Research progress on numerical simulations of ceramic friction and wear

The tribological properties of ceramic materials are crucial for the long-term reliability of ceramic components. Understanding the friction and wear mechanisms of ceramics is essential for designing, optimizing, and improving the operating performance. Numerical simulation methods, because of their low cost and high efficiency, are valuable for analyzing tribological behavior. They allow for real-time analysis of stress, temperature, cracks, and molecular motion during friction and wear. These capabilities make numerical simulations a widely discussed approach in tribology research. However, most studies on the tribological behavior of ceramics using simulations remain fragmented and lack systematic induction and summary.

This paper categorizes numerical simulations of ceramic tribological behavior into three main methods: finite element method (FEM), molecular dynamics (MD), and discrete element method (DEM). The applicable scenarios, research status, and limitations of each method are reviewed. FEM uses mathematical approximations to solve differential equations, simulating real-world physical systems. Initially, it was applied to study elastic stress distribution on ceramic surfaces during friction, serving primarily as an experimental support tool. Over time, FEM has advanced to incorporate surface fracture analysis, thermomechanical coupling, and wear modeling. Recent developments allow FEM to investigate subsurface crack initiation, crack propagation, and temperature distribution at friction interfaces under high-stress conditions, such as those in ceramic cutting tools and machining. Furthermore, FEM-based wear models can quantitatively estimate the wear volume of ceramic surfaces; however, they are highly dependent on experimental data, limiting their general applicability. MD simulations, based on Newton's laws of motion, track the trajectories of atoms and molecules during ceramic friction and wear processes by modeling interatomic interactions. This method provides a detailed view of the microfriction and wear mechanisms in ceramics. However, current research is primarily focused on SiC ceramics, with limited research on other ceramics. DEM simulations model ceramics as a collection of discrete elements and predict their tribological behavior based on interactions between these elements. This approach overcomes the continuous medium assumption and provides insights into microcrack initiation and propagation during ceramic friction and wear. However, its application is limited, primarily focusing on ceramic cutting tools and grinding wheels.

Numerical simulations are crucial for understanding the tribological behavior and mechanisms of ceramic materials and components. While its use is increasingly widespread, existing studies often focus on specific scales and boundary conditions, hindering a comprehensive understanding of the tribological mechanisms of ceramics. Moreover, a single numerical simulation method cannot completely account for the complex physical and chemical boundary conditions involved. Therefore, the development of multiscale, multifield simulation methods is essential. Additionally, tribological information methods based on machine learning and artificial intelligence can enhance data correlations, improve empirical parameter exploration, and accelerate numerical simulations with approximate calculations. Integrating these advanced techniques with traditional numerical methods can create more efficient and innovative computational tools for ceramic tribology.