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.

Spatial structure of a turbulent boundary layer with irregular surface roughness

2010 ◽  
Vol 655 ◽  
pp. 380-418 ◽  
Author(s):  
Y. WU ◽  
K. T. CHRISTENSEN
Keyword(s):  
Spatial Structure ◽  
Outer Layer ◽  
Decomposition Analysis ◽  
Wall Turbulence ◽  
Rough Wall ◽  
Smooth Wall ◽  
Structure Of Flow ◽  
Moderate Reynolds Number ◽  
Wall Flow ◽  
The Impact

Particle image velocimetry experiments were performed to study the impact of realistic roughness on the spatial structure of wall turbulence at moderate Reynolds number. This roughness was replicated from an actual turbine blade damaged by deposition of foreign materials and its features are quite distinct from most roughness characterizations previously considered as it is highly irregular and embodies a broad range of topographical scales. The spatial structure of flow over this rough surface near the outer edge of the roughness sublayer is contrasted with that of smooth-wall flow to identify any structural modifications due to roughness. Hairpin vortex packets are observed in the outer layer of the rough-wall flow and are found to contribute heavily to the Reynolds shear stress, consistent with smooth-wall flow. While similar qualitative consistency is observed in comparisons of smooth- and rough-wall two-point correlations, some quantitative differences are also apparent. In particular, a reduction in the streamwise extent of two-point correlations of streamwise velocity is noted which could be indicative of a roughness-induced modification of outer-layer vortex organization. Proper orthogonal decomposition analysis reveals the streamwise coherence of the larger scales to be most sensitive to roughness while the spatial characteristics of the smaller scales appear relatively insensitive to such effects.

Perspective: Flow at High Reynolds Number and Over Rough Surfaces—Achilles Heel of CFD

1998 ◽  
Vol 120 (3) ◽  
pp. 434-444 ◽  
Author(s):  
V. C. Patel
Keyword(s):  
Numerical Solutions ◽  
Practical Importance ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Wall Turbulence ◽  
Law Of The Wall ◽  
High Reynolds Numbers ◽  
Wall Flow ◽  
High Reynolds ◽  
Near Wall

The law of the wall and related correlations underpin much of current computational fluid dynamics (CFD) software, either directly through use of so-called wall functions or indirectly in near-wall turbulence models. The correlations for near-wall flow become crucial in solution of two problems of great practical importance, namely, in prediction of flow at high Reynolds numbers and in modeling the effects of surface roughness. Although the two problems may appear vastly different from a physical point of view, they share common numerical features. Some results from the ’superpipe’ experiment at Princeton University are analyzed along with those of previous experiments on the boundary layer on an axisymmetric body to identify features of near-wall flow at high Reynolds numbers that are useful in modeling. The study is complemented by a review of some computations in simple and complex flows to reveal the strengths and weaknesses of turbulence models used in modern CFD methods. Similarly, principal results of classical experiments on the effects of sand-grain roughness are reviewed, along with various models proposed to account for these effects in numerical solutions. Models that claim to resolve the near-wall flow are applied to the flow in rough-wall pipes and channels to illustrate their power and limitations. The need for further laboratory and numerical experiments is clarified as a result of this study.

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.

scholarly journals Velocity and spatial distribution of inertial particles in a turbulent channel flow

2019 ◽  
Vol 872 ◽  
pp. 367-406 ◽  
Author(s):  
Kee Onn Fong ◽  
Omid Amili ◽  
Filippo Coletti
Keyword(s):  
Spatial Distribution ◽  
Particle Velocity ◽  
Turbulent Channel Flow ◽  
Wall Turbulence ◽  
Buffer Layers ◽  
Working Fluid ◽  
Wall Region ◽  
Inertial Particles ◽  
Velocity Fluctuations ◽  
Near Wall

We present experimental observations of the velocity and spatial distribution of inertial particles dispersed in turbulent downward flow through a vertical channel at friction Reynolds numbers $\mathit{Re}_{\unicode[STIX]{x1D70F}}=235$ and 335. The working fluid is air laden with size-selected glass microspheres, having Stokes numbers $St=\mathit{O}(10)$ and $\mathit{O}(100)$ when based on the Kolmogorov and viscous time scales, respectively. Cases at solid volume fractions $\unicode[STIX]{x1D719}_{v}=3\times 10^{-6}$ and $5\times 10^{-5}$ are considered. In the more dilute regime, the particle concentration profile shows near-wall and centreline maxima compatible with a turbophoretic drift down the gradient of turbulence intensity; the particles travel at speed similar to that of the unladen flow except in the near-wall region; and their velocity fluctuations generally follow the unladen flow level over the channel core, exceeding it in the near-wall region. The denser regime presents substantial differences in all measured statistics: the near-wall concentration peak is much more pronounced, while the centreline maximum is absent; the mean particle velocity decreases over the logarithmic and buffer layers; and particle velocity fluctuations and deposition velocities are enhanced. An analysis of the spatial distributions of particle positions and velocities reveals different behaviours in the core and near-wall regions. In the channel core, dense clusters form which are somewhat elongated, tend to be preferentially aligned with the vertical/streamwise direction and travel faster than the less concentrated particles. In the near-wall region, the particles arrange in highly elongated streaks associated with negative streamwise velocity fluctuations, several channel heights in length and spaced by $\mathit{O}(100)$ wall units, supporting the view that these are coupled to fluid low-speed streaks typical of wall turbulence. The particle velocity fields contain a significant component of random uncorrelated motion, more prominent for higher $St$ and in the near-wall region.

Evolution and dynamics of shear-layer structures in near-wall turbulence

1991 ◽  
Vol 224 ◽  
pp. 579-599 ◽  
Author(s):  
Arne V. Johansson ◽  
P. Henrik Alfredsson ◽  
John Kim
Keyword(s):  
Turbulent Channel Flow ◽  
Wall Turbulence ◽  
Turbulent Shear ◽  
Spanwise Direction ◽  
Wall Structures ◽  
Layer Structures ◽  
Turbulence Production ◽  
Near Wall Turbulence ◽  
Probe Measurements ◽  
Near Wall

Near-wall flow structures in turbulent shear flows are analysed, with particular emphasis on the study of their space–time evolution and connection to turbulence production. The results are obtained from investigation of a database generated from direct numerical simulation of turbulent channel flow at a Reynolds number of 180 based on half-channel width and friction velocity. New light is shed on problems associated with conditional sampling techniques, together with methods to improve these techniques, for use both in physical and numerical experiments. The results clearly indicate that earlier conceptual models of the processes associated with near-wall turbulence production, based on flow visualization and probe measurements need to be modified. For instance, the development of asymmetry in the spanwise direction seems to be an important element in the evolution of near-wall structures in general, and for shear layers in particular. The inhibition of spanwise motion of the near-wall streaky pattern may be the primary reason for the ability of small longitudinal riblets to reduce turbulent skin friction below the value for a flat surface.

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.

Small-scale characteristics of a turbulent boundary layer over a rough wall

1997 ◽  
Vol 342 ◽  
pp. 263-293 ◽  
Author(s):  
H. S. SHAFI ◽  
R. A. ANTONIA
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Outer Layer ◽  
Large Scale ◽  
Energy Dissipation Rate ◽  
Wall Layer ◽  
Rough Wall ◽  
Small Scale ◽  
Smooth Wall ◽  
Velocity Derivative

Measurements of the spanwise and wall-normal components of vorticity and their constituent velocity derivative fluctuations have been made in a turbulent boundary layer over a mesh-screen rough wall using a four-hot-wire vorticity probe. The measured spectra and variances of vorticity and velocity derivatives have been corrected for the effect of spatial resolution. The high-wavenumber behaviour of the spectra conforms closely with isotropy. Over most of the outer layer, the normalized magnitudes of the velocity derivative variances differ significantly from those over a smooth wall layer. The differences are such that the variances are much more nearly isotropic over the rough wall than on the smooth wall. This behaviour is consistent with earlier observations that the large-scale structure in this rough wall layer is more isotropic than that in a smooth wall layer. Isotropy-based approximations for the mean energy dissipation rate and mean enstrophy are consequently more reliable in this rough wall layer than in a smooth wall layer. In the outer layer, the vorticity variances are slightly larger than those over a smooth wall; reflecting structural differences between the two flows.

Analysis and modelling of subgrid-scale motions in near-wall turbulence

1998 ◽  
Vol 356 ◽  
pp. 327-352 ◽  
Author(s):  
CARLOS HÄRTEL ◽  
LEONHARD KLEISER
Keyword(s):  
Eddy Viscosity ◽  
Numerical Study ◽  
Reynolds Numbers ◽  
Large Eddy Simulations ◽  
Inverse Cascade ◽  
Large Eddy ◽  
Wall Flow ◽  
Definition Of ◽  
Subgrid Stress ◽  
Near Wall

A numerical study of turbulent channel flow at various Reynolds numbers (Reτ=115, 210, 300) is conducted in order to examine the requirements for a reliable subgrid modelling in large-eddy simulations of wall-bounded flows. Using direct numerical simulation data, the interactions between large and small scales in the near-wall flow are analysed in detail which sheds light on the origin of the inverse cascade of turbulent kinetic energy observed in the buffer layer. It is shown that the correlation of the wall-normal subgrid stress and the wall-normal derivative of the streamwise grid-scale velocity plays the key role in the occurrence of the inverse cascade. A brief a priori test of several subgrid models shows that currently applied models are not capable of accounting properly for the complex interactions in the near-wall flow. A series of large-eddy simulations gives evidence that this deficiency may cause significant errors in important global quantities of the flow such as the mean wall shear stress. A study of the eddy-viscosity ansatz is conducted which reveals that the characteristic scales usually employed for the definition of the eddy viscosity are inappropriate in the vicinity of a wall. Therefore, a novel definition of the eddy viscosity is derived from the analysis of the near-wall energy budget. This new definition, which employs the wall-normal subgrid stress as a characteristic scale, is more consistent with the near-wall physics. No significant Reynolds-number effects are encountered in the present analysis which suggests that the findings may be generalized to flows at higher Reynolds numbers.

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.

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