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Implicit large-eddy simulation of compressible flows using the Interior Embedded Discontinuous Galerkin method

机译:使用内部嵌入不连续Galerkin方法对可压缩流动的隐式大涡模拟

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摘要

We present a high-order implicit large-eddy simulation (ILES) approach for simulating transitional turbulent\udflows. The approach consists of an Interior Embedded Discontinuous Galerkin (IEDG) method for the discretization of the compressible Navier-Stokes equations and a parallel preconditioned Newton-GMRES solver for the resulting nonlinear system of equations. The IEDG method arises from the marriage of the Embedded Discontinuous Galerkin (EDG) method and the Hybridizable Discontinuous Galerkin (HDG) method.\udAs such, the IEDG method inherits the advantages of both the EDG method and the HDG method to make itself well-suited for turbulence simulations. We propose a minimal residual Newton algorithm for solving the nonlinear system arising from the IEDG discretization of the Navier-Stokes equations. The preconditioned GMRES algorithm is based on a restricted additive Schwarz (RAS) preconditioner in conjunction with a block incomplete LU factorization at the subdomain level. The proposed approach is applied to the ILES of transitional turbulent flows over a NACA 65-(18)10 compressor cascade at Reynolds number 250,000 in both design and off-design conditions. The high-order ILES results show good agreement with a subgrid-scale LES model discretized with a second-order finite volume code while using significantly less degrees of freedom. This work shows that high-order accuracy is key for predicting transitional turbulent flows without a SGS model.
机译:我们提出了一种用于模拟过渡湍流\溢流的高阶隐式大涡模拟(ILES)方法。该方法由用于可压缩Navier-Stokes方程离散化的内部嵌入式间断Galerkin(IEDG)方法和用于所得非线性方程组的并行预处理Newton-GMRES求解器组成。 IEDG方法源于嵌入式不连续Galerkin(EDG)方法和可混合不连续Galerkin(HDG)方法的结合。适用于湍流模拟。我们提出了一种最小残留牛顿算法,用于求解由Navier-Stokes方程的IEDG离散化产生的非线性系统。预处理GMRES算法基于受限加性Schwarz(RAS)预处理器以及子域级别的块不完全LU分解。在设计和非设计条件下,该方法均适用于雷诺数为250,000的NACA 65-(18)10压缩机级联上的过渡湍流ILES。高阶ILES结果表明,与使用二阶有限体积代码离散化的亚网格规模LES模型具有良好的一致性,而使用的自由度却少得多。这项工作表明,在没有SGS模型的情况下,高阶精度是预测过渡湍流的关键。

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