Additive manufacturing techniques such as direct energy deposition (DED) have many advantages over traditional subtractive manufacturing technologies. However, the phenomena associated with the DED process, including the absorption and scattering of the laser radiation in the powder concentration region and substrate, thermal conduction, the formation and solidification of the melt pool, and so on, are extremely complex. As a result, it is difficult to determine the individual effects of the processing parameters on the quality of the final DED parts using experimental methods. Accordingly, the present study proposes a systematic approach for calculating the absorptivity of the laser radiation in the DED process. In the proposed approach, Computational fluid dynamics (CFD) simulations are first performed to establish the dimensions and location of the powder concentration region. The powder mass distribution and number of particles in the concentration region are then attained via self-written MATLAB code. Finally, Monte Carlo ray-tracing simulations are performed to calculate the total powder energy absorptivity of the concentration region. It is shown that the total absorptivity of the whole system, including the substrate region and the powder particles, is in good agreement with the published experimental results. The effects of the powder mass flow rate and powder-gas flow rate on the average absorptivity of the metal powder and substrate are explored. It is shown that the powder energy absorptivity increases with an increasing powder feeding rate, but is insensitive to the powder-gas flow rate. Overall, the results presented in this study provide a useful insight into the initial thermal and state conditions of the powder particles entering the melt pool. As such, the proposed modeling approach plays an important role in performing high-fidelity numerical simulations of the DED process.
|頁（從 - 到）||1765-1776|
|期刊||International Journal of Advanced Manufacturing Technology|
|出版狀態||Published - 2019 十一月 1|
All Science Journal Classification (ASJC) codes