arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2010.02166math.NAcs.NA
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基于目标矩阵optimization范式的高阶网格的hr-自适应性

hr-adaptivity for nonconforming high-order meshes with the target matrix optimization paradigm

Veselin Dobrev, Patrick Knupp, Tzanio Kolev, Ketan Mittal, Vladimir Tomov

摘要:

我们提出了一个$hr$ -自适应框架优化高阶网格。这项工作扩展了Dobrev等人的网格优化的$r$自适应方法,其中,我们利用目标矩阵优化范式(TMOP)来最小化取决于每个元素的当前和目标几何参数的函数:元素纵横比,大小,偏斜和方向。由于固定的网格拓扑结构限制了在每个位置实现目标尺寸和纵横比的能力,在本文中,我们增加了$r$自适应框架与自适应网格细化,以进一步减少相对于目标几何参数的误差。所提出的配方,称为$hr$自适应,引入TMOP为基础的质量估计,以满足纵横比目标通过各向异性的细化和大小目标通过各向同性的细化在每个元素的网格。所提出的方法是纯代数的,扩展到单形和六面体/四边形的任何顺序,并支持在2D和3D的各向同性和各向异性的细化。使用一个已知的精确解的问题,我们证明了$hr$的有效性,自适应超过$r-$和$h$ -自适应在获得类似的精度的解决方案,具有显着更少的自由度。我们还提出了几个例子表明,$hr$ -自适应可以帮助满足几何目标,即使当$r$ -自适应无法做到这一点,由于初始网格的拓扑结构。

英文摘要:

We present an $hr$-adaptivity framework for optimization of high-order meshes. This work extends the $r$-adaptivity method for mesh optimization by Dobrev et al., where we utilized the Target-Matrix Optimization Paradigm (TMOP) to minimize a functional that depends on each element's current and target geometric parameters: element aspect-ratio, size, skew, and orientation. Since fixed mesh topology limits the ability to achieve the target size and aspect-ratio at each position, in this paper we augment the $r$-adaptivity framework with nonconforming adaptive mesh refinement to further reduce the error with respect to the target geometric parameters. The proposed formulation, referred to as $hr$-adaptivity, introduces TMOP-based quality estimators to satisfy the aspect-ratio-target via anisotropic refinements and size-target via isotropic refinements in each element of the mesh. The methodology presented is purely algebraic, extends to both simplices and hexahedra/quadrilaterals of any order, and supports nonconforming isotropic and anisotropic refinements in 2D and 3D. Using a problem with a known exact solution, we demonstrate the effectiveness of $hr$-adaptivity over both $r-$ and $h$-adaptivity in obtaining similar accuracy in the solution with significantly fewer degrees of freedom. We also present several examples that show that $hr$-adaptivity can help satisfy geometric targets even when $r$-adaptivity fails to do so, due to the topology of the initial mesh.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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