The performance of smooth-wall drag reducing outer-layer devices in rough-wall boundary layers

1985 ◽  
Author(s):  
P. BANDYOPADHYAY
Keyword(s):  
Boundary Layers ◽  
Outer Layer ◽  
Rough Wall ◽  
Smooth Wall ◽  
Wall Boundary

Applicability of Taylor’s hypothesis in rough- and smooth-wall boundary layers

2016 ◽  
Vol 812 ◽  
pp. 398-417 ◽  
Author(s):  
D. T. Squire ◽  
N. Hutchins ◽  
C. Morrill-Winter ◽  
M. P. Schultz ◽  
J. C. Klewicki ◽  
...  
Keyword(s):  
Boundary Layers ◽  
Outer Region ◽  
Rough Wall ◽  
Turbulent Shear ◽  
Normal Velocity ◽  
Turbulent Shear Flow ◽  
Smooth Wall ◽  
Wall Boundary ◽  
Taylor’S Hypothesis ◽  
Velocity Spectra

The spatial structure of smooth- and rough-wall boundary layers is examined spectrally at approximately matched friction Reynolds number ($\unicode[STIX]{x1D6FF}^{+}\approx 12\,000$). For each wall condition, temporal and true spatial descriptions of the same flow are available from hot-wire anemometry and high-spatial-range particle image velocimetry, respectively. The results show that over the resolved flow domain, which is limited to a streamwise length of twice the boundary layer thickness, true spatial spectra of smooth-wall streamwise and wall-normal velocity fluctuations agree, to within experimental uncertainty, with those obtained from time series using Taylor’s frozen turbulence hypothesis (Proc. R. Soc. Lond. A, vol. 164, 1938, pp. 476–490). The same applies for the streamwise velocity spectra on rough walls. For the wall-normal velocity spectra, however, clear differences are observed between the true spatial and temporally convected spectra. For the rough-wall spectra, a correction is derived to enable accurate prediction of wall-normal velocity length scales from measurements of their time scales, and the implications of this correction are considered. Potential violations to Taylor’s hypothesis in flows above perturbed walls may help to explain conflicting conclusions in the literature regarding the effect of near-wall modifications on outer-region flow. In this regard, all true spatial and corrected spectra presented here indicate structural similarity in the outer region of smooth- and rough-wall flows, providing evidence for Townsend’s wall-similarity hypothesis (The Structure of Turbulent Shear Flow, vol. 1, 1956).

scholarly journals On the decay of dispersive motions in the outer region of rough-wall boundary layers

2019 ◽  
Vol 862 ◽  
Author(s):  
Johan Meyers ◽  
Bharathram Ganapathisubramani ◽  
Raúl Bayoán Cal
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Boundary Layers ◽  
Outer Layer ◽  
Stokes Equations ◽  
Outer Region ◽  
Rough Wall ◽  
Rough Boundary ◽  
Mean Flow ◽  
Wall Boundary

In rough-wall boundary layers, wall-parallel non-homogeneous mean-flow solutions exist that lead to so-called dispersive velocity components and dispersive stresses. They play a significant role in the mean-flow momentum balance near the wall, but typically disappear in the outer layer. A theoretical framework is presented to study the decay of dispersive motions in the outer layer. To this end, the problem is formulated in Fourier space, and a set of governing ordinary differential equations per mode in wavenumber space is derived by linearizing the Reynolds-averaged Navier–Stokes equations around a constant background velocity. With further simplifications, analytically tractable solutions are found consisting of linear combinations of $\exp (-kz)$ and $\exp (-Kz)$, with $z$ the wall distance, $k$ the magnitude of the horizontal wavevector $\boldsymbol{k}$, and where $K(\boldsymbol{k},Re)$ is a function of $\boldsymbol{k}$ and the Reynolds number $Re$. Moreover, for $k\rightarrow \infty$ or $k_{1}\rightarrow 0$ (with $k_{1}$ the stream-wise wavenumber), $K\rightarrow k$ is found, in which case solutions consist of a linear combination of $\exp (-kz)$ and $z\exp (-kz)$, and are independent of the Reynolds number. These analytical relations are compared in the limit of $k_{1}=0$ to the rough boundary layer experiments by Vanderwel & Ganapathisubramani (J. Fluid Mech., vol. 774, 2015, R2) and are in reasonable agreement for $\ell _{k}/\unicode[STIX]{x1D6FF}\leqslant 0.5$, with $\unicode[STIX]{x1D6FF}$ the boundary-layer thickness and $\ell _{k}=2\unicode[STIX]{x03C0}/k$.

scholarly journals Outer-layer turbulence intensities in smooth- and rough-wall boundary layers

2013 ◽  
Vol 727 ◽  
pp. 119-131 ◽  
Author(s):  
Ian P. Castro ◽  
Antonio Segalini ◽  
P. Henrik Alfredsson
Keyword(s):  
Pressure Gradient ◽  
Boundary Layers ◽  
Turbulence Intensity ◽  
Outer Layer ◽  
Rough Wall ◽  
Published Data ◽  
Outer Flow ◽  
Effective Roughness ◽  
Wall Boundary ◽  
Wide Range

AbstractClear differences in turbulence intensity profiles in smooth, transitional and fully rough zero-pressure-gradient boundary layers are demonstrated, using the diagnostic plot introduced by Alfredsson, Segalini & Örlü (Phys. Fluids, vol. 23, 2011, p. 041702) – ${u}^{\prime } / U$ versus $U/ {U}_{e} $, where ${u}^{\prime } $ and $U$ are the local (root mean square) fluctuating and mean velocities and ${U}_{e} $ is the free stream velocity. A wide range of published data are considered and all zero-pressure-gradient boundary layers yield outer flow ${u}^{\prime } / U$ values that are roughly linearly related to $U/ {U}_{e} $, just as for smooth walls, but with a significantly higher slope which is completely independent of the roughness morphology. The difference in slope is due largely to the influence of the roughness parameter ($ \mathrm{\Delta} {U}^{+ } $ in the usual notation) and all the data can be fitted empirically by using a modified form of the scaling, dependent only on $ \mathrm{\Delta} U/ {U}_{e} $. The turbulence intensity, at a location in the outer layer where $U/ {U}_{e} $ is fixed, rises monotonically with increasing $ \mathrm{\Delta} U/ {U}_{e} $ which, however, remains of $O(1)$ for all possible zero-pressure-gradient rough-wall boundary layers even at the highest Reynolds numbers. A measurement of intensity at a point in the outer region of the boundary layer can provide an indication of whether the surface is aerodynamically fully rough, without having to determine the surface stress or effective roughness height. Discussion of the implication for smooth/rough flow universality of differences in outer-layer mean velocity wake strength is included.

Turbulence structure in rough- and smooth-wall boundary layers

2007 ◽  
Vol 592 ◽  
pp. 263-293 ◽  
Author(s):  
R. J. VOLINO ◽  
M. P. SCHULTZ ◽  
K. A. FLACK
Keyword(s):  
Boundary Layers ◽  
Outer Region ◽  
Reynolds Numbers ◽  
Rough Wall ◽  
Turbulence Structure ◽  
Smooth Wall ◽  
Hairpin Vortices ◽  
Wall Flows ◽  
Wall Boundary ◽  
Cross Correlations

Turbulence measurements for rough-wall boundary layers are presented and compared to those for a smooth wall. The rough-wall experiments were made on a woven mesh surface at Reynolds numbers approximately equal to those for the smooth wall. Fully rough conditions were achieved. The present work focuses on turbulence structure, as documented through spectra of the fluctuating velocity components, swirl strength, and two-point auto- and cross-correlations of the fluctuating velocity and swirl. The present results are in good agreement, both qualitatively and quantitatively, with the turbulence structure for smooth-wall boundary layers documented in the literature. The boundary layer is characterized by packets of hairpin vortices which induce low-speed regions with regular spanwise spacing. The same types of structure are observed for the rough- and smooth-wall flows. When the measured quantities are normalized using outer variables, some differences are observed, but quantitative similarity, in large part, holds. The present results support and help to explain the previously documented outer-region similarity in turbulence statistics between smooth- and rough-wall boundary layers.

Extended Models for Transitional Rough Wall Boundary Layers With Heat Transfer: Part I—Model Formulations

2008 ◽  
Author(s):  
M. Stripf ◽  
A. Schulz ◽  
H.-J. Bauer ◽  
S. Wittig
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Boundary Layers ◽  
Turbulence Model ◽  
Turbulence Intensity ◽  
Discrete Element ◽  
Rough Wall ◽  
Test Cases ◽  
Wall Boundary ◽  
Turbine Vane

Two extended models for the calculation of rough wall transitional boundary layers with heat transfer are presented. Both models comprise a new transition onset correlation, which accounts for the effects of roughness height and density, turbulence intensity and wall curvature. In the transition region, an intermittency equation suitable for rough wall boundary layers is used to blend between the laminar and fully turbulent state. Finally, two different submodels for the fully turbulent boundary layer complete the two models. In the first model, termed KS-TLK-T in this paper, a sand roughness approach from Durbin et al., which builds upon a two-layer k-ε-turbulence model, is used for this purpose. The second model, the so-called DEM-TLV-T model, makes use of the discrete-element roughness approach, which was recently combined with a two-layer k-ε-turbulence model by the present authors. The discrete element model will be formulated in a new way suitable for randomly rough topographies. Part I of the paper will provide detailed model formulations as well as a description of the database used for developing the new transition onset correlation. Part II contains a comprehensive validation of the two models, using a variety of test cases with transitional and fully turbulent boundary layers. The validation focuses on heat transfer calculations on both, the suction and the pressure side of modern turbine airfoils. Test cases include extensive experimental investigations on a high-pressure turbine vane with varying surface roughness and turbulence intensity, recently published by the current authors as well as new experimental data from a low-pressure turbine vane. In the majority of cases, the predictions from both models are in good agreement with the experimental data.

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.

scholarly journals Assessment of inner–outer interactions in the urban boundary layer using a predictive model

2019 ◽  
Vol 875 ◽  
pp. 44-70 ◽  
Author(s):  
Karin Blackman ◽  
Laurent Perret ◽  
Romain Mathis
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Predictive Model ◽  
Boundary Layers ◽  
Large Scale ◽  
Reynolds Numbers ◽  
Limited Range ◽  
Rough Wall ◽  
Wall Boundary ◽  
Layer Flow

Urban-type rough-wall boundary layers developing over staggered cube arrays with plan area packing density, $\unicode[STIX]{x1D706}_{p}$, of 6.25 %, 25 % or 44.4 % have been studied at two Reynolds numbers within a wind tunnel using hot-wire anemometry (HWA). A fixed HWA probe is used to capture the outer-layer flow while a second moving probe is used to capture the inner-layer flow at 13 wall-normal positions between $1.25h$ and $4h$ where $h$ is the height of the roughness elements. The synchronized two-point HWA measurements are used to extract the near-canopy large-scale signal using spectral linear stochastic estimation and a predictive model is calibrated in each of the six measurement configurations. Analysis of the predictive model coefficients demonstrates that the canopy geometry has a significant influence on both the superposition and amplitude modulation. The universal signal, the signal that exists in the absence of any large-scale influence, is also modified as a result of local canopy geometry suggesting that although the nonlinear interactions within urban-type rough-wall boundary layers can be modelled using the predictive model as proposed by Mathis et al. (J. Fluid Mech., vol. 681, 2011, pp. 537–566), the model must be however calibrated for each type of canopy flow regime. The Reynolds number does not significantly affect any of the model coefficients, at least over the limited range of Reynolds numbers studied here. Finally, the predictive model is validated using a prediction of the near-canopy signal at a higher Reynolds number and a prediction using reference signals measured in different canopy geometries to run the model. Statistics up to the fourth order and spectra are accurately reproduced demonstrating the capability of the predictive model in an urban-type rough-wall boundary layer.

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