Predictive FEM modeling of dry sliding wear in WC-Co incorporating UMESHMOTION and sliding-distance scaling

This study presents a finite element modeling framework for predicting dry sliding wear in WC–Co by integrating Archard’s wear law with the UMESHMOTION subroutine in Abaqus. Pin-on-disk experiments were conducted to obtain the steady-state friction coefficient, wear coefficient, and surface profile, which were used to calibrate the numerical model. A short sliding distance of 1 mm was simulated and subsequently scaled to represent a 1000 m sliding test, enabling substantial reduction in computational cost. The model accurately reproduced the experimental wear behavior, predicting a maximum wear depth within 8% relative error (0.23 μm simulated vs. 0.25 μm measured), and captured the overall geometry of the wear track. Sensitivity analysis confirmed the linear dependence of wear depth on the wear coefficient and sliding distance, supporting the validity of the scaling strategy. The results demonstrate that combining FEM, UMESHMOTION, and a sliding-distance scaling approach provides an efficient and reliable method for long-distance wear prediction in hard materials. This framework is applicable to tribological component design and can be extended to more complex multi-physics wear mechanisms in future studies.