算法995

Juliette Pardue, Andrey N. Chernikov
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引用次数: 0

摘要

从顶点插入和Delaunay三角形的基本操作出发,构建了网格生成器,提出了一种自下而上的并行各向异性网格生成方法。专注于高升力设计或动态失速的应用,或数值方法和建模测试用例,仍然专注于二维领域。这种自动并行网格生成方法可以生成具有各向异性边界层的高保真非结构化网格,用于计算流体力学领域。各向异性要求增加了并行网格算法的复杂性,因为计算依赖于元素的局部对齐,而这又由几何边界和密度函数(由指数分布生成的一维间隔函数)决定。这种方法在网格生成和流动求解中节省了计算量,通过形状良好的各向异性三角形代替各向同性三角形。通过与已验证的参考解的解特征比较,证明了网格的有效性。数值实验表明,该算法在1024个分布式存储节点上的并行弱缩放效率为79%,在512个分布式存储节点上的并行效率为72%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm 995
A bottom-up approach to parallel anisotropic mesh generation is presented by building a mesh generator starting from the basic operations of vertex insertion and Delaunay triangles. Applications focusing on high-lift design or dynamic stall, or numerical methods and modeling test cases, still focus on two-dimensional domains. This automated parallel mesh generation approach can generate high-fidelity unstructured meshes with anisotropic boundary layers for use in the computational fluid dynamics field. The anisotropy requirement adds a level of complexity to a parallel meshing algorithm by making computation depend on the local alignment of elements, which in turn is dictated by geometric boundaries and the density functions— one-dimensional spacing functions generated from an exponential distribution. This approach yields computational savings in mesh generation and flow solution through well-shaped anisotropic triangles instead of isotropic triangles. The validity of the meshes is shown through solution characteristic comparisons to verified reference solutions. A 79% parallel weak scaling efficiency on 1,024 distributed memory nodes, and a 72% parallel efficiency over the fastest sequential isotropic mesh generator on 512 distributed memory nodes, is shown through numerical experiments.
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