Fast and efficient simulations of metal additive manufacturing (AM) processes are highly relevant to exploring the full potential of this promising manufacturing technique. The microstructure composition plays an important role in characterizing the part quality and deriving mechanical properties. When complete parts are simulated, one often needs to resort to strong simplifications such as layer-wise heating due to the large number of simulated time steps compared to the small time step sizes. This article proposes a scan-resolved approach to the coupled thermo-microstructural problem. Building on a highly efficient thermal model, we discuss the implementation of a phenomenological microstructure model for the evolution of the three main constituents of Ti-6Al-4V: stable $\alpha_s$-phase, martensite $\alpha_m$-phase and $\beta$-phase. The implementation is tailored to modern hardware features using vectorization and fast approximations of transcendental functions. A performance model and numerical examples verify the high degree of optimization. We demonstrate the applicability and predictive power of the approach and the influence of scan strategy and geometry. Depending on the specific example, results can be obtained with moderate computational resources in a few hours to days. The numerical examples include a prediction of the microstructure on the full NIST AM Benchmark cantilever specimen.

翻译：金属增材制造过程的快速高效模拟对于探索这一有前景制造技术的全部潜力至关重要。微观结构组成在表征部件质量和推导力学性能方面发挥着重要作用。当模拟完整部件时，由于模拟时间步长数量庞大而时间步长尺寸较小，通常需要采用强烈的简化方法，例如逐层加热。本文提出了一种针对热-微观结构耦合问题的扫描解析方法。基于一个高效的热模型，我们讨论了一种现象学微观结构模型的实现，该模型用于描述Ti-6Al-4V三种主要成分的演变：稳定的$\alpha_s$相、马氏体$\alpha_m$相和$\beta$相。该实现针对现代硬件特性进行了定制，利用了矢量化技术和超越函数的快速近似。性能模型和数值示例验证了其高度优化性。我们展示了该方法的适用性和预测能力，以及扫描策略和几何形状的影响。根据具体示例，使用适中的计算资源可在数小时到数天内获得结果。数值示例包括对完整NIST AM基准悬臂梁试样的微观结构预测。