论文标题
金属合金粉末床融合加工的多尺度模拟
Multiscale simulation of powder-bed fusion processing of metallic alloys
论文作者
论文摘要
我们提供了一个计算框架，用于对金属合金的粉末状融合进行仿真，其中结合了：（1）calphad计算温度依赖性合金性能和相图，（2）宏观有限元（Fe）材料添加和融合的热模拟，以及（3）Microscopic Phopific相位（PF）solidequip pool simalification in soperification in soluce pool ins soper pool pool pool pool pool pool pool pool pool。该方法用于模拟Inconel 718合金的选择性激光熔融（SLM），使用现实的处理参数。我们讨论了依赖温度的特性的影响以及对粉末床和宏观热模拟中致密材料之间不同特性的重要性。使用通过FE模拟计算的热场的二维纵向切片，我们在整个熔体池的尺度上进行了适当的PF固化模拟，导致计算超过十亿个网格点，但在单个群集节点上执行了具有八个图形处理单元（GPUS）的单个集群节点（GPU）。这些显微镜模拟通过在现实的SLM条件下通过多晶增长竞争提供了对谷物纹理选择的新见解，并具有一定程度的细节。
We present a computational framework for the simulations of powder-bed fusion of metallic alloys, which combines: (1) CalPhaD calculations of temperature-dependent alloy properties and phase diagrams, (2) macroscale finite element (FE) thermal simulations of the material addition and fusion, and (3) microscopic phase-field (PF) simulations of solidification in the melt pool. The methodology is applied to simulate the selective laser melting (SLM) of an Inconel 718 alloy using realistic processing parameters. We discuss the effect of temperature-dependent properties and the importance of accounting for different properties between the powder bed and the dense material in the macroscale thermal simulations. Using a two-dimensional longitudinal slice of the thermal field calculated via FE simulations, we perform an appropriately-converged PF solidification simulation at the scale of the entire melt pool, resulting in a calculation with over one billion grid points, yet performed on a single cluster node with eight graphics processing units (GPUs). These microscale simulations provide new insight into the grain texture selection via polycrystalline growth competition under realistic SLM conditions, with a level of detail down to individual dendrites.
