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Supersonic turbulent flow simulation using a scalable parallel modal discontinuous Galerkin numerical method

机译:超音速湍流流动的可扩展并行模态不连续Galerkin数值方法

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摘要

The scalability and efficiency of numerical methods on parallel computer architectures is of prime importance as we march towards exascale computing. Classical methods like finite difference schemes and finite volume methods have inherent roadblocks in their mathematical construction to achieve good scalability. These methods are popularly used to solve the Navier-Stokes equations for fluid flow simulations. The discontinuous Galerkin family of methods for solving continuum partial differential equations has shown promise in realizing parallel efficiency and scalability when approaching petascale computations. In this paper an explicit modal discontinuous Galerkin (DG) method utilizing Implicit Large Eddy Simulation (ILES) is proposed for unsteady turbulent flow simulations involving the three-dimensional Navier-Stokes equations. A study of the method was performed for the Taylor-Green vortex case at a Reynolds number ranging from 100 to 1600. The polynomial order P = 2 (third order accurate) was found to closely match the Direct Navier-Stokes (DNS) results for all Reynolds numbers tested outside of Re = 1600, which had a normalized RMS error of 3.43 × 10−4 in the dissipation rate for a 603 element mesh. The scalability and performance study of the method was then conducted for a Reynolds number of 1600 for polynomials orders from P = 2 to P = 6. The highest order polynomial that was tested (P = 6) was found to have the most efficient scalability using both the MPI and OpenMP implementations.
机译:随着我们向亿亿级计算迈进,并行计算机体系结构上数值方法的可伸缩性和效率至关重要。诸如有限差分方案和有限体积方法之类的经典方法在其数学构造中具有固有的障碍,以实现良好的可伸缩性。这些方法普遍用于求解流体流动模拟的Navier-Stokes方程。求解Petascale计算时,用于求解连续偏微分方程的不连续Galerkin方法系列已显示出实现并行效率和可伸缩性的希望。在本文中,针对涉及三维Navier-Stokes方程的非定常湍流模拟,提出了一种利用隐式大涡模拟(ILES)的显式模态不连续Galerkin(DG)方法。对泰勒-格林涡旋情况下的雷诺数范围为100至1600的方法进行了研究。发现多项式阶数P =(2(三阶精确度)与Direct Navier-Stokes(DNS)结果与在Re = 1600之外测试的所有雷诺数,在60 3 元素网格的耗散率中,均方根误差为3.43×10 −4 。然后针对从P = 2到P = 6的多项式阶数,针对1600的雷诺数进行了该方法的可扩展性和性能研究,发现使用该方法测试的最高阶多项式(P = 6)具有最有效的可扩展性。 MPI和OpenMP实施。

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