Yang Xiang I A, Abkar Mahdi
Center for Turbulence Research, Stanford University, Stanford, CA 94305, USA.
Mechanical and Nuclear Engineering, Penn State University, State College, PA 16801, USA.
J Fluid Mech. 2018 May 10;842:354-380. doi: 10.1017/jfm.2018.139.
The kinematics of a fully developed passive scalar is modelled using the hierarchical random additive process (HRAP) formalism. Here, 'a fully developed passive scalar' refers to a scalar field whose instantaneous fluctuations are statistically stationary, and the 'HRAP formalism' is a recently proposed interpretation of the Townsend attached eddy hypothesis. The HRAP model was previously used to model the kinematics of velocity fluctuations in wall turbulence: , where the instantaneous streamwise velocity fluctuation at a generic wall-normal location is modelled as a sum of additive contributions from wall-attached eddies ( ) and the number of addends is ~ log(/). The HRAP model admits generalized logarithmic scalings including 〈 〉~log(/), 〈()(+ )〉 ~ log(/ ), 〈(() - (+ ))〉 ~ log( /), where is the streamwise velocity fluctuation, is an outer length scale, is the two-point displacement in the streamwise direction and 〈·〉 denotes ensemble averaging. If the statistical behaviours of the streamwise velocity fluctuation and the fluctuation of a passive scalar are similar, we can expect first that the above mentioned scalings also exist for passive scalars (i.e. for being fluctuations of scalar concentration) and second that the instantaneous fluctuations of a passive scalar can be modelled using the HRAP model as well. Such expectations are confirmed using large-eddy simulations. Hence the work here presents a framework for modelling scalar turbulence in high Reynolds number wall-bounded flows.
利用分层随机加法过程(HRAP)形式体系对充分发展的被动标量的运动学进行建模。这里,“充分发展的被动标量”指的是一个标量场,其瞬时涨落在统计上是平稳的,而“HRAP形式体系”是最近提出的对汤森德附着涡假设的一种解释。HRAP模型先前被用于对壁面湍流中速度涨落的运动学进行建模: ,其中在一般壁面法向位置处的瞬时流向速度涨落被建模为来自附着于壁面的涡( )的加法贡献之和,并且加数的数量为 ~ log(/)。HRAP模型允许广义对数标度,包括〈 〉~log(/),〈()(+ )〉 ~ log(/ ),〈(() - (+ ))〉 ~ log( /),其中 是流向速度涨落, 是外部长度尺度, 是流向方向上的两点位移,〈·〉表示系综平均。如果流向速度涨落和被动标量涨落的统计行为相似,我们首先可以预期上述标度对于被动标量也存在(即对于 是标量浓度的涨落),其次可以预期被动标量的瞬时涨落也可以用HRAP模型进行建模。通过大涡模拟证实了这些预期。因此,这里的工作提出了一个用于对高雷诺数壁面边界流中的标量湍流进行建模的框架。