Pulsed laser micro polishing: Surface prediction model

Abstract

This project is focused on developing physics-based models to predict the outcome of pulsed laser micro polishing (PLµP). Perry et al. [1][2][3] have modeled PLµP as oscillations of capillary waves with damping resulting from the forces of surface tension and viscosity and a one-dimensional spatial frequency domain analysis was proposed. They have also proposed a critical spatial frequency, f cr , above which a significant reduction in the amplitude of the spatial Fourier components is expected. The current work extends the concept of critical frequency to two dimensional spatial frequency analysis of PLµP. We propose a physics-based prediction methodology to predict the spatial frequency content and surface roughness after polishing, given the features of the original surface, the material properties, and laser parameters used for PLµP.The proposed prediction methodology was tested using PLµP line polishing data for stainless steel 316L and area polishing results for pure Nickel, Ti6Al4V, and Al-6061-T6. The predicted average surface roughnesses were within 10% to 12% of the values measured on the polished surfaces. The results show that the critical frequency continues to be a useful predictor of polishing results in the 2-D spatial frequency domain. The laser processing parameters, as represented by the critical frequency, and the initial surface texture can be used to predict the final surface roughness before actually implementing PLµP.

Surface prediction model for thermocapillary regime pulsed laser micro polishing of metals

“…The initial average surface roughness was S a = 84 nm, which was reduced to 37 nm through capillary regime PLP ( Table 5). The average surface roughness was predicted to be S a = 39 nm by thermocapillary flow model (presented in this paper) and 37 nm by the capillary regime surface prediction model [17]. The 2 nm difference between the two polishing models indicates that the "thermocapillary regime model" can provide accurate prediction results for capillary regime polishing, and it should probably be renamed.…”

“…Low-pass filtering of unpolished surface using the capillary smoothing model This step predicts the smoothing effect of capillary waves on the surface of the melt pool. A capillary regime polishing model was first proposed by Vadali et al [16,17] using a physically relevant critical frequency, f cr , above which a significant reduction in amplitude of the spatial frequency content of a surface and its asperities could be expected. The filter limits the attenuation effect in the spatial frequency spectrum of the initial surface and can be viewed as a special case of the low-pass Gaussian spatial filter.…”

“…Both the "original" capillary flow model [17] and the "new" thermocapillary flow model presented in this paper were used to predict the surface topography of the micro-end milled Ti-6Al-4V surface after pulsed laser polishing. The surface color maps of the initial surface, measured polished surface, and surfaces predicted by the capillary and new thermocapillary flow models are shown in Fig.…”

“…The spatial frequency spectrums of the unpolished surface, measured surface, surface predicted by the thermocapillary regime model (presented in this paper), and the surface predicted by the capillary regime model [17] are shown in Figs. 10 and 11, respectively.…”

“…Ukar et al [15] have proposed a prediction methodology based on the thermal field prediction generated by the laser utilizing the critical frequency. Vadali et al [17] have developed a physics-based surface prediction methodology combining an analytical fluid flow model and a numerical heat transfer model, which can be used to accurately predict the polished surface topography in the capillary regime. However, the capillary regime surface prediction model deteriorates when predicting the polished results for thermocapillary regime PLP due to not taking the Maragoni flow into consideration.…”