generation, were applied to rutted slab specimens after grinding to perform five additional stages of abrasion tests. Through comparisons with the established pavement skid resistance deterioration model, the optimal maintenance timing under the abrasion test conditions of this study was determined as 230,000 abrasion cycles, as determined via the time/pavement condition analysis approach. Cost-effectiveness analysis was performed for different surface treatment techniques, which yielded an equivalent annual cost of 6.7 for the SMA-5 ultra-thin overlay, which was identified as the most promising maintenance approach. This study provides a scientific basis for preventing traffic accidents and improving traffic safety by offering valuable insights into the evolution of pavement skid resistance and offers guidance on decision-making for the preventive maintenance of pavements for high-antiwear and optimized skid-resistance performance.

Real-time wear rate prediction and analysis: Gradient-weighted class activation mapping (Grad-CAM) in 1D convolutional neural network bridges experiments and neural networks

In this study, we propose a one-dimensional convolutional neural network (1D-CNN) for predicting wear rates using friction coefficient data. The model achieves high prediction accuracy for both training and testing sets, surpassing other machine learning methods. To ensure model reliability, we employ the Grad-CAM method, calculating importance scores correlating well with wear severity assessed by surface roughness (Ra) and wear track topography. The 1D-CNN model promises a precise, quantitative assessment of wear severity compared to traditional classification-based approaches. Furthermore, the model exhibits robust generalization abilities and potential as a base model for predicting wear rates of other materials, broadening its applicability in the tribology field.

Analysis of sample size for friction test of short fiber reinforced polymer composites

AbstractAccording to the recommendations of literature and standards, the minimum sample size for the friction test of thermoplastics is usually 3–5. While this size is valid for the friction test of neat polymer resins with homogeneous structures, its applicability to short fiber reinforced polymer composites with inhomogeneous structures remains unclear because the uneven distribution of discontinuous fibers or fillers in the matrix leads to the performance of the composites being dispersed. In this work, as a typical example, 100 friction samples made of short carbon fiber reinforced polyetherimide (SCF/PEI) composite with a typical content of 10 vol% SCFs are prepared, and their friction coefficients are measured. The maximum likelihood estimation and goodness of fit methods are employed to assess the fitting degree between the overall friction coefficient results and five mathematical distributions. The results show that the overall friction coefficient data distribution is in good agreement with the Lognormal, Generalized extreme value (GEV), and Burr distributions, respectively. Based on the fitting result, the minimum sample size is analyzed by Monte Carlo Simulation. It shows that the minimum sample size strongly depends on the property dispersion parameter (COV: coefficient of variation). Based on this parameter, the minimum sample size is given. In a practical test, the performance dispersion degree of a composite cannot be known in advance, hence a sample size determination method is proposed to yield a reasonable performance description parameter by applying the results of this work, and this method is validated by the overall test data.Highlights Proposed a sample size determination method for practical friction tests. The minimum sample size for the friction test is yielded statistically. The minimum sample size strongly depends on a property dispersion parameter.

Study on the Tribological Properties of Polymer Interface and the Mapping Mechanism of Friction Noise in a Wide Temperature Range

In order to study the tribological properties and frictional noise mapping mechanism of polymer interface at a wide temperature range, tribological and frictional noise acquisition tests were carried out on a Ball-on-Three-Plates Tribology Accessory. The friction coefficient and noise signal data sets were collected for 15 minutes from the friction surfaces of polytetrafluoroethylene and 0Cr18Ni9 austenitic steel pairs at six temperatures and three constant loading-speed contact points in a wide temperature range of -150°C-25°C. The wear rate of the polymer was measured and the wear state of the polymer interface was studied by field emission environmental scanning electron microscopy (SEM). Based on the analysis of the time-frequency domain characteristics of friction noise and the qualitative mapping relationship between the wide-temperature domain tribological properties and friction noise, the theoretical and experimental basis is provided for establishing online early warning monitoring of the tribological performance of polymer-metal friction pairs based on the time-frequency domain characteristics of friction noise.

Lifetime extension of gears and main bearings in wind turbines, scientific calculations and practical implementation

REWITEC, as a part of Cargill Bioindustrial, is a developer and manufacturer of an innovative particle-based surface treatment phyllosilicate-technology for increasing the reliability and the lifetime of wind turbine gears and bearings. The active particles are compatible to all common oils and greases and use lubricants as a carrier to build through their adsorption a protective and repairing phyllosilicate-based coating on the surface. The modified surface has a significantly lower surface roughness, which ensures a better load distribution, lower local pressure and lower tribological stress. Additionally, due to the special layered material structure the particles can be sheared in the tribological contact, which leads to a reduction in friction. All in all, when applying the products systems can run better with reduced friction, wear, surface roughness and temperature. These effects lead to higher reliability and a longer lifetime and thus to cost savings for operators. We would like to show our new scientific study about the lifetime calculation of a grease-lubricated wind turbine main bearing (1.5 MW) with and without the use of technology. The project is a cooperation between REWITEC and Sentient Science who performs lifetime calculations using digital clone method based on real friction coefficient and surface roughness data. The project includes data generation using MTM test bench, in a wind turbine bearing and subsequent simulation based on this data and bearing geometry. The simulation shows that with REWITEC the probability for a bearing failure significantly decreases which leads to a lifetime extension of up to 17.3 years.

Tribological behavior of MgO doped alumina ceramics

In this study, the coefficient of frictions under variable normal load and reciprocating frequencies of alumina ceramics have been investigated with various level (upto 4 wt%) of nano-crystalline MgO addition. A linear reciprocating tribotester was used to carry out the experimental investigations in dry condition using a silicon nitride (Si3N4) ball as a counter surface on the sintered samples. The friction tests were performed for a sliding time of 30 min with reciprocating frequency of 15, 30, 45, 60 Hz keeping the normal load fixed at 0.5 kgf and at normal loads of 0.3, 0.5, 0.7, 1.0 kgf keeping the sliding frequency fixed at 30 Hz. The friction coefficient increases with increasing sliding frequency, normal load but decreases with nano-magnesia addition. The friction coefficient data is used to develop an algorithm following the best fit topology to predict the addition level of magnesia in alumina for given friction coefficient and sliding frequency or normal load. Among various curve fitting techniques like polynomial fit of degree two, exponential fit of degree one and two, smoothing spline and Weibull fit, with minimum root mean square error, cubicspline fit method is adopted to form smooth curves in MATLAB. The validated result lies within a maximum error of 3.37% for cubicspline fit.

Experimental Data Mining Research on Factors Influencing Friction Coefficient of Wet Clutch

Abstract In this study, an experiment is conducted for assessing the friction characteristics of a wet clutch on actual working conditions, to determine how various factors influence the friction coefficient in the actual working process of a wet clutch. Based on the experimental data of a wet clutch under different engagement conditions, a data surrogate model construction method is proposed for the friction coefficient. According to this model, the decoupling between different influencing factors of friction coefficient is realized, and their influence on friction coefficient is obtained. To reveal the change mechanism of the friction coefficient, a theoretical analysis model of the friction coefficient is established by using the elastic contact theory and the elastic fluid dynamic pressure lubrication theory. In addition, based on the constructed friction coefficient data surrogate model, the sensitivity of different influencing factors on the friction coefficient and the coupling relationship between the different influencing factors are studied.

Prediction of tribocorrosion processes in titanium-based dental implants using acoustic emission technique: Initial outcome

The use of dental implants is growing rapidly for the last few decades and Ti-based dental implants are a commonly used prosthetic structure in dentistry. Recently, the combined effect of corrosion and wear, called tribocorrosion, is considered as a major driving process in the early failure of dental implants. However, no previous study has reported the prediction of tribocorrosion processes in advance. Therefore, this study is a novel investigation on how the acoustic emission (AE) technique can predict tribocorrosion processes in commercially-pure titanium (cpTi) and titanium-zirconium (TiZr) alloys. In this study, tribocorrosion tests were performed under potentiostatic conditions and AE detection system associated with it captures AE data. Current evolution and friction coefficient data obtained from the potentiostatic evaluations were compared with AE absolute energy showcased the same data interpretation of tribocorrosion characteristics. Other AE data such as duration, count, and amplitude, matched more closely with other potentiostatic corrosion evaluations and delivered more promising results in the detection of tribocorrosion. Hence, AE can be consider as a tool for predicting tribocorrosion in dental implants. Experimental results also reveal Ti5Zr as one of the most appropriate dental implant materials while exposing Ti10Zr's lower effectiveness to withstand in the simulated oral environment.

Extraction of Frictional Vibration Features with Multifractal Detrended Fluctuation Analysis and Friction State Recognition

For the purpose of extracting the frictional vibration characteristics of the friction pair during friction and wear in different friction states, the friction and wear tests of friction pair in different friction states were conducted on a testing machine. Higher-dimensional fractal and multifractal characteristics hidden in time series can be examined by multifractal detrended fluctuation analysis (MFDFA) method. The frictional vibration time-domain signals, the friction coefficient signals and the frictional vibration frequency-domain signals were analyzed and multifractal spectra were acquired by using the MFDFA algorithm. According to the spectra, the multifractal spectrum parameters of these signals were calculated to realize the quantitative characterization of frictional vibration characteristics in different friction states. The analysis shows that it is symmetric in the variation trends of the multifractal spectrum parameters of the frictional vibration signals and the friction coefficient data. Based on the multifractal spectrum parameters of frictional vibration, the principal component analysis (PCA) algorithm was applied to establish the friction state recognition method. The results show that the multifractal spectra and their parameters can characterize the frictional vibrations, and the friction state recognition can be realized based on the multifractal spectrum parameters of frictional vibrations.

Study on Friction Behavior of Ferroalloy and Wet Granulation Sulfur under Low Normal Load Conditions

To study the friction behavior of ferroalloy and wet granulation sulfur under low normal load conditions, a series of experiments were performed using a homemade rotating test apparatus. Scanning electron microscopy with an energy dispersive spectrometer (SEM-EDS) and X-ray diffraction (XRD) were utilized to examine the friction products. The experimentally monitored friction coefficient data were used to develop a finite element model to simulate the temperature field and a theoretical model to calculate the flash temperature of the contact area of the friction surface. The experimental, simulation, and theoretical results showed that the flash temperature of the friction surface is much higher than the average temperature of the friction surface and allows the reaction of iron and sulfur to form iron–sulfide compounds.

Hydraulic resistance and heat transfer augmentation in pipes with inner helical micro-ribs: Review, data generalisation, and technical recommendations

The paper presents the data generalization and development of general correlations for heat transfer and pressure drop in pipes with inner helical micro-ribs. Heat transfer and friction coefficient data were gathered from related investigations on single-phase turbulent flow of Newtonian fluid in pipes with various shape inner helically-ribbed surfaces

Model Friction Studies of Chemical Mechanical Planarization Using a Pin-on-Disk Tribometer

A pin-on-disk attachment for a commercial rheometer was used as a model system for chemical–mechanical planarization. The system enables real-time measurements of friction and the pin height changes as a function of velocity and load. We found the pin-on-disk tribology geometry was able to achieve a range of down pressures relevant to CMP processes (24.5 kPa at Fn = 1.5 N). It was possible to measure changes in the pin height, or gap, on the order of 1 µm during the test, which was useful to determine the amount of wear on the polishing pad and whether the system moves into hydrodynamic lubrication. The pad conditioning, or break-in process with water using a stainless steel disk with embedded diamond teeth, was conducted right before the tribology test, as in CMP processes, to give a consistent texture and remove surface impurities. Control studies of pure water at various pH’s showed the friction coefficient data and gap changes between the pad and the silicon wafer vary with the pH and ionic strength of the solution. CMP polishing was also studied with commercial slurries, pads and silicon wafers, showing that COF and pad wear can be measured reliably in the tribometer and compares well to measurements made on a 200 mm CMP commercial polisher for both water and the slurry. Overall, the pin-on-disk attachment was found to provide good insights of the tribology of a full CMP system.

Nonlinear thermo-solutal convective flow of Casson fluid over an oscillating plate due to non-coaxial rotation with quadratic density fluctuation

PurposeThe nonlinear density thermal/solutal fluctuations in the buoyancy force term cannot be ignored when the temperature/concentration difference between the surface and fluid is large. The purpose of this paper is to investigate the nonlinear density fluctuations across a flowing fluid with heat mass transfer effects on a non-axial rotating plate. Therefore, the impact of nonlinear convection in the flow of Casson fluid over an oscillating plate has been analytically investigated.Design/methodology/approachThe governing equations are modeled with the help of conservation equations of velocity, energy and concentration under the transient-state situation. The dimensional governing equations are non-dimensionalized by utilizing non-dimensional variables. Later, the subsequent non-dimensional problem has been solved analytically using Laplace transform method.FindingsThe effects of thermal Grashof number, solute Grashof number, nonlinear convection parameters, Casson fluid parameter, unsteady parameter, Prandtl number as well as Schmidt number on hydrodynamic, thermal and solute characteristics have been quantified. The numeric data for skin friction coefficient, Nusselt number and Sherwood number are presented. It is established the nonlinear convection aspect has a significant influence on heat and mass transport characteristics.Originality/valueThe effect of nonlinear convection in the dynamics of Casson fluid past an oscillating plate which is rotating non-axially is investigated for the first time.

Tribological Behavior of Glycerol/Water-Based Magnetorheological Fluids in PMMA Point Contacts

The understanding of the tribological behavior of magnetorheological fluids is crucial for many applications, in particular for those related with high quality surface finishing. In this contribution, we describe a thorough experimental investigation on the tribological properties of magnetorheological (MR) fluids in poly(methyl methacrylate) (PMMA) point contacts. First, magnetic iron oxide particles with diameters of approximately 0.4, 1,3 and 2.0 µm were prepared using wet chemistry procedures. Then, MR fluids were formulated by dispersion of the magnetic particles in glycerol/water mixtures. The tribological experiments were run in a PMMA ball-on-three plates tribometer and Stribeck regions were identified for a wide range of sliding speeds. The wear tracks were also visualized in a confocal microscope to correlate them with friction coefficient data. The results show the effect of both particle size and applied magnetic field in the friction coefficient and wear scar volume, suggesting a slight decrease on the wear process when the magnetic field is present.

The wear characteristics of CeO2 containing nanocomposite coating made by aluminate-based PEO on AM 50 magnesium alloy

This study examined the influence of CeO2 nanoparticles on the wear characteristics of aluminate-based PEO coatings formed on the AM50 magnesium alloy, which was developed for the automotive industry. Sliding wear assessments were conducted on a ball-on-disk tribometer at 2 N, 5 N and 10 N loads (against an AISI 52100 steel ball). It was found that the wear characteristics were greatly affected by the addition of CeO2 nanoparticles, especially under intermediate and high loads. The coatings with and without CeO2 remained intact during the sliding test at 2 N. Under an intermediate load of 5 N, the coating treated in the absence of CeO2 failed, while the one made in the presence of CeO2 offered superior wear resistance without any signs of wear failure. Under the 10 N load, the CeO2-free coating was completely removed and the substrate emerged, which was mainly due to a combined adhesive–abrasive wear damage mechanism; in contrast, the CeO2-containing coating (PEO-CeO2) offered much superior wear resistance to the Mg alloy, which was consistent with the friction coefficient data. SEM-EDS analysis of the worn surface of the steel balls also indicated that the transfer of the coating fragments to the ball surface was more intensive for the nanoparticle-free coating, as compared to that observed for the PEO-CeO2 coating. Also, the appearance of some deep scoring in the worn surface of the balls could be considered as a result of the three-body abrasive wear. The superior wear resistance of the CeO2 embedded nanocomposite coating could be mainly attributed to its lower porosity, lower roughness, and higher hardness.

Corrosion inhibition and friction-reduction property of tetrazole derivatives on copper

PurposeThis paper aims to evaluate the inhibitive effect and adsorption behavior of 5-(ethylthio)-1H-tetrazole (EHT) and 5-(benzylthio)-1H-tetrazole (BHT) on copper in a sulfur-ethanol system.Design Methodology ApproachEvaluation was carried out using electrochemical measurement and surface analysis techniques. Measurements of static friction coefficient by scanning electron microscopy and contact angle analysis were applied and finally confirmed the existence of the adsorbed film. The inhibitive mechanism of the two compounds was evaluated by means of quantitative calculation and molecular dynamics simulation. The friction coefficient of corrosion surface before and after adding corrosion inhibitor was determined through static friction coefficient measurements.FindingsThe electrochemical measurement indicated that the most effective concentration of two corrosion inhibitors was 70 mg L–1, while the inhibition efficiency of that was EHT > BHT. The friction coefficient data showed that the addition of corrosion inhibitor reduced the roughness of the corrosion surface. Adsorption behavior of two inhibitors followed the Langmuir’s adsorption isotherm and was attributed to mixed-type adsorption. The results of quantitative calculation and molecular dynamics simulation showed that tetrazole rings of the two inhibitors and its connected S atoms were adsorbed on Cu(111) surface in parallel.Originality ValueThe corrosion inhibition performance of two tetrazolium derivatives in a sulfur-ethanol system was studied by combining experiments with theory, which provided a theoretical basis for the future research.

Determination of the best distribution and effective interval using statistical characterization of uncertain variables

Abstract In this paper, an algorithm for estimating the best distribution about data containing uncertainties is proposed. The proposed algorithm combines sequence statistical modeling (SSM) and a method for determining the minimum experimental data. SSM is a method for selecting the best distribution about data using a goodness of fit (GoF) test and a comparison of the likelihood. The method used to determine the minimum experimental data determines the minimum data needed to an estimate the best distribution. The SSM presented herein is a method for selecting a suitable data distribution when considering only a parametric distribution. Thus, in this paper, the SSM was improved in order to select the correct distribution of both parametric and non-parametric distributions simultaneously. In addition, with the existing method for determining the minimum data, the data should be added based on actual experiments when the results data show an insufficient number, and there is a limitation in that the designers cannot broadly identify the data required. To overcome this limitation, SSM and random sampling are applied to the method to determine the minimum data, and thereby, ensure that the designer knows the approximate minimum data needed. To verify the validity of the proposed algorithm, it was applied to a real world case study on determining multiple statistical parameters in the bolt fastening problem. The sequence of verification methods used is as follows: First, the best distribution of the bearing surface and thread friction coefficient estimated by the proposed algorithm and based on a normal distribution are selected as comparison targets. Second, the bearing surface and thread friction coefficient data are sampled within the 95% confidence interval of the two distributions. Third, the reliability of the sampled friction coefficient data are compared using a Monte-Carlo simulation and an equation to calculate the bolt fastening force. In this study, the effectiveness of the proposed algorithm is validated. Highlights The algorithm to determine appropriate probability distribution of data is proposed. The sequential statistical modeling is improved to consider both parametric and non-parametric distribution. The method to determine minimum data is improved to verify sufficiency of data without actual experiments. The effectiveness and validation of the proposed algorithm is verified using the bolt-fastening data.

In situ stylus profilometer for a high frequency reciprocating tribometer

Measuring the friction and wear characteristics of a tribological contact is essential to gaining a detailed understanding of its performance and predicted life. Wear rate and friction coefficient measurements are obtained from instrumented benchtop tribometers designed to replicate specific tribological contacts. Due to the difficulty of measuring wear in situ, measurements are typically made before and after an experiment. The wear rate must be assumed to be linear for it to be used to predict product life, however this is assumption can hide changes occurring during an experiment which indicate wear transitions. This paper details the design and validation of an in situ stylus profilometer for a reciprocating sliding tribometer to provide an insight into the wear transitions occurring during dry sliding of 52100 bearing steel against graphitic flake cast iron. The profilometer’s performance was validated using ground roughness standards and the accuracy found to be approximately 110 nm. Incubation, run-in and steady state wear regimes were identified by the profilometer and corroborated with friction coefficient data, providing an enhanced understanding of the tribological contact behaviour.