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Parallelization of Unsteady Adaptive Mesh Refinement for Unstructured Navier-Stokes Solvers

机译:非结构化Navier-Stokes解算器的非稳态自适应网格细化的并行化

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This paper explores the implementation of MPI parallelization in an unstructured Navier-Stokes solver. It uses dynamic adaptive mesh refinement of hexahedral cells to increase grid density in regions with strong gradients. Implicit and explicit time advancement methods are considered. Distributed implementation of the Data-Parallel Line Relaxation implicit operator is discussed for grids with hanging nodes. Parallel performance of simulations for an unsteady, inviscid flow are examined for both adapted and unadapted meshes in order to provide a baseline for comparison. Relative costs for adaptation and time stepping provide insight into computational bottlenecks. The flow solver and methods presented here are validated with data from a double cone experiment in hypersonic flow. For a given level of accuracy, adapted grids provide predictions that are less expensive than those obtained on unadapted grids for this staple test problem. Unsteady adaptation provides considerable savings for all problems considered.
机译:本文探讨了非结构化Navier-Stokes求解器中MPI并行化的实现。它使用六面体单元的动态自适应网格细化来增加具有强梯度的区域中的网格密度。考虑了隐式和显式时间提前方法。对于带有悬挂节点的网格,讨论了数据并行线松弛隐式运算符的分布式实现。为适应和不适应的网格检查了不稳定,不粘流的仿真的并行性能,以便为比较提供基线。适应和时间步长的相对成本提供了对计算瓶颈的洞察力。本文介绍的流动求解器和方法已通过高超声速双锥实验数据进行了验证。对于给定的精度水平,经过调整的网格所提供的预测要比针对该常规测试问题在未经调整的网格上获得的预测便宜。不稳定的适应可为所有考虑到的问题节省大量资金。

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