Direct Numerical Simulation of Particle Motion in Relation to Structures in the Convective Boundary Layer

2000 ◽  
pp. 37-50 ◽  
Author(s):  
Bas van Haarlem ◽  
Frans T. M. Nieuwstadt
Keyword(s):  
Numerical Simulation ◽  
Boundary Layer ◽  
Direct Numerical Simulation ◽  
Convective Boundary Layer ◽  
Particle Motion ◽  
Convective Boundary

Direct numerical simulation of top-down and bottom-up diffusion in the convective boundary layer

2013 ◽  
Vol 724 ◽  
pp. 581-606 ◽  
Author(s):  
Scott B. Waggy ◽  
Sedat Biringen ◽  
Peter P. Sullivan
Keyword(s):  
Numerical Simulation ◽  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Viscous Sublayer ◽  
Rough Wall ◽  
Smooth Wall ◽  
Top Down ◽  
Convective Boundary ◽  
Bottom Up ◽  
Gradient Function

AbstractA direct numerical simulation (DNS) of an unstably stratified convective boundary layer with system rotation was performed to study top-down and bottom-up diffusion processes. In order to better understand near-wall dynamics associated with scalar diffusion in the absence of surface roughness, direct simulation is utilized to numerically integrate the governing equations that model the atmospheric boundary layer. The ratio of the inversion height to Obukhov length scale, ${z}_{i} / L= - 49. 1$, indicates moderately strong heating for the case studied. Two passive scalars were initialized in the flow field: the first with a zero gradient at the wall (${q}_{t} $, top-down diffusion), and the second with a non-zero wall gradient and a close-to-zero gradient at the height of the temperature inversion (${q}_{b} $, bottom-up diffusion). Scalar flux, variance and covariance profiles show good agreement between the DNS and rough-wall large-eddy simulation (LES). The top-down gradient function displays a slight increase in amplitude, indicating reduced mixing efficiency for the smooth-wall, low-Reynolds-number convective boundary layer. For the bottom-up process, the gradient matches other rough-wall simulations. The only notable difference between the smooth-wall DNS data and other rough-wall simulations is an increase in the gradient function near the wall. This indicates that the bottom-up gradient functions for a rough wall and a smooth wall are nearly identical except as the viscous sublayer is approached. Finally, a new empirical model for the scalar variance of a bottom-up scalar is proposed: here, a single function replaces two piecewise relationships to accurately capture the DNS results up to the viscous sublayer. The scalar covariance between top-down and bottom-up processes agrees with rough-wall and tree-canopy LES results; this indicates that the scalar covariance is independent of both Reynolds number and surface friction.

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