scholarly journals Turbulent flow over transitionally rough surfaces with varying roughness densities

2016 ◽  
Vol 804 ◽  
pp. 130-161 ◽  
Author(s):  
M. MacDonald ◽  
L. Chan ◽  
D. Chung ◽  
N. Hutchins ◽  
A. Ooi
Keyword(s):  
Turbulent Flows ◽  
Reynolds Shear Stress ◽  
Three Dimensional ◽  
Turbulent Energy ◽  
Rough Wall ◽  
Momentum Balance ◽  
Wall Flows ◽  
Roughness Elements ◽  
The Difference ◽  
Near Wall

We investigate rough-wall turbulent flows through direct numerical simulations of flow over three-dimensional transitionally rough sinusoidal surfaces. The roughness Reynolds number is fixed at $k^{+}=10$, where $k$ is the sinusoidal semi-amplitude, and the sinusoidal wavelength is varied, resulting in the roughness solidity $\unicode[STIX]{x1D6EC}$ (frontal area divided by plan area) ranging from 0.05 to 0.54. The high cost of resolving both the flow around the dense roughness elements and the bulk flow is circumvented by the use of the minimal-span channel technique, recently demonstrated by Chung et al. (J. Fluid Mech., vol. 773, 2015, pp. 418–431) to accurately determine the Hama roughness function, $\unicode[STIX]{x0394}U^{+}$. Good agreement of the second-order statistics in the near-wall roughness-affected region between minimal- and full-span rough-wall channels is observed. In the sparse regime of roughness ($\unicode[STIX]{x1D6EC}\lesssim 0.15$) the roughness function increases with increasing solidity, while in the dense regime the roughness function decreases with increasing solidity. It was found that the dense regime begins when $\unicode[STIX]{x1D6EC}\gtrsim 0.15{-}0.18$, in agreement with the literature. A model is proposed for the limit of $\unicode[STIX]{x1D6EC}\rightarrow \infty$, which is a smooth wall located at the crest of the roughness elements. This model assists with interpreting the asymptotic behaviour of the roughness, and the rough-wall data presented in this paper show that the near-wall flow is tending towards this modelled limit. The peak streamwise turbulence intensity, which is associated with the turbulent near-wall cycle, is seen to move further away from the wall with increasing solidity. In the sparse regime, increasing $\unicode[STIX]{x1D6EC}$ reduces the streamwise turbulent energy associated with the near-wall cycle, while increasing $\unicode[STIX]{x1D6EC}$ in the dense regime increases turbulent energy. An analysis of the difference of the integrated mean momentum balance between smooth- and rough-wall flows reveals that the roughness function decreases in the dense regime due to a reduction in the Reynolds shear stress. This is predominantly due to the near-wall cycle being pushed away from the roughness elements, which leads to a reduction in turbulent energy in the region previously occupied by these events.

Direct simulations of a rough-wall channel flow

2007 ◽  
Vol 571 ◽  
pp. 235-263 ◽  
Author(s):  
TOMOAKI IKEDA ◽  
PAUL A. DURBIN
Keyword(s):  
Friction Velocity ◽  
Three Dimensional ◽  
Turbulent Energy ◽  
High Energy ◽  
Rough Wall ◽  
Roughness Sublayer ◽  
Wall Friction ◽  
Turbulence Structure ◽  
The Difference ◽  
Grain Roughness

In this study, we performed simulations of turbulent flow over rectangular ribs transversely mounted on one side of a plane in a channel, with the other side being smooth. The separation between ribs is large enough to avoid forming stable vortices in the spacing, which exhibits k-type, or sand-grain roughness. The Reynolds number Reτ of our representative direct numerical simulation case is 460 based on the smooth-wall friction velocity and the channel half-width. The roughness height h is estimated as 110 wall units based on the rough-wall friction velocity. The velocity profile and kinetic energy budget verify the presence of an equilibrium, logarithmic layer at y≳2h. In the roughness sublayer, however, a significant turbulent energy flux was observed. A high-energy region is formed by the irregular motions just above the roughness. Visualizations of vortical streaks, disrupted in all three directions in the roughness sublayer, indicate that the three-dimensional flow structure of sand-grain roughness is replicated by the two-dimensional roughness, and that this vortical structure is responsible for the high energy production. The difference in turbulence structure between smooth- and rough-wall layers can also be seen in other flow properties, such as anisotropy and turbulence length scales.

Turbulence structure of a reattaching mixing layer

1981 ◽  
Vol 110 ◽  
pp. 171-194 ◽  
Author(s):  
C. Chandrsuda ◽  
P. Bradshaw
Keyword(s):  
Boundary Layer ◽  
Shear Stress ◽  
Reynolds Shear Stress ◽  
Mixing Layer ◽  
Three Dimensional ◽  
Flow Region ◽  
Turbulent Energy ◽  
Turbulence Structure ◽  
Hot Wire ◽  
Recirculating Flow

Hot-wire measurements of second- and third-order mean products of velocity fluctuations have been made in the flow behind a backward-facing step with a thin, laminar boundary layer at the top of the step. Measurements extend to a distance of about 12 step heights downstream of the step, and include parts of the recirculating-flow region: approximate limits of validity of hot-wire results are given. The Reynolds number based on step height is about 105, the mixing layer being fully turbulent (fully three-dimensional eddies) well before reattachment, and fairly close to self-preservation in contrast to the results of some previous workers. Rapid changes in turbulence quantities occur in the reattachment region: Reynolds shear stress and triple products decrease spectacularly, mainly because of the confinement of the large eddies by the solid surface. The terms in the turbulent energy and shear stress balances also change rapidly but are still far from the self-preserving boundary-layer state even at the end of the measurement region.

scholarly journals Physical changes within a large tropical hydroelectric reservoir induced by wintertime cold front activity

2014 ◽  
Vol 18 (8) ◽  
pp. 3079-3093 ◽  
Author(s):  
M. P. Curtarelli ◽  
E. H. Alcântara ◽  
C. D. Rennó ◽  
J. L. Stech
Keyword(s):  
Weather Forecasting ◽  
Cold Front ◽  
Three Dimensional ◽  
Remote Sensing Data ◽  
Turbulent Energy ◽  
Heat Fluxes ◽  
Physical Processes ◽  
Tropical Reservoir ◽  
The Difference

Abstract. We investigated the influence of wintertime cold front activity on the physical processes within a large tropical reservoir located in Brazil. The period chosen for this study consisted of 49 days between 28 April 2010 and 15 July 2010. This period was defined based on information from the Brazilian Center for Weather Forecasting and Climate Studies (CPTEC), data collected in situ and the interpretation of remotely sensed images. To better understand the governing processes that drive changes in the heat balance, differential cooling and mixing dynamics, a simulation was performed that utilized a three-dimensional hydrodynamic model enforced with in situ and remote sensing data. The results showed that during a cold front passage over the reservoir, the sensible and latent heat fluxes were enhanced by approximately 77 and 16%, respectively. The reservoir's daily averaged heat loss was up to 167% higher on the days with cold front activity than on the days without activity. The cold front passage also intensified the differential cooling process; in some cases the difference between the water temperature of the littoral and pelagic zones reached up to 8 °C. The occurrence of cold front passages impacted the diurnal mixed layer (DML), by increasing the turbulent energy input (∼54%) and the DML depth (∼41%). Our results indicate that the cold front events are one of the main meteorological disturbances driving the physical processes within hydroelectric reservoirs located in tropical South America during the wintertime. Hence, cold front activity over these aquatic systems has several implications for water quality and reservoir management in Brazil.

Shared dynamical features of smooth- and rough-wall boundary-layer turbulence

2016 ◽  
Vol 792 ◽  
pp. 435-469 ◽  
Author(s):  
R. L. Ebner ◽  
Faraz Mehdi ◽  
J. C. Klewicki
Keyword(s):  
Structural Features ◽  
Momentum Equation ◽  
Rough Wall ◽  
Momentum Balance ◽  
Normal Velocity ◽  
Advective Transport ◽  
Vorticity Field ◽  
Wall Flows ◽  
The Mean ◽  
Spanwise Vorticity

The structure of smooth- and rough-wall turbulent boundary layers is investigated using existing data and newly acquired measurements derived from a four element spanwise vorticity sensor. Scaling behaviours and structural features are interpreted using the mean momentum equation based framework described for smooth-wall flows by Klewicki (J. Fluid Mech., vol. 718, 2013, pp. 596–621), and its extension to rough-wall flows by Mehdiet al.(J. Fluid Mech., vol. 731, 2013, pp. 682–712). This framework holds potential relative to identifying and characterizing universal attributes shared by smooth- and rough-wall flows. As prescribed by the theory, the present analyses show that a number of statistical features evidence invariance when normalized using the characteristic length associated with the wall-normal transition to inertial leading-order mean dynamics. On the inertial domain, the spatial size of the advective transport contributions to the mean momentum balance attain approximate proportionality with this length over significant ranges of roughness and Reynolds number. The present results support the hypothesis of Mehdiet al., that outer-layer similarity is, in general, only approximately satisfied in rough-wall flows. This is because roughness almost invariably leaves some imprint on the vorticity field; stemming from the process by which roughness influences (generally augments) the near-wall three-dimensionalization of the vorticity field. The present results further indicate that the violation of outer similarity over regularly spaced spanwise oriented bar roughness correlates with the absence of scale separation between the motions associated with the wall-normal velocity and spanwise vorticity on the inertial domain.

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.

Prediction of Turbulent Rough-Wall Skin Friction Using a Discrete Element Approach

1985 ◽  
Vol 107 (2) ◽  
pp. 251-257 ◽  
Author(s):  
R. P. Taylor ◽  
H. W. Coleman ◽  
B. K. Hodge
Keyword(s):  
Turbulent Flows ◽  
Three Dimensional ◽  
Element Model ◽  
Discrete Element ◽  
Boundary Layer Flows ◽  
Basic Principles ◽  
Roughness Model ◽  
Roughness Elements ◽  
Element Approach ◽  
Using Data

A discrete element model for turbulent flow over rough surfaces has been derived from basic principles. This formulation includes surface roughness form drag and blockage effects as a constituent part of the partial differential equations and does not rely on a single-length-scale concept such as equivalent sandgrain roughness. The roughness model includes the necessary empirical information on the interaction between three-dimensional roughness elements and the flow in a general way which does not require experimental data on each specific surface. This empirical input was determined using data from well-accepted experiments. Predictions using the model are compared with additional data for fully-developed and boundary layer flows. The predictions are shown to compare equally well with both transitionally rough and fully rough turbulent flows without modification of the roughness model.

Three Dimensional Volumetric Velocity Measurements in the Inner Part of a Turbulent Boundary Layer Over a Rough Wall Using Digital HPIV

2010 ◽  
Author(s):  
Siddharth Talapatra ◽  
Joseph Katz
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Three Dimensional ◽  
Sample Volume ◽  
Rough Wall ◽  
Roughness Sublayer ◽  
Uniform Grid ◽  
Roughness Elements ◽  
Particle Pairs ◽  
Particle Images

Microscopic digital Holographic PIV is used to measure the 3D velocity distributions in the roughness sublayer of a turbulent boundary layer over a rough wall. The sample volume extends from the surface, including the space between the tightly packed, 0.45 mm high, pyramidal roughness elements, up to about 5 roughness heights away from the wall. To facilitate observations though a rough surface, experiments are performed in a facility containing fluid that has the same optical refractive index as the acrylic rough walls. Magnified in line holograms are recorded on a 4864×3248 pixel camera at a resolution of 0.67μm/pixel. The flow field is seeded with 2μm silver coated glass particles, which are injected upstream of the same volume. A multiple-step particle tracking procedure is used for matching the particle pairs. In recently obtained data, we have typically matched ∼5000 particle images per hologram pair. The resulting unstructured 3D vectors are projected onto a uniform grid with spacing of 60 μm in all three directions in a 3.2×1.8×1.8 mm sample volume. The paper provides sample data showing that the flow in the roughness sublayer is dominated by slightly inclined, quasi-streamwise vortices whose coherence is particularly evident close to the top of the roughness elements.

Near-Wall Stereo PIV Investigation of the Turbulent Channel Flow Over Rough-Walls

2008 ◽  
Author(s):  
Jiarong Hong ◽  
Joseph Katz ◽  
Michael Schultz
Keyword(s):  
Channel Flow ◽  
Optical Measurement ◽  
Measurement Techniques ◽  
Three Dimensional ◽  
Turbulent Channel Flow ◽  
Mean Velocity ◽  
Roughness Elements ◽  
Sample Data ◽  
Near Wall

The near-wall turbulent flow in the rough-wall channel is of great significance in engineering applications, but remains a challenge for both experimental measurement and numerical modeling due to the complexity of the roughness geometry. For optical measurement techniques, e.g. PIV, obstruction by the roughness elements and reflection from the surface adversely affect the quality of near wall data. Our present study utilizes a facility containing a fluid with the same refractive index as the rough acrylic wall, making the interface almost invisible, and employs Stereo PIV to obtain the three-dimensional flow field in the vicinity of the roughness elements. The roughness shape is a uniformly distributed and closely packed, 0.5 mm high pyramid, corresponding to 95 wall units, with a pitch angle of 22.5 degrees. The length of the rough surface is sufficiently long to obtain self-similar roughness boundary layer, turbulent channel flow at a mean velocity of 3.8 m/s, with a clearly defined log layer. Results will include sample data of the complete flow, both around and above the roughness elements. Issues related to implementation of Stereo PIV in an index-matched facility will be discussed.

scholarly journals Direct numerical simulation of turbulent mixing

2013 ◽  
Vol 371 (2003) ◽  
pp. 20120216 ◽  
Author(s):  
V. P. Statsenko ◽  
Yu. V. Yanilkin ◽  
V. A. Zhmaylo
Keyword(s):  
Experimental Data ◽  
Turbulent Flows ◽  
Turbulent Mixing ◽  
Mixed Type ◽  
Three Dimensional ◽  
Turbulent Energy ◽  
Type Problem ◽  
Buoyant Jet ◽  
And Shock Waves ◽  
Problem Comparison

The results of three-dimensional numerical simulations of turbulent flows obtained by various authors are reviewed. The paper considers the turbulent mixing (TM) process caused by the development of the main types of instabilities: those due to gravitation (with either a fixed or an alternating-sign acceleration), shift and shock waves. The problem of a buoyant jet is described as an example of the mixed-type problem. Comparison is made with experimental data on the TM zone width, profiles of density, velocity and turbulent energy and degree of homogeneity.

Experimental study on dominant vortex structures in near-wall region of turbulent boundary layer based on tomographic particle image velocimetry

2019 ◽  
Vol 874 ◽  
pp. 426-454 ◽  
Author(s):  
Chengyue Wang ◽  
Qi Gao ◽  
Jinjun Wang ◽  
Biao Wang ◽  
Chong Pan
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Image ◽  
Three Dimensional ◽  
Vortex Structures ◽  
Wall Region ◽  
Tomographic Particle Image Velocimetry ◽  
Image Velocimetry ◽  
Inclination Angles ◽  
The Difference ◽  
Near Wall

Vortex structures are very popular research objects in turbulent boundary layers (TBLs) because of their prime importance in turbulence modelling. This work performs a tomographic particle image velocimetry measurement on the near-wall region ($y<0.1\unicode[STIX]{x1D6FF}$) of TBLs at three Reynolds numbers $Re_{\unicode[STIX]{x1D70F}}=1238$, 2286 and 3081. The main attention is paid to the wall-normal evolution of the vortex geometries and topologies. The vortex is identified with swirl strength ($\unicode[STIX]{x1D706}_{ci}$), and its orientation is recognized by using the real eigenvector of the velocity gradient tensor. The vortex inclination angles in the streamwise–wall-normal plane and in the streamwise–spanwise plane as functions of wall-normal positions are investigated, which provide useful information to speculate on the three-dimensional shape of the vortex tubes in a TBL. The difference between the orientations of vorticity and swirl is discussed and their inherent relationship is revealed based on the governing equation of vorticity. Linear stochastic estimation (LSE) is further deployed to directly extract three-dimensional vortex models. The LSE velocity fields for ejection events happening at different wall-normal positions shed light on the evolution of the topologies for the vortices dominating ejection events. LSE based on a centred prograde spanwise vortex provides a typical packet model, which indicates that the population density of the packets in a TBL is large enough to leave footprints in conditionally averaged flow fields. This work should help to settle the severe debate on the existence of packet structures and also lays some foundation for the TBL model theory.

Sign in / Sign up

Export Citation Format

Share Document