Dynamic Prediction Model for Uneven Slipper Wear Under Complex Lubrication Conditions Considering Lubrication–Wear Coupling
Year: 2025
Type: article
Abstract: It is difficult to experimentally determine the real-time wear coefficient of a slipper pair under complex lubrication conditions. To address this challenge, this study proposes a predictive method for slipper wear, eliminating the need for experimental measurement of the slipper pair’s friction coefficient under complex lubrication conditions. The force and motion characteristics of the slipper pair are analyzed to determine the non-uniform clearance distribution caused by elastic deformation and micro-motion. Based on the Greenwood–Williamson (G–W) model and Hertzian contact theory, the contact regions and stresses on the slipper bottom are accurately evaluated under mixed lubrication conditions. The Archard wear equation, combined with wear coefficients obtained from dry friction tests, is employed to calculate the instantaneous uneven wear of the slipper. This wear is then incorporated into iterative calculations of non-uniform clearance, forming a dynamic prediction model that captures the coupled relationship between lubrication and wear. The numerically simulated wear profile was compared with previously reported experimental measurements, and the discrepancies between them were analyzed. The results indicate that the proposed model can effectively predict the outer-side bottom wear of the slipper under steady-state operating conditions. Furthermore, the contact and wear behaviors under extreme conditions are investigated, the modeling results show revealing the variations in wear location and contact stress for ideal flat-bottom, low-speed, and high-speed operating states. The proposed model provides theoretical and methodological insights for optimizing the lubrication performance of slipper pairs during the stable wear stage.
Source: Lubricants
Authors: Hu Mo, Shigang Qin, Wei Zhou, Yunan Yang, Penghui Duan, Fu Peng
Institution: Hunan Electrical College of Technology
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G5044612815
OpenAlex ID: W7106029667
