Mesh adaptivity is a useful tool for efficient solution to partial differential equations in very complex geometries. In the present paper we discuss the use of polygonal mesh refinement in order to tackle two common issues: first, adaptively refine a provided good quality polygonal mesh preserving quality, second, improve the quality of a coarse poor quality polygonal mesh during the refinement process on very complex domains. For finite element methods and triangular meshes, convergence of a posteriori mesh refinement algorithms and optimality properties have been widely investigated, whereas convergence and optimality are still open problems for polygonal adaptive methods. In this article, we propose a new refinement method for convex cells with the aim of introducing some properties useful to tackle convergence and optimality for adaptive methods. The key issues in refining convex general polygons are: a refinement dependent only on the marked cells for refinement at each refinement step; a partial quality improvement, or, at least, a non degenerate quality of the mesh during the refinement iterations; a bound of the number of unknowns of the discrete problem with respect to the number of the cells in the mesh. Although these properties are quite common for refinement algorithms of triangular meshes, these issues are still open problems for polygonal meshes
翻译:网状适应性是高效解决非常复杂的地貌中部分差异方程的有用工具。在本文件中,我们讨论如何使用多边形网格改进,以解决两个共同问题:第一,适应性地改进一个高质量的多边形网格,以保持质量;第二,在非常复杂的域的精细过程中,改进一个粗略、质量差的多边形网格网格的质量;对于有限的元素方法和三角网格,已广泛调查了后世网格精细算法和最佳性能的趋同性,而对于多边形适应方法来说,趋同性和最佳性仍然是尚未解决的问题。在本篇文章中,我们提出了一个新的软形细胞改进方法,目的是引入一些有助于解决趋同性和适应方法最佳性的特性。在精细化过程中,一般圆形多边网格的关键问题是:改进仅取决于每个精细化步骤的标记单元格;部分质量改进,至少是改进后的网格质量;对于多边形适应方法来说,趋同性细胞的不为人知的细化性问题。虽然这些是三角形的细微的。