Grain growth is a well-known and complex phenomenon occurring during annealing of all polycrystalline materials. Its numerical modeling is a complex task when anisotropy sources such as grain orientation and grain boundary inclination have to be taken into account. This article presents the application of the front-tracking methodology ToRealMotion introduced in previous works, to the context of anisotropic grain boundary motion at the mesoscopic scale. The new formulation of boundary migration can take into account any source of anisotropy both at grain boundaries as well as at multiple junctions (MJs) (intersection point of three or more grain boundaries). Special attention is given to the decomposition of high-order MJs for which an algorithm is proposed based on local grain boundary energy minimisation. Numerical tests are provided using highly heterogeneous configurations, and comparisons with a recently developed Finite-Element Level-Set (FE-LS) approach are given. Finally, the computational performance of the model will be studied comparing the CPU-times obtained with the same model but in an isotropic context.

中文翻译：

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用于模拟各向异性晶粒生长的二维前跟踪拉格朗日模型

晶粒生长是一种众所周知的复杂现象，发生在所有多晶材料的退火过程中。当必须考虑晶粒取向和晶界倾角等各向异性来源时，其数值建模是一项复杂的任务。本文介绍了在先前工作中引入的前向跟踪方法 ToRealMotion 在介观尺度上的各向异性晶界运动的背景下的应用。边界迁移的新公式可以考虑晶界和多个结点 (MJ)（三个或更多晶界的交点）处的任何各向异性来源。特别注意高阶 MJ 的分解，为此提出了一种基于局部晶界能量最小化的算法。使用高度异构的配置提供了数值测试，并给出了与最近开发的有限元水平集 (FE-LS) 方法的比较。最后，将比较使用相同模型但在各向同性环境中获得的 CPU 时间来研究模型的计算性能。