Prediction of lack-of-fusion porosity in laser powder-bed fusion considering boundary conditions and sensitivity to laser power absorption

This paper proposes an analytical modeling method for the prediction of lack-of-fusion porosity of parts fabricated by laser powder-bed fusion (LPBF), with the consideration of boundary heat transfer and sensitivity to laser power absorption. The temperature distribution of the part was first predicted by an analytical thermal model, which consists of a linear heat source solution and a heat sink solution. The temperature increase due to laser power input was calculated by the point moving heat source solution. The temperature drop due to thermal conduction, convection, and radiation at part boundaries was calculated by the heat sink solution. The coefficient of laser power absorption was inversely obtained by comparing predicted molten pool widths with experimental measurements. The lack-of-fusion area was then calculated by plotting molten pool shapes of multi-tracks and multi-layers on a transverse cross-sectional area of the part. The powder bed porosity was calculated by an advancing front method with the consideration of powder size distribution and packing pattern. Finally, the lack-of-fusion porosity was obtained by multiplying the lack-of-fusion area with powder bed porosity. The predicted results were close to the measurements of Ti6Al4V in LPBF. The maximum deviation for porosity prediction is 5.91%. The presented model shows high computational efficiency without relying on iteration-based numerical method. The computational time for five consecutive layers is less than 100 s. The acceptable accuracy, short computational time, and the ability to consider complex boundary effects make the proposed method a good basis for future research and a promising tool for optimization of process parameters in LPBF of complex parts.

Automated summary

This study proposes an analytical modeling method for predicting lack-of-fusion porosity in parts fabricated by LPBF, taking into account boundary heat transfer and laser power absorption sensitivity. The model accurately predicts temperature distribution and porosity by considering complex boundary effects, demonstrating high computational efficiency and accuracy. The method has the potential to be a valuable tool for optimizing process parameters in LPBF.