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Fast Spherical Centroidal Voronoi Mesh Generation: A Lloyd-preconditioned LBFGS Method in Parallel

机译:快速球形中心Voronoi网格生成:a   Lloyd预处理LBFGs方法并行

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摘要

Centroidal Voronoi tessellation (CVT)-based mesh generation is a veryeffective technique for creating high-quality Voronoi meshes and their dualDelaunay triangulations that often play a crucial role in applications,including ocean and atmospheric simulations using finite volume schemes. In thenext generation climate models, the spacing scales change dramatically acrossthe whole sphere and require ultra-high resolution and smooth transitions fromcoarse to fine grid regions. Thus fast and robust spherical CVT (SCVT) meshingalgorithms become highly desirable. In this paper, we first propose aLloyd-preconditioned limited-memory BFGS method for constructing SCVTs that isalso applicable to the construction of CVTs of general domains. This method isthen parallelized based on overlapping domain decomposition, enabling excellentscalability on distributed systems. Results of several computationalexperiments show that the new method could incur computational time costs oneorder of magnitude smaller compared with some existing methods for generatinglarge-scale highly variable-resolution meshes, while also providingsignificantly improvements in mesh quality.
机译:基于质心Voronoi细分(CVT)的网格生成是创建高质量Voronoi网格及其DualDelaunay三角剖分的非常有效的技术,它们经常在应用程序中发挥关键作用,包括使用有限体积方案的海洋和大气模拟。在下一代气候模型中,间隔尺度在整个球体中发生巨大变化,需要超高分辨率和从粗到细网格区域的平滑过渡。因此,快速和鲁棒的球形CVT(SCVT)网格划分算法变得非常理想。在本文中,我们首先提出一种用劳埃德预处理的有限内存BFGS方法构造SCVT,该方法也适用于通用域CVT的构造。然后,该方法基于重叠域分解而并行化,从而在分布式系统上具有出色的可伸缩性。若干计算实验的结果表明,与一些现有的生成大规模高可变分辨率网格的方法相比,该新方法可以使计算时间成本小一个数量级,同时还可以显着提高网格质量。

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