论文标题
使用随机的一维湍流将被动标量转移到墙壁的预测建模
Predictive modeling of passive scalar transfer to a wall using stochastic one-dimensional turbulence
论文作者
论文摘要
湍流通道流中的被动标量被研究为湍流边界层流中热和传质的规范问题。一维的湍流模型用于数字研究施密特和雷诺数的数字依赖性，而标量转移到壁上的依赖性由于波动的壁正常运输。首先，对低阶速度统计进行校准该模型。之后，我们将模型参数固定并研究相关的Schmidt和Reynolds数字范围的低阶被动标量统计。我们表明，该模型始终预测边界层结构和缩放模式，其接近渐近的一维理论。
Passive scalars in turbulent channel flows are investigated as canonical problem for heat and mass transfer in turbulent boundary-layer flows. The one-dimensional turbulence model is used to numerically investigate the Schmidt and Reynolds number dependence of the scalar transfer to a wall due to fluctuating wall-normal transport. First, the model is calibrated for low-order velocity statistics. After that, we keep the model parameters fixed and investigate low-order passive scalar statistics for a relevant Schmidt and Reynolds number range. We show that the model consistently predicts the boundary layer structure and the scaling regimes, for which it is close to asymptotic one-dimensional theory.
