Research Papers

Melt Pool Flow and Surface Evolution During Pulsed Laser Micro Polishing of Ti6Al4V

[+] Author and Article Information
Chao Ma

e-mail: cma25@wisc.edu

Madhu Vadali

e-mail: vadali@wisc.edu

Neil A. Duffie

Fellow ASME
e-mail: duffie@engr.wisc.edu

Frank E. Pfefferkorn

Associate Professor
ASME Member
e-mail: pfefferk@engr.wisc.edu

Xiaochun Li

ASME Member
e-mail: xcli@engr.wisc.eduDepartment of Mechanical Engineering,
University of Wisconsin-Madison,
Madison, WI 53706

1Corresponding author.

Manuscript received April 2, 2013; final manuscript received October 23, 2013; published online November 27, 2013. Assoc. Editor: Yung Shin.

J. Manuf. Sci. Eng 135(6), 061023 (Nov 27, 2013) (8 pages) Paper No: MANU-13-1141; doi: 10.1115/1.4025819 History: Received April 02, 2013; Revised October 23, 2013

Extensive experimental work has shown that pulsed laser micro polishing (PLμP) is effective for polishing micro metallic parts. However, the process physics have not been fully understood yet, especially with respect to the melt pool flow. A reliable physical model can be of significant assistance in understanding the fluid flow in the melt pool and its effect on PLμP. In this paper, a two-dimensional axisymmetric transient model that couples heat transfer and fluid flow is described that was constructed using the finite element method. The model not only provided the solutions to the temperature and velocity fields but also predicted the surface profile evolution on a free deformable surface. The simulated melt depth and resolidified surface profiles matched those obtained from optical images of PLμPed Ti6Al4V sample cross-sections. The model was also used to study the effect of laser pulse duration on the melt pool flow. The study suggests that longer pulses produce more significant fluid flows. The cut-off pulse duration between capillary and thermocapillary regimes, below which minimal Maragoni flow should be expected, was estimated to be 0.66 μs for Ti6Al4V, which also matched well with the experimental results. It is evident that the coupled model offers reliable predictions and thus can be extended for a more complex parametric study to provide further insights for PLμP.

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Fig. 3

Experimental setup for PLμP

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Fig. 2

The schematic of the computational domain (not to scale)

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Fig. 1

Temperature-dependent properties of Ti6Al4V: (a) thermal conductivity, (b) specific heat, and (c) dynamic viscosity from room temperature (298 K) to boiling temperature (3560 K), and (d) dynamic viscosity around solidification range

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Fig. 4

Ti6Al4V surfaces after radiation with 8.8 μs pulses using different energies: (a) 0.493 mJ; (b) 0.607 mJ; (c) 0.704 mJ; and (d) 0.801 mJ

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Fig. 5

The temperature history of the melt pool center

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Fig. 6

Temperature field, velocity field and surface profile at time (a) 8.6 μs and (b) 11.5 μs after laser pulse initiation with a pulse duration of 8.6 μs

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Fig. 7

Optical image of the PLμPed sample cross-section

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Fig. 8

Comparison between numerical and experimental results: (a) melt pool shape; (b) solidified surface profile

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Fig. 9

Simulation results for pulse duration = 1 μs: (a) melt pool shape; (b) solidified surface profile

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Fig. 10

Simulation results for pulse duration = 3 μs: (a) melt pool shape; (b) solidified surface profile

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Fig. 11

Simulation results for pulse duration = 5 μs: (a) melt pool shape; (b) solidified surface profile

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Fig. 12

The relationship between normalized PVH and pulse duration




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