A computational study on wear behavior in piston ring-cylinder liner assemblies

The interaction between piston rings and cylinder liner, constituting a pivotal frictional pair within an internal combustion engine, profoundly impacts both engine efficiency and longevity. This study models the wear process of engine components, specifically the dry sliding wear of 2D piston ring-on-cylinder liner interactions, specifically under lubrication-free conditions, in a uniflow scavenged two-stroke engine using finite element method (FEM) in ANSYS APDL using the differential Archard wear model. The <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mi>k</mml:mi> <mml:mo>−</mml:mo> <mml:mi>ε</mml:mi> </mml:math> turbulence model is employed to simulate in-cylinder pressure in an engine cycle, showing minimal discrepancies from experimental data. The wear model incorporates material properties, contact mechanics, and operational parameters, employing advanced finite element method to simulate real-world conditions accurately. Key variables such as material hardness and contact pressure are examined to determine their influence on wear depth. The simulation results indicate that wear is significantly affected by the surface hardness of the interacting materials. The liner experiences more wear than the piston ring due to its lower hardness and higher wear coefficient. The developed model is validated against Hertz contact pressures, demonstrating high accuracy and reliability. In other words, the FEM results for contact pressure closely matched the predictions from the Hertz analytical solution. This study introduces integrating OpenFOAM simulation outputs as input for ANSYS APDL, enabling a more comprehensive and accurate wear analysis. Additionally, the wear simulation is conducted on a real large two-stroke engine, enhancing the practical relevance of the findings. This approach provides deeper insights into the wear behavior of piston ring–liner interactions under real-world operating conditions, offering a significant advancement over conventional modeling techniques.