Evolution of the scalar dissipation rate downstream of a concentrated line source in turbulent channel flow

2014 ◽  
Vol 749 ◽  
pp. 227-274 ◽  
Author(s):  
E. Germaine ◽  
L. Mydlarski ◽  
L. Cortelezzi
Keyword(s):  
Scalar Field ◽  
Channel Flow ◽  
Line Source ◽  
Dissipation Rate ◽  
Turbulent Channel Flow ◽  
Scalar Fields ◽  
Small Scale ◽  
Wall Region ◽  
Small Scales ◽  
Near Wall

AbstractThe dissipation rate,$\varepsilon _{\theta }$, of a passive scalar (temperature in air) emitted from a concentrated source into a fully developed high-aspect-ratio turbulent channel flow is studied. The goal of the present work is to investigate the return to isotropy of the scalar field when the scalar is injected in a highly anisotropic manner into an inhomogeneous turbulent flow at small scales. Both experiments and direct numerical simulations (DNS) were used to study the downstream evolution of$\varepsilon _{\theta }$for scalar fields generated by line sources located at the channel centreline$(y_s/h = 1.0)$and near the wall$(y_s/h = 0.17)$. The temperature fluctuations and temperature derivatives were measured by means of a pair of parallel cold-wire thermometers in a flow at$Re_{\tau } = 520$. The DNS were performed at$Re_{\tau } = 190$using a spectral method to solve the continuity and Navier–Stokes equations, and a flux integral method (Germaine, Mydlarski & Cortelezzi,J. Comput. Phys., vol. 174, 2001, pp. 614–648) for the advection–diffusion equation. The statistics of the scalar field computed from both experimental and numerical data were found to be in good agreement, with certain discrepancies that were attributable to the difference in the Reynolds numbers of the two flows. A return to isotropy of the small scales was never perfectly observed in any region of the channel for the downstream distances studied herein. However, a continuous decay of the small-scale anisotropy was observed for the scalar field generated by the centreline line source in both the experiments and DNS. The scalar mixing was found to be more rapid in the near-wall region, where the experimental results exhibited low levels of small-scale anisotropy. However, the DNS, which were performed at lower$Re_{\tau }$, showed that persistent anisotropy can also exist near the wall, independently of the downstream location. The role of the mean velocity gradient in the production of$\varepsilon _{\theta }$(and therefore anisotropy) in the near-wall region was highlighted.

scholarly journals Correlation between small-scale velocity and scalar fluctuations in a turbulent channel flow

2009 ◽  
Vol 627 ◽  
pp. 1-32 ◽  
Author(s):  
HIROYUKI ABE ◽  
ROBERT ANTHONY ANTONIA ◽  
HIROSHI KAWAMURA
Keyword(s):  
Strain Rate ◽  
Channel Flow ◽  
Dissipation Rate ◽  
Compressive Strain ◽  
Outer Region ◽  
Turbulent Channel Flow ◽  
Scalar Fields ◽  
Scalar Dissipation ◽  
Small Scale ◽  
Scalar Dissipation Rate

Direct numerical simulations of a turbulent channel flow with passive scalar transport are used to examine the relationship between small-scale velocity and scalar fields. The Reynolds number based on the friction velocity and the channel half-width is equal to 180, 395 and 640, and the molecular Prandtl number is 0.71. The focus is on the interrelationship between the components of the vorticity vector and those of the scalar derivative vector. Near the wall, there is close similarity between different components of the two vectors due to the almost perfect correspondence between the momentum and thermal streaks. With increasing distance from the wall, the magnitudes of the correlations become smaller but remain non-negligible everywhere in the channel owing to the presence of internal shear and scalar layers in the inner region and the backs of the large-scale motions in the outer region. The topology of the scalar dissipation rate, which is important for small-scale scalar mixing, is shown to be associated with the organized structures. The most preferential orientation of the scalar dissipation rate is the direction of the mean strain rate near the wall and that of the fluctuating compressive strain rate in the outer region. The latter region has many characteristics in common with several turbulent flows; viz. the dominant structures are sheetlike in form and better correlated with the energy dissipation rate than the enstrophy.

scholarly journals Geometric study of Lagrangian and Eulerian structures in turbulent channel flow

2011 ◽  
Vol 674 ◽  
pp. 67-92 ◽  
Author(s):  
YUE YANG ◽  
D. I. PULLIN
Keyword(s):  
Reynolds Number ◽  
Channel Flow ◽  
Inclination Angle ◽  
Turbulent Channel Flow ◽  
Small Scale ◽  
Wall Region ◽  
Sweep Angle ◽  
Multi Scale ◽  
Geometric Study ◽  
Near Wall

We report the detailed multi-scale and multi-directional geometric study of both evolving Lagrangian and instantaneous Eulerian structures in turbulent channel flow at low and moderate Reynolds numbers. The Lagrangian structures (material surfaces) are obtained by tracking the Lagrangian scalar field, and Eulerian structures are extracted from the swirling strength field at a time instant. The multi-scale and multi-directional geometric analysis, based on the mirror-extended curvelet transform, is developed to quantify the geometry, including the averaged inclination and sweep angles, of both structures at up to eight scales ranging from the half-height δ of the channel to several viscous length scales δν. Here, the inclination angle is on the plane of the streamwise and wall-normal directions, and the sweep angle is on the plane of streamwise and spanwise directions. The results show that coherent quasi-streamwise structures in the near-wall region are composed of inclined objects with averaged inclination angle 35°–45°, averaged sweep angle 30°–40° and characteristic scale 20δν, and ‘curved legs’ with averaged inclination angle 20°–30°, averaged sweep angle 15°–30° and length scale 5δν–10δν. The temporal evolution of Lagrangian structures shows increasing inclination and sweep angles with time, which may correspond to the lifting process of near-wall quasi-streamwise vortices. The large-scale structures that appear to be composed of a number of individual small-scale objects are detected using cross-correlations between Eulerian structures with large and small scales. These packets are located at the near-wall region with the typical height 0.25δ and may extend over 10δ in the streamwise direction in moderate-Reynolds-number, long channel flows. In addition, the effects of the Reynolds number and comparisons between Lagrangian and Eulerian structures are discussed.

scholarly journals Large eddy simulation of turbulent channel flow using differential equation wall model

2018 ◽  
Vol 15 (2) ◽  
pp. 75-89
Author(s):  
Muhammad Saiful Islam Mallik ◽  
Md. Ashraf Uddin
Keyword(s):  
Differential Equation ◽  
Flow Field ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Computational Domain ◽  
Wall Model ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Near Wall

A large eddy simulation (LES) of a plane turbulent channel flow is performed at a Reynolds number Re? = 590 based on the channel half width, ? and wall shear velocity, u? by approximating the near wall region using differential equation wall model (DEWM). The simulation is performed in a computational domain of 2?? x 2? x ??. The computational domain is discretized by staggered grid system with 32 x 30 x 32 grid points. In this domain the governing equations of LES are discretized spatially by second order finite difference formulation, and for temporal discretization the third order low-storage Runge-Kutta method is used. Essential turbulence statistics of the computed flow field based on this LES approach are calculated and compared with the available Direct Numerical Simulation (DNS) and LES data where no wall model was used. Comparing the results throughout the calculation domain we have found that the LES results based on DEWM show closer agreement with the DNS data, especially at the near wall region. That is, the LES approach based on DEWM can capture the effects of near wall structures more accurately. Flow structures in the computed flow field in the 3D turbulent channel have also been discussed and compared with LES data using no wall model.

Assessing the Effects of Near Wall Corrections of the Force Acting on Particles in Gas-Solid Channel Flows

2005 ◽  
Author(s):  
Boris Arcen ◽  
Anne Tanie`re ◽  
Benoiˆt Oesterle´
Keyword(s):  
Channel Flow ◽  
Lift Force ◽  
Particle Concentration ◽  
Turbulent Channel Flow ◽  
Shear Velocity ◽  
Solid Particles ◽  
Wall Region ◽  
Wall Effects ◽  
Strong Shear ◽  
Near Wall

The importance of using the lift force and wall-corrections of the drag coefficient for modeling the motion of solid particles in a fully-developed channel flow is investigated by means of direct numerical simulation (DNS). The turbulent channel flow is computed at a Reynolds number based on the wall-shear velocity and channel half-width of 185. Contrary to most of the numerical simulations, we consider in the present study a lift force formulation that accounts for the weak and strong shear as well as for the wall effects (hereinafter referred to as optimum lift force), and the wall-corrections of the drag force. The DNS results show that the optimum lift force and the wall-corrections of the drag together have little influence on most of the statistics (particle concentration, mean velocities, and mean relative and drift velocities), even in the near wall region.

Wall accumulation and spatial localization in particle-laden wall flows

2012 ◽  
Vol 699 ◽  
pp. 50-78 ◽  
Author(s):  
G. Sardina ◽  
P. Schlatter ◽  
L. Brandt ◽  
F. Picano ◽  
C. M. Casciola
Keyword(s):  
Turbulent Flows ◽  
Pair Correlation ◽  
Turbulent Channel Flow ◽  
Wall Turbulence ◽  
Small Scale ◽  
Wall Region ◽  
Inertial Particles ◽  
Wall Flows ◽  
Domain Truncation ◽  
Near Wall

AbstractWe study the two main phenomenologies associated with the transport of inertial particles in turbulent flows, turbophoresis and small-scale clustering. Turbophoresis describes the turbulence-induced wall accumulation of particles dispersed in wall turbulence, while small-scale clustering is a form of local segregation that affects the particle distribution in the presence of fine-scale turbulence. Despite the fact that the two aspects are usually addressed separately, this paper shows that they occur simultaneously in wall-bounded flows, where they represent different aspects of the same process. We study these phenomena by post-processing data from a direct numerical simulation of turbulent channel flow with different populations of inertial particles. It is shown that artificial domain truncation can easily alter the mean particle concentration profile, unless the domain is large enough to exclude possible correlation of the turbulence and the near-wall particle aggregates. The data show a strong link between accumulation level and clustering intensity in the near-wall region. At statistical steady state, most accumulating particles aggregate in strongly directional and almost filamentary structures, as found by considering suitable two-point observables able to extract clustering intensity and anisotropy. The analysis provides quantitative indications of the wall-segregation process as a function of the particle inertia. It is shown that, although the most wall-accumulating particles are too heavy to segregate in homogeneous turbulence, they exhibit the most intense local small-scale clustering near the wall as measured by the singularity exponent of the particle pair correlation function.

scholarly journals Local dissipation scales and energy dissipation-rate moments in channel flow

2012 ◽  
Vol 701 ◽  
pp. 419-429 ◽  
Author(s):  
P. E. Hamlington ◽  
D. Krasnov ◽  
T. Boeck ◽  
J. Schumacher
Keyword(s):  
Energy Dissipation ◽  
Channel Flow ◽  
Dissipation Rate ◽  
Isotropic Turbulence ◽  
Turbulent Channel Flow ◽  
Reynolds Numbers ◽  
Energy Dissipation Rate ◽  
Wall Region ◽  
Dissipation Scale ◽  
High Order Statistics

AbstractLocal dissipation-scale distributions and high-order statistics of the energy dissipation rate are examined in turbulent channel flow using very high-resolution direct numerical simulations at Reynolds numbers ${\mathit{Re}}_{\tau } = 180$, $381$ and $590$. For sufficiently large ${\mathit{Re}}_{\tau } $, the dissipation-scale distributions and energy dissipation moments in the channel bulk flow agree with those in homogeneous isotropic turbulence, including only a weak Reynolds-number dependence of both the finest and largest scales. Systematic, but ${\mathit{Re}}_{\tau } $-independent, variations in the distributions and moments arise as the wall is approached for ${y}^{+ } \lesssim 100$. In the range $100\lt {y}^{+ } \lt 200$, there are substantial differences in the moments between the lowest and the two larger values of ${\mathit{Re}}_{\tau } $. This is most likely caused by coherent vortices from the near-wall region, which fill the whole channel for low ${\mathit{Re}}_{\tau } $.

scholarly journals On peculiar property of the velocity fluctuations in wall-bounded flows

2005 ◽  
Vol 9 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jovan Jovanovic ◽  
Rafaela Hillerbrand
Keyword(s):  
Statistical Analysis ◽  
Numerical Simulations ◽  
Direct Numerical Simulations ◽  
Small Scale ◽  
Wall Region ◽  
Major Conclusion ◽  
Velocity Fluctuations ◽  
Small Scales ◽  
Wall Bounded Flows ◽  
Near Wall

Statistical analysis of the velocity fluctuations is performed for the near-wall region of wall-bounded flows. By demanding that the small-scale part of the fluctuations satisfies constraints imposed by local ax symmetry it was found that the small scales must be entirely suppressed in the near-wall region. This major conclusion is well supported by all available data from direct numerical simulations.

Correlation between Temperature and Velocity Fluctuations in the Near-Wall Region of Rotating Turbulent Channel Flow

2012 ◽  
Vol 29 (5) ◽  
pp. 054702 ◽  
Author(s):  
Zi-Xuan Yang ◽  
Gui-Xiang Cui ◽  
Chun-Xiao Xu ◽  
Zhao-Shun Zhang ◽  
Liang Shao
Keyword(s):  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Velocity Fluctuations ◽  
Near Wall
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