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.
翻译:谷物增长是一个众所周知和复杂的现象,它发生在所有聚晶体材料的麻醉过程中,当谷物方向和谷物边界倾角等厌食源必须加以考虑时,其数字模型是一个复杂的任务。本篇文章介绍了以前作品中引入的前跟踪方法“Realmotion To Realmotion”应用到中观规模的厌食谷底线运动的背景中。新的边界迁移配方可以考虑到谷物边界和多关口(三或三个以上谷物边界的交点)的厌食性反应的任何来源。特别注意高序MJ的分解,为此根据当地谷物边界能源的最小化提出了算法。提供数字测试时使用了高度混杂的配置,并与最近开发的Finite-Ementlement level-Set(FE-LS)方法进行了比较。最后,将研究该模型的计算性能,将同同一模型相比,但在异地范围内获得的CPU-时间。