融合
材料科学
激光器
粒子(生态学)
粒径
惯性约束聚变
核工程
复合材料
光学
化学工程
物理
语言学
海洋学
地质学
工程类
哲学
标识
DOI:10.1016/j.optlastec.2022.108402
摘要
• Laser particle interactions were studied in L-PBF. • The effect of powder bed thickness on the energy distribution was studied. • New heat source model was proposed based on laser and particle features. The use of powder is one of the special features in laser powder bed fusion additive manufacturing (L-PBF AM). How the powder affects the L-PBF process is the basic mechanism determining the accurate prediction of the melt pool and the temperatures in finite element heat transfer simulations. The laser is treated as electromagnetic wave essentially and the powder particles can be heated by the formation of the inducted current on the particle surfaces. The laser energy density absorbed by the powder particles was calculated based on the laser-particle interaction. Based on the statistical analysis of particles in spatial distribution, the new volumetric heat source model was obtained and then applied to finite element heat transfer simulations. Results indicate that the temperature rise of the individual particle is not uniform and relates to the distribution of electromagnetic energy density on the surface of particles. The distribution of electromagnetic energy density on the surface of the individual particle at different positions is different. The energy absorbed by the upper particles is mainly determined by the direct irradiation of the laser. The energy absorbed by the bottom particles is mainly caused by the laser reflections. Due to the change of the mechanism for energy absorption, the maximum energy absorption occurs at the location which is near the average diameter away from the top surface of the powder bed. When the powder bed thickness is small, the laser energy density along build direction is in Gaussian distribution. With the increase of the powder bed thickness, the laser energy density distribution along build direction can be fit for 4-order polynomial function.
科研通智能强力驱动
Strongly Powered by AbleSci AI