On the optimal texture shape with the consideration of surface roughness.

Area of Science:

• Tribology and surface engineering
• Computational fluid dynamics
• Materials science

Background:

• Surface texture optimization is key to reducing friction and wear in mechanical systems.
• Understanding the impact of surface roughness on tribological performance is essential.
• Existing models often simplify or neglect the complex interplay of roughness and texture geometry.

Purpose of the Study:

• To determine the optimal texture shape considering surface roughness effects.
• To investigate the influence of surface roughness parameters (RMS, pattern parameter) and operating conditions on friction, area ratio, and depth.
• To compare the impact of roughness on optimal dimple shapes versus optimal self-defined shapes.

Main Methods:

• Solving the average Reynolds equation with Jakobsson-Floberg-Olsson boundary conditions.
• Employing a genetic algorithm for texture shape optimization.
• Analyzing the effects of combined root-mean-square (RMS) roughness, surface pattern parameter, and operating parameters.

Main Results:

• Significant reduction in friction coefficient achieved through shape optimization that incorporates surface roughness.
• Established variation laws for optimal dimple area ratio based on RMS, pattern parameter, minimum film thickness, and sliding speed.
• Determined the variation law for the optimal depth of self-defined shapes concerning roughness and working parameters.

Conclusions:

• Surface roughness significantly influences the optimal texture shape, leading to reduced friction.
• Roughness parameters have a greater impact on the optimal dimple shape compared to the optimal self-defined shape across various sliding speeds.