Wear Model Research Articles

Development and Evaluation of Machine Learning Based Predictive Models for Tribological Properties of Blended Coatings at Elevated Temperature

The current research is undertaken to evaluate the Tribological properties like wear and Coefficient of Friction (CoF) of three popular blended coatings on a mild steel substrate at elevated temperature. The scope of the research also includes predicting the tribological properties by employing three Machine Learning (ML) based predictive models viz. Elastic Net, k-NN and Random Forest regressions. The regressions are fit and tested at different proportions of Training and Testing data to find the best proportion. Random Forest regression is observed to be the best fit based on the acceptable values of MSE and R-Squared. Random Forest regression model of wear yielded MSE and R-Squared values as 22.01 and 0.95 for Coating 1, 5.75 and 1 for Coating 2, and 14.13 and 1 for Coating 3, respectively. Likewise, Random Forest regression model of CoF yielded MSE and R-Squared values as 0.01 and 0.99 for Coating 1, 0 and 1 for Coating 2, and 0 and 1 for Coating 3, respectively. The deviation between the experimental and predicted results (tested data: experimental runs 3, 14, and 29) in wear using the Random Forest algorithm for Coating 1, Coating 2, and Coating 3 is found to be 21.18%, − 2.72%, and 0.42%; − 4.54%, − 13.87, and 2.57%; 11.85%, 1.69%, and 1.89%, respectively. The deviation for CoF is found to be 6.29%, 1.56%, and 2.93%; − 0.86%, − 0.56%, and 0.20%; 0.85%, − 0.19%, and 0.17%, respectively. The variance between the actual experimental and predicted results from Random Forest regression is observed to be relatively acceptable.

Effect of Aspect Ratio on Asymmetrical Wear of Brake Pads Under High-Speed and Heavy-Load Braking Conditions

This study investigates the influence and mechanisms of friction blocks with varying aspect ratios on the asymmetrical wear of brake pads under high-speed and heavy-load braking conditions. A large megawatt-level wind turbine brake device was used, and the Archard wear model was integrated into the analysis of brake interface wear characteristics through finite element method (FEM) and arbitrary Lagrangian-Eulerian (ALE) technology. A thermal-mechanical-wear coupling model was developed for brake systems with five different aspect ratio friction blocks, and its accuracy was validated through wear tests on an inertial brake test bench. A method for calculating tangential and radial wear is proposed to characterize the degree of asymmetrical wear at the friction interface. The study revealed a non-uniform wear distribution at the contact interface, with greater wear observed at the leading and outer edges of the friction block. A small aspect ratio (L/W < 1.5) predominantly results in radial wear, while a large aspect ratio (L/W > 1.5) leads to tangential wear. An aspect ratio of 2:1 balances radial and tangential wear, indicating improved wear resistance.

Modeling of erosion wear in labyrinths seals using CFD approach

Modeling of erosion wear in labyrinths seals using CFD approach

Comprehensive Analysis of Milling Performance and Multi-Objective Parameter Optimization for YG6C Milling Tool

Numerous conflicting objectives exist in the engineering field, and resolving these conflicts to reduce costs constitutes a problem that demands top-priority consideration. A model for tool wear and a multi-quadratic regression model for milling forces were developed to accurately predict the trends of wear on the rake face of the milling tool and the variations in milling forces. The influence of milling parameters (spindle speed, n; feed rate, vf; axial milling depth, ap) on both the wear of the rake face and milling force was analyzed by means of orthogonal experiments. The findings indicated that the impact of these parameters on the wear ranked in the following order: n &gt; vf &gt; ap. In contrast, for milling force, F, the ranking was ap &gt; vf &gt; n. Utilizing MATLAB’s genetic algorithm, an optimization procedure was conducted with multiple objectives including the wear of the rake face, milling force, and material removal rate; subsequently, a Pareto optimal solution set was generated for milling parameters based on practical processing requirements.

Research on wear and grinding models of high-speed turnouts based on semi-Hertz contact

In order to reduce turnout rail wear, the paper establishes a coupled dynamics model and a turnout rail wear model that consider the true profile of the turnout rail, the vehicle’s continuous traction force while passing, and the operational resistance. Comparative analysis of various models for predicting turnout rail wear indicates that the wear energy model is better suited for this purpose. The ideal profile update step for the turnout rail is 0.05 mm, and the adaptive filtering algorithm, tailored to the turnout characteristics, smooths wear distribution effectively while retaining crucial data features. The wear model developed in the paper predicts wear depth that is 89.91% consistent with the measured data. The grinding model introduced in the paper significantly enhances the wheel-rail contact conditions in the turnout, with lateral and vertical vibration accelerations of the vehicle reduced by 52.56% and 30.43%, respectively, during turnout passage. The research offers theoretical support for mitigating rail wear in high-speed turnouts.

Computational wear prediction of articular cartilage based on a new anisotropic wear law.

Excessive wear can result in irreversible damage to the cartilage. Experimental studies indicate that cartilage wear is significantly influenced by both the orientation of unidirectionally aligned surface fibers and the biphasic structure of the tissue. Given challenges with invasive in vivo wear experiments, there is a pressing need for computational models to predict wear of the cartilage accurately. However, existing models that account for anisotropic and biphasic wear behaviors are lacking. The aim of this study was to develop a finite element (FE) wear prediction model that accounts for the complex anisotropic and biphasic nature of the cartilage. To achieve this, an anisotropic wear law was proposed based on the wear tests conducted on bovine cartilage pins reciprocally rubbed against cobalt chromium molybdenum plates. Subsequently, this anisotropic wear law was integrated into a biphasic FE model of the cartilage. Compared to the isotropic wear model, this model demonstrates improved accuracy in capturing cartilage wear patterns, effectively representing both the anisotropic wear behavior influenced by the angle between the superficial fiber orientation and the sliding direction, and the biphasic wear behavior affected by solid phase stresses. This modelling framework not only holds promise for assessing cartilage wear in physiological conditions but also offers potential applications to a broader range of materials and may facilitate the development of osteochondral grafts.

Experimental and computational evaluation of knee implant wear and creep under in vivo and ISO boundary conditions

Abstract Background Experimental knee implant wear testing according to ISO 14243 is a standard procedure, but it inherently possesses limitations for preclinical evaluations due to extended testing periods and costly infrastructure. In an effort to overcome these limitations, we hereby develop and experimentally validate a finite-element (FE)-based algorithm, including a novel cross-shear and contact pressure dependent wear and creep model, and apply it towards understanding the sensitivity of wear outcomes to the applied boundary conditions. Methods Specifically, we investigated the application of in vivo data for level walking from the publicly available “Stan” data set, which contains single representative tibiofemoral loads and kinematics derived from in vivo measurements of six subjects, and compared wear outcomes against those obtained using the ISO standard boundary conditions. To provide validation of the numerical models, this comparison was reproduced experimentally on a six-station knee wear simulator over 5 million cycles, testing the same implant Stan’s data was obtained from. Results Experimental implementation of Stan’s boundary conditions in displacement control resulted in approximately three times higher wear rates (4.4 vs. 1.6 mm3 per million cycles) and a more anterior wear pattern compared to the ISO standard in force control. While a force-controlled ISO FE model was unable to reproduce the bench test kinematics, and thus wear rate, due to a necessarily simplified representation of the simulator machine, similar but displacement-controlled FE models accurately predicted the laboratory wear tests for both ISO and Stan boundary conditions. The credibility of the in silico wear and creep model was further established per the ASME V&amp;V-40 standard. Conclusions The FE wear model is suitable for supporting future patient-specific models and development of novel implant designs. Incorporating the Stan data set alongside ISO boundary conditions emphasized the value of using measured kinematics in displacement control for reliably replicating in vivo joint mechanics in wear simulation. Future work should focus on expanding the range of daily activities simulated and addressing model sensitivity to contact mechanics to further enhance predictive accuracy.

Erosive-abrasive wear modeling of a water jet pump in a slurry medium

In the study, water jet pump transfers the slurry in the well through pipe system to centrifugal pump. Sand-water mixture causes amount of material loss in the water jet pump structure computed by a software program. The purpose of the study is to determine the most critical part in the water jet pump. The wear amount is affected by many parameters such as sand particle diameter, mass flow rate of abrasive and inlet velocity. So, it is investigated that the wear amount on the jet pump is changed according to sand percentage in the well water, inlet velocity and erodent diameter. Mass flow rates of sand have a value of 0.097 kg/s for w.p. % 5, 0.194 kg/s for w.p. % 10, 0.291 kg/s for w.p. % 15 at an inlet velocity of 3.98 m/s. The maximum erosion wear rate is raised from 2.26x10-4 kg/(s m2) to 6.84x10-8 kg/s2m2 for inlet velocities of 1.99 m/s, 3.98 and 7.96 m/s, respectively for the case of weight percentages of %15 in Finnie erosion wear model. Finnie, Mclaury, Generic and Oka erosion models have been compared. It is found that Mclaury’s erosion model demonstrates the highest erosion value of 1.38x10-3 kg/(s m2) for w.p. % 15 at 3.98 m/s inlet velocity for the erodent diameter of 0.0005m in all. It is claimed that erosive wear has been concentrated on the nozzle of the water jet pump. The wear rate can be predicted as straightforwardly for different conditions.

Identification of parameter-dependent machine learning models for tool flank wear prediction in dry titanium machining

This study uses machine learning (ML) techniques to predict maximum flank wear on cutting tools during the turning of Ti6Al4V, a titanium alloy known for its challenging machinability. We used three models (a) support vector machines (SVM), (b) random forests (RF), and (c) neural networks (NN) to predict maximum flank wear. The machining parameters are taken as input data sets, which compromise cutting speed, feed, and machining time. All the experiments are done at a constant depth of cut to predict maximum flank wear as an output variable. The forecasted maximum flank wear was validated using experimental data to verify their precision. The SVM model outperformed the other ML models in a wider range of cutting parameters concerning tool flank wear. The SVR model is the most accurate model with an average forecasting error of 3.24%. In forecasting maximum flank wear, the RF and NN models followed, with average forecasting errors of 3.88% and 3.71%, respectively. Additionally, the SVM model's robustness was further validated by its ability to maintain stability at varying cutting speeds and feed rates. The research enhances the economics of the machining process by predicting tool flank wear and fostering sustainability in the manufacturing industry, thereby demonstrating the applicability of ML techniques.

Моделирование износа при трении качения с проскальзыванием

The paper views mathematical and numerical models of wear of elastomeric materials developed by the authors in dead rolling with sliding movement. When developing a mathematical model, classical ideas about the kinematic characteristics of a massive elastomeric tire rolling along the abrasive surface of the disc were used. To describe the intensity of wear, the model uses the concepts of wear formulated by D. Archard and modified in relation to the studied objects - rubber-based resin elastics SRI-3 and SRS-30–ARKM-15 rubbers reinforced with carbon nanostructures. The numerical implementation of the mathematical model is performed in the Matlab software package. In order to simplify the numerical calculation, it was decided to switch the rolling slip model to the pure sliding model. The choice of the integration step in time allowed to stabilize the instability of the solution. Thus, the numerical model examined sliding of an elastomeric cylinder along the abrasive surface of the disk at a speed equal to the sliding speed and varying the normal load. The finite element method (FEM) was used as a numerical calculation method. At a fixed depth of indentation, the verification of the developed model was carried out. According to the simulation results, the dependences of the wear intensity of an elastomeric material on the magnitude of specific pressures are obtained. A comparative analysis of the simulation results and the data obtained experimentally make it possible to determine the difference at the level of 20 percent, which may be due to the limitations of the model when thermal characteristics of the materials are not taken into consideration. Thus, the developed model has demonstrated its viability and will be further refined upon taking into account the identified limitations.

Evaluation of the parameters of contact interaction and wear of parts with cylindrical friction surfaces

The purpose of the presented research work was to evaluate various factors affecting the wear process of parts with cylindrical friction surfaces, which will allow to simulate their contact interaction taking into account the parameters of roughness and physico-mechanical properties of the surface layer.Methods. Modeling of the process of contact interaction of cylindrical surfaces is performed by considering the sliding contact of two cylindrical surfaces, represented as the contact of a smooth elastic sleeve and a shaft with the given (equivalent) values of roughness parameters. The modeling takes into account elastic deformations of conjugate bodies, as well as elastic-plastic deformations of micro-dimensions. When modeling a geometric contact, a certain section of the cylindrical surface is considered, located along the plane forming in the section of the cylinder passing through its axis. This section of the cylindrical surface is considered as an elementary area of the total geometric contact area of cylindrical surfaces and is a section of a cylindrical surface, the width of which is determined by the length of the larger axis of the ellipse at the base of the elliptical paraboloid when modeling a rough surface.Results. Based on the modeling of the contact interaction of cylindrical surfaces, the main factors influencing the process of their wear are established, such as: the actual contact area; the amount of convergence of the contacting surfaces; the actual pressure; the intensity of wear of the mating cylindrical surfaces. A kinetic wear model is proposed that takes into account the parameters of the roughness and physico-mechanical properties of the surface layer.Conclusion. Based on the proposed model of wear of parts with cylindrical friction surfaces, taking into account the parameters of roughness and physico-mechanical properties of the surface layer, it became possible to provide the required intensity of wear of cylindrical friction surfaces.

Experimental and Numerical Investigations of the Sediment Abrasion Mechanism at the Leading Edge of an Airfoil

Multiple engineering projects have confirmed that hydraulic machinery operating in sediment-laden rivers undergoes sediment abrasion. Guide vanes are among the most severely worn flow-passing components and have long been a key research focus in hydraulic machinery. In this research, a wear test of the NACA0012 cascade under a 10° incoming flow angle was carried out in the Venturi test system, and the evolution process of the wear was analyzed. The three-dimensional flow channel of the cascade was constructed, and the Finnie wear model was adopted for computational fluid dynamics (CFD) simulations to analyze the wear mechanism at the initial stage. The results indicate that abrasion primarily occurs at the airfoil’s leading edge and progresses through three stages: initiation, development, and stabilization. The calculated results closely matched the latest wear outcomes: In the initial stage, the wear rate density was influenced by the particle impact velocity, angle, volume fraction, and y-direction shear stress. A low-velocity zone near the impact point, combined with rebounding particles causing secondary impacts, increases the particle volume fraction and wear rate density. These secondary impacts are the primary causes of erosion on both the upstream and downstream surfaces. Furthermore, flow separation downstream from the leading edge makes this region highly susceptible to wear. This study provides valuable insights for addressing wear in hydraulic machinery for practical engineering applications.

Research on reciprocating sealing performance and leakage rate prediction based on GA-PSO-BPNN hybrid algorithm

Purpose This study aims to investigate the sealing performance of reciprocating seals under the effect of rubber abrasion using ABAQUS simulation software, and to propose a prediction framework based on a hybrid algorithm (GA-PSO-BPNN) to predict the leakage of reciprocating seals of downhole gauging instrumentation under different working condition parameters. Design/methodology/approach The authors combined the UMESHMOTION user program with the improved Archard wear model to investigate reciprocating seal performance. GA and a PSO were proposed as ways to enhance the BPNN’s predictive model. Findings The results show that the impact of fluid pressure fluctuations on the wear of the seal lip is more pronounced during the rapid wear phase compared to the steady wear phase. Similarly, variations in compression rate have a greater impact on seal lip wear at different stages of wear. The GA-PSO-BPNN prediction model outperforms the single-prediction model in terms of prediction accuracy. Originality/value The authors investigated sealing performance through simulation software and propose a GA-PSO-BPNN-based fault diagnosis method for rotating machinery. To verify the accuracy of the prediction model, a reciprocating sealing test platform for gauge work cylinders is constructed. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2024-0293/

50 Years of scientific thought on Machine Diagnostics in PolanD anD its influence on MaritiMe aPPlications

Abstract This article presents a condensed outline of how approaches to solving technical diagnostics tasks have changed over the last 50 years. It reviews different approaches to the modelling of wear and tear phenomena that are the subject of diagnosis, and draws attention to groundbreaking papers which are still of topical interest. Particular emphasis is placed on the development of vibroacoustic diagnostics methods, an area in which Polish scientists were among the world’s avant garde. It is also shown how methodologies have changed with the progress of digital signal analysis. The example presented in the second part of the article demonstrates that the well-known and technically important task of diagnosing a gear set can now be solved without looking for a classic state→symptom relationship through an accurate dynamic description of the machine and comparing it with the results of an experiment, but instead by comparing observations at different points in the n-dimensional space with an abstract pattern generated by a sequence of logical transformations. This formulation of the task opens up avenues for AI methods. Attention is paid to the fact that maritime shipping is one of the main fields of application for modern diagnostic methods, and it is shown that the increase in the accuracy of vibroacoustic diagnostics techniques and the correctness of the diagnosis allows for the use of this methodology in marine applications.

Tool Wear Prediction in Machining of Aluminum Matrix Composites with the Use of Machine Learning Models.

This paper discusses the diagnostic models of tool wear during face milling of Aluminum Matrix Composite (AMC), classified as a difficult-to-cut material. Prediction and classification models were considered. The models were based on one-dimensional simple regression or on multidimensional regression trees, random forest, nearest neighbor and multilayer perceptron neural networks. Measures of diagnostic signals obtained from measurements of cutting forces and vibration accelerations of the workpiece were used. The study demonstrated that multidimensional models outperformed one-dimensional models in terms of prediction accuracy and classification performance. Specifically, multidimensional predictive models exhibited lower maximum and average absolute prediction errors (0.036 mm vs. 0.050 mm and 0.026 mm vs. 0.045 mm, respectively), and classification models recorded fewer Type I and Type II errors. Despite the increased complexity, the higher predictive accuracy (up to 0.97) achieved with multidimensional models was shown to be suitable for industrial applications. However, simpler one-dimensional models offered the ad-vantage of greater reliability in signal acquisition and processing. It was also highlighted that the advantage of simple models from a practical point of view is the reduced complexity and consequent greater reliability of the system for acquiring and processing diagnostic signals.

Unveiling the temperature effect on reciprocating sliding wear mechanism of a TA15 alloy fabricated by wire-arc additive manufacturing

TA15 alloy has been widely used for load-bearing structural components in aircraft engines and subjected to sliding wear at different temperatures in operation. Therefore, the temperature effect on sliding wear mechanism of a TA15 alloy fabricated by wire-arc additive manufacturing was investigated in detail. Results showed that the coefficient of friction and wear volume exhibited multi-stage changes with increasing temperature. As the temperature increased, the crack morphology changed from randomly distributed pores to delamination cracks. The classic oxidative wear model collapsed at high temperatures. We modify the model by introducing dissipated energy and delamination coefficient to accurately predict the wear volume of TA15 alloy.

Frictional Abrasion of Rubber: Transition from Sliding to Rolling

ABSTRACT To develop applicable friction and wear models on tire scale, reliable test data are required. Consequently, friction tests on block level are requested because the distribution of contact pressure as well as slip velocity is nearly homogeneous at the contact surface of the sliding rubber block. However, wear mechanism and energy intensity levels of sliding rubber blocks and rolling rubber wheels or tires differ significantly. Consequently, linking both sliding and rolling frictional abrasion is required; thus, a wear model for rubber material is introduced to consider both deformation slip and sliding. The model input for sliding friction and resulting wear rate is derived from linear friction test experiments using sliding rubber blocks at different loading. A unique and sophisticated re-mesh algorithm ensures proper mesh modification due to abrasion of the structure. A wear energy evolution approach is developed to consider low abrasion with small sliding distances to predict wear at rolling rubber wheels. The simulation framework of abrasion modeling is successfully validated using laboratory abrasion tests.

Modeling and Measurement of Tool Wear During Angular Positioning of a Round Cutting Insert of a Toroidal Milling Tool for Multi-Axis Milling

The aim of this study was to develop a concept for an angular positioning method for a round cutting insert in a torus cutter body dedicated to the multi-axis milling process under high-speed machining cutting conditions. The method concept is based on a developed wear model using a non-linear estimation method adopting a quasi-linear function. In addition, a tool life model was developed, taking into account the cutting blade work angle parameter, the laser marking method for the round cutting insert, and a wear measurement methodology. The developed tool wear model provides an accuracy of 90% in predicting the flank wear of the cutting blade. The developed procedure for angular positioning of the round cutting insert enables the entire cutting edge to be fully utilized, extending the total tool life. In addition, the measured largest defect values between the worn cutting edge and the nominal outline of the round cutting insert indicate the location of notching-type wear.

Study on failure analysis and erosion wear of four-way cross in high-pressure gas well test process

High pressure gas well ground testing process working pressure can reach up to 105 MPa. Under severe loading conditions and the influence of internal high-pressure media, the manifold is highly vulnerable to erosion wear damage from solid particles. This study focuses on a failed four-way cross at a high-pressure gas well test site, to characterize its failure modes and features. Utilizing methods such as macroscopic feature observation, scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS) analysis. The primary failure mode is identified as the micro-cutting action of stratum solid particles, which cuts and collides with the inner wall under the carriage of high-speed fluid. The erosion defect features present as band-shaped wear marks and parabolic pits. To reveal the erosion failure mechanism of the four-way cross under the multiphase flow, an erosion wear prediction model is developed. This model is based on the theory of gas–solid two-phase flow and the operational parameters of the testing operation process. Secondly, an experiment on the gas–solid two-phase erosion wear of the main material 35CrMo used in the testing process is conducted for the specific operating conditions. Based on the experiment result, a comparative analysis of erosion simulations under different empirical erosion wear models is conducted, and the appropriate erosion wear model for the material is selected, and the empirical coefficient of the model is revised. Finally, an erosion wear simulation prediction of the four-way cross is performed based on the optimal erosion wear model, and the results are compared with the failure location of the failed parts on site. Simultaneously, a study is conducted on erosion wear patterns under varying conditions of gas displacement, sand production volume, particle size, and particle shape factors.

Modelling and theoretical research on transient lubrication and wear coupling behavior of main bearing during start-up of low-speed diesel engine

This study endeavors to establish a transient mixed lubrication model for time-varying wear of main bearings under dynamic loading conditions during the startup process. This model accounts for variations in oil film thickness attributable to deformation, wear profiles, and journal misalignment throughout the operational cycle. The evolution of main bearing lubrication characteristics during the startup process was analyzed, as well as the evolution of wear profiles and their effects on lubricating properties under different numbers of startups. The results indicate that as the number of startup cycles increases, the wear rate gradually levels off. With increasing startup times, there is a decrease in contact pressure and a slight reduction in oil film pressure, resulting in enhanced lubricating performance. Furthermore, the influence of startup duration on wear is significantly greater than that of radial clearance.