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On the interaction between dynamic model dissipation and numerical dissipation due to streamline upwind/Petrov-Galerkin stabilization

机译:流线型上风/ Petrov-Galerkin稳定引起的动力模型耗散与数值耗散之间的相互作用

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Here we investigate the roles of physical and numerical subgrid-scale modeling. The subgrid-scales are represented by a physical large-eddy simulation model, namely the popular dynamic Smagorinsky model (or simply dynamic model), as well as by a numerical model in the form of the well-known streamline upwind/Petrov-Galerkin stabilization for finite element discretizations of advection-diffusion systems. The latter is not a physical model, as its purpose is to provide sufficient algorithmic dissipation for a stable, consistent, and convergent numerical method. We study the interaction between the physical and numerical models by analyzing energy dissipation associated to the two. Based on this study, a modification to the dynamic model is proposed as a way to discount the numerical method's algorithmic dissipation from the total subgrid-scale dissipation. The modified dynamic model is shown to be successful in simulations of turbulent channel flow.
机译:在这里,我们研究物理和数值子网格规模建模的作用。子网格规模由物理大涡模拟模型表示,即流行的动态Smagorinsky模型(或简称为动态模型),以及以众所周知的流线上风/ Petrov-Galerkin稳定形式的数值模型表示用于对流扩散系统的有限元离散化。后者不是物理模型,因为其目的是为稳定,一致和收敛的数值方法提供足够的算法耗散。我们通过分析与两者相关的能量耗散来研究物理模型和数值模型之间的相互作用。在此基础上,提出了对动态模型的修正,作为从总子网格规模耗散中减去数值方法的算法耗散的一种方法。改进后的动力学模型在湍流通道流动的模拟中被证明是成功的。

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