A new method for the simulation of evolving multi-domains problems has been introduced in a previous work (RealIMotion), Florez et al. (2020). In this article further developments of the model will be presented. The main focus here is a robust parallel implementation using a distributed-memory approach with the Message Passing Interface (MPI) library OpenMPI. The original 2D sequential methodology consists in a modified front-tracking approach where the main originality is that not only interfaces between domains are discretized but their interiors are also meshed. The interfaces are tracked based on the topological degree of each node on the mesh and the remeshing and topological changes of the domains are driven by selective local operations performed over an element patch. The accuracy and the performance of the sequential method has proven very promising in Florez et al. (2020). In this article a parallel implementation will be discussed and tested in context of motion by curvature flow for polycrystals, i.e. by considering Grain Growth (GG) mechanism. Results of the performance of the model are given and comparisons with other approaches in the literature are discussed.

中文翻译：

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一种用于大规模多域模拟的新型高效拉格朗日模型：并行上下文

Florez 等人在之前的工作 (RealIMotion) 中引入了一种用于模拟不断发展的多域问题的新方法。(2020)。本文将介绍该模型的进一步发展。这里的主要重点是使用分布式内存方法和消息传递接口 (MPI) 库 OpenMPI 的强大并行实现。原始的 2D 顺序方法包括一种改进的前向跟踪方法，其中主要的独创性是不仅域之间的界面被离散化，而且它们的内部也被网格化。界面根据网格上每个节点的拓扑度进行跟踪，域的重新网格划分和拓扑变化由在元素补丁上执行的选择性局部操作驱动。Florez 等人证明了顺序方法的准确性和性能非常有前途。(2020)。在本文中，将在多晶曲率流运动的背景下讨论和测试并行实现，即通过考虑晶粒生长 (GG) 机制。给出了模型的性能结果，并讨论了与文献中其他方法的比较。