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Multi-scale modeling of selective electron beam melting of Ti6Al4V titanium alloy

  • Trong-Nhan Le
  • Yu-Lung LoEmail author
  • Hong-Chuong Tran
ORIGINAL ARTICLE
  • 148 Downloads

Abstract

Selective electron beam melting (SEBM) is one of the most promising powder-based metal additive manufacturing (AM) technologies. However, controlling the SEBM process parameters in such a way as to maximize the quality of the fabricated components represents a significant challenge. Accordingly, taking Ti6Al4V titanium alloy for illustration purposes, the present study constructs a novel multi-scale modeling framework to examine the effects of three SEBM process parameters (namely the beam current, the beam diameter, and the scanning speed) on the dimensions and temperature distribution of the melt pool. In microscale, an effective model considering the interactions between the electron beam and the Ti6Al4V atoms was constructed based on the Monte Carlo ray-tracing simulations, and the electron beam total absorption of Ti6Al4V material as a function of incidence angle was obtained. In mesoscopic level, in order to take the absorption property of the porous structure of the powder layer into account, absorptivity profile along the depth of the powder bed was calculated by utilizing the absorptivity of Ti6Al4V for various incidence angles and the 3-D powder bed model. It is found that the total laser absorptivity of the Ti6Al4V powder bed is around 12% higher than that of the bulk material of Ti6Al4V due to the multiple reflection of electron beam inside the powder layer. Finally, three-dimensional finite element heat transfer simulations are performed using the proposed volumetric heat source to predict the melt pool geometry and thermal distribution during the SEBM process. It is shown that the simulation results are in good agreements with the experimental results reported in the literature.

Keywords

Selective electron beam melting Ray tracing Volumetric heat source Melt pool 

Notes

Funding information

This study received financial support from the Ministry of Science and Technology of Taiwan (MOST) under Grant No.107-2218-E-006-051. The research was also supported in part by the Ministry of Education, Taiwan, under funding provided to the Headquarters of University Advancement to the Intelligent Manufacturing Research Center (iMRC), National Cheng Kung University (NCKU).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringNational Cheng Kung UniversityTainan CityTaiwan

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