Metallurgical and Materials Transactions B

, Volume 46, Issue 2, pp 906–918 | Cite as

Fluid Flow Characteristics and Porosity Behavior in Full Penetration Laser Welding of a Titanium Alloy

  • Baohua ChangEmail author
  • Chris Allen
  • Jon Blackburn
  • Paul Hilton
  • Dong Du


In this paper, a computational fluid mechanics model is developed for full penetration laser welding of titanium alloy Ti6Al4V. This has been used to analyze possible porosity formation mechanisms, based on predictions of keyhole behavior and fluid flow characteristics in the weld pool. Numerical results show that when laser welding 3 mm thickness titanium alloy sheets with given laser beam focusing optics, keyhole depth oscillates before a full penetration keyhole is formed, but thereafter keyhole collapses are not predicted numerically. For lower power, lower speed welding, the fluid flow behind the keyhole is turbulent and unstable, and vortices are formed. Molten metal is predicted to flow away from the center plane of the weld pool, and leave a gap or void within the weld pool behind the keyhole. For higher power, higher speed welding, fluid flow is less turbulent, and such vortices are not formed. Corresponding experimental results show that porosity was absent in the melt runs made at higher power and higher welding speed. In contrast, large pores were present in melt runs made at lower power and lower welding speed. Based on the combination of experimental results and numerical predictions, it is proposed that porosity formation when keyhole laser welding may result from turbulent fluid flow behind the keyhole, with the larger the value of associated Reynolds number, the higher the possibility of porosity formation. For such fluid flow controlled porosities, measures to decrease Reynolds number of the fluid flow close to the keyhole could prove effective in reducing or avoiding porosity.


Welding Weld Pool Welding Speed Molten Pool Welding Condition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was supported by a Marie Curie International Incoming Fellowship with the 7th European Community Framework Programme (Grant Nos. 253487; 919487), whose financial support is gratefully appreciated. Thanks also go to Mathew Spinks and Paul Fenwick of TWI Ltd for performing the welding trials.


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Copyright information

© The Minerals, Metals & Materials Society and ASM International 2014

Authors and Affiliations

  • Baohua Chang
    • 1
    • 2
    Email author
  • Chris Allen
    • 2
  • Jon Blackburn
    • 2
  • Paul Hilton
    • 2
  • Dong Du
    • 1
  1. 1.State Key Laboratory of Tribology, Department of Mechanical EngineeringTsinghua UniversityBeijingP.R. China
  2. 2.TWI LtdCambridgeU.K.

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