Surface prediction model for thermocapillary regime pulsed laser micro polishing of metals Academic Article uri icon


  • 2015 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved. The objective of this work is to develop a surface prediction model for thermocapillary regime pulsed laser micro polishing (PLP). Two distinct polishing regimes have been discovered: capillary and thermocapillary. The difference between the two regimes is the melt pool flow mechanisms. A surface prediction model for capillary regime PLP has been developed with results within 10% of experimental measurements. However, this model's predictions deviate from measured outcomes for longer pulse durations due to the presence of thermocapillary flow, which is not included in the capillary regime model. Previous work has also shown that this thermocapillary flow can be well predicted by multiphysics modeling [5] and that a simpler analytical relation can be derived to predict the extent of thermocapillary flow in the form of a normalized average displacement (NAD) of the liquid metal during laser polishing [5]. The current work incorporates the NAD analytical prediction for thermocapillary flow into the capillary regime surface prediction method to create a model that is valid for both the capillary and thermocapillary polishing regimes. The proposed thermocapillary flow model was tested for area polishing of titanium alloy Ti-6Al-4V and S7 tool steel. Conditions were chosen to include both the capillary and thermocapillary regimes. In all cases, the predicted average surface roughnesses were within 15% of the measured values. The results indicate that the proposed prediction model adequately captures the process physics and can provide a guide for parameter selection and process optimization of PLP across a wide processing window.

published proceedings

  • Journal of Manufacturing Processes

altmetric score

  • 3

author list (cited authors)

  • Wang, Q., Morrow, J. D., Ma, C., Duffie, N. A., & Pfefferkorn, F. E.

citation count

  • 38

complete list of authors

  • Wang, Qinghua||Morrow, Justin D||Ma, Chao||Duffie, Neil A||Pfefferkorn, Frank E

publication date

  • January 2015