In this paper we propose a robust adaptation method for hybrid mesh including both refinement and coarsening. Elements of different types are refined through isotropic subdivision in a similar way. Their unrefined neighbours are converted to polyhedrons, which benefits to localize mesh refinement. Mesh elements are coarsened by reversing refinement based on a multi-levels data structure. Elements subdivision can be conducted in entirely parallel mode by introducing a non-overlap number range for each processor. Then feature data is devised to recover the uniqueness of new ghost points and elements through parallel communication. A repartition-migration method is adopted to rebalance the computing load. We illustrate our method by an application of flow simulation. With mesh adaptation, the structures of shocks and vortices are resolved better.

在本文中，我们提出了一种鲁棒的混合网格自适应方法，包括细化和粗化。通过各向同性细分以类似方式细化不同类型的元素。它们的未精炼邻居被转换为多面体，这有利于局部化网格细化。通过基于多级数据结构的逆向细化来粗化网格元素。通过为每个处理器引入一个非重叠数范围，可以在完全并行模式下进行元素细分。然后设计特征数据，以通过并行通信恢复新幻影点和元素的唯一性。采用分区迁移的方法来重新平衡计算负载。我们通过应用流模拟来说明我们的方法。通过网格自适应，可以更好地解决震动和漩涡的结构。