An idealised assessment of Townsend’s outer-layer similarity hypothesis for wall turbulence

2014 ◽  
Vol 742 ◽  
Author(s):  
D. Chung ◽  
J. P. Monty ◽  
A. Ooi
Keyword(s):  
Boundary Conditions ◽  
Order Statistics ◽  
Outer Layer ◽  
Solid Wall ◽  
Turbulent Channel Flow ◽  
Viscous Sublayer ◽  
Wall Turbulence ◽  
Outer Flow ◽  
Similarity Hypothesis ◽  
Stress Boundary Conditions

AbstractDirect numerical simulations of turbulent channel flow at the matched friction Reynolds number of 590, comparing the effect of no-slip versus shear-stress boundary conditions, reveal that the outer flow of wall turbulence, in accord with Townsend’s outer-layer similarity hypothesis, remains largely independent of the viscous sublayer. First- and second-order statistics, including spectra, agree closely from the buffer region out to the centre of the channel. Higher-order statistics also appear to obey the hypothesised similarity, although the influence of boundary conditions is more pronounced than in the lower-order statistics. The statistical agreement in the outer layer, in spite of the structural differences in the viscous sublayer, support Townsend’s idea that the primary effect of the wall is not the no-slip condition, but the impermeability condition imposed by a solid wall.

Modelling smooth- and transitionally rough-wall turbulent channel flow by leveraging inner–outer interactions and principal component analysis

2019 ◽  
Vol 863 ◽  
pp. 407-453 ◽  
Author(s):  
Sicong Wu ◽  
Kenneth T. Christensen ◽  
Carlos Pantano
Keyword(s):  
Principal Component Analysis ◽  
Outer Layer ◽  
Principal Component ◽  
Turbulent Channel Flow ◽  
Reynolds Numbers ◽  
Wall Turbulence ◽  
Rough Wall ◽  
Smooth Wall ◽  
Wall Flow ◽  
Near Wall

Direct numerical simulations (DNS) of turbulent channel flow over rough surfaces, formed from hexagonally packed arrays of hemispheres on both walls, were performed at friction Reynolds numbers $Re_{\unicode[STIX]{x1D70F}}=200$, $400$ and $600$. The inner normalized roughness height $k^{+}=20$ was maintained for all Reynolds numbers, meaning all flows were classified as transitionally rough. The spacing between hemispheres was varied within $d/k=2$–$4$. The statistical properties of the rough-wall flows were contrasted against a complementary smooth-wall DNS at $Re_{\unicode[STIX]{x1D70F}}=400$ and literature data at $Re_{\unicode[STIX]{x1D70F}}=2003$ revealing strong modifications of the near-wall turbulence, although the outer-layer structure was found to be qualitatively consistent with smooth-wall flow. Amplitude modulation (AM) analysis was used to explore the degree of interaction between the flow in the roughness sublayer and that of the outer layer utilizing all velocity components. This analysis revealed stronger modulation effects, compared to smooth-wall flow, on the near-wall small-scale fluctuations by the larger-scale structures residing in the outer layer irrespective of roughness arrangement and Reynolds number. A predictive inner–outer model based on these interactions, and exploiting principal component analysis (PCA), was developed to predict the statistics of higher-order moments of all velocity fluctuations, thus addressing modelling of anisotropic effects introduced by roughness. The results show excellent agreement between the predicted near-wall statistics up to fourth-order moments compared to the original statistics from the DNS, which highlights the utility of the PCA-enhanced AM model in generating physics-based predictions in both smooth- and rough-wall turbulence.

On unified boundary conditions for improved predictions of near-wall turbulence

2010 ◽  
Vol 656 ◽  
pp. 530-539 ◽  
Author(s):  
S. JAKIRLIĆ ◽  
J. JOVANOVIĆ
Keyword(s):  
Boundary Conditions ◽  
Viscous Sublayer ◽  
Wall Turbulence ◽  
Wall Region ◽  
Homogeneous Part ◽  
Wall Distance ◽  
Wall Boundary Conditions ◽  
Close Proximity ◽  
Near Wall Turbulence ◽  
Near Wall

A novel formulation of the wall boundary conditions relying on the asymptotic behaviour of the Taylor microscale λ and its relationship to the homogeneous part of the viscous dissipation rate of the kinetic energy of turbulence εh=5νq2/λ2, applicable to near-wall turbulence, is examined. The linear dependence of λ on the wall distance in close proximity to the solid surface enables the wall-closest grid node to be positioned immediately below the edge of the viscous sublayer, leading to a substantial coarsening of the grid resolution. This approach provides bridging of a major portion of the viscous sublayer, higher grid flexibility and weaker sensitivity against the grid non-uniformities in the near-wall region. The performance of the proposed formulation was checked against available direct numerical simulation databases of complex wall-bounded flows featured by swirl and separation.

The effect of wall-normal gravity on particle-laden near-wall turbulence

2019 ◽  
Vol 873 ◽  
pp. 475-507 ◽  
Author(s):  
Junghoon Lee ◽  
Changhoon Lee
Keyword(s):  
Turbulent Channel Flow ◽  
Viscous Sublayer ◽  
Stokes Number ◽  
Wall Turbulence ◽  
Small Scale ◽  
Gravitational Acceleration ◽  
Lower Wall ◽  
Low Speed ◽  
Near Wall Turbulence ◽  
Near Wall

We performed two-way coupled direct numerical simulations of turbulent channel flow with Lagrangian tracking of small, heavy spheres at a dimensionless gravitational acceleration of 0.077 in wall units, which is based on the flow condition in the experiment by Gerashchenko et al. (J. Fluid Mech., vol. 617, 2008, pp. 255–281). We removed deposited particles after several collisions with the lower wall and then released new particles near the upper wall to observe direct interactions between particles and coherent structures of near-wall turbulence during gravitational settling through the mean shear. The results indicate that when the Stokes number is approximately 1 on the basis of the Kolmogorov time scale of the flow ($St_{K}\approx 1$), the so-called preferential sweeping occurs in association with coherent streamwise vortices, while the effect of crossing trajectories becomes significant for $St_{K}>1$. Consequently, in either case, the settling particles deposit on the wall without strong accumulation in low-speed streaks in the viscous sublayer. When particles settle through near-wall turbulence from the upper wall, more small-scale vortical structures are generated in the outer layer as low-speed fluid is pulled farther in the direction of gravity, while the opposite is true near the lower wall.

Near Wall Turbulence Effects on Particle Transport and Deposition in Human Tracheobronchial Multi-Level Bifurcation Model

2015 ◽  
Author(s):  
Amir A. Mofakham ◽  
Lin Tian ◽  
Goodarz Ahmadi
Keyword(s):  
Boundary Conditions ◽  
Particle Deposition ◽  
Flow Simulation ◽  
Tracheobronchial Tree ◽  
Lung Model ◽  
Wall Turbulence ◽  
Nano Particles ◽  
Turbulent Regime ◽  
Computationally Efficient ◽  
Multi Level

Transport and deposition of micro and nano-particles in the upper tracheobronchial tree were analyzed using a multi-level asymmetric lung bifurcation model. The multi-level lung model is flexible and computationally efficient by fusing sequence of individual bifurcations with proper boundary conditions. Trachea and the first two generations of the tracheobronchial airway were included in the analysis. In these regions, the airflow is in turbulent regime due to the disturbances induced by the laryngeal jet. Anisotropic Reynolds stress transport turbulence model (RSTM) was used for mean the flow simulation, together with the enhanced two-layer model boundary conditions. Particular attention is given to evaluate the importance of the “quadratic variation of the turbulent fluctuations perpendicular to the wall” on particle deposition in the upper tracheobroncial airways.

scholarly journals Turbulence Intensity Modulation by Micropolar Fluids

Fluids ◽  
2021 ◽  
Vol 6 (6) ◽  
pp. 195
Author(s):  
George Sofiadis ◽  
Ioannis Sarris
Keyword(s):  
Reynolds Number ◽  
Turbulence Intensity ◽  
Fluid Flows ◽  
Turbulent Channel Flow ◽  
High Volume ◽  
Reynolds Numbers ◽  
Intensity Modulation ◽  
Wall Turbulence ◽  
Volume Fractions ◽  
Physical Phenomena

Fluid microstructure nature has a direct effect on turbulence enhancement or attenuation. Certain classes of fluids, such as polymers, tend to reduce turbulence intensity, while others, like dense suspensions, present the opposite results. In this article, we take into consideration the micropolar class of fluids and investigate turbulence intensity modulation for three different Reynolds numbers, as well as different volume fractions of the micropolar density, in a turbulent channel flow. Our findings support that, for low micropolar volume fractions, turbulence presents a monotonic enhancement as the Reynolds number increases. However, on the other hand, for sufficiently high volume fractions, turbulence intensity drops, along with Reynolds number increment. This result is considered to be due to the effect of the micropolar force term on the flow, suppressing near-wall turbulence and enforcing turbulence activity to move further away from the wall. This is the first time that such an observation is made for the class of micropolar fluid flows, and can further assist our understanding of physical phenomena in the more general non-Newtonian flow regime.

A Complete Solution for Thermal-Elastohydrodynamic Lubrication of Line Contacts Using Circular Non-Newtonian Fluid Model

1992 ◽  
Vol 114 (3) ◽  
pp. 540-551 ◽  
Author(s):  
Hsing-Sen S. Hsiao ◽  
Bernard J. Hamrock
Keyword(s):  
Boundary Conditions ◽  
Newtonian Fluid ◽  
Energy Equation ◽  
Control Volume ◽  
Fluid Model ◽  
Complete Solution ◽  
Circular Model ◽  
Line Contacts ◽  
Stress Boundary Conditions ◽  
Stress Boundary

A complete solution is obtained for elastohydrodynamically lubricated conjunctions in line contacts considering the effects of temperature and the non-Newtonian characteristics of lubricants with limiting shear strength. The complete fast approach is used to solve the thermal Reynolds equation by using the complete circular non-Newtonian fluid model and considering both velocity and stress boundary conditions. The reason and the occasion to incorporate stress boundary conditions for the circular model are discussed. A conservative form of the energy equation is developed by using the finite control volume approach. Analytical solutions for solid surface temperatures that consider two-dimensional heat flow within the solids are used. A straightforward finite difference method, successive over-relaxation by lines, is employed to solve the energy equation. Results of thermal effects on film shape, pressure profile, streamlines, and friction coefficient are presented.

‘Inactive’ motion and pressure fluctuations in turbulent boundary layers

1967 ◽  
Vol 30 (2) ◽  
pp. 241-258 ◽  
Author(s):  
P. Bradshaw
Keyword(s):  
Boundary Layer ◽  
Outer Layer ◽  
Pressure Fluctuations ◽  
Turbulent Energy ◽  
Viscous Sublayer ◽  
Wave Number ◽  
Noticeable Effect ◽  
Frequency Spectra ◽  
Active Motion ◽  
Order Of Magnitude

Townsend's (1961) hypothesis that the turbulent motion in the inner region of a boundary layer consists of (i) an ‘active’ part which produces the shear stress τ and whose statistical properties are universal functions of τ and y, and (ii) an ‘inactive’ and effectively irrotational part determined by the turbulence in the outer layer, is supported in the present paper by measurements of frequency spectra in a strongly retarded boundary layer, in which the ‘inactive’ motion is particularly intense. The only noticeable effect of the inactive motion is an increased dissipation of kinetic energy into heat in the viscous sublayer, supplied by turbulent energy diffusion from the outer layer towards the surface. The required diffusion is of the right order of magnitude to explain the non-universal values of the triple products measured near the surface, which can therefore be reconciled with universality of the ‘active’ motion.Dimensional analysis shows that the contribution of the ‘active’ inner layer motion to the one-dimensional wave-number spectrum of the surface pressure fluctuations varies as τ2w/k1 up to a wave-number inversely proportional to the thickness of the viscous sublayer. This result is strongly supported by the recent measurements of Hodgson (1967), made with a much smaller ratio of microphone diameter to boundary-layer thickness than has been achieved previously. The disagreement of the result with most other measurements is attributed to inadequate transducer resolution in the other experiments.

What are we learning from simulating wall turbulence?

2007 ◽  
Vol 365 (1852) ◽  
pp. 715-732 ◽  
Author(s):  
Javier Jiménez ◽  
Robert D Moser
Keyword(s):  
Energy Production ◽  
Wall Layer ◽  
Wall Turbulence ◽  
Buffer Layers ◽  
Upper And Lower Bounds ◽  
Nonlinear Structures ◽  
Outer Flow ◽  
Global Properties ◽  
Dynamic Experiments ◽  
Lower Limits

The study of turbulence near walls has experienced a renaissance in the last decade, largely owing to the availability of high-quality numerical simulations. The viscous and buffer layers over smooth walls are essentially independent of the outer flow, and there is a family of numerically exact nonlinear structures that account for about half of the energy production and dissipation. The rest can be modelled by their unsteady bursting. Many characteristics of the wall layer, such as the dimensions of the dominant structures, are well predicted by those models, which were essentially completed in the 1990s after the increase in computer power made the kinematic simulations of the late 1980s cheap enough to undertake dynamic experiments. Today, we are at the early stages of simulating the logarithmic (or overlap) layer, and a number of details regarding its global properties are becoming clear. For instance, a finite Reynolds number correction to the logarithmic law has been validated in turbulent channels. This has allowed upper and lower limits of the overlap region to be clarified, with both upper and lower bounds occurring at much larger distances from the wall than commonly assumed. A kinematic picture of the various cascades present in this part of the flow is also beginning to emerge. Dynamical understanding can be expected in the next decade.

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