Keyhole-induced porosities in Laser-based Powder Bed Fusion (L-PBF) of Ti6Al4V: High-fidelity modelling and experimental validation

By M. Bayat, Aditi Thanki, Sankhya Mohanty, Ann Witvrouw, Shoufeng Yang, J. Thorborg, N. Tiedje, Jesper Henri Hattel. Additive Manufacturing, 2019

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Abstract Metal additive manufacturing, despite of offering unique capabilities e.g. unlimited design freedom, short manufacturing time, etc., suffers from raft of intrinsic defects. Porosity is of the defects which can badly deteriorate a part’s performance. In this respect, enabling one to observe and predict the porosity during this process is of high importance. To this end, in this work a combined numerical and experimental approach has been used to analyze the formation, evolution and disappearance of keyhole and keyhole-induced porosities along with their initiating mechanisms, during single track L-PBF of a Ti6Al4V alloy. In this respect, a high-fidelity numerical model based on the Finite Volume Method (FVM) and accomplished in the commercial software Flow-3D is developed. The model accounts for the major physics taking place during the laser-scanning step of the L-PBF process. To better simulate the actual laser-material interaction, multiple reflection with the ray-tracing method has been implemented along with the Fresnel absorption function. The results show that during the keyhole regime, the heating rises dramatically compared to the shallow-depth melt pool regime due to the large entrapment of laser rays in the keyhole cavities. Also a detailed parametric study is performed to investigate the effect of input power on thermal absorptivity, heat transfer and melt pool anatomy. Furthermore, an X-ray Computed Tomography (X-CT) analysis is carried out to visualize the pores formed during the L-PBF process. It is shown, that the predicted shape, size and depth of the pores are in very good agreement with those found by either X-CT or optical and 3D digital microscopic images.

Subfields: Automotive Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/498a4db6073e19b3a30e0b81271584d05e5f10b3

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In Mechanical Engineering

  1. D. Gu
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