A massively-parallel, unstructured overset method for mesh connectivity

被引:25
|
作者
Horne, Wyatt James [1 ]
Mahesh, Krishnan [1 ]
机构
[1] Univ Minnesota, Dept Aerosp Engn & Mech, Minneapolis, MN 55414 USA
关键词
Overset; Unstructured; O(hundred thousand) meshes; Connectivity; Dynamic; Parallel; DIRECT NUMERICAL-SIMULATION;
D O I
10.1016/j.jcp.2018.09.053
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We present a method that dynamically and efficiently performs connectivity calculations between many (O(10(5))) moving, unstructured overset meshes in parallel. In order to connect overset meshes, elements exterior to the solution domain must be removed from the simulation. In regions with many overlapping meshes, elements must be selectively removed to reduce redundancy while maintaining a solution over the entire domain. Around masked regions interpolation partner pairing is required between meshes to provide boundary conditions. For general unstructured meshes, these steps involve challenging computational geometry calculations which must be efficient and automatic. For many moving meshes each step must be massively parallelized and scalable to large numbers of computational cores. To establish communication patterns a parallelized master/slave algorithm is used which minimizes global communication and storage. To remove elements a parallel 'Forest Fire' flood-fill algorithm is used to set a masking variable. For interpolation partner pairing, and other necessary searches, k-dimensional tree data structures (k-d trees) are extensively used. Often in a calculation, the connectivity between overset meshes remains largely the same between time steps. The temporal coherence of the various objects in the connectivity calculation is directly used to only update necessary information with time, resulting in substantial cost savings. Details of the different algorithms are presented. Resulting connectivity and timings are shown for complex geometries. Parallel scaling is demonstrated for 100,000 spherical particles within a channel up to 492,000 processors. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:585 / 596
页数:12
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