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首页> 外文期刊>International Journal for Numerical Methods in Fluids >Wall modeling via function enrichment within a high-order DG method for RANS simulations of incompressible flow
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Wall modeling via function enrichment within a high-order DG method for RANS simulations of incompressible flow

机译：通过函数富集在不可压缩流量的高阶DG方法中通过功能富集

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摘要

We present a novel approach to wall modeling for the Reynolds-averaged Navier-Stokes equations within the discontinuous Galerkin method. Wall functions are not used to prescribe boundary conditions as usual, but they are built into the function space of the numerical method as a local enrichment, in addition to the standard polynomial component. The Galerkin method then automatically finds the optimal solution among all shape functions available. This idea is fully consistent and gives the wall model vast flexibility in separated boundary layers or high adverse pressure gradients. The wall model is implemented in a high-order discontinuous Galerkin solver for incompressible flow complemented by the Spalart-Allmaras closure model. As benchmark examples, we present turbulent channel flow starting from Re=180 and up to Re=100000 as well as flow past periodic hills at Reynolds numbers based on the hill height of Re-H=10595 and Re-H=19000.
机译：我们在不连续的Galerkin方法中提出了一种新的壁式墙壁建模方法，返回雷诺平均海军 - 斯托克斯方程式。 除了标准多项式组件之外，壁函数不用于像往常一样规定边界条件。 然后，Galerkin方法自动在所有形状功能中找到最佳解决方案。 这个想法完全一致，并为墙体模型在分离的边界层或高压压力梯度方面的巨大灵活性。 墙面模型在高阶不连续的Galerkin求解器中实现，用于由Spalart-Allmaras闭合模型补充的不可压缩流。 作为基准示例，我们呈现从Re = 180开始的动荡的通道流程，并基于RE-H = 10595的山坡高度和RE-H = 19000，在REYNOLDS数字处流过RE = 100000以及流过周期山。

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