论文标题
一个新的基于ODE的湍流墙模型,占压力梯度和雷诺数的影响
A new ODE-based turbulence wall model accounting for pressure gradient and Reynolds number effects
论文作者
论文摘要
在壁模型的大涡模拟(WMLES)中,近壁模型在预测皮肤摩擦方面起着重要作用,尽管大多数边界层通过外部大涡模拟(LES)求解器解决。在这项工作中,我们旨在开发一种新的普通微分方程(ODE)的墙模型,该模型与经典平衡模型一样简单,但能够捕获非平衡效应和较低的雷诺数效应。提出的模型通过引入新的非二维混合长度函数来重新制定经典平衡模型。新的混合长度函数是用边界层形状因子而不是常用的压力梯度参数来参数化的。结果,新引入的混合长度函数在粘性子层,缓冲层和日志区域内表现出很大的普遍性(即$ 0 <y <0.1Δ$,其中通常将壁模型部署在WMELS设置中)。新模型的性能通过预测摩擦雷诺数在200到5200之间的广泛规范流,以及与经典平衡壁模型相比,与经典平衡壁模型相比,新模型可获得较大的差异,而新模型可获得显着的差异。此外,由于新模型是基于ODE的,因此可以简单地将其用于预测具有复杂几何形状的流量,因此对于广泛的应用程序有望。
In wall-modeled large-eddy simulations (WMLES), the near-wall model plays a significant role in predicting the skin friction, although the majority of the boundary layer is resolved by the outer large-eddy simulation (LES) solver. In this work, we aim at developing a new ordinary differential equation (ODE)-based wall model, which is as simple as the classical equilibrium model yet capable of capturing non-equilibrium effects and low Reynolds number effects. The proposed model reformulates the classical equilibrium model by introducing a new non-dimensional mixing-length function. The new mixing-length function is parameterized in terms of the boundary layer shape factor instead of the commonly used pressure-gradient parameters. As a result, the newly introduced mixing-length function exhibits great universality within the viscous sublayer, the buffer layer, and the log region (i.e., $0 < y < 0.1δ$, where the wall model is typically deployed in a WMLES setup). The performance of the new model is validated by predicting a wide range of canonical flows with the friction Reynolds number between 200 and 5200, and the Clauser pressure-gradient parameter between -0.3 and 4. Compared to the classical equilibrium wall model, remarkable error reduction in terms of the skin friction prediction is obtained by the new model. Moreover, since the new model is ODE-based, it is straightforward to be deployed for predicting flows with complex geometries and therefore promising for a wide range of applications.