Theoretical and experimental study of bulge formation in laser polishing of 304 stainless steel

As an emerging surface treatment process, laser polishing is dedicated to reducing the surface roughness of the sample, but some new surface structures (such as ripples, undercuts, bulges, step structures, and martensite needles) may be introduced into the polished surface, affecting the effect of laser polishing. This work aims to reveal the formation mechanism of bulges in the center of the polished track. The effect of laser polishing process parameters on the size parameters of bulges was studied through experiments of laser polishing. And a twodimensional numerical model was developed by coupling heat transfer and fluid flow. The evolution of bulges, the temperature field, and the velocity field was presented with this model. Furthermore, through the analysis of the surface forces and surface velocities of the molten pool, it was found that the thermocapillary force affected by surface-active elements (oxygen, sulfur, and phosphorus) is the main driving force for the formation of bulges. And some measures to reduce or eliminate bulges were proposed to improve the surface finish of laser polishing. In addition, the final surface profile of the bulges after laser polishing was simulated, which was in good agreement with the experimental results. And this model can be extended to predict the evolution of surface topography in laser polishing, guiding the optimization of process parameters in laser polishing.

Automated summary

This study reveals the formation mechanism of bulges in laser polishing through experiments and numerical modeling. By analyzing surface forces and velocities, the main driving force for bulge formation was identified as the thermocapillary force affected by surface-active elements. Measures to reduce or eliminate bulges were proposed to enhance the surface finish of laser polishing. The developed model can accurately predict the evolution of surface topography in laser polishing, guiding the optimization of process parameters.