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Wear is a complex phenomenon, which depends on various parameters such as load, velocity, material properties, surface, environmental conditions, etc. Hence, wear prediction is a challenging part of engineering. This paper focuses on numerically predicting the wear of 304 stainless steel pin sliding against AISI 52100 bearing steel disc, using pin-on-disc tribometer setup. The experiments are performed for loads of 10 N, 30 N, and 50 N and a sliding speed of 0.4 m/s. The wear coefficient and coefficient of friction obtained from the experiments are given as input to a 2D elastic finite element method model using a commercially available finite element method-based software ABAQUS. The differential form of the Archard’s wear law is used to obtain the wear depth at the contact nodes. The UMESHMOTION+ Arbitrary Lagrangian–Eulerian technique is used to update the contact geometry after each wear increment. The major drawback of wear simulation is the large computational time requirement. To address this, three extrapolation techniques are used namely, the constant extrapolation, the linear extrapolation, and the constant pressure extrapolation technique. A new criterion for using extrapolation during sliding wear simulation was proposed. The extrapolation techniques take into consideration the evolution of the contact pressure and contact geometry during sliding wear. The effectiveness of these techniques based on the computational time and accuracy are analysed. Based on the accuracy, the linear extrapolation technique was found to be most effective, while the constant pressure extrapolation technique was most useful in reducing the computational time. The numerical results obtained are validated with the experimental results.

This article presents the findings from a parametric study examining the effect of four contaminants (soot, oxidation, moisture, and sulphuric acid) at varying levels (four for each). It was observed that all contaminants and contaminant levels reduce the conductivity of the oil. Oxidation and soot contaminants produced large increases in viscosity. The wear rate was mainly influenced by acid and soot additions, while the coefficient of friction was increased by all contaminants and contaminant levels. The steady-state charge levels changed for some contaminants. The best correlation of steady-state charge with the other measured tribological parameters of wear rate, friction, and temperature is seen for the series of oxidized oils. The multi-contaminated oil (L4 Â 4) shows remarkably little degradation in tribological performance.Analysis of the wear mechanisms shows that soot and oxidation produced abrasion and polishing wear, respectively, while sulphuric acid and moisture produced corrosive wear.

The aim of this work is to better understand the relationship between the wear of sliding tribo-couples and contamination such as soot, sulphuric acid, moisture and oxidation levels to simulate the influence of contamination in model diesel engine oils using electrostatic condition monitoring.

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