Grain-scale microstructure evolution during additive manufacturing is a complex physical process. As with traditional solidification methods of material processing (e.g. casting and welding), microstructural properties are highly dependent on the solidification conditions involved. Additive manufacturing processes however, incorporate additional complexity such as remelting, and solid-state evolution caused by subsequent heat source passes and by holding the entire build at moderately high temperatures during a build. We present a three-dimensional model that simulates both solidification and solid-state evolution phenomena using stochastic Monte Carlo and Potts Monte Carlo methods. The model also incorporates a finite-difference based thermal conduction solver to create a fully integrated microstructural prediction tool. The three modeling methods and their coupling are described and demonstrated for a model study of laser powder-bed fusion of 300-series stainless steel. The investigation demonstrates a novel correlation between the mean number of remelting cycles experienced during a build, and the resulting columnar grain sizes.

增材制造过程中晶粒尺度的微观结构演变是一个复杂的物理过程。与传统的材料加工凝固方法（例如铸造和焊接）一样，微观结构特性高度依赖于所涉及的凝固条件。但是，增材制造工艺会带来额外的复杂性，例如重熔和后续热源通过以及在建造过程中将整个建造物保持在中等高温下而导致的固态演变。我们提出了一个三维模型，该模型使用随机蒙特卡洛和波茨蒙特卡洛方法来模拟凝固和固态演化现象。该模型还结合了基于有限差分的热传导求解器，以创建完全集成的微结构预测工具。描述并演示了这三种建模方法及其耦合，以用于300系列不锈钢激光粉末床熔合的模型研究。研究表明，在构建过程中经历的平均重熔周期数与所产生的柱状晶粒尺寸之间存在新颖的相关性。