Powder spreading precedes creation of every new layer in powder bed additive manufacturing (AM). The powder spreading process can lead to powder layer defects such as porosity, poor surface roughness and particle segregation. Therefore, the creation of homogeneous layers is the first task for optimal part printing. Discrete element methods (DEM) powder spreading simulations are typically limited to a single layer and/or small number of particles. Therefore, results from such model configurations may not be generalized to multiple layer processes. In this study, a computationally efficient multi-layer powder spreading DEM simulation model is proposed. The model is calibrated experimentally using static Angle of Repose measurements. The adhesion model parameter, cohesive energy density is related to adhesive surface energy and strain energy release rate parameters. The model results show that interaction between particle and the powder spreading rake leads to noticeable variation in packing density, surface roughness, dynamic angle of repose (AOR), particle size distribution, and particle segregation. The powder model is experimentally validated using a recoater spreading rig to measure the dynamic AOR at spreading speeds consistent with recoating speeds and layer heights used in AM processes.

在粉末床增材制造（AM）中，粉末铺展先于每个新层的创建。粉末散布过程会导致粉末层缺陷，例如孔隙率，不良的表面粗糙度和颗粒偏析。因此，创建均质层是实现最佳零件打印的首要任务。离散元素方法（DEM）粉末散布模拟通常限于单层和/或少量颗粒。因此，这种模型配置的结果可能不会推广到多层过程。在这项研究中，提出了一种计算效率高的多层粉末铺展DEM仿真模型。使用静态休止角测量值通过实验对模型进行校准。附着力模型参数 内聚能密度与粘合剂表面能和应变能释放速率参数有关。模型结果表明，颗粒与粉末散布耙之间的相互作用导致堆积密度，表面粗糙度，动态休止角（AOR），颗粒尺寸分布和颗粒分离明显变化。粉末模型通过使用重涂机铺展装置进行实验验证，以在与AM工艺中使用的重涂速度和层高一致的铺展速度下测量动态AOR。