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Fast spherical centroidal Voronoi mesh generation: A Lloyd-preconditioned LBFGS method in parallel

机译:快球状质心Voronoi网格生成:一个Lloyd-preconditeded LBFGS方法并行

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Centroidal Voronoi tessellation (CVT)-based mesh generation is a very effective technique for creating high-quality Voronoi meshes and their dual Delaunay triangulations that often play a crucial role in applications, including ocean and atmospheric simulations using finite volume schemes. In the next generation climate models, the spacing scales change dramatically across the whole sphere and require ultra-high resolution and smooth transitions from coarse to fine grid regions. Thus fast and robust spherical CVT (SCVT) meshing algorithms become highly desirable. In this paper, we first propose a Lloydpreconditioned limited-memory BFGS method for constructing SCVTs that is also applicable to the construction of CVTs of general domains. This method is then parallelized based on overlapping domain decomposition, enabling excellent scalability on distributed systems. Results of several computational experiments show that the new method could incur computational time costs one order of magnitude smaller compared with some existing methods for generating large-scale highly variable-resolution meshes, while also providing significant improvements in mesh quality. (C) 2018 Elsevier Inc. All rights reserved.
机译:基于Civroidal Voronoi Tessellation(CVT)的网格产生是一种非常有效的技术,用于创造高质量的voronoi网格及其双德拉尼亚三角形,通常在应用中发挥至关重要的作用,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,间距尺度在整个球体上急剧变化,并且需要超高分辨率和从粗糙度到细网区域的平滑过渡。因此,快速且坚固的球形CVT(SCVT)网格化算法变得非常希望。在本文中,我们首先提出了一种Lloydecroconded-Memory的BFGS方法,用于构建SCVTS,该方法也适用于施工总域的CVT。然后基于重叠域分解并行化该方法,从而在分布式系统上实现了出色的可扩展性。几个计算实验的结果表明,与生成大规模高度变量分辨率网格的一些现有方法相比,新方法可能会使计算时间较小,其数量级较小,同时还提供了对网格质量的显着改进。 (c)2018年Elsevier Inc.保留所有权利。

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